Some communities recover more quickly after a disaster than others. Some differentials in recovery are explained by variation in the level of disaster-related community damage and differences in pre-disaster community characteristics, e.g., the quality of housing stock. But distinct communities that are similar on the above characteristics may experience different recovery trajectories, and, if so, these different trajectories must be due to more subtle differences among them. Our principal objective is to assess short-term and long-term post-disaster mental health for Vietnamese and African Americans living in two adjacent communities in eastern New Orleans that were similarly flooded by Hurricane Katrina. We employ data from two population-based cohort studies that include a sample of African American adults (the Gulf Coast Child and Family Health [GCAFH study]) and a sample of Vietnamese American adults (Katrina Impacts on Vietnamese Americans [KATIVA NOLA study]) living in adjacent neighborhoods in eastern New Orleans who were assessed near the second and thirteenth anniversaries of the disaster. Using the 12-Item Short Form Survey (SF-12) as the basis of our outcome measure, we find in multivariate analysis a significant advantage in post-disaster mental health for Vietnamese Americans over their African American counterparts at the two-year mark, but that this advantage had disappeared by the thirteenth anniversary of the Katrina disaster.
The presented work analyzes the energy prices, climate shock, and health deprivation nexus in the BRICS economies for the period 1995-2020. Panel ARDL-PMG technique is used to reveal the underexplored linkages. The long-run estimates of energy prices are observed to be negatively significant to the health expenditure and life expectancy model, whereas, positively significant to the climate change model. These findings suggest that energy prices significantly reduce health expenditures and life expectancy and, thus, increase the death rate in the BRICS economies. The long-run country-wise estimate of energy prices is found negatively significant in case of Brazil, India, China, and South Africa. Alongside, the group-wise significance of CO2 emissions is discovered to be negatively, positively, and insignificant in the cases of life expectancy, death rate, and health expenditure models, respectively. Besides, country-wise long-run estimate of CO2 emissions witnesses negative significance for Russia, India, China, and South Africa.
Human health is linked to climatic factors in complex ways, and climate change can have profound direct and indirect impacts on the health status of any given region. Susceptibility to climate change is modulated by biological, ecological and socio-political factors such as age, gender, geographic location, socio-economic status, occupation, health status and housing conditions, among other. In the Eastern Mediterranean and Middle East (EMME), climatic factors known to affect human health include extreme heat, water shortages and air pollution. Furthermore, the epidemiology of vector-borne diseases (VBDs) and the health consequences of population displacement are also influenced by climate change in this region. To inform future policies for adaptation and mitigation measures, and based on an extensive review of the available knowledge, we recommend several research priorities for the region. These include the generation of more empirical evidence on exposure-response functions involving climate change and specific health outcomes, the development of appropriate methodologies to evaluate the physical and psychological effects of climate change on vulnerable populations, determining how climate change alters the ecological determinants of human health, improving our understanding of the effects of long-term exposure to heat stress and air pollution, and evaluating the interactions between adaptation and mitigation strategies. Because national boundaries do not limit most climate-related factors expected to impact human health, we propose that adaptation/mitigation policies must have a regional scope, and therefore require collaborative efforts among EMME nations. Policy suggestions include a decisive region-wide decarbonisation, the integration of environmentally driven morbidity and mortality data throughout the region, advancing the development and widespread use of affordable technologies for the production and management of drinking water by non-traditional means, the development of comprehensive strategies to improve the health status of displaced populations, and fostering regional networks for monitoring and controlling the spread of infectious diseases and disease vectors.
Heatwaves are increasing in frequency, duration, and intensity due to climate change. They are associated with high mortality rates and cross-sectional impacts including a reduction in crop yield and power outages. Here we demonstrate that there are large deficiencies in reporting of heatwave impacts in international disasters databases, international organization reports, and climate bulletins. We characterize the distribution of heat stress across the world focusing on August in the Northern Hemisphere, when notably heatwaves have taken place (i.e., 2003, 2010, and 2020) for the last 20 years using the ERA5-HEAT reanalysis of the Universal Thermal Comfort Index and establish heat stress has grown larger in extent, more so during a heatwave. Comparison of heat stress against the emergency events impacts database and climate reports reveals underreporting of heatwave-related impacts. This work suggests an internationally agreed protocol should be put in place for impact reporting by organizations and national government, facilitating implementation of preparedness measures, and early warning systems.
El Nino is a critical part of global inter-annual climate variability, and the intensity of El Nino has major implications for rainfall-induced natural hazards in many vulnerable countries. The impact of landslides triggered by rainfall is likely to be modulated by the strength of El Nino, but the nature of this connection and the places where it is most relevant remains unconstrained. Here we combine new satellite rainfall data with a global landslide exposure model to show that El Nino has far-reaching effects on landslide impacts to people and infrastructure. We find that the impact of El Nino on landslide exposure can be greater in parts of Southeast Asia and Latin America than that due to seasonal rainfall variability. These findings improve our understanding of hazard variability around the world and can assist disaster mitigation efforts on seasonal timescales.
Background: Most respiratory viruses show pronounced seasonality, but for SARS-CoV-2, this still needs to be documented. Methods: We examined the disease progression of COVID-19 in 6,914 patients admitted to hospitals in Europe and China. In addition, we evaluated progress of disease symptoms in 37,187 individuals reporting symptoms into the COVID Symptom Study application. Findings: Meta-analysis of the mortality risk in seven European hospitals estimated odds ratios per 1-day increase in the admission date to be 0.981 (0.973-0.988, p < 0.001) and per increase in ambient temperature of 1°C to be 0.854 (0.773-0.944, p = 0.007). Statistically significant decreases of comparable magnitude in median hospital stay, probability of transfer to the intensive care unit, and need for mechanical ventilation were also observed in most, but not all hospitals. The analysis of individually reported symptoms of 37,187 individuals in the UK also showed the decrease in symptom duration and disease severity with time. Interpretation: Severity of COVID-19 in Europe decreased significantly between March and May and the seasonality of COVID-19 is the most likely explanation.
The policies of response to and prevention of heat waves in France in 2003 and in South Korea in 2018 were compared and reviewed to see how public health policy orientation was being expanded in connection with urban and social policies. The statistics of the patients with heat illness and resulted death in France in 2003 and South Korea in 2018 were analyzed. The results and limitations of the French and Korean responses to heat waves were compared and discussed. The heat wave in France in 2003 caused an excess death of 14,802. The 2018 heat wave in South Korea resulted in 4,526 cases of heat illness and 48 deaths. France’s National Heat wave Plan established in 2004 introduced the warning system and strengthened support for the vulnerable. The heat wave in South Korea in 2018 revealed the success and limitations of the national measures that have been gradually implemented since the mid-2000s. Both France and South Korea are making efforts in preventing heat illness and managing health risk through the warning systems, providing public and social support for the vulnerable, and expanding urban infrastructure. Paris puts priority on the long-term prevention of heat wave, in the wider context of climate change response, while Seoul shows a relatively strong point in immediate infrastructural expansion. In order to respond to the climate crisis and the following health risk, public health policies need to be contrived with deeper connection with urban social policies for sustainable development.
The environmental conditions during the Tokyo Olympic and Paralympic Games are expected to be challenging, which increases the risk for participating athletes to develop heat-related illnesses and experience performance loss. To allow safe and optimal exercise performance of Dutch elite athletes, the Thermo Tokyo study aimed to determine thermoregulatory responses and performance loss among elite athletes during exercise in the heat, and to identify personal, sports-related, and environmental factors that contribute to the magnitude of these outcomes. For this purpose, Dutch Olympic and Paralympic athletes performed two personalized incremental exercise tests in simulated control (15°C, relative humidity (RH) 50%) and Tokyo (32°C, RH 75%) conditions, during which exercise performance and (thermo)physiological parameters were obtained. Thereafter, athletes were invited for an additional visit to conduct anthropometric, dual-energy X-ray absorptiometry (DXA), and 3D scan measurements. Collected data also served as input for a thermophysiological computer simulation model to estimate the impact of a wider range of environmental conditions on thermoregulatory responses. Findings of this study can be used to inform elite athletes and their coaches on how heat impacts their individual (thermo)physiological responses and, based on these data, advise which personalized countermeasures (i.e. heat acclimation, cooling interventions, rehydration plan) can be taken to allow safe and maximal performance in the challenging environmental conditions of the Tokyo 2020 Olympic and Paralympic Games.
Climate change is one of the biggest health threats facing humanity and can directly affect human health through heat waves. This study aims to evaluate excess deaths during heat waves between the summer months of 2004 and 2017 in Istanbul and to determine a definition of heat waves that can be used in the development of an early warning system, a part of prospective urban heat-health action plans. In this study, heat waves were determined using the Excess Heat Factor, an index based on a three-day-averaged daily mean temperature. The death rates during heat waves and non-heat wave days of the summer months were compared with a Z test of the difference of natural logarithms. Thirty heat waves were recorded in Istanbul during the summer months of 2004-2017. In 67% of the heat waves, the death rate was significantly higher than the reference period and 4281 excess deaths were recorded. The mortality risk was especially higher during heat waves of higher intensity. The study showed an excess risk of mortality during heat waves in Istanbul, and the findings suggest that the Excess Heat Factor could be an appropriate tool for an early warning system in Istanbul.
Tropical cyclones are highly destructive weather systems, especially in coastal areas. Tropical cyclones with maximum sustained winds exceeding 74 mph (≈119 kph) are classified as typhoons in the Northwest Pacific, whilst the term ‘hurricanes’ applies to other regions. This study aims to investigate the general characteristics of the most devastating and catastrophic tropical cyclones in the USA Europe, and Asia. To achieve the study objectives, the three most devastating typical tropical cyclones in each region were selected. The tropical cyclones were examined based on various features, such as the number of deaths, minimum pressure, highest wind speed, total financial losses, and frequency per year. In contrast to Europe and Asia, the USA has recorded the highest number of catastrophic tropical cyclones. The damage induced by hurricanes Katrina, Harvey, and Maria in the USA totalled approximately USD USD 380 billion. In addition, the present research highlights the demand to improve the public attitude and behaviour toward the impact of climate change along with the enhancement of climate change alleviation strategies. The number of intense tropical cyclones is expected to rise, and the tropical cyclone-related precipitation rate is expected to increase in warmer-climate areas. Stakeholders and industrial practitioners may use the research findings to design resilience and adaptation plans in the face of tropical cyclones, allowing them to assess the effects of climate change on tropical cyclone incidents from an academic humanitarian logistics viewpoint in the forthcoming years.
First Nations Peoples have a long history of living in Australia’s changing climate and a deep knowledge of their traditional estate (‘Country’). However, human-induced climate change raises unforeseen risks to the health of First Nations Peoples-especially in remotely located communities. This includes the Torres Strait Islands, where a local leader asked our Torres Strait Islander co-author, ‘We know that you will return to your Country-unlike previous researchers. So how can you help with climate change?’ In response, this research describes four core values focused on supporting First Nations Peoples’ health and wellbeing: co-design, appropriate governance, support for self-determination, and respectfully incorporating Indigenous Knowledges into health-protective climate initiatives. Supporting the health and wellbeing of Torres Strait Islanders to continue living in the remote Torres Strait Islands in a changing climate can enable long-term care for Country, maintenance of culture, and a sense of identity for First Nations Peoples. Ensuring these core values are implemented can support the health of present and future generations and will likely be applicable to other First Nations communities.
Associated with rapid urbanization and escalation of bushfire events, Sydney has experienced significant air quality degradation in the XXI century. In this study, we present a 15-year retrospective analysis on the influence of individual meteorological factors on major air pollutants (NO(2), O(3), PM(10) and PM(2.5)) at 14 different sites in Greater Sydney and Illawarra. By applying a newly developed “zooming in” approach to long-term ground-based data, we disclose general, seasonal, daily and hourly patterns while increasing the level of spatial associativity. We provide evidence on the pivotal role played by urbanization, sprawling dynamics, global warming and bushfires on local meteorology and air pollution. We strike associations between temperature and O(3), both as average trends and extremes, on account of increasing heat island effects. The role of wind in a coastal-basin environment, influenced by a vast desert biome inland, is investigated. A steady trend towards stagnation is outlined, boosted by enhanced urban roughness and intensified heat island circulation. Relative humidity is also crucial in the modulation between NO(2) and O(3). With a sharp tendency towards drier and hotter microclimates, NO(2) levels dropped by approximately 50% over the years at all locations, while O(3)’s median levels almost doubled in the last 10 years. Further, O(3) and PMs shifted towards more frequent extreme events, strongly associated with the exacerbation of bushfire events. Such results suggest an urgent need to prioritize emission control, building air tightness improvement and urban heat mitigation, towards a future-proof governance in Sydney and similar regions in the world.
Despite the enormous gains in reducing child mortality resulting from the United Nations Millennium Development Goals, in some ways children’s future wellbeing has never been under greater threat. Climate and environmental change, primarily driven by poor air quality, represents a major threat to child health and wellbeing, through both direct and indirect effects. Climate change has multiple environmental consequences impacting negatively on child health and wellbeing, including increases in ambient temperature, rising atmospheric carbon dioxide (CO(2)) , altered distribution of rainfall, ocean warming, rising sea level and more frequent and severe adverse weather events. Multiple pathways link these exposures to a wide variety of adverse health outcomes. Countries in Oceania are especially likely to be subjected to the effects of increases in ambient temperature, altered distribution of rainfall, ocean warming and sea level rise. These changes pose a significant risk to children and provide a moral imperative for us to act to protect child health.
Despite evidence that Indigenous peoples’ multiple subjectivities engender diverse lived experiences both between and within Indigenous groups, the influence of multiple subjectivities on Indigenous peoples’ vulnerability and adaptation to climate change is largely un-explored. Drawing on ethnographic research with Indigenous Maori women in Aotearoa New Zealand, this paper provides empirical evidence that subjectivity-mediated power dynamics operating within Indigenous societies (at the individual and household scale) are important determinants of vulnerability and adaptation which should be considered in both scholarship and policy. Using an intersectional framework, I demonstrate how different Maori women and their whanau (families) live, cope with, and adapt to the embodied physical and emotional health effects of climate change in radically different ways because of their subject positionings, even though they belong to the same community, hapu (sub-tribe), or iwi (tribe). In underlining these heterogenous experiences, I provide an avenue for reconsidering how climate adaptation scholarship, policies, and practices might better engage with the complex, amorphous realities within Maori and other Indigenous communities. I argue it is possible to develop more inclusive, tailored, and sustainable adaptation that considers divergent vulnerabilities and adaptive capacities within Indigenous communities, groups, and societies and supports customised vulnerability-reduction strategies.
PURPOSE: There are increasing calls for planetary health (which includes sustainable healthcare) to be included in tertiary health professions education. With already busy curricula, particularly in medicine, educators need to find innovative ways of integrating these important concepts without adding to learners’ workload. This study investigated whether planetary health concepts could be integrated into a Physiology subject as a stop-gap approach while longitudinal planning for longitudinal curriculum integration was underway. MATERIALS AND METHODS: Each week, a planetary health fact (Did you know?) with a corresponding link were embedded at the bottom of a relevant PowerPoint lecture slide to match the topic of the week in a health science and medicine Physiology subject. The embedded facts were a mix of effects on health and the environmental impacts of healthcare activities, such as medical imaging. No other formal planetary health teaching was conducted in the subject. At the end of the semester, 44% of 100 students completed a survey regarding their perceptions of the planetary health inclusions. RESULTS: Participants reported an appreciation of the facts, found them helpful for their overall learning, and were interested in learning about healthcare’s large environmental footprint. Seventy-one percent were able to provide a reasonable definition of planetary health. Half of the participants reported their actions, behaviours, and thoughts had changed as a result of the planetary health inclusions. CONCLUSIONS: This study provides a relatively simple approach for individual educators to include planetary health concepts into existing health professions subjects until more longitudinal curriculum revisions can be undertaken. Based on our findings, we would, however, recommend providing students with a brief introduction in terms of why planetary health has been included either at the start of the first lecture or as a 10-min video.
Existing frameworks for interpreting and acting upon the health consequences of climate change fail to engage with the multiple and complex forms of loss and damage that Indigenous peoples experience to their health and wellbeing in a changing climate. Using a case study of Maori in Aotearoa New Zealand, we call for a new research agenda that foregrounds Indigenous peoples’ collective, relational perspectives on health and wellbeing in order to better conceptualise the health implications of climate change. The agenda builds understanding and recognition of intangible loss and damages, bringing multiple knowledge systems and worldviews into conversation to drive adaptation that not only safeguards but also promotes the visions Indigenous peoples have for their health and wellbeing.
BACKGROUND: Dire forecasts predict that an increasingly hostile environment globally will increase the threats to human health. Infants and young children are especially at risk because children are particularly vulnerable to climate-related stressors. The childhood diseases most affected, the breadth and magnitude of future health problems and the time frame over which these problems will manifest remain largely unknown. OBJECTIVES: To review the possibility that spacially explicit analyses can be used to determine how climate change has affected children’s health to date and whether these analyses can be used for future projections. METHODS: As an example of whether these objectives can be achieved, all available Australian environmental and health databases were reviewed. RESULTS: Environmental and health data in Australia have been collected for up to 30 years for the same spatial areas at ‘Statistical Area level 1’ (SA1) scale. SA1s are defined as having a population of between 200 and 800 people and collectively they cover the whole of Australia without gaps or overlap. Although the SA1 environmental and health data have been collected separately, they can be merged to allow detailed statistical analyses that can determine how climate change has affected the health of children. CONCLUSIONS: The availability of environmental and health datasets that share the same precise spatial coordinates provides a pathway whereby past and emerging effects on child health can be measured and predicted into the future. Given that the future health and well-being of children is one of society’s greatest concerns, this information is urgently needed.
Objective Identify the views of healthcare leaders towards public healthcare’s carbon footprint; the importance or not of healthcare energy supply and sources and; the perceived key barriers for Victorian health care to show leadership on renewable energy sources and supply. Methods Self-administered questionnaire (10 Likert scale, two open-ended questions) among 24 Victorian Health Chief Executive Officers (CEOs). Responses were anonymous. Descriptive analysis was conducted. Results Overall, 13/24 (54%) of CEOs responded. A majority (11/13) agreed that climate change is causing real and accelerating harm to health and the environment, with impacts on patients, staff and services a current issue. One hundred percent (13/13) saw leadership by the public healthcare sector on environmental sustainability as an important responsibility (strongly agreed, 9/13 (69%); agreed, 4/13 (31%)), with most CEOs supporting their institution increasing the amount of renewable electricity supply over-and-above grid levels (strongly agreed, 3/13 (23%); agreed, 9/13 (69%)). However, support for renewable electricity was, for the most part, aspirational and not perceived as a current priority. The key perceived barriers to increasing renewable electricity supply were Health Purchasing Victoria contract and financial constraints. Conclusions Health care itself has a carbon footprint. Public healthcare CEOs are supportive of their institutions increasing use of renewable electricity supply, yet perceived barriers regarding inflexible and poorly transparent purchasing contracts and financial cost exist. What is known about the topic? Australian health care contributes ~7 percent to Australia’s total carbon emissions, with hospital energy consumption (coal-generated electricity and natural/fossil gas) a large majority. An executive level champion is a consistent factor across health services that are taking the lead on environmental sustainability. What does this paper add? Our research is original in understanding the views of Victorian public healthcare CEOs on climate change, renewable energy supply and key barriers to increasing uptake. A majority of public healthcare CEOs see energy choices as an important issue for their patients, staff and institution, and that greater leadership should be shown by health care in light of the urgency required to address greenhouse gas emissions. However, support for renewable electricity was, for the most part, aspirational, with specific barriers identified across the healthcare network. What are the implications for practitioners? This research provides information that can inform a pathway to healthcare decarbonisation via sector-wide action.
Introduction: Flooding causes significant mortality and morbidity, with impacts expected to increase with climate change. Ensuring adequate country-level flood mitigation and response capacity is key. Lifeguards, traditionally used for drowning prevention, may represent an additional workforce for flood emergency response. Methods: Through an anonymous, online survey, we explored experiences, beliefs, and attitudes of a convenience sample of surf lifeguards from Australia and England towards lifeguards’ involvement in flood response. Respondents were recruited via Surf Life Saving Australia and Great Britain and had prior training in flood rescue. Analysis comprised descriptive statistics and thematic coding of free-text responses. Results: Forty-four responses were received (93.2% male, 34.1% aged 50-59 years; 61.4% from Australia; 61.4% with >= 16 years lifesaving experience). Twenty-nine respondents (65.9%) self-reported having previously responded to flooding, 15 of which responded prior to receiving flood training. Lifeguards commonly reported being involved in the flood response phase (n = 28). Respondents identified rescue skills (n = 43; 97.7%), awareness of water conditions (n = 40; 90.9%), and radio communication protocols (n = 40; 90.9%) as relevant in a flood scenario. Respondents broadly agreed lifeguards were an asset in flood response due to transferrable skills, including to bolster existing capacity. However, respondents noted need for greater recognition, for involvement earlier in flood response and for flood-specific training and equipment prior to deployment. Discussion & Conclusions: Lifeguards represent a willing and able workforce to support flood mitigation and response, some of whom are already being tasked with such work. Provision of flood-specific training and equipment are vital, as is addressing intemperability tensions.
BACKGROUND: Education is a social tipping intervention necessary for stabilising the earth’s climate by 2050. Integrating sustainable healthcare into healthcare professions curricula is a key action to raise awareness. OBJECTIVES: This study aimed to: i) investigate nursing students’ attitudes towards and awareness of climate change and sustainability issues and its inclusion in nurse education, ii) explore differences across a range of countries, and iii) compare attitudes in 2019 with those of a similar sample in 2014. DESIGN: A cross-sectional multicentre study. Data were collected through the Sustainability Attitudes in Nursing Survey (SANS_2) questionnaire. SETTINGS: Seven different universities and schools of nursing in five countries (UK, Spain, Germany, Sweden, and Australia). PARTICIPANTS: A convenience sample of first-year undergraduate nursing students. METHODS: The SANS_2 questionnaire was self-administered by nursing students at the seven participating universities at the start of their undergraduate degree, between September 2019 and February 2020. RESULTS: Participants from all seven universities (N = 846) consistently showed awareness and held positive attitudes towards the inclusion of climate change and sustainability issues in the nursing curriculum (M = 5.472; SD: 1.05; min-max 1-6). The relevance of climate change and sustainability to nursing were the highest scored items. Esslingen-Tübingen students scored the highest in the ‘inclusion of climate change and sustainability in the nursing curricula’. Students at all universities applied the principles of sustainability to a significant extent at home. Nursing students’ attitudes towards climate change and sustainability showed significantly higher values in 2019 (Universities of Plymouth, Brighton, Esslingen-Tübingen, Jaen, Murcia, Dalarna, and Queensland) than in 2014 (universities of Plymouth, Jaen, Esslingen, and Switzerland). CONCLUSIONS: Nursing students have increasingly positive attitudes towards the inclusion of sustainability and climate change in their nursing curriculum. They also recognise the importance of education regarding sustainability and the impact of climate change on health, supporting formal preparation for environmental literacy. It is time to act on this positive trend in nursing students’ attitudes by integrating these competencies into nursing curricula.
Wildfires can have rapid and long-term effects on air quality, human health, climate change, and the environment. Smoke from large wildfires can travel long distances and have a harmful effect on human health, the environment, and climate in other areas. More recently, in 2018-2019 there have been many large fires. This study focused on the wildfires that occurred in the United States of America (USA), Brazil, and Australia using Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP) and a TROPOspheric Monitoring Instrument (TROPOMI). Specifically, we analyzed the spatial-temporal distribution of black carbon (BC) and carbon monoxide (CO) and the vertical distribution of smoke. Based on the results, the highest detection of smoke (similar to 14 km) was observed in Brazil; meanwhile, Australia showed the largest BC column burden of similar to 1.5 mg/m(2). The meteorological conditions were similar for all sites during the fires. Moderate temperatures (between 32 and 42 degrees C) and relative humidity (30-50%) were observed, which resulted in drier conditions favorable for the burning of fires. However, the number of active fires was different for each site, with Brazil having 13 times more active fires than the USA and five times more than the number of active fires in Australia. However, the high number of active fires did not translate to higher atmospheric constituent emissions. Overall, this work provides a better understanding of wildfire behavior and the role of meteorological conditions in emissions at various sites.
Sexual violence is largely absent from studies on violence against women in disasters. The role of men in perpetrating violence against women is overlooked or excused and women are usually blamed in both countries. A review of 2 studies of men’s violence against women after floods and earthquakes in Iran and bushfires in Australia show remarkable similarities. Although cultural contexts and the way gender inequality is established and demonstrated are different, these studies reveal unexpected parallels. The context of disaster lays it bare. Participants of both studies were disaster-affected people in Iran and Australia who revealed the taboos that prevent women speaking of violence that is exacerbated in a disaster context. Men play important roles in preventing and responding to violence against women as the result of their responsibilities and positions at the household and community levels. The objective of this paper was to compare the findings from these studies and consider the difficulties faced in conducting studies related to the roles of men and women roles during and after disaster events.
There is limited knowledge about how crises are framed on different social media platforms specifically in a non-Western cultural context. This study compares how extreme environmental crises-Hurricane Maria and haze-were framed on Twitter and Weibo. Through word-cloud, co-occurrence, and thematic analyses with Hurricane Maria-related tweets, this study identified two major frames of this crisis: a disaster frame and a political frame. Similarly, by analyzing haze-related posts on Sina Weibo, two major frames emerged: an environmental frame and a health frame. Both crises were largely framed as environmental issues rather than health risks or crises. Such framing helps shape the existence of Hurricane Maria and haze as legitimate facts. The findings also reveal that cultural variances, eg, power distance, collectivist-individualist culture, and uncertainty avoidance, impact crisis framing. This study indicates the importance of designing culture-fit messages and incorporating social media strategies in crisis communication while developing emergency management plans and adds knowledge to the limited literature on social-mediated crisis communication in different cultural contexts. Such knowledge will provide theoretical and practical implications for crisis scholars, emergency management practitioners, and policymakers.
Aim The distribution of Yersinia pestis, the pathogen that causes plague in humans, is reliant upon transmission between host species; however, the degree to which host species distributions dictate the distribution of Y. pestis, compared with limitations imposed by the environmental niche of Y. pestis per se, is debated. We test whether the present-day environmental niche of Y. pestis differs between its native range and an invaded range and whether biotic factors (host distributions) can explain observed discrepancies. Location North America and Central Asia. Major taxa studied Yersinia pestis. Methods We use environmental niche models to determine whether the current climatic niche of Y. pestis differs between its native range in Asia and its invaded range in North America. We then test whether the inclusion of information on the distribution of host species improves the ability of models to capture the North American niche. We use geographical null models to guard against spurious correlations arising from spatially autocorrelated occurrence points. Results The current climatic niche of Y. pestis differs between its native and invaded regions. The Asian niche overpredicted the distribution of Y. pestis across North America. Including biotic factors along with the native climatic niche increased niche overlap between the native and invaded models, and models containing only biotic factors performed better than the native climatic niche alone. Geographical null models confirmed that the increased niche overlap through inclusion of biotic factors did not, with a couple of exceptions, arise solely from spatially autocorrelated occurrences. Main conclusions The current climatic niche in Central Asia differs from the current climatic niche in North America. Inclusion of biotic factors improved the fit of models to the Y. pestis distribution data in its invaded region better than climate variables alone. This highlights the importance of host species when investigating zoonotic disease introductions and suggests that climatic variables alone are insufficient to predict disease distribution in novel environments.
This study examines point and non-point sources of air pollution and particulate matter and their associated socioeconomic and health impacts in South Asian countries, primarily India, China, and Pakistan. The legislative frameworks, policy gaps, and targeted solutions are also scrutinized. The major cities in these countries have surpassed the permissible limits defined by WHO for sulfur dioxide, carbon monoxide, particulate matter, and nitrogen dioxide. As a result, they are facing widespread health problems, disabilities, and causalities at extreme events. Populations in these countries are comparatively more prone to air pollution effects because they spend more time in the open air, increasing their likelihood of exposure to air pollutants. The elevated level of air pollutants and their long-term exposure increases the susceptibility to several chronic/acute diseases, i.e., obstructive pulmonary diseases, acute respiratory distress, chronic bronchitis, and emphysema. More in-depth spatial-temporal air pollution monitoring studies in China, India, and Pakistan are recommended. The study findings suggest that policymakers at the local, national, and regional levels should devise targeted policies by considering all the relevant parameters, including the country’s economic status, local meteorological conditions, industrial interests, public lifestyle, and national literacy rate. This approach will also help design and implement more efficient policies which are less likely to fail when brought into practice.
Mountainous regions are highly hazardous, and these hazards often lead to loss of human life. The Hindu Kush Himalaya (HKH), like many mountainous regions, is the site of multiple and overlapping natural hazards, but the distribution of multi-hazard risk and the populations exposed to it are poorly understood. Here, we present high-resolution transboundary models describing susceptibility to floods, landslides, and wildfires to understand population exposure to multi-hazard risk across the HKH. These models are created from historical remotely sensed data and hazard catalogs by the maximum entropy (Maxent) machine learning technique. Our results show that human settlements in the HKH are disproportionately concentrated in areas of high multi-hazard risk. In contrast, low-hazard areas are disproportionately unpopulated. Nearly half of the population in the region lives in areas that are highly susceptible to more than one hazard. Warm low-altitude foothill areas with perennially moist soils were identified as highly susceptible to multiple hazards. This area comprises only 31% of the study region, but is home to 49% of its population. The results also show that areas susceptible to multiple hazards are also major corridors of current migration and urban expansion, suggesting that current rates and patterns of urbanization will continue to put more people at risk. This study establishes that the population in the HKH is concentrated in areas susceptible to multiple hazards and suggests that current patterns of human movement will continue to increase exposure to multi-hazards in the HKH.
Several countries have been affected by natural hazards during the COVID-19 pandemic. The combination of the pandemic and natural hazards has led to serious challenges that include financial losses and psychosocial stress. Additionally, this compound disaster affected evacuation decision making, where to evacuate, volunteer participation in mitigation and recovery, volunteer support acceptance, and interest in other hazard risks. This study investigated the impact of COVID-19 on disaster response and recovery from various types of hazards, with regard to preparedness, evacuation, volunteering, early recovery, awareness and knowledge of different types of hazards, and preparedness capacity development. This study targets hazards such as Cyclone Amphan in India, the Kumamoto flood in Japan, Typhoon Rolly in the Philippines, and the California wildfires in the U.S. This study made several recommendations, such as the fact that mental health support must be taken into consideration during COVID-19 recovery. It is necessary to improve the genral condition of evacuation centers in order to encourage people to act immediately. A pandemic situation necessitates a strong communication strategy and campaign with particular regard to the safety of evacuation centers, the necessity of a lockdown, and the duration required for it to reduce the psychological impact. Both national and local governments are expected to strengthen their disaster risk reduction (DRR) capacity, which calls for the multi-hazard management of disaster risk at all levels and across all sectors.
Cascading hazards occur frequently. Unexpected casualties and losses of properties, or even impacts on the society and the environment may ensue from failure to anticipate the amplified risks induced by cascading hazards. Current risk assessment methods pay relatively less attention to quantifying the increased human risk related to “cascading” events. An improved framework for quantifying the human risk caused by cascading hazards is proposed in this paper. The framework considers the interactions among the cascading hazards and among the vulnerabilities of elements to these hazards. Its kernel is to scientifically anticipate and gear up for any new intensified hazards, which may otherwise lead to serious social aftermath. The framework is illustrated with a multi-hazard example close to the epicenter of the Wenchuan earthquake, which involved a chain of hazards including slope failures, a large debris flow, river damming, and flooding.
Indigenous perspectives on the effects of climate change are frequently elicited through surveys and interviews, and the responses are compared to meteorological data. However, there remains a limited approach to examining the underlying predictors that best determine Indigenous support for adaptation strategies. This study utilizes partial least squares-structural equation modeling (PLS-SEM) to identify the main indicators of Indigenous support for coping with unfavorable climate impacts. Using a case study and a purposive sampling approach, a survey of 328 Indigenous peoples was conducted in rural Kinabatangan, Sabah, Malaysia. Results showed that communities’ attitudes had a large effect on the Indigenous support for adaptation (f(2) = 0.380), followed by the communities’ awarenesses (f(2) = 0.063), rapid onset events (f(2) = 0.051), and climate impacts on tourism (f(2) = 0.016). Communities prioritize the impacts of climate change on their health, livelihoods, and environmental resources. Nevertheless, they do not draw a causal link between the effects and responses to climate hazards. Coping strategies such as the inclusion of Indigenous livelihoods, a bottom-up approach, and transparent communication are suggested to cultivate Indigenous support for climate change adaptation. Decision-makers can apply these findings to prepare climate change policies and enhance the adaptation strategies of Indigenous communities.
PURPOSE: To investigate the effect of climatic parameters in the mesothermal climate area on clinical pregnancy and live birth following fresh single blastocyst transfer. METHODS: This study investigated clinical pregnancies and live births that resulted from 555 ovarian stimulation cycles followed by fresh single blastocyst transfer. The samples were stratified according to climatic conditions (low T, temperature < 12.9 °C; middle T, 12.9 °C ≤ temperature < 22.6 °C; high T, temperature ≥ 22.6 °C; low H, relative humidity < 62.1%; middle H, 62.1% ≤ relative humidity < 66.5%; high H, relative humidity ≥ 66.5%; short S, sunlight duration < 5.2 h; middle S, 5.2 h ≤ sunlight duration < 6.7 h; long S, sunlight duration ≥ 6.7 h). Clinical pregnancy and live birth rates among three groups from each climatic parameter were compared. Multivariable analyses were performed to investigate the effects of climatic conditions on blastocyst development, endometrial thickness, clinical pregnancy, and live birth. RESULTS: A statistically significant difference was found in pregnancy rates among low T (48.8%), middle T (37.3%), and high T (36.6%) groups. Multivariable analyses revealed that temperature was associated with clinical pregnancy and live birth rates with adjustment for patient age, BMI, type of ovarian stimulation, endometrial thickness, and expansion grade of the transferred blastocyst. The association between climatic parameters and blastocyst development and endometrial thickness was not confirmed. CONCLUSIONS: This study suggests that lower temperatures in the mesothermal climate area could favorably affect the rates of clinical pregnancy and live birth achieved by fresh single blastocyst transfer.
Previous studies have demonstrated that outdoor temperature exposure was an important risk factor for respiratory diseases. However, no study investigates the effect of indoor temperature exposure on respiratory diseases and further assesses cumulative effect. The objective of this study is to study the cumulative effect of indoor temperature exposure on emergency department visits due to infectious (IRD) and non-infectious (NIRD) respiratory diseases among older adults. Subjects were collected from the Longitudinal Health Insurance Database in Taiwan. The cumulative degree hours (CDHs) was used to assess the cumulative effect of indoor temperature exposure. A distributed lag nonlinear model with quasi-Poisson function was used to analyze the association between CDHs and emergency department visits due to IRD and NIRD. For IRD, there was a significant risk at 27, 28, 29, 30, and 31 °C when the CDHs exceeded 69, 40, 14, 5, and 1 during the cooling season (May to October), respectively, and at 19, 20, 21, 22, and 23 °C when the CDHs exceeded 8, 1, 1, 35, and 62 during the heating season (November to April), respectively. For NIRD, there was a significant risk at 19, 20, 21, 22, and 23 °C when the CDHs exceeded 1, 1, 16, 36, and 52 during the heating season, respectively; the CDHs at 1 was only associated with the NIRD at 31 °C during the cooling season. Our data also indicated that the CDHs was lower among men than women. We conclude that the cumulative effects of indoor temperature exposure should be considered to reduce IRD risk in both cooling and heating seasons and NIRD risk in heating season and the cumulative effect on different gender.
This study investigated the correlation between spontaneous pneumothorax (SP) and meteorological factors during different seasons. Patients who visited emergency rooms (ERs) in large cities in Korea and were discharged with SP from 2014 to 2016 were included in this study. Data on temperature, air pressure, and wind speed for each region were collected to obtain each factor’s daily maximum, minimum, average, and changes. Days with more than 1 case of SP per million were referred to as pneumothorax days (PD) and those with less than 1 case of SP per million were referred to as non-pneumothorax days (NPD). The environmental factors were assessed on the same day (Day 0), 1 day prior (Day-1), and 2 days prior (Day-2) to PD and NPD per season. A total of 17,846 patients were included in this study. During winter, 4080 patients with SP visited the ERs of large cities with low population densities. The maximum temperature (0.16°C vs 0.76°C, 0.04°C vs 0.87°C, and 0.09°C vs 0.91°C), change in temperature (0.24°C vs 0.90°C, 0.38°C vs 0.81°C, and 0.41°C vs 0.83°C), average atmospheric pressure (0.16 vs 0.52 hPa, 0.25 vs 0.42 hPa, 0.34 vs 0.40 hPa), and maximum atmospheric pressure (0.15 vs 0.53 hPa, 0.28 vs 0.49 hPa, 0.33 vs 0.71 hPa) were greater for Day 0, Day-1, and Day-2, respectively, in PD than in NPD. Meanwhile, the average (0.31 vs 0.48 m/s, 0.28 vs 0.46 m/s, 0.20 vs 0.40 m/s), minimum (0.20 vs 0.31 m/s, 0.18 vs 0.25 m/s, 0.16 vs 0.25 m/s), and maximum (0.44 vs 0.67 m/s, 0.36 vs 0.71 m/s, 0.26 vs 0.58 m/s) wind speeds were slower, and the changes in wind speed (0.44 vs 0.67 m/s, 0.36 vs 0.71 m/s, 0.16 vs 0.25 m/s) were lower for all 3 days in PD than in NPD. High average and change in temperature, slow and unchanging wind speed, and high average and maximum atmospheric pressure were associated with SP. Since many findings of this study were contradictory to previous studies, it is assumed that the interaction of various factors affects SP.
BACKGROUND: The inverse association between ambient temperature and blood pressure (BP) has been investigated in the context of excess cardiovascular mortality in winter. However, the role of skin temperature (ST), which reflects our external and internal thermal environments, in BP regulation remains unclear. Therefore, we examined the association between ST and ambulatory BP and the mediation of ST in BP responses to ambient temperature in real-life settings. METHODS: We conducted a longitudinal analysis using repeated measurements of ambulatory BP and ST for 48 hours (30 711 daytime readings and 17 382 nighttime readings) among 584 older adults between October and March (2012-2014). Linear mixed-effect models were used to examine the association of distal (mean of wrist and ankle) and proximal (abdomen) ST with systolic BP. The mediation of ST in BP responses to ambient temperature was examined using path analysis. RESULTS: Distal and proximal STs were significantly associated with systolic BP during the daytime (regression coefficients: -4.27 mm Hg [95% CI, -4.58 to -3.96] and -2.74 mm Hg [95% CI, -3.14 to -2.56] per SD of ST, respectively), independent of potential confounders. The significant associations also existed during nighttime. The mediation effect of distal ST was 7.1 times higher than that of proximal ST during daytime, while those of distal and proximal STs during nighttime were almost identical. CONCLUSIONS: ST, especially in distal regions, was inversely associated with ambulatory BP. Our results have the potential for application to interventional studies targeting ST regulation to reduce excess cardiovascular deaths in winter.
Thermal environment can greatly influence one’s sleep quality, yet research into thermal satisfaction and sleep quality is lacking. This study investigates the thermal environment, thermal sensation, satisfaction and sleep quality of university students residing in dormitory in Hong Kong in winter. Based on subjective questionnaire and environmental measurement, it was found that under the same thermal condition, females selected a bedding system with higher total thermal resistance than males. Self-assessed overall sleep quality was associated with mid-sleep/early awakenings, refreshment and duration of sleep, and sleep quality was largely influenced by thermal comfort and satisfaction. Thermally satisfied subjects and those with neutral thermal sensation had significantly better sleep quality. Thermal satisfaction and sleep quality toward hot and cold environments were also different. Existing sleeping thermal comfort models failed to predict accurately the thermal sensation in sleeping state, suggesting a need for the development of better prediction model for sleeping person.
CONTEXT: Climate change is the biggest global health threat and also the greatest health opportunity of the 21(st) century. Five warmest years among the last 140 years occurred between 2015 and 2019. Limited information is available regarding the knowledge and practices of medical students towards climate change, especially in India. SETTINGS AND DESIGN: A cross-sectional survey was conducted in two medical colleges of Karimnagar city from January 2021 to July 2021 involving MBBS and Post-graduate students as study participants. METHODS AND MATERIAL: 903 undergraduate and post-graduate medical students who consented for the study were included. A pre-structured questionnaire was used. STATISTICAL ANALYSIS USED: Data is presented in frequencies and proportions with 95% confidence interval and Chi-square test is used as test of significance. RESULTS: Poor knowledge regarding Sustainable Developmental Goal for climate action, Organisations dealing climate change and Government actions towards climate change were observed among study participants. Cardiovascular and respiratory diseases (84%) were answered as the major health impacts of climate change. Majority (97.4%) of the participants agreed that ‘human actions are also the cause for global warming’. Environment-friendly practices were observed significantly high among participants with adequate knowledge. Major (72%) source of learning about climate change was via internet. CONCLUSIONS: Our study found that major proportion of participants doesn’t have environment-friendly practices. However, the participants with adequate knowledge about climate change were observed to have more eco-friendly practices compared to participants with inadequate knowledge.
Air pollution has massive impacts on human life and poor air quality results in three million deaths annually. Air pollution can result from natural causes, including volcanic eruptions and extreme droughts, or human activities, including motor vehicle emissions, industry, and the burning of farmland and forests. Emission sources emit multiple pollutant types with diverse characteristics and impacts. However, there has been little research on the risk of multiple air pollutants; thus, it is difficult to identify multi-pollutant mitigation processes, particularly in Southeast Asia, where air pollution moves dynamically across national borders. In this study, the main objective was to develop a multi-air pollution risk index product for CO, NO(2), and SO(2) based on Sentinel-5P remote sensing data from 2019 to 2020. The risk index was developed by integrating hazard, vulnerability, and exposure analyses. Hazard analysis considers air pollution data from remote sensing, vulnerability analysis considers the air pollution sources, and exposure analysis considers the population density. The novelty of this study lies in its development of a multi-risk model that considers the weights obtained from the relationship between the hazard and vulnerability parameters. The highest air pollution risk index values were observed in urban areas, with a high exposure index that originates from pollution caused by human activity. Multi-risk analysis of the three air pollutants revealed that Singapore, Vietnam, and the Philippines had the largest percentages of high-risk areas, while Indonesia had the largest total high-risk area (4361 km(2)). Using the findings of this study, the patterns and characteristics of the risk distribution of multiple air pollutants in Southeast Asia can be identified, which can be used to mitigate multi-pollutant sources, particularly with respect to supporting the clean air targets in the Sustainable Development Goals.
BACKGROUND: An unprovoked seizure is a seizure or a cluster of seizures occurring within 24 h in a patient older than 1 month of age without precipitating factors. Recent studies have reported that extrinsic factors, such as meteorological conditions and air pollutants, may be important in seizure occurrence. Thus, this study aimed to examine the association between the number of visits to the emergency department (ED) by children for nighttime unprovoked seizures and exposure to multi-faceted factors, such as meteorological conditions and air pollution. METHODS: We conducted a clinical observational analysis and reviewed consecutive patients younger than 16 years of age who visited the primary ED center in Kobe City, Japan, during nighttime (7:30 p.m.-7:00 a.m.) between January 1, 2011 and December 31, 2015. We investigated the effects of meteorological factors and air pollutants on the number of patients with unprovoked seizures using multivariate analysis of Poisson regression estimates. RESULTS: In total, 151,119 children visited the ED, out of which 97 patients presented with unprovoked seizures. The mean age of the patients was 4.7 years (range, 1 month to 15.3 years), and 54.6% of them were boys. The total number of patients with unprovoked seizures showed no significant changes with the seasons; however, there were dominant peaks during the fall and fewer visits during the summer. The multivariate analysis of Poisson regression estimates revealed a significant positive relationship between the number of patients presenting with unprovoked seizures and precipitation (+1 patient/87 mm; p=0.03) and methane (+1 patient/0.14ppm; p=0.03) levels and a negative relationship between the number of patients presenting with unprovoked seizures and nitrogen dioxide level (-1 patient/0.02ppm; p=0.04). CONCLUSIONS: The present study is the first to evaluate the association between the number of children who presented to the ED with nighttime unprovoked seizures and environmental factors after controlling for confounding factors.
Objective: Acute pharyngitis is common worldwide. Meteorological changes contribute to respiratory infections. This study aims to explore the correlation between acute pharyngitis and meteorological parameters. Methods: We collected the monthly acute pharyngitis cases in our hospital and the meteorological data, including temperature, relative humidity, and air quality index (AQI) of Shanghai, China, from January, 2015, to December, 2017. Pearson correlation and multivariable regression analysis were used to explore the association between meteorological parameters and the monthly hospital visits. Results: A total of 8287 patients were included in this study, and the monthly number of hospital visits was 230.2 ± 39.0. The best air quality index was 46.4 and the worst was 113.2. Temperature ranged from 5.2 °C to 32.0 °C, and relative humidity ranged from 59.4% to 83.1%. The monthly hospital visits of acute pharyngitis were negatively correlated with temperature (r = -.558, 95% CI -.746, -.274) and relative humidity (r = -.480, 95% CI -.695, -.137). A decrease of 1 °C could cause an increase in hospital visits by 1.9. No significant correlation was found were found between acute pharyngitis cases and AQI (P = .051, 95% CI -.005, .590). Multivariable linear regression analysis showed the temperature was the independent risk factor of acute pharyngitis (coefficient = -1.906, P = .022). Conclusion: Low temperature might cause an increased incidence of acute pharyngitis.
PURPOSE: With the aging population in Japan, the prediction of ambulance transports is needed to save the limited medical resources. Some meteorological factors were risks of ambulance transports, but it is difficult to predict in a classically statistical way because Japan has 4 seasons. We tried to make prediction models for ambulance transports using the deep learning (DL) framework, Prediction One (Sony Network Communications Inc., Tokyo, Japan), with the meteorological and calendarial variables. MATERIALS AND METHODS: We retrospectively investigated the daily ambulance transports and meteorological data between 2017 and 2019. First, to confirm their association, we performed classically statistical analysis. Second, to test the DL framework’s utility for ambulance transports prediction, we made 3 prediction models for daily ambulance transports (total daily ambulance transports more than 5 or not, cardiopulmonary arrest (CPA), and trauma) using meteorological and calendarial factors and evaluated their accuracies by internal cross-validation. RESULTS: During the 1095 days of 3 years, the total ambulance transports were 5948, including 240 CPAs and 337 traumas. Cardiogenic CPA accounted for 72.3%, according to the Utstein classification. The relation between ambulance transports and meteorological parameters by polynomial curves were statistically obtained, but their r(2)s were small. On the other hand, all DL-based prediction models obtained satisfactory accuracies in the internal cross-validation. The areas under the curves obtained from each model were all over 0.947. CONCLUSION: We could statistically make polynomial curves between the meteorological variables and the number of ambulance transport. We also preliminarily made DL-based prediction models. The DL-based prediction for daily ambulance transports would be used in the future, leading to solving the lack of medical resources in Japan.
Urolithiasis is a prevalent medical disease affecting the general population. Many epidemiological studies reported an association between a geographic area with a high mean daily temperature and urolithiasis disease. However, it is unclear if the seasonal variation in a high temperature geographical area will affect the acute presentation of renal colic to the emergency department. The aim of this study was to identify the effect of the seasonal variation on the presentation with acute urolithiasis disease. The design was a retrospective chart review, using the database in King Abdulaziz Medical City that was retrieved by the data management office in King Abdullah International Medical Research Center, Riyadh, Kingdom of Saudi Arabia. The study period was from January 26, 2016, to the end of December 2019. All patients who presented with renal colic, and diagnosed with urolithiasis using a noncontrast-enhanced computed tomography scan, have been included. A total of 1057 patients were included in this study. The majority (71.24%, n = 753) were male, and the mean age was 42.33 ± 16.12 years. The highest proportion presented in summer (31.22%), followed by spring (26.87%), fall (24.12%), and winter (17.79%). The majority of the sample (84.77%) presented with ureteral stones, and 15.23%with kidney stones. Most of the sample (78.33%) had no history of previous stone formation, with 21.67% being current stone former. The acute presentation with urolithiasis is higher during summer, followed by spring, fall, and winter. A public educational program is highly recommended to increase awareness about stone formation and the appropriate avoidance methods. To this end, additional research is required to understand the stone composition and appropriate methods to avoid developing urolithiasis.
OBJECTIVES: This study aimed to analyse if there were any associations between patulous Eustachian tube occurrence and climatic factors and seasonality. METHODS: The correlation between the monthly average number of patients diagnosed with patulous Eustachian tube and climatic factors in Seoul, Korea, from January 2010 to December 2016, was statistically analysed using national data sets. RESULTS: The relative risk for patulous Eustachian tube occurrence according to season was significantly higher in summer and autumn, and lower in winter than in spring (relative risk (95 per cent confidence interval): 1.334 (1.267-1.404), 1.219 (1.157-1.285) and 0.889 (0.840-0.941) for summer, autumn and winter, respectively). Temperature, atmospheric pressure and relative humidity had a moderate positive (r = 0.648), negative (r = -0.601) and positive (r = 0.492) correlation with the number of patulous Eustachian tube cases, respectively. CONCLUSION: The number of patulous Eustachian tube cases was highest in summer and increased in proportion to changes in temperature and humidity, which could be due to physiological changes caused by climatic factors or diet trends.
Previous studies have suggested an increased risk of ischemic heart disease related to air pollution. This study aimed to explore both the short-term and long-term effects of air pollutants on the risk of ischemic heart disease after adjusting for meteorological factors. The Korean National Health Insurance Service-Health Screening Cohort from 2002 to 2013 was used. Overall, 2155 participants with ischemic heart disease and 8620 control participants were analyzed. The meteorological data and air pollution data, including SO(2) (ppm), NO(2) (ppm), O(3) (ppm), CO (ppm), and particulate matter (PM)(10) (μg/m(3)), were analyzed using conditional logistic regression. Subgroup analyses were performed according to age, sex, income, and region of residence. One-month exposure to SO(2) was related to 1.36-fold higher odds for ischemic heart disease (95% confidence interval [95% CI] 1.06-1.75). One-year exposure to SO(2), O(3), and PM(10) was associated with 1.58- (95% CI 1.01-2.47), 1.53- (95% CI 1.27-1.84), and 1.14 (95% CI 1.02-1.26)-fold higher odds for ischemic heart disease. In subgroup analyses, the ≥ 60-year-old group, men, individuals with low income, and urban groups demonstrated higher odds associated with 1-month exposure to SO(2). Short-term exposure to SO(2) and long-term exposure to SO(2,) O(3), and PM(10) were related to ischemic heart disease.
OBJECTIVE: Many epidemiological studies have observed the association of air pollutant exposure with the onset, progression, and mortality of stroke. The aim of this study was to investigate the associations of air pollutants, including SO(2), NO(2), O(3), CO, and PM(10), with stroke according to exposure duration. METHODS: Data from the Korean National Health Insurance Service-Health Screening Cohort from 2002 to 2015 were obtained. The 21,240 patients who were admitted for or died due to stroke were 1:4 matched for age, sex, income, and region of residence with 84,960 control participants. The meteorological factors of mean, highest, and lowest temperatures; relative humidity; ambient atmospheric pressure; and air pollutant concentrations (SO(2), NO(2), O(3), CO, and PM(10)) were analyzed to determine their associations with stroke. The odds ratios for stroke after exposure to each meteorological factor and air pollutant at 7 and 30 days were calculated in the stroke and control groups. Subgroup analyses were conducted according to age, sex, income, and region of residence. RESULTS: The odds ratio associated with seven days of exposure to CO was 1.16 (95% CI = 1.04-1.31) in stroke patients. For 30 days of exposure, the odds ratio associated with CO was 1.16 (95% CI = 1.02-1.32) in stroke patients. Seven and 30 days of NO(2) exposure were inversely associated with stroke. The odds ratio associated with seven days of exposure to O(3) was 1.16 (95% CI = 1.01-1.32) in ischemic stroke patients. Both ischemic and hemorrhagic stroke had negative associations with 7 and 30 days of NO(2) exposure. CONCLUSION: Both short- and long-term exposure to CO were related to stroke.
BACKGROUND: The association between short-term exposure to ambient air pollution and blood pressure has been inconsistent, as reported in the literature. OBJECTIVE: This study aimed to investigate the relationship between short-term ambient air pollution exposure and patient-level home blood pressure (HBP). METHODS: Patients with chronic cardiovascular diseases from a telehealth care program at a university-affiliated hospital were enrolled as the study population. HBP was measured by patients or their caregivers. Hourly meteorological data (including temperature, relative humidity, wind speed, and rainfall) and ambient air pollution monitoring data (including CO, NO(2), particulate matter with a diameter of <10 µm, particulate matter with a diameter of <2.5 µm, and SO(2)) during the same time period were obtained from the Central Weather Bureau and the Environmental Protection Administration in Taiwan, respectively. A stepwise multivariate repeated generalized estimating equation model was used to assess the significant factors for predicting systolic and diastolic blood pressure (SBP and DBP). RESULTS: A total of 253 patients and 110,715 HBP measurements were evaluated in this study. On multivariate analysis, demographic, clinical, meteorological factors, and air pollutants significantly affected the HBP (both SBP and DBP). All 5 air pollutants evaluated in this study showed a significant, nonlinear association with both home SBP and DBP. Compared with demographic and clinical factors, environmental factors (meteorological factors and air pollutants) played a minor yet significant role in the regulation of HBP. CONCLUSIONS: Short-term exposure to ambient air pollution significantly affects HBP in patients with chronic cardiovascular disease.
Although several studies have attempted to develop a model for predicting 30-day re-hospitalization, few attempts have been made for sufficient verification and multi-center expansion for clinical use. In this study, we developed a model that predicts unplanned hospital readmission within 30 days of discharge; the model is based on a common data model and considers weather and air quality factors, and can be easily extended to multiple hospitals. We developed and compared four tree-based machine learning methods: decision tree, random forest, AdaBoost, and gradient boosting machine (GBM). Above all, GBM showed the highest AUC performance of 75.1 in the clinical model, while the clinical and W-score model showed the best performance of 73.9 for musculoskeletal diseases. Further, PM10, rainfall, and maximum temperature were the weather and air quality variables that most impacted the model. In addition, external validation has confirmed that the model based on weather and air quality factors has transportability to adapt to other hospital systems.
The time-placement scheme of climate extreme changes is important. In this regard, a set of a compound indices derived using daily resolution climatic time series data is examined to assess climate change in Iran. The compound indices were examined for 47 synoptic meteorological stations during 1981-2015. The results show that most stations experienced a negative trend for the cool/dry (CD) and cool/wet (CW) index and a positive trend in CW was observed in some dispersed small areas. Both warm/dry (WD) and warm/wet (WW) indices have similar behavior, but the magnitude and spatial consistency of WW days were much less than WD days. The results show that more than 80% of stations experienced a decrease in the annual occurrence of the cold modes and an increase in the annual occurrence of the warm modes. On the other hand, universal thermal climate index (UTCI) change demonstrated a significant increase in the annual occurrence of strong heat stress (32-38 degrees C) and significant decrease in the annual occurrence of no thermal stress class (9-26 degrees C). Moreover, trends in tourism climate index (TCI), including TCI >= 60 and TCI >= 80, showed similar changes but with weak spatial coherence.
Local and Indigenous knowledge systems worldwide indicate adaptation and mitigation strategies to climate change. Particularly in regions that are massively affected by climatic changes, such as the Pacific Island States, there is a need for increased and combined research on the role which these knowledge systems can play internationally. For this reason, this article provides a synthesis of empirical results and approaches to local and Indigenous climate change adaptation and mitigation strategies in selected South Pacific Island States by using a meta-ethnographic approach. The reviewed literature is associated with the sub-disciplinary perspective of the Anthropology of Climate Change. The results of the meta-ethnographic analysis are discussed based on three thematic focal points: First, the empirical ground of local understandings of climate change and its theoretical conceptualization(s) are constituted. Second, the results of practices for adaptation to climate change are synthesized and presented in detail throughout one example. Third, the synthesis of climate change mitigation practices is outlined with a specific focus on human-environment relationships.
[This corrects the article DOI: 10.2147/COPD.S224198.].
PURPOSE: To investigate environmental factors associated with corneal morphologic changes. METHODS: A cross-sectional study was conducted, which enrolled adults of the Han ethnicity aged 18 to 44 years from 20 cities. The cornea-related morphology was measured using an ocular anterior segment analysis system. The geographic indexes of each city and meteorological indexes of daily city-level data from the past 40 years (1980-2019) were obtained. Correlation analyses at the city level and multilevel model analyses at the eye level were performed. RESULTS: In total, 114,067 eyes were used for analysis. In the correlation analyses at the city level, the corneal thickness was positively correlated with the mean values of precipitation (highest r [correlation coefficient]: >0.700), temperature, and relative humidity (RH), as well as the amount of annual variation in precipitation (r: 0.548 to 0.721), and negatively correlated with the mean daily difference in the temperature (DIF T), duration of sunshine, and variance in RH (r: -0.694 to 0.495). In contrast, the anterior chamber (AC) volume was negatively correlated with the mean values of precipitation, temperature, RH, and the amount of annual variation in precipitation (r: -0.672 to -0.448), and positively associated with the mean DIF T (r = 0.570) and variance in temperature (r = 0.507). In total 19,988 eyes were analyzed at the eye level. After adjusting for age, precipitation was the major explanatory factor among the environmental factors for the variability in corneal thickness and AC volume. CONCLUSIONS: Individuals who were raised in warm and wet environments had thicker corneas and smaller AC volumes than those from cold and dry ambient environments. Our findings demonstrate the role of local environmental factors in corneal-related morphology.
Nowadays, owing to population growth, increasing environmental pollution, and lifestyle changes, the number of asthmatics has significantly increased. Therefore, the purpose of our study was to determine the asthma-prone areas in Tehran, Iran considering environmental, spatial factors. Initially, we built a spatial database using 872 locations of children with asthma and 13 environmental factors affecting the disease-distance to parks and streets, rainfall, temperature, humidity, pressure, wind speed, particulate matter (PM 10 and PM 2.5), ozone (O(3)), sulfur dioxide (SO(2)), carbon monoxide (CO), and nitrogen dioxide (NO(2)). Subsequently, utilizing this spatial database, a random forest (RF) machine learning model, and a geographic information system, we prepared a map of asthma-prone areas. For modeling and validation, we deployed 70% and 30%, respectively, of the locations of children with asthma. The results of spatial autocorrelation and RF model showed that the criteria of distance to parks and streets as well as PM 2.5 and PM 10 had the greatest impact on asthma occurrence in the study area. Spatial autocorrelation analyses indicated that the distribution of asthma cases was not random. According to receiver operating characteristic results, the RF model had good accuracy (the area under the curve was 0.987 and 0.921, respectively, for training and testing data).
Arsenic pollution of shallow groundwater is serious in Hetao Basin. At present, there are few studies on the seasonal variation and mechanism of high As groundwater. In order to master the risk difference and influence mechanism of high As groundwater in different seasons, we collected 506 shallow groundwater samples in the Hetao Basin, and used climatic factors, topographic factors, and others (influence of irrigation channels, vegetation index) that are closely distributed with As in groundwater to establish a high-precision random forest model of high As groundwater in the Hetao Basin in summer. We used climate factors as dynamic predictors to predict the distribution of high As risks in winter and established human health risk zones in the Hetao Basin. The results show that from winter to summer, the probability of high As in high risk areas further increases with the influence of factors such as temperature increase, rainfall increase, and enhanced evapotranspiration, while the probability of high As in low risk areas is the opposite and shows a downward trend. The areas with increased probability of high human health risks and stable areas are mainly distributed along the drainage canals and concentrated in the middle of the basin. From winter to summer, as the local residents’ demand for groundwater increases, the probability of high As has increased and stabilized in high risk areas. The number of threatened populations reached 246,000 and 108,000, respectively. Therefore, we need to focus on them. The results of this research explored the changing trend and mechanism of high As groundwater risks under the influence of climate, further enriching the regional high As groundwater research system, and can also be provided as a reference for similar research in other regions.
BACKGROUND AND OBJECTIVES: Climate change impacts are felt unequally worldwide; populations that experience geographical vulnerability, those living in small island states and densely populated coastal areas, and children and women are affected disproportionately. This scoping review aims to synthesize evidence from relevant studies centred on South Asia, identify research gaps specifically focused on children and women’s health, and contribute to knowledge about South Asia’s existing mitigation and adaptation strategies. METHODS: A research librarian executed the search on six databases using controlled vocabulary (e.g., MeSH, Emtree, etc.) and keywords representing the concepts “vulnerable populations” and “climate change” and “health impacts” and “South Asia.” Databases were searched from January 2010 to May 2020. Papers were screened independently by two researchers. RESULTS: Forty-two studies were included, of which 23 were based in India, 14 in Bangladesh, and five in other South Asian countries. Nineteen studies focused on meteorological factors as the primary exposure. In contrast, thirteen focused on extreme weather events, nine on air pollution, and one on salinity in coastal areas. Thirty-four studies focused on the health impacts on children related to extreme weather events, meteorological factors, and air pollution, while only eight studies looked at health impacts on women. Undernutrition, ARI (acute respiratory infection), diarrheal diseases, low birth weight, and premature mortality were the major health impacts attributed to extreme weather events, meteorological factors, and air pollution exposure in children and women in the region. CONCLUSION: Extreme weather events, meteorological factors and air pollution have affected the health of children and women in South Asia. However, the gap in the literature across the South Asian countries concerning relationships between exposure to extreme weather events, meteorological factors, air pollution and health effects, including mental health problems in children and women, are opportunities for future work.
Air pollution has been reported to be associated with chronic obstructive pulmonary disease (COPD). Our study aim was to examine the mediating effects of air pollution on climate-associated health outcomes of COPD patients. A cross-sectional study of 117 COPD patients was conducted in a hospital in Taiwan. We measured the lung function, 6-min walking distance, oxygen desaturation, white blood cell count, and percent emphysema (low attenuation area, LAA) and linked these to 0-1-, 0-3-, and 0-5-year lags of individual-level exposure to relative humidity (RH), temperature, and air pollution. Linear regression models were conducted to examine associations of temperature, RH, and air pollution with severity of health outcomes. A mediation analysis was conducted to examine the mediating effects of air pollution on the associations of RH and temperature with health outcomes. We observed that a 1 % increase in the RH was associated with increases in forced expiratory volume in 1 s (FEV(1)), eosinophils, and lymphocytes, and a decrease in the total-lobe LAA. A 1 °C increase in temperature was associated with decreases in oxygen desaturation, and right-, left-, and upper-lobe LAA values. Also, a 1 μg/m(3) increase in PM(2.5) was associated with a decrease in the FEV(1) and an increase in oxygen desaturation. A 1 μg/m(3) increases in PM(10) and PM(2.5) was associated with increases in the total-, right-, left, upper-, and lower-lobe (PM(2.5) only) LAA. A one part per billion increase in NO(2) was associated with a decrease in the FEV(1) and an increase in the upper-lobe LAA. Next, we found that NO(2) fully mediated the association between RH and FEV(1). We found PM(2.5) fully mediated associations of temperature with oxygen saturation and total-, right-, left-, and upper-lobe LAA. In conclusion, climate-mediated air pollution increased the risk of decreasing FEV(1) and oxygen saturation and increasing emphysema severity among COPD patients. Climate change-related air pollution is an important public health issue, especially with regards to respiratory disease.
Background: There are insufficient studies on clinical and environmental factors that affect the use of emergency medical services (EMS) in pediatric patients. Objectives: We sought to identify the clinical characteristics of pediatric patients transported to the emergency department (ED) by EMS and meteorological factors affecting the use of EMS. Methods: We reviewed the medical records of patients younger than 19 years who visited the ED from January 2005 to December 2019. Results: The rate of EMS use was higher among older patients [adjusted odds ratio (aOR): 1.12; 95% confidence interval (CI): 1.11 -1.13] and increased with disease severity (aOR: 0.35; 95% CI: 0.33 -0.37 for KTAS and aOR: 0.73; 95% CI: 0.70 -0.77 for GCS). The rate of EMS use was higher in patients with injury than in those with disease (aOR:3.47; 95% CI: 3.15 -3.83). Compared with winter, the summer season was a risk factor for EMS use (aOR: 1.36; 95% CI: 1.08-1.72). Precipitation greater than 40 mm per day increased the risk of EMS use (aOR: 1.31; 95% CI: 1.03-1.72), as did higher concentrations of O(3 )and NO2 (aOR per 0.001 ppm: 1.006; 95% CI: 1.001-1.011 for O-3 and aOR per 0.001 ppm: 1.02; 95% CI: 1.01-1.03 for NO2, respectively). Conclusions: Several clinical characteristics, meteorological factors, and air pollutants might increase the risk of EMS use among pediatric patients.
The current climate crisis poses new uncertainties, risks, and vulnerabilities, and is leading to losses for millions of people depending on fragile food systems. Food systems are, however, vastly different across landscapes and communities, and their capacities to respond to climate impacts evolves and changes through time. Humanitarian and development organizations are struggling to keep pace with these changes. Monitoring a large number of diverse food systems during an evolving climate crisis can be expensive and time-consuming. This paper introduces a monitoring approach that uses a combination of open-source earth observations along with national data sources to produce highly contextualized metrics for monitoring Food And Nutrition Security under Climate Evolution (FANSCE). Entirely data-driven, the FANSCE approach has been designed to produce policy recommendations to help monitor, assess, and mitigate climatic impacts on food systems. We developed and tested this approach in Vietnam, where climate variability has become a growing threat to food systems. Our results show that predictors of food and nutrition security differ drastically with the intensity of climate variability. More specifically, our analyses suggest that in areas of high climate variability, levels of food and nutrition security can be significantly predicted based on economic activities, ethnicity, education, health of mothers, and the level of readiness and preparedness to climate impacts of villages and communities. On the other hand, in areas of low climate variability, food and nutrition security are mostly predictable based on the ability of households to access essential services (such as education, health) and communal resources (water, storage, etc.). To support the resilience of food systems, policymakers must regularly monitor how these dimensions react to the changing climate. Addition critical actions to increase food system sustainability in Vietnam include 1) enhanced coordination of institutional responses and capacities across governmental and non-governmental agencies, and 2) better integration of scientific knowledge into national and sub-national decision-making processes.
OBJECTIVES: The environmental effect in heart failure (HF) patients is well established. However, the data is limited from low-to middle-income countries like India. This study determined the impact of environment on acute decompensated HF (ADHF) admissions and mortality in India. METHODS: Retrospectively, the data of all HF patients admitted between April 2017 and March 2019 was accessed through electronic hospital records. Simultaneously, the environmental-related data was collected from the central pollution control board. RESULTS: The study included 4561 patients of ADHF. The peak of monthly ADHF events (admission and mortality) was observed during the chilly month (January) while the lowest rates were observed in summer months (May-June). The most significant factor correlating inversely with the monthly ADHF admission (r = -0.78, p = 0.003) and mortality (r = -0.65, p = 0.004) was the maximum air temperature, and it was found to be the independent predictor for both ADHF mortality [t = -2.78, β = -0.84; 95%CI(-6.0 to -0.6), p = 0.021] and admission [t = -4.83, β = -0.91; 95%CI(-19.8 to -6.9), p = 0.001]. The above correlation was better seen in the elderly subset and male gender. Humidity and the air pollution attributes did not have a significant correlation with ADHF admission or mortality. CONCLUSION: In conclusion, even in low-to middle-income country like India, a periodic effect of season was demonstrated for ADHF mortality and admission, with a peak in ADHF events noted during winter months especially in the regions having extremes of seasons. Air pollution could not affect the ADHF outcome for which further studies are needed.
Background: Electrical storm (ES) has profound psychological effects and is associated with a higher mortality in patients with implantable cardioverter-defibrillator (ICD). Assessing the incidence and features of ES, is vital. Previous studies have shown winter peaks for ventricular tachyarrhythmia (VTA) in ICD patients. However, the effects of heat with a high relative humidity remain unclear. Thus, this study aimed to assess the nonlinear and lagged effects of apparent temperature [or heat index (HI)] on VTA among patients with and without ES after ICD implantation. Methods: Of 626 consecutive patients who had ICDs implanted from January 2004 to June 2017 at our hospital, 172 who experienced sustained VTAs in ICD recording were analyzed, and their clinical records were abstracted to assess the association between VTA incidence and HI by time-stratified case-crossover analysis. Cubic splines were used for the nonlinear effect of HI, with adjustment for air pollutant concentrations. Results: A significant seasonal effect for ES patients was noted. Apparent temperature, but not ambient temperature, was associated with VTA occurrences. The low and high HI thresholds for VTA incidence were <15° and >30°C, respectively, with a percentage change in odds ratios of 1.06 and 0.37, respectively, per 1°C. Lagged effects could only be demonstrated in ES patients, which lasted longer for low HI (in the next 4 days) than high HI (in the next 1 day). Conclusion: VTA occurrence in ICD patients was strongly associated with low HI and moderately associated with high HI. Lagged effects of HI on VTA were noted in patients with ES. Furthermore, patients with ES were more vulnerable to heat stress than those without ES. Patients with ICD implantation, particularly in those with ES, should avoid exposure to low and high HI to reduce the risk of VTAs, improve quality of life and possibly reduce mortality.
Despite the growing interest in energy-efficient homes (EEHs), there is still a lack of evidence regarding whether the mechanical ventilation system of an EEH positively or negatively impacts indoor air quality (IAQ) and the health and wellbeing of occupants. This study aimed to evaluate the IAQ level and daily health symptoms of adults and children living in EEHs compared to conventional buildings over the course of one year. A two-way mixed analysis of variance was conducted to compare the level of IAQ between the two housing types. A binomial generalized linear mixed model (GLMM) and generalized additive mixed model was developed to investigate the association between IAQ and daily risks of symptoms. Differences in the daily prevalence of symptoms between the two housing types were assessed using a Poisson GLMM model. Overall, the indoor concentrations of particulate matter (PM(10) and PM(2.5)), carbon dioxide (CO(2)), and volatile organic compounds (VOCs) were lower in EEH after controlling for seasonality. The indoor temperature and relative humidity level were relatively constant in the EEH. We also found that an increased level of indoor air quality parameters, particularly CO(2,) which is closely related to the indoor ventilation rate, was associated with the daily risk of eye fatigue, allergic rhinitis, and atopic dermatitis symptoms. Considering that EEH effectively reduced indoor air pollutants and IAQ improvement was associated with a reduction in the risk of individual symptoms, the IAQ improvement of EEH may have positively impacted occupants’ health. Symptoms such as eye fatigue and skin dryness, which have been reported in previous studies as potential side effects of mechanical ventilation, were reported in this study; however, they were not found to be statistically significantly different from those reported in the conventional building.
To establish whether serum bilirubin levels vary in healthy term neonates according to seasonal variations and meteorological factors, we retrospectively studied 3344 healthy term neonates born between 2013 and 2018. Total serum bilirubin (TSB) levels were measured on the fourth day after birth. The monthly and seasonal variations in TSB levels and clinical and meteorological effects on TSB levels were assessed. In the enrolled neonates, the median TSB level was 195 µmol/L. The TSB level peaked in December and was the lowest in July, but the variation was not statistically significant. The TSB level was significantly higher in the cold (October to March) than in the warm season (April to September; p = 0.01). The comparison between seasonal differences according to sex showed TSB levels were significantly higher in the cold than in the warm season in male infants (p = 0.001), whereas no significant difference was observed in female infants. A weakly negative but significant association existed between TSB levels and the mean daily air temperature (r = -0.07, p = 0.007) in only the male population; the female population showed no significant correlation between TSB levels and meteorological parameters. The season of birth is an etiological factor in neonatal jaundice, with an additional influence from sex.
OBJECTIVE: To investigate the effects of seasonal and climatic changes on postoperative in-hospital mortality and length of stay (LOS) in patients with type A acute aortic dissection (AAD). METHODS: Patients undergoing implantation of the modified triple-branched stent graft to replace the descending aorta in addition to aortic root reconstruction for type A AAD in our hospital from January 2016 to December 2019 were included. Relevant data were retrospectively collected and analyzed. RESULTS: A total of 404 patients were included in our analyses. The multivariate unconditional logistic regression analysis showed that patients admitted in autumn (OR 4.027, 95% CI 1.023-17.301, P = 0.039) or with coronary heart disease (OR 8.938, 95% CI 1.991-29.560, P = 0.049) were independently associated with an increased risk of postoperative in-hospital mortality. Furthermore, patients admitted in autumn (OR 5.956, 95% CI 2.719-7.921, P = 0.041) or with hypertension (OR 3.486, 95% CI 1.192-5.106, P = 0.035) were independently associated with an increased risk of longer LOS. CONCLUSION: Patients admitted in autumn or with coronary heart disease are at higher risk of in-hospital mortality following surgery for type A AAD. Also, patients admitted in autumn or with hypertension have a longer hospital LOS. In the autumn of the temperature transition, we may need to strengthen the management of medical quality after surgery for type A AAD.
Weather conditions affect the incidence of acute myocardial infarction (AMI). However, little is known on the association of weather temperature and humidity with AMI hospitalizations in a super-aging society. This study sought to examine this association. We included 87,911 consecutive patients with AMI admitted to Japanese acute-care hospitals between April 1, 2012 and March 31, 2015. The primary outcome was the number of AMI hospitalizations per day. Multilevel mixed-effects linear regression models were used to estimate the association of the average temperature and humidity, 1 day before hospital admission, with AMI hospitalizations, after adjusting for weather, hospital, and patient demographics.Lower temperature and humidity were associated with an increased number of AMI hospitalizations (coefficient – 0.500 [- 0.524 to – 0.474] per °C change, p<0.001 and coefficient - 0.012 [- 0.023 to - 0.001] per % change, p=0.039, respectively). The effects of temperature and humidity on AMI hospitalization did not differ by age and sex (all interaction p>0.05), but differed by season. However, higher temperatures in spring (coefficient 0.089 [0.025 to 0.152] per °C change, p=0.010) and higher humidity in autumn (coefficient 0.144 [0.121 to 0.166] per % change, p<0.001) were risk factors for AMI hospitalization. Increased average temperatures and humidity, 1 day before hospitalization, are associated with a decreased number of AMI hospitalizations.
Climate and temperature have long been considered in relation to human diseases and mortality. In this study, we investigated whether daily temperature and humidity and patients’ personal history affect the volume of peritonsillar abscesses (PTAs). We included 52 patients with PTAs who were admitted to the emergency department of the study hospital; their computed tomography data were analyzed, and PTA volume was measured. We investigated the possible correlation between PTA volume and mean/minimum/maximum temperature and humidity. Furthermore, we obtained personal history data, including information on drinking status, smoking status, dental problems, and patients’ treatment experiences at local clinics before visiting the emergency department. The mean PTA volume was 3.93 mL, which was significantly correlated with temperature differences between 1 and 2 days before hospitalization and the day of hospitalization (P < .05) and also with a lack of treatment experience at local clinics (P < .001). However, no significant correlation was noted between PTA volume and the mean/minimum/maximum temperature and humidity on the day of hospitalization (P > .05). Similar findings were obtained for drinking status, smoking status, and dental problems (P > .1). PTA volume appears to be strongly associated with temperature differences between 1 and 2 days before hospitalization and the day of hospitalization. Patients with treatment experience at local clinics exhibited substantial increases in PTA volume. Thus, an increased PTA volume may be observed in patients who visit the emergency department without any treatment experience at local clinics or from environments that differ considerably from their current environment in terms of temperature.
INTRODUCTION: Thyroid cancer has increased sharply in China in recent years. This change may be attributable to multiple factors. The current study aimed to explore the environmental and social determinants of thyroid cancer. METHODS: Incidence data from 487 cancer registries in 2016 were collected. Eight factors were considered, namely, air pollution, green space, ambient temperature, ultraviolet radiation, altitude, economic status, healthcare, and education level. A geographical detector (measured by q statistic) was used to evaluate the independent and interactive impact of the eight factors on thyroid cancer. RESULTS: Social factors, especially economic status and healthcare level (q > 0.2), were most influential on thyroid cancer.Ultraviolet radiation, air pollution, and temperature had more impact on women, while green space and altitude had more influence on men. Enhanced effects were observed when two factors interacted. Spatially, economic status, healthcare, and air pollution were positively associated with thyroid cancer, while education level, green space, and altitude were negatively related to thyroid cancer. CONCLUSION: The socio-environmental determinants and spatial heterogeneity of thyroid cancer were observed in this study. These findings may improve our understanding of thyroid cancer epidemiology and help guide public health interventions.
BACKGROUND: Patients with ankylosing spondylitis (AS) have reported that their pain becomes worse when the local weather changes. However, there is limited evidence verifying the short-term associations between meteorological factors and outpatient visits for patients with AS. Therefore, this study evaluates this possible association. METHODS: Meteorological data and data on daily AS outpatient visits to a general hospital in Hefei, China, from 2014 to 2019 were collected and analysed. Distributed lag nonlinear models and Poisson regression models were employed to determine the association between weather conditions and outpatient visits; the results were also stratified by gender and age. RESULTS: High relative humidity is significantly associated with all patient visits in lag 1 (RR = 1.113, 95% CI 1.021 to 1.213) and lag 7 days (RR = 1.115, 95% CI 1.014 to 1.227). A low relative risk to the nadir is observed in lag 4 days (RR = 0.920, 95% CI 0.862 to 0.983). Male and young patients (< 65 years) are more vulnerable to damp weather, and elderly people (≥ 65 years) are significantly affected by high temperatures in lag 7 days (RR = 3.004, 95% CI 1.201 to 7.510). CONCLUSIONS: Our findings suggest a potential relationship between exposure to weather conditions and increased risk of AS outpatient visits. These results can aid hospitals in preparing for and managing hospital visits by AS patients when the local weather conditions change.
Monastic houses are an essential part of the Tibetan monastic system in China. In this study, the monastic houses of Labrang in the Tibetan region of Gannan were used as the research objects. Physical parameters such as indoor temperature, humidity, and radiation temperature of the monastic houses were measured. The measured results were compared with the standard values, while the air temperature was linearly fitted using TSV, PMV, and aPMV. The results show that the temperature inside and outside the monastic houses fluctuates considerably; the theoretical thermal neutral temperature of the tested monks in winter is 22.46 °C, which is higher than the measured thermal neutral temperature in winter of 16.43 °C. When analyzing the results, it was found that the local climate, dress code, and the monks’ specific habits all impact the perception of thermal comfort, which creates a discrepancy between the accurate results and the standard values. The above findings provide a more comprehensive reference for the thermal comfort requirements of the monks in cold areas, which can be used as a guide for the improvement and evaluation of the monastic houses in cold areas.
Asia’s food systems have undergone rapid economic and socio-cultural transformations in the past 60 years. During the period, almost all the countries in the region eradicated famines and achieved food self-sufficiency and heterogeneous levels of poverty reduction. Food system transformation in Asian countries has had similarities and differences and has been closely tied to structural transformation, political processes, and integration with the global economy. This article conducts a historical assessment of food systems transformations in seven Asian countries between 1960 and 2020 and their main economic, social, and demographic drivers. Food systems transformations are presented in terms of four phases. In the first phase, between 1960 and 1980, when most Asian countries were low-income and low-middle-income, the central focus was on hunger reduction. We explore the policies and the politics of the green revolution as various Asian countries tried to achieve self-sufficiency in food grains. In the second phase (1980-2000), agricultural productivity growth led to structural transformation, income growth, and the divergence of lower-middle-income and middle-income economies, directly impacting demand for food quantity, quality, and diversity in various countries. The third phase (2000 onwards) marked a quantum change in food systems as globalization, trade integration, and changes in consumer tastes were significant drivers of food systems. We assess the changing trends in organized retail expansion, increased consumption of processed foods, and rising incidence of obesity in lower and upper-middle-income countries. In the final phase (beyond 2020), we highlight how the digital revolution has changed consumer behavior, and is further transforming food systems. Future food systems challenges of hunger, malnutrition, rising non-communicable diseases, and climate change are discussed and multisectoral and multicountry policy interventions for addressing them are presented.
BACKGROUND: Changes in climatic conditions have increased the variability in rainfall patterns worldwide. A negative rainfall shock faced by children in the initial 1000 days of life and the resulting malnutrition can harm the likelihood of children’s survival, overall growth, development of the brain, motor skills, and cognitive abilities, leading to poor performance in education and labor market. While the existing findings about the long-run outcomes are mixed, it is essential to understand the nuances in such an estimation. METHODS: Using the exogenous variation in rainfall in India, we estimate the impact of adverse shocks at birth on the cognitive abilities of children at ages 5, 8, 12, and 15, on educational attainments, and the likelihood of studying STEM at higher secondary school. RESULTS: The Young Lives Survey data from Andhra Pradesh, India, presents evidence of the negative impact of rainfall shocks at birth on cognitive abilities from age 5 to 8, attenuating at age 12. Using nationally representative data, while we investigate the impact of adverse rainfall shocks at birth on academic performance measured by the high school grades and STEM choice at higher secondary school, we do not find a persistent impact. CONCLUSION: We unfold the impact of rainfall shocks on a chain of outcomes connected to long-run educational pursuits, as it helps to identify the most crucial stage for policymaking. Since STEM subjects are strongly associated with the labor market, connecting the association with early life shocks seems to be an essential addition to the literature. While we find evidence of reduced cognitive abilities in the early years, those do not seem to persist in the long run. The potential sample selection or attrition biases and the estimates of those biases can explain the nuances of estimating the long-run impact of adverse shocks at birth.
BACKGROUND: Pneumonia is the leading cause of death and hospitalization among young children worldwide, but its risk factors remain unclear. OBJECTIVE: To evaluate the effect of maternal exposure to diurnal temperature variation (DTV) during preconceptional and prenatal periods on childhood pneumonia. METHODS: A retrospective cohort study by case-control design was conducted for pneumonia (N = 699) and normal (N = 811) children under age of 14 who were enrolled in XiangYa Hospital, Changsha, China from May 2017 to April 2019. Demographic data including gender, age, birth season, gestational age, parity, mode of delivery, and parental atopy were collected from the electronic medical records in the hospital system. We obtained the data of daily DTV in Changsha during 2003-2019 from China Meteorological Administration. Maternal exposure to DTV during preconceptional and prenatal periods was respectively calculated by the average of daily DTV during one year and three months before conception and entire pregnancy as well as the three trimesters. The association between maternal exposure to outdoor DTV and childhood pneumonia was analyzed by multiple logic regression model. RESULTS: We found that childhood pneumonia was significantly associated with exposure to an increase in DTV during one year before conception and entire pregnancy, with ORs (95 % CI) = 2.53 (1.56-4.10) and 1.85 (1.24-2.76). We further identified a significant risk of pneumonia of DTV exposure during the first and second trimester of pregnancy. Sensitivity analysis showed that boys were more susceptible to the effect of prenatal exposure to outdoor DTV during pregnancy particularly in the first two trimesters compared to girls. CONCLUSIONS: Preconceptional and prenatal exposure to DTV plays an important role in development of childhood pneumonia, especially during the first and second trimesters of pregnancy.
Weather temperatures affect the incidence of cardiovascular diseases (CVD), but there is limited information on whether CVD hospitalizations are affected by changes in weather temperatures in a super-aging society. We aimed to examine the association of diurnal weather temperature changes with CVD hospitalizations. We included 1,067,171 consecutive patients who were admitted to acute-care hospitals in Japan between April 1, 2012 and March 31, 2015. The primary outcome was the number of CVD hospitalizations per day. The diurnal weather temperature range (DTR) was defined as the minimum weather temperature subtracted from the maximum weather temperature on the day before hospitalization. Multilevel mixed-effects linear regression models were used to estimate the association of DTR with cardiovascular hospitalizations after adjusting for weather, hospital, and patient demographics. An increased DTR was associated with a higher number of CVD hospitalizations (coefficient, 4.540 [4.310-4.765]/°C change, p < 0.001), with greater effects in those aged 75-89 (p < 0.001) and ≥ 90 years (p = 0.006) than among those aged ≤ 64 years; however, there were no sex-related differences (p = 0.166). Greater intraday weather temperature changes are associated with an increased number of CVD hospitalizations in the super-aging society of Japan, with a greater effect in older individuals.
It is analysed that the urban disaster with pandemic and its related consequences are associated with the global warming induced by the carbon-emitted fossil fuels. In ‘urban disaster’, the result is shown as a stepwise form in which the effectiveness of urban disaster increases. In addition, ‘energy-mix’ and ‘energy’ decrease in their effectiveness, although ‘traffic, communication, etc.’, ‘health, quarantine, etc.’, and ‘resilience’ increase in their effectiveness. This means that three variables, ‘traffic, communication, etc.’, ‘health, quarantine, etc.’, and ‘resilience’, affect the ‘energy-mix’ and ‘energy’ as the feedback algorithm. It is analysed for urban disasters with ecological pandemic situations where the social distancing is very important in the urban places due to the higher population density than the rural areas. In this work, the prospects of pandemic society incorporated with the climate change mitigating by energy-mix policy are investigated.
Public health and effective risk response cannot be promoted without a coordinated emergency process during a natural disaster. One primary problem with the emergency relief chain is the homogeneous layout of rescue organizations and reserves. There is a need for government-enterprise coordination to enhance the systemic resilience and demand orientation. Therefore, a bi-level multi-phase emergency plan model involving procurement, prepositioning and allocation is proposed. The tradeoff of efficiency, economy and fairness is offered through the multi-objective cellular genetic algorithm (MOCGA). The flood emergency in Hunan Province, China is used as a case study. The impact of multi-objective and coordination mechanisms on the relief chain is discussed. The results show that there is a significant boundary condition for the coordinated location strategy of emergency facilities and that further government coordination over the transition phase can generate optimal relief benefits. Demand orientation is addressed by the proposed model and MOCGA, with the realization of the process coordination in multiple reserves, optimal layout, and transition allocation. The emergency relief chain based on government-enterprise coordination that adapts to the evolution of disasters can provide positive actions for integrated precaution and health security.
In the context of global climate change and increasingly severe environmental pollution, drinking water quality risk assessments to provide crucial early warnings have become essential routine work. At present, traditional water quality assessment methods are commonly used without considering the correlation among different indicators and the substantial uncertainty from multiple sources, which limit their applications. To address this issue, a copula-based Bayesian network (CBN) method was proposed in this study to concretely evaluate the water quality risk with multiple environmental risk indicators in a large drinking water reservoir in Tianjin city, China. Taking rainfall and water temperature (WT) as external environmental risk indicators and pH, ammonia nitrogen (NH(3)-N), total nitrogen (TN), total phosphorus (TP), and permanganate index (COD(Mn)) as internal environmental risk indicators, the CBN model was constructed to investigate the interaction between the indicators and water quality state and assess the contingent risk. Our results showed that TN and NH(3)-N should be considered key risk indicators. Additionally, we performed forward and backward risk analyses to assess water quality risk during different seasons and determined the distributions of key indicators under different water quality risk grades. From a time perspective, the reservoir’s water quality risk is much higher in winter and spring than in other seasons affected by winter snowfall. From a spatial perspective, the water quality risk is much higher at the reservoir’s entrance than at other locations affected by water diversion. Furthermore, we found that the probability of water quality risk events may be relatively high when the TN concentration is 3.6 mg/L to 6.4 mg/L at the reservoir’s entrance. The results reveal that the CBN method could be an invaluable decision-support tool for reservoir managers and scientists, which could provide an early warning of water quality degradation by only inputting monitoring data.
This narrative review aims to assess the effects of the climate crisis on various aspects of adolescent wellbeing, and community level coping mechanisms being used to build resilience. This study summarizes research findings from eight South Asian countries based on a scoping review of the peer-reviewed and grey literature (critically evaluated) published between 1st January 2000 and 31st December 2021. We have included multiple dimensions of climate change such as drought, floods, cyclones, tsunamis, storms, raised temperature/heatwaves, heavy rainfall, rising sea level, and glacier melt-related extreme weather events. Findings suggest Extreme Weather Events (EWE) affect adolescents and their wellbeing in various ways, with adolescent girls disproportionately harmed, as EWE are linked to early marriage, trafficking, gender based sexual and physical violence. Regional variation suggested, with Bangladeshi adolescents most vulnerable to EWE, followed by India and Pakistan. Floods, droughts and cyclones are the most commonly reported EWE affecting adolescents in the South Asian region. As the climate crisis is expected to increase the frequency and intensity of EWE, it will be critical to understand the gender sensitive impacts in more in-depth and find more sustainable solutions for the global problem that is adversely impacting the adolescent’s life, wellbeing, and development.
In recent years, the subject of Indigenous peoples and global climate change adaptation has become a rapidly growing area of international study. Despite this trend, Taiwan, home to many Indigenous communities, has received relatively little attention. To date, no comprehensive review of the literature on Taiwan’s Indigenous peoples and global climate change has been conducted. Therefore, this article presents a bibliometric analysis and literature review of both domestic and international studies on Taiwan’s Indigenous peoples in relation to resilience, climate change, and climate shocks in the 10-year period after Typhoon Morakot (2009). We identified 111 domestic and international peer-reviewed articles and analyzed their presentation of the current state of knowledge, geographical and temporal characteristics, and Indigenous representation. Most studies were discovered to focus on post-disaster recovery, particularly within the context of Typhoon Morakot, as well as Indigenous cultures, ecological wisdom, and community development. This study also discovered relatively few studies investigating how traditional ecological knowledge systems can be integrated into climate change adaptation. Most studies also adopted a somewhat narrow focus on Indigenous resilience. Large-scale quantitative and longitudinal studies are found to be in their infancy. We observed a geographical skewness among the studies in favor of southern Taiwan and relatively limited engagement with contemporary studies on Indigenous peoples and climate change. We furthermore determined a large overlap between the destruction path of Morakot and study sites in the articles. Indigenous scholars have managed to find a voice among domestic and international outlets, and an increasing number of scholars have argued for more culturally sensitive approaches to post-disaster recovery and disaster management in Taiwan.
In Southeast Asia, the West Bengal coastal region is one of the significant hotspots of climate-induced vulnerability. This article defines vulnerability as a function of exposure, sensitivity, and adaptive capacity. We selected 43 subcomponent indicators under nine major components for constructing the Integrated Agricultural Livelihood Vulnerability Index (IALVI). Understanding the spatial distribution of IALVI to climate change is vital to formulate proper sustainable adaptation strategies for the future. Results revealed that high to very high vulnerability in the south and southeastern coastal C.D. Blocks due to high exposure and high sensitivity and agricultural livelihood of 5.02 million people were highly vulnerable to the adverse effect of climate change. On the contrary, moderate to low vulnerability is experienced in the western and northern parts of the region due to less exposure, less sensitivity, and high adaptive capacity. This study applies geospatial techniques and examines the spatial distribution of climate change vulnerability in the coastal region of West Bengal. The most vulnerable region in this study area comprises a gentle slope, low elevation, high drainage density, and poor socio-economic conditions. Consequently, several adaptation methods, such as a better cyclone shelter, embankments, a more robust transportation and communication system, and improved healthcare facilities, may help to raise the level of adaptive capacity in the vulnerable regions. These findings will be helpful for policymakers in formulating proper climate risk mitigation strategies in coastal West Bengal. To validate the secondary results primary investigation was also done in this study.(c) 2022 Elsevier B.V. All rights reserved.
In 2019, the National Geographic and Rolex Perpetual Planet Everest expedition successfully retrieved the greatest diversity of scientific data ever from the mountain. The confluence of geologic, hydrologic, chemical and microbial hazards emergent as climate change increases glacier melt is significant. We review the findings of increased opportunity for landslides, water pollution, human waste contamination and earthquake events. Further monitoring and policy are needed to ensure the safety of residents, future climbers, and trekkers in the Mt. Everest watershed.
BACKGROUND: Although various studies have been conducted on the effects of seasonal climate changes or emotional variables on the risk of AMI, many of them have limitations to determine the predictable model. The currents study is conducted to assess the effects of meteorological and emotional variables on the incidence and epidemiological occurrence of acute myocardial infarction (AMI) in Sari (capital of Mazandaran, Iran) during 2011-2018. METHODS: In this study, a time series analysis was used to determine the variation of variables over time. All series were seasonally adjusted and Poisson regression analysis was performed. In the analysis of meteorological data and emotional distress due to religious mourning events, the best results were obtained by autoregressive moving average (ARMA) (5,5) model. RESULTS: It was determined that average temperature, sunshine, and rain variables had a significant effect on death. A total of 2375 AMI’s were enrolled. Average temperate (°C) and sunshine hours a day (h/day) had a statistically significant relationship with the number of AMI’s (β=0.011, P=0.014). For every extra degree of temperature increase, the risk of AMI rose [OR=1.011 (95%CI 1.00, 1.02)]. For every extra hour of sunshine, a day a statistically significant increase [OR=1.02 (95% CI 1.01, 1.04)] in AMI risk occurred (β=0.025, P=0.001). Religious mourning events increase the risk of AMI 1.05 times more. The other independent variables have no significant effects on AMI’s (P > 0.05). CONCLUSION: Results demonstrate that sunshine hours and the average temperature had a significant effect on the risk of AMI. Moreover, emotional distress due to religious morning events increases AMI. More specific research on this topic is recommended.
BACKGROUND: Growing evidence indicates that air pollution is capable of disrupting the immune system and therefore, might be associated with an onset of Type 1 diabetes (T1D). OBJECTIVES: We explored possible links of T1D with ambient exposures in the population of southern Israel, characterized by hot and dry climate and frequent dust storms. METHODS: We conducted a matched nested case-control study where exposure to environmental pollutants during gestation in T1D cases was compared to that of healthy children. Up to 10 controls were matched to every case by age, gender and ethnicity, in all 362 cases and 3512 controls. Measurements of pollutants’ concentrations, nitrogen dioxide (NO(2)), sulphur dioxide (SO(2)), ozone (O(3)) and particulate matter of size less than 10 and 2.5 μm in diameter (PM(10) and PM(2.5)), as well as the mean daily measurements of meteorological conditions were obtained from the local monitoring stations. The association between T1D and pollution, solar radiation (SR), temperature and relative humidity was adjusted for socioeconomic status, temperature, maternal age and pre-gestational maternal DM, using conditional logistic regression. The environmental exposures were presented as indicators of quartiles averaged over whole pregnancy and by trimesters. RESULTS: Exposure to ozone and solar radiation during gestation were both associated with the T1D in offspring, although at borderline significance. Compared to the lowest quartile, the odds ratio (OR) for exposure to 3rd and 4th quartile of O(3) was equal 1.61 (95%CI: 0.95; 2.73) and 1.45 (95%CI: 0.83; 2.53), respectively. Likewise, the ORs for exposure to SR were equal 1.83 (95%CI: 0.92; 3.64), 2.54 (95%CI: 1.21; 5.29) and 2.06 (95%CI: 0.95; 4.45) for to 2nd, 3rd and 4th quartiles, respectively. Exposure to SO(2) followed a dose-response pattern, but was not statistically significant. Other environmental factors were not independently related to T1D. Analysis of exposures one year prior to the disease onset indicated a positive association between T1D and SR. CONCLUSIONS: We showed that exposure to high ozone levels and solar radiation during gestation might be related to the T1D. More scientific evidence needs to accumulate to support the study findings.
Heart failure increases among the elderly; however, the influence of ambient temperature on cardiorenal function has not been well investigated. Patients (n = 110, mean age 82.9 years, 43 males) with stable heart failure and creatinine < 3.0 mg/dl were studied. Medical records, such as ejection fraction, B-type natriuretic peptide (BNP), and estimated glomerular filtration rate (eGFR) at each visit every 1-3 months were collected by the end-point for death, additional prescription to treat heart failure, or heart failure hospitalization. The ambient temperatures at each visit were obtained from the Japan Meteorological Agency. During the follow-up period (median 399 days and 7 visits), follow-up BNP showed a trend toward a positive correlation with the diurnal temperature range. After dividing into two groups by median baseline eGFR, follow-up BNP was positively correlated with minimum temperature (p = 0.039) and the diurnal temperature range (p = 0.007) in the Low-eGFR group but not in the High-eGFR group. Follow-up eGFR was negatively correlated with the ambient day temperature in both groups (p ≤ 0.002). Follow-up BNP was positively correlated with follow-up eGFR (p < 0.0001) only in the Low-eGFR group and not in the High-eGFR group, suggesting that BNP and eGFR increase in winter and BNP and eGFR decrease in summer in the Low-eGFR group. In conclusions, heart failure may be worsened by larger diurnal temperature range or in winter in patients with renal impairment. This population should be carefully managed in the clinic according to the ambient temperature.
This study aimed to clarify the association between the onset of acute coronary syndrome (ACS) and weather conditions in summer and winter in the same region. At a general hospital inJapan, weather conditions during the onset of 2,381 cases diagnosed with ACS over 25 years were analyzed using a generalized additive model adopting log-quasi-Poisson distribution as the link function, with the occurrence of ACS as the dependent variable and weather data as the independent variable. In conclusion, we found that ACS occurred at about the same frequency in winter and summer, and the season did not affect the onset. The onset rate decreased 0.960-fold per 1 °C increase in the minimum temperature one day before the day of onset and decreased 0.987-fold per 1 hPa increase in the mean station pressure of the previous day.
BACKGROUND: Inconsistent results about the effect of air pollution on chronic rhinosinusitis (CRS) have been reported. This study aimed to evaluate the impact of meteorological conditions/air pollution on the prevalence of CRS in adult Koreans. METHODOLOGY: The data from the Korean National Health Insurance Service-Health Screening Cohort from 2002 through 2015 were used. A CRS group (defined as ICD-10 codes J32, n=6159) was matched with a control group (n=24,636) in 1:4 ratios by age, sex, income, and region of residence. The meteorological conditions and air pollution data included the daily mean, highest, and lowest temperature (°C), daily temperature range (°C), relative humidity (%), ambient atmospheric pressure (hPa), sunshine duration (hr), and the rainfall (mm), SO2 (ppm), NO2 (ppm), O3 (ppm), CO (ppm), and PM10 (μg/m3) levels before the CRS diagnosis. Crude and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for CRS were analyzed using logistic regression analyses. RESULTS: When the NO2 level increased by 0.1 ppm, the odds for CRS increased 5.40 times, and when the CO level increased by 1 ppm and PM10 increased by 10 μg/m3, the odds for CRS decreased 0.75 times and 0.93 times, respectively. Other meteorological conditions, such as the mean/highest/lowest temperature, temperature range, rainfall and other air pollution, such as SO2 and O3, were not statistically significant. NO2 for 90 days before the index date increased the risk of CRS in all subgroups, except for the nasal polyp and older age subgroups. CONCLUSION: CRS is related to high concentrations of NO2.
Mounting evidence indicated the associations between air pollution and outpatient visits for allergic rhinitis (AR), while few studies assessed the effect modification of these associations by ambient temperature and relative humidity (RH). In this study, dataset of AR outpatients was obtained from Chinese People’s Liberation Army Strategic Support Force Characteristic Medical Center in Beijing during 2014 to 2019, and the average concentrations of air pollutants including particulate matter ≤2.5 μm in diameter (PM(2.5)) and ≤10 μm (PM(10)), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and meteorological factors (temperature and RH) at the same period were collected from one nearby air monitoring station. We performed a time-series study with Poisson regression model to examine the effects of air pollutants on AR outpatients after adjustment for potential confounders. And the effects modification analysis was further conducted by stratifying temperature and RH by tertiles into three groups of low, middle and high. In total of 33,599 outpatient visits for AR were recorded during the study period. Results found that a 10 μg/m(3) increase in PM(2.5), PM(10), NO(2) and SO(2) was associated with significant increases in AR outpatients of 1.24% (95% confidence interval (CI): 0.69%, 1.78%), 0.79% (95% CI: 0.43%, 1.15%), 3.05% (95% CI: 1.72%, 4.40%) and 5.01% (95% CI: 1.18%, 8.96%), respectively. Stronger associations were observed in males than those in females, as well as in young adults (18-44 years) than those in other age groups. Air pollution effects on AR outpatients increased markedly at low temperature (<33.3th percentile) and high RH (>66.7th percentile). Findings in this study indicate that air pollution is associated with increased risk of AR outpatients, and the effects of air pollution on AR could be enhanced at low temperature and high RH.
OBJECTIVES: Evidence on the associations between short-term and long-term air temperature exposure and cognitive function in older adults, particularly those in Asia, is limited. We explored the relationships of short-term and long-term air temperature exposure with cognitive function in Taiwanese older adults through a repeated measures survey. DESIGN AND SETTING: We used data the ongoing Taiwan Longitudinal Study on Aging, a multiple-wave nationwide survey. PARTICIPANTS: We identified 1956, 1700, 1248 and 876 older adults in 1996, 1999, 2003 and 2007, respectively. PRIMARY AND SECONDARY OUTCOME MEASURES: Participants’ cognitive function assessment was based on the Short Portable Mental Status Questionnaire. We calculated the temperature moving average (TMA) for temperature exposure windows between 1993 and 2007 using data from air quality monitoring stations, depending on the administrative zone of each participant’s residence. Generalised linear mixed models were used to examine the effects of short-term and long-term temperature changes on cognitive function. RESULTS: Short-term and long-term temperature exposure was significantly and positively associated with moderate-to-severe cognitive impairment, with the greatest increase in ORs found for 3-year TMAs (OR 1.247; 95% CI 1.107 to 1.404). The higher the quintiles of temperature exposure were, the higher were the ORs. The strongest association found was in long-term TMA exposure (OR 3.674; 95CI 2.103 to 6.417) after covariates were controlled for. CONCLUSIONS: The risk of mild cognitive impairment increased with ambient temperature in community-dwelling older adults in Taiwan.
Painful diabetic neuropathy (PDN) is a common complication of diabetes mellitus, which reduces the quality of life. However, the association between PDN and environmental factors, especially ambient humidity, remains unclear. Therefore, this study investigated the impact of extreme humidity events on PDN. Data on PDN-related hospital admissions to two tertiary hospitals in Hefei, China (2014-2019) were obtained. A distributed lag non-linear model with a case-crossover design was used to quantitatively estimate the effects of ambient humidity on PDN, and the results were stratified by sex and age. The 1st, 10th, 90th, and 99th percentiles of relative humidity (RHU) were defined as extreme humidity, and the average relative humidity (74.94%) was set as the reference value. Non-linear exposure-response curves between the RHU and PDN cases were obtained. Extreme humidity (92%) had a significant effect on PDN with a relative risk (RR) of 1.13 (95% confidence interval (CI): 1.01-1.26) on a particular day, which increased with the RHU (RR: 1.21, 95% CI: 1.02-1.45 at 98% extreme humidity). Stratification analysis showed that women (RR: 1.38, 95% CI: 1.07-1.77) and patients aged < 65 years (RR: 1.26, 95% CI: 1.01-1.57) were highly susceptible to this effect on the same day. The results suggest that extreme humidity is a crucial trigger for PDN onset in diabetes patients. Furthermore, the effects vary with sex and age. This study provides detailed evidence of the adverse effects of extreme weather on diabetes patients.
AIMS: Evidence on the association between ambient temperature and the onset of acute heart failure (AHF) is scarce and mixed. We sought to investigate the incidence of AHF admissions based on ambient temperature change, with particular interest in detecting the difference between AHF with preserved (HFpEF), mildly reduced (HFmrEF), and reduced ejection fraction (HFrEF). METHODS AND RESULTS: Individualized AHF admission data from January 2015 to December 2016 were obtained from a multicentre registry (Tokyo CCU Network Database). The primary event was the daily number of admissions. A linear regression model, using the lowest ambient temperature as the explanatory variable, was selected for the best-estimate model. We also applied the cubic spline model using five knots according to the percentiles of the distribution of the lowest ambient temperature. We divided the entire population into HFpEF + HFmrEF and HFrEF for comparison. In addition, the in-hospital treatment and mortality rates were obtained according to the interquartile ranges (IQRs) of the lowest ambient temperature (IQR1 <5.5°C; IQR25.5-13.3°C; IQR3 13.3-19.7°C; and IQR4 >19.7°C). The number of admissions for HFpEF, HFmrEF and HFrEF were 2736 (36%), 1539 (20%), and 3354 (44%), respectively. The lowest ambient temperature on the admission day was inversely correlated with the admission frequency for both HFpEF + HFmrEF and HFrEF patients, with a stronger correlation in patients with HFpEF + HFmrEF (R(2) = 0.25 vs. 0.05, P < 0.001). In the sensitivity analysis, the decrease in the ambient temperature was associated with the greatest incremental increases in HFpEF, followed by HFmrEF and HFrEF patients (3.5% vs. 2.8% vs. 1.5% per -1°C, P < 0.001), with marked increase in admissions of hypertensive patients (systolic blood pressure >140 mmHg vs. 140-100 mmHg vs. <100 mmHg, 3.0% vs. 2.0% vs. 0.8% per -1°C, P for interaction <0.001). A mediator analysis indicated the presence of the mediator effect of systolic blood pressure. The in-hospital mortality rate (7.5%) did not significantly change according to ambient temperature (P = 0.62). CONCLUSIONS: Lower ambient temperature was associated with higher frequency of AHF admissions, and the effect was more pronounced in HFpEF and HFmrEF patients than in those with HFrEF.
BACKGROUND: To identify the association of meteorological factors/ambient air pollutants with medical care utilization for urolithiasis and estimate the effect size/time lags. METHODS: This is a population-based time-series analysis of 300,000 urolithiasis cases from eight large metropolitan areas in Korea. Seventeen meteorological factors and ambient air pollutants were measured daily during 2002-2017 for each metropolis. Data on daily medical utilization owing to urolithiasis were collected. A generalized additive model was used while factoring in the nonlinear relationship between meteorological factors/ambient air pollutants and urolithiasis and a time lag of ≤10 days. A multivariate analysis was performed. Backward elimination with an Akaike information criterion was used for fitting the multivariate model. RESULTS: Urolithiasis was significantly associated with average temperature, diurnal temperature range, sunshine duration, particulate matter (PM) ≤2.5 μm, and carbon monoxide (CO) levels. The incidence of ureteral stones was positively correlated with average temperature, PM ≤2.5 μm level, and CO level (time lags 0-9, 2-4, and 0-9 days, respectively). The incidence of renal stones was positively correlated with PM ≤2.5 μm and CO levels (time lags 2-4 and 0-9 days, respectively). PM≤2.5 μm (0.05 and 0.07% per 10 μg/m^3) and CO (2.05 and 2.25% per 0.1ppm) conferred the highest excess risk on ureteral and renal stones. CONCLUSIONS: Urolithiasis is affected by various meteorological factors and ambient air pollutants, PM PM≤2.5 μm, and CO levels may be novel potential risk factors for this condition.
The influences of weather and air pollutants on chronic obstructive pulmonary disease (COPD) have been well-studied. However, the heterogeneous effects of different influenza viral infections, air pollution and weather on COPD admissions and re-admissions have not been thoroughly examined. In this study, we aimed to elucidate the relationships between meteorological variables, air pollutants, seasonal influenza, and hospital admissions and re-admissions due to COPD in Hong Kong, a non-industrial influenza epicenter. A total number of 507703 hospital admissions (i.e., index admissions) and 301728 re-admission episodes (i.e., episodes within 30 days after the previous discharge) for COPD over 14 years (1998-2011) were obtained from all public hospitals. The aggregated weekly numbers were matched with meteorological records and outdoor air pollutant concentrations. Type-specific and all-type influenza-like illness positive (ILI+) rates were used as proxies for influenza activity. Generalized additive models were used in conjunction with distributed-lag non-linear models to estimate the associations of interest. According to the results, high concentrations of fine particulate matter, oxidant gases, and cold weather were strong independent risk factors of COPD outcomes. The cumulative adjusted relative risks exhibited a monotone increasing trend except for ILI+ B, and the numbers were statistically significant over the entire observed range of ILI+ total and ILI+ A/H3N2 when the reference rate was zero. COPD hospitalization risk from influenza infection was higher in the elderly than that in the general population. In conclusion, our results suggest that health administrators should impose clean air policies, such as strengthening emissions control on petrol vehicles, to reduce pollution from oxidant gases and particulates. An extension of the influenza vaccination program for patients with COPD may need to be encouraged: for example, vaccination may be included in hospital discharge planning, particularly before the winter epidemic.
BACKGROUND: Myocardial infarction is an important cause of cardiovascular mortality and can be precipitated by climatic factors. The temperature dependence of myocardial infarction risk has been well examined in temperate settings. Fewer studies have investigated this in the tropics where thermal amplitudes are narrower. This study investigated how ambient temperature influenced the risk of non-ST segment elevation myocardial infarction (NSTEMI), an increasingly common type of myocardial infarction, in the tropical city-state of Singapore. METHODS: All nationally reported NSTEMI cases from 2009 to 2018 were included and assessed for its short-term association with ambient temperature using conditional Poisson regression models that comprised a three-way interaction term with year, month and day of the week and adjusted for relative humidity. The Distributed Lag Non-Linear Modelling (DLNM) was used to account for the immediate and lagged effects of environmental exposures. Stratified analysis by sex and age groups was undertaken to assess potential effect modification. RESULTS: There were 60,643 reports of NSTEMI. Temperature decline (cool effect) was associated with a delayed cumulative, non-linear increase in NSTEMI risk over 10 days post exposure [Relative Risk (RR(lag0)(-)(10, 10th percentile): 1.12, 95%CI: 1.02-1.24)]. Those aged 65 years and above were potentially more susceptible (RR (lag0)(-)(10, 10th percentile): 1.19, 95 % CI: 1.06-1.33) to the cool effect compared to those below that age (RR(lag0)(-)(10, 10th percentile): 1.00, 95 % CI: 0.85-1.18) (p-value for difference = 0.087). CONCLUSION: Short-term temperature fluctuations were independently associated with NSTEMI incidence in the tropics, with age as a potential effect modifier of this association. An increase in the frequency of climate change driven temperature events may trigger more instances of NSTEMI in tropical cosmopolitan cities.
BACKGROUND AND PURPOSE: The correlation between meteorological parameters and intracerebral hemorrhage (ICH) occurrence is controversial. Our research explored the effect of daily meteorological parameters on ICH risk in a subtropical monsoon basin climate. METHODS: We retrospectively analyzed patients with ICH in a teaching hospital. Daily meteorological parameters including temperature (TEM), atmospheric pressure (PRE), relative humidity (RHU), and sunshine duration (SSD) were collected, with the diurnal variation (daily maximum minus minimum) and day-to-day variation (average of the day minus the previous day) calculated to represent their fluctuation. We adopted a time-stratified case-crossover approach and selected conditional logistic regression to explore the effect of meteorological parameters on ICH risk. The influence of monthly mean temperature proceeded via stratified analysis. Air pollutants were gathered as covariates. RESULTS: Our study included 1052 eligible cases with ICH. In a single-factor model, the risk of ICH decreased by 5.9% (P<0.001) for each 1??C higher of the daily mean TEM, and the risk increased by 2.4% (P=0.002) for each 1hPa higher of the daily mean PRE. Prolongation of daily SSD inhibited the risk of ICH, and OR was 0.959 (P=0.007). The risk was raised by 7.5% (P=0.0496) with a 1°C increment of day-to-day variation of TEM. In a two-factor model, the effect of daily mean TEM or daily SSD on ICH risk was still statistically significant after adjusting another factor. The influence of meteorological parameters on ICH risk continued in cold months but disappeared in warm months after stratified analysis. CONCLUSION: This research indicates daily TEM and SSD had an inverse correlation to ICH risk in a subtropical monsoon basin climate. They were independent when adjusted by another factor. Daily PRE and day-to-day TEM variation were positively related to ICH risk. The correlation of daily meteorological factors on ICH risk was affected by the monthly thermal background.
BACKGROUND: Climate change and its subsequent effects on temperature have raised global public health concerns. Although numerous epidemiological studies have shown the adverse health effects of temperature, the association remains unclear for children aged below five years old and those in tropical climate regions. METHODS: We conducted a two-stage time-stratified case-crossover study to examine the association between temperature and under-five mortality, spanning the period from 2014 to 2018 across all six regions in Malaysia. In the first stage, we estimated region-specific temperature-mortality associations using a conditional Poisson regression and distributed lag nonlinear models. We used a multivariate meta-regression model to pool the region-specific estimates and examine the potential role of local characteristics in the association, which includes geographical information, demographics, socioeconomic status, long-term temperature metrics, and Healthcare by region. RESULTS: Temperature in Malaysia ranged from 22 °C to 31 °C, with a mean of 27.6 °C. No clear seasonality was observed in under-five mortality. We found no strong evidence of the association between temperature and under-five mortality, with an “M-” shaped exposure-response curve. The minimum mortality temperature (MMT) was identified at 27.1 °C. Among several local characteristics, only education level and hospital bed rates reduced the residual heterogeneity in the association. However, effect modification by these variables were not significant. CONCLUSION: This study suggests a null association between temperature and under-five mortality in Malaysia, which has a tropical climate. The “M-” shaped pattern suggests that under-fives may be vulnerable to temperature changes, even with a small temperature change in reference to the MMT. However, the weak risks with a large uncertainty at extreme temperatures remained inconclusive. Potential roles of education level and hospital bed rate were statistically inconclusive.
OBJECTIVES: To examine the association among acute bronchiolitis-related hospitalisation in children, meteorological variation and outdoor air pollution. METHODS: We obtained the daily counts of acute bronchiolitis-related admission of children≤2 years old from all public hospitals, meteorological data and outdoor air pollutants’ concentrations between 1 January 2008 and 31 December 2017 in Hong Kong. We used quasi-Poisson generalised additive models together with distributed lag non-linear models to estimate the associations of interest adjusted for confounders. RESULTS: A total of 29 688 admissions were included in the analysis. Increased adjusted relative risk (ARR) of acute bronchiolitis-related hospitalisation was associated with high temperature (ambient temperature and apparent temperature) and was marginally associated with high vapour pressure, a proxy for absolute humidity. High concentration of NO(2) was associated with elevated risk of acute bronchiolitis admission; the risk of bronchiolitis hospitalisation increased statistically significantly with cumulative NO(2) exposure over the range 66.2-119.6 µg/m(3). For PM(10), the significant effect observed at high concentrations appears to be immediate but not long lasting. For SO(2), ARR increased as the concentration approached the 75th percentile and then decreased though the association was insignificant. CONCLUSIONS: Acute bronchiolitis-related hospitalisation among children was associated with temperature and exposure to NO(2) and PM(10) at different lag times, suggesting a need to adopt sustainable clean air policies, especially to target pollutants produced by motor vehicles, to protect young children’s health.
BACKGROUND: The associations between ambient temperatures and stroke are still uncertain, although they have been widely studied. Furthermore, the impact of latitudes or climate zones on these associations is still controversial. The Tropic of Cancer passes through the middle of Taiwan and divides it into subtropical and tropical areas. Therefore, the Taiwan National Health Insurance Database can be used to study the influence of latitudes on the association between ambient temperature and stroke events. METHODS: In this study, we retrieved daily stroke events from 2010 to 2015 in the New Taipei and Taipei Cities (the subtropical areas) and Kaohsiung City (the tropical area) from the National Health Insurance Research Database. Overall, 70,338 and 125,163 stroke events, including ischemic stroke and intracerebral hemorrhage, in Kaohsiung City and the Taipei Area were retrieved from the database, respectively. We also collected daily mean temperatures from the Taipei and Kaohsiung weather stations during the same period. The data were decomposed by ensemble empirical mode decomposition (EEMD) into several intrinsic mode functions (IMFs). There were consistent 6-period IMFs with intervals around 360 days in most decomposed data. Spearman’s rank correlation test showed moderate-to-strong correlations between the relevant IMFs of daily temperatures and events of stroke in both areas, which were higher in the northern area compared with those in the southern area. CONCLUSIONS: EEMD is a useful tool to demonstrate the regularity of stroke events and their associations with dynamic changes of the ambient temperature. Our results clearly demonstrate the temporal association between the ambient temperature and daily events of ischemic stroke and intracranial hemorrhage. It will contribute to planning a healthcare system for stroke seasonally. Further well-designed prospective studies are needed to elucidate the meaning of these associations.
A substantial number of studies have demonstrated the association between air pollution and adverse health effects. However, few studies have explored the potential interactive effects between meteorological factors and air pollution. This study attempted to evaluate the interactive effects between meteorological factors (temperature and relative humidity) and air pollution ([Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]) on cardiovascular diseases (CVDs). Next, the high-risk population susceptible to air pollution was identified. We collected daily counts of CVD hospitalizations, air pollution, and weather data in Nanning from January 1, 2014, to December 31, 2015. Generalized additive models (GAMs) with interaction terms were adopted to estimate the interactive effects of air pollution and meteorological factors on CVD after controlling for seasonality, day of the week, and public holidays. On low-temperature days, an increase of [Formula: see text] in [Formula: see text], [Formula: see text], and [Formula: see text] was associated with increases of 4.31% (2.39%, 6.26%) at lag 2; 2.74% (1.65%, 3.84%) at lag 0-2; and 0.13% (0.02%, 0.23%) at lag 0-3 in CVD hospitalizations, respectively. During low relative humidity days, a [Formula: see text] increment of lag 0-3 exposure was associated with increases of 3.43% (4.61%, 2.67%) and 0.10% (0.04%, 0.15%) for [Formula: see text] and [Formula: see text], respectively. On high relative humidity days, an increase of [Formula: see text] in [Formula: see text] was associated with an increase of 5.86% (1.82%, 10.07%) at lag 0-2 in CVD hospitalizations. Moreover, elderly (≥ 65 years) and female patients were vulnerable to the effects of air pollution. There were interactive effects between air pollutants and meteorological factors on CVD hospitalizations. The risk that [Formula: see text], [Formula: see text], and [Formula: see text] posed to CVD hospitalizations could be significantly enhanced by low temperatures. For [Formula: see text] and [Formula: see text], CVD hospitalization risk increased in low relative humidity. The effects of [Formula: see text] were enhanced at high relative humidity.
Background: The impacts of temperature variability on cardiac autonomic function remain unclear. Objective: To explore the short-term associations between daily temperature variability and parameters of heart rate variability (HRV). Methods: This is a repeated-measure study among 78 eligible participants in Shanghai, China. We defined temperature variability as diurnal temperature range (DTR), the standard-deviation of temperature (SDT) and temperature variability (TV). We evaluated 3 frequency-domain HRV parameters (VLF, LF and HF) and 4 time domain parameters (SDNN, SDANN, rMSSD and pNN50). We used linear mixed-effect models to analyze the data after controlling for environmental and individual confounders. Results: Temperature variability was significantly associated with decreased HRV, especially on the concurrent day. The exposure-response relationships were almost inversely linear for most parameters. Every one inter quartile range (IQR) increase of DTR was associated with a decrease of 3.92% for VLF, 6.99% for LF, 5.88% for HF, 3.94% for rMSSD and 1.30% for pNN50. Each IQR increase of SDT was associated with a decline of 6.48% for LF, 5.91% for HF, 4.26% for rMSSD and 1.87% for pNN50. Every IQR increase of SDT was associated with a decrease of 4.39% for VLF, 7.67% for LF, 6.52% for HF, 3.22% for SDNN, 2.98% for SDANN, 4.05% for rMSSD, and 1.41% for pNN50. The decrements in HRV associated with temperature variability were more prominent in females. Conclusion: Temperature variability on the concurrent day could significantly decrease cardiac autonomic function, especially in females.
Building envelopes are a key element of green building design due to the immense amount of building energy and consumables. However, the quantitative evaluation of the embodied environmental impact of the envelope structure in green buildings is limited. This study aims to minimize the embodied environmental impact of the envelope structure. First, the types of embodied environmental impacts are classified into 12 categories (global warming, ozone depletion, eutrophication, smog, acidification, criteria air pollutants, indoor air quality, human health, ecotoxicity, habitat alteration, water intake, and fossil fuel combustion) using the causal network method and the equivalent factor method. Second, a quantitative model for evaluating the embodied environmental impact is developed based on the distance-to-target approach. Third, a green building in Jiangsu Province, China, is used as a case to form a green building envelope technology checklist by considering building envelope design principles. Building for Environment and Economic Sustainability (BEES) software is used to calculate the life cycle environmental impact inventory and embodied environmental impact. Furthermore, C# programming language is used to select 25 green building envelope packages with minimal environmental impact. This study offers an indepth understanding of the embodied environmental impact of green building envelope. The developed model not only calculates the accurate embodied environmental impact of green building but also provides an effective platform for identifying and determining the best building envelope structure to minimize the environmental impact of green buildings.
INTRODUCTION: It has been demonstrated that weather conditions have significant impacts on freeway safety. However, when employing an econometric model to examine freeway crash injury severity, most of the existing studies tend to categorize several different adverse weather conditions such as rainy, snowy, and windy conditions into one category, “adverse weather,” which might lead to a large amount of information loss and estimation bias. Hence, to overcome this issue, real-time weather data, the value of meteorological elements when crashes occurred, are incorporated into the dataset for freeway crash injury analysis in this study. METHODS: Due to the possible existence of spatial correlations in freeway crash injury data, this study presents a new method, the spatial multinomial logit (SMNL) model, to consider the spatial effects in the framework of the multinomial logit (MNL) model. In the SMNL model, the Gaussian conditional autoregressive (CAR) prior is adopted to capture the spatial correlation. In this study, the model results of the SMNL model are compared with the model results of the traditional multinomial logit (MNL) model. In addition, Bayesian inference is adopted to estimate the parameters of these two models. RESULT: The result of the SMNL model shows the significance of the spatial terms, which demonstrates the existence of spatial correlation. In addition, the SMNL model has a better model fitting ability than the MNL model. Through the parameter estimate results, risk factors such as vertical grade, visibility, emergency medical services (EMS) response time, and vehicle type have significant effects on freeway injury severity. Practical Application: According to the results, corresponding countermeasures for freeway roadway design, traffic management, and vehicle design are proposed to improve freeway safety. For example, steep slopes should be avoided if possible, and in-lane rumble strips should be recommended for steep down-slope segments. Besides, traffic volume proportion of large vehicles should be limited when the wind speed exceeds a certain grade.
Delivery of automatic electrical defibrillator (AED) by unmanned aerial vehicle (UAV) was suggested for out-of-hospital cardiac arrest (OHCA). The goal of this study is to assess the effect of topographic and weather conditions on call to AED attach time by UAV-AED. We included OHCA patients from 2013 to 2016 in Seoul, South Korea. We developed a UAV-AED flight simulator using topographic information of Seoul for Euclidean and topographic flight pathway including vertical flight to overcome high-rise structures. We used 4 kinds of UAV flight scenarios according to weather conditions or visibility. Primary outcome was emergency medical service (EMS) call to AED attach time. Secondary outcome was pre-arrival rate of UAV-AED before current EMS based AED delivery. Call to AED attach time in topographic pathway was 7.0 min in flight and control advanced UAV and 8.0 min in basic UAV model. Pre-arrival rate in Euclidean pathway was 38.0% and 16.3% for flight and control advanced UAV and basic UAV. Pre-arrival rate in the topographic pathway was 27.0% and 11.7%, respectively. UAV-AED topographic flight took longer call to AED attach time than Euclidean pathway. Pre-arrival rate of flight and control advanced UAV was decreased in topographic flight pathway compared to Euclidean pathway.
With global warming and rapid urban growth, cities get warmer, which poses additional stress on human thermal comfort and health. Complex three-dimensional (3D) urban forms change radiation fluxes and shade patterns in cities, but most studies that link urban form to thermal exposure have traditionally investigated the horizontal, two-dimensional composition and configuration of urban landscapes. Supported by high-precision airborne LiDAR data and IKONOS satellite data, this study calculates 3D urban landscape metrics for central Nanjing, China, including vegetation above ground biomass (AGB), building volume (V-B), standard deviation of building and vegetation heights (HSDB, HSDV), the building normalized compactness radio (nCR), sky view factor (SVF), surface roughness (SR), and shadow patterns (SP). Diurnal hourly mean radiant temperature (T-mrt) is simulated using the UMEP (Urban Multi-scale Environmental Predictor) tool forced with fixed-point observation data for a typical hot summer day. Correlation and multiple regression analyses are conducted to investigate the relationship between the 3D form metrics and T-mrt and to identify key factors that influence the thermal environment. T-mrt varies spatially and diurnally and is strongly related to SP during the day, revealing the importance of solar access for modulating the thermal environment. AGB is negatively, but SVF, SP, and building nCR are positively correlated with daytime T-mrt. At night, T-mrt is more homogeneous across space and mainly impacted by the urban fabric’s ability to lose heat. Open areas cool faster than areas with low SVF and complex urban forms with high building nCR. Findings from this study have great scientific and practical significance for optimizing urban landscape patterns from a human-centered heat exposure perspective and will guide planning and design strategies to promote thermally comfortable urban environments.
BACKGROUND: Although mounting evidence has associated air pollution and environmental temperature with children’s health problems, it is unclear whether there is an interaction between these factors on childhood asthma. OBJECTIVES: To explore the effects of temperature-pollution interactions during pre- and post-natal periods on asthma among pre-schoolers. METHODS: A retrospective cohort study of 39,782 pre-schoolers was performed during 2010-2012, in seven cities in China. Exposure to three temperature indicators (TI) and three critical ambient air pollutants, including particulate matter with aerodynamic diameter ≤ 10 μm (PM(10)), sulfur dioxide (SO(2)) and nitrogen dioxide (NO(2)) as proxies of industrial and vehicular air pollution, was estimated by an inverse distance weighted (IDW) method. Two-level logistical regression analysis was used to examine the association between both pre- and post-natal exposure and childhood asthma in terms of odds ratio (OR) and 95 % confidence interval (CI). RESULTS: Asthma prevalence in pre-schoolers at age of 3-6 years (6.9 %) was significantly associated with traffic-related air pollutant (NO(2)) exposure, with ORs (95 % CI) of 1.17 (1.06, 1.28), 1.19 (1.05-1.34) and 1.16 (1.03-1.31) for an IQR increase in NO(2) exposure during lifetime, pregnancy, and entire postnatal period respectively. Furthermore, childhood asthma was positively associated with exposure to increased temperature during lifetime, pregnancy, and entire postnatal period with ORs (95 % CI) = 1.89 (1.66, 2.16), 1.47 (1.34, 1.61), and 1.15 (1.11, 1.18) respectively, while was negatively associated with decreased temperatures. Childhood asthma was positively related with exposure to extreme heat days (EHD) during postnatal period particularly in first year of life respectively with ORs (95 % CI) = 1.23 (1.04, 1.46) and 1.26 (1.07, 1.47), but was not related with extreme cold days (ECD) exposure. A combination of high air pollutant levels and high temperatures significantly increased the risk of asthma during both pre- and post-natal periods. Strikingly, we found a significantly positive interaction of temperature and PM(10) or SO(2) on asthma risk among boys and younger children. CONCLUSIONS: Prenatal and postnatal exposure to ambient air pollution and high temperatures are independently and jointly associated with asthma risk in early childhood.
BACKGROUND: Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand. METHODS: This longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 μm (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), ozone (O(3)), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005-2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM(10), O(3), NO(2), SO(2), and CO. RESULTS: After controlling for potential confounders, we found that an IQR increase in PM(10) was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO(2) was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O(3) and NO(2). CONCLUSIONS: Long-term exposure to air pollution, especially for PM(10) and SO(2) was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population.
RATIONALE Chronic obstructive lung disease (COPD) is a chronic progressive disease. Although smoking is the most important risk factor, 30% of COPD patients are never smokers, and environmental agents are also influential. The effects of air pollutants and meteorological factors on COPD exacerbations have not been studied extensively. OBJECTIVE We aimed to investigate the air pollutants and meteorological factors that impact the incidence of COPD exacerbations. METHODS We obtained clinical data of COPD exacerbation cases from The National Health Insurance Service (NHIS) and merged it with 24-hour average values of air pollutants and meteorological factors from national databases. Patients who reside in eight metropolitan cities, where observatory stations are densely located, were selected for analysis. RESULTS In 1,404,505 COPD patients between 2013 and 2018, 15,282 COPD exacerbations leading to hospitalization or emergency room visits were identified. Among the various air pollutants and meteorological factors, particulate matter (PM)2.5, PM10, NO2, SO2, CO, O3, average temperature and diurnal temperature range (DTR) were associated with COPD exacerbations. GAM model analysis with cubic splines showed an inverted U-shaped relationship with PM2.5, PM10, CO, NO2, SO2, O3, DTR and humidity, while it displayed a U-shaped pattern with the average temperature. Distinct patterns were found from 2015-2016 to 2017-2018. CONCLUSIONS PM2.5, PM10, CO, NO2, O3, SO2, average temperature, humidity, and DTR affected the incidence of COPD exacerbations in various patterns, up to 10 lag days.
Few investigations have assessed the impact of short-term ambient temperature change on pneumonia risk. We aimed to study the relation of temperature variability (TV) with daily hospitalizations for pneumonia in China. We conducted a time-series study in 184 major cities by extracting daily hospital data between 2014 and 2017 from a medical insurance claims database of 0.28 billion beneficiaries. TV was calculated as standard deviation of daily minimum and maximum temperatures over exposure days. We estimated associations of pneumonia admissions with TV for each city using over-dispersed generalized linear models controlling for weather conditions and ambient air pollution, and pooled city-specific estimates using random effects meta-analyses. We also investigated exposure-response relationship curve and potential effect modifiers. We identified 4.2 million pneumonia hospitalizations during the study period. TV was positively related to daily pneumonia admissions. At the national-average level, each 1-°C increase in TV at 0-6 days’ exposure corresponded to a 0.65 % (95 % CI: 0.34 %-0.96 %) increase in pneumonia admissions. An approximately linear exposure-response curve for the relation of TV with pneumonia admission was noted. The relations were more evident in cities with larger average age (P = 0.038). As the first study in China to assess the impact of temperature change on pneumonia on a national scale, our results indicated that acute TV exposure was related to higher admissions for pneumonia. Our findings should provide new insight into the health impacts associated with climate change.
BACKGROUNDS: Evidence for the effects of temperature variability on risk of congenital anomalies is lacking. We aimed to examine the association of temperature variability during fetal organogenesis period (weeks 3-8 post-conception) with major congenital anomalies. METHODS: A retrospective cohort study comprising 4,787,356 singleton live-births and stillbirths in China was performed. We defined two temperature variability indices within gestational week i: the standard deviation (SD) of daily temperature (TVSD(i)) and the maximum day-to-day temperature difference (TVD(i)). At 6-week long timescales, we computed the SD of daily temperature (TVSD(3-8)) and the average value of TVD(i) (TVD(3-8)). We matched two temperature variability indices, pollutant exposure levels over entire exposure window and data of each mother-infant pairs. An extended generalized estimating equation log-binomial regression model was constructed to explore their associations after adjusting for individual characters, temperature extremes and air pollutants. Stratified and sensitivity analyses were also performed. RESULTS: 59,571 neonates were registered as major congenital anomalies besides genetic and chromosomal anomalies. At weekly levels, the highest risk estimates of two temperature variability indices occurred at the 5th week for most anomaly groups. All TVSD(5), TVD(5), and maximum weekly TVSD and TVD were significantly associated with all anomaly groups; with the increment of 1 °C, the estimated risk ratio (RR) and corresponding 95% confidence interval (CI) ranges from 1.03 (1.01-1.05) to 1.19 (1.08-1.31). At 6-week scales, TVSD(3-8) and TVD(3-8) were associated with most anomaly subgroups. Overall, the strongest associations were estimated for isolated defects among morphology subgroups and cardiac defects among type subgroups. CONCLUSIONS: Exposure to temperature variability during fetal organogenesis period of pregnancy is associated with increased risk of major congenital defects. Our findings provide a research foundation for public health policies, and further mechanism investigation.
BACKGROUNDS: Abnormal sperm quality in men is one of the common causes of infertility. Both ambient temperature and extreme heat exposure have been shown to be associated with sperm quality, but there is no epidemiological evidence for the effect of ambient temperature variability. Our aim was to investigate the association between ambient temperature variability exposure and a decline in sperm quality at different stages of sperm development. METHODS: A total of 4912 semen samples collected from the Guangdong Human Sperm Bank between 1 January 2019 and 31 December 2019 were analyzed. We selected three exposure periods: the full-stage (0-90 lag days), early-stage (34-77 lag days) and late-stage (0-37 lag days) of sperm development, and then calculated the standard deviation of daily temperature (TVSD), the maximum day-to-day temperature difference (TVD(max)) and the mean day-to-day temperature difference (TVD(mean)) for the three exposure periods. A linear mixed model was used to explore the exposure response relationship between temperature variability exposure and sperm quality indicators (including sperm concentration, sperm count and sperm motility). RESULTS: There was a significant negative association of decreased sperm count with the exposure to temperature variability during 0-90 days prior to sperm collection. (TVD(max): -0.041; -0.063, -0.019; TVD(mean): -0.237; -0.386, -0.088; TVSD: -0.103; -0.196, -0.011). We observed a significant association between the decline in sperm concentration, sperm count and per 1 °C increase in TVD(mean) during early spermatogenesis. No significant association of temperature variability with sperm motility was found. CONCLUSIONS: The results indicate that exposure to temperature variability during the entire period of sperm development is significantly associated with a decline in sperm counts. We found that mean day-to-day temperature differences had a detrimental effect on sperm counts in the early-stage. Our findings provide a scientific basis for public health policy and further mechanistic studies.
The mortality of the bath-related cardiac arrest (BRCA) is extremely high. While air temperature is reported to be associated with the BRCA occurrence, it is unclear whether daily minimum temperatures or the difference between maximum and minimum air temperatures influences BRCA occurrence the most.A retrospective cohort study of adult patients was conducted between January 2015 and February 2020 at Hirosaki University Hospital Emergency Department. The following data were collected: age, sex, day of cardiac arrest event, location of the event, initial cardiac rhythm, presence of return of spontaneous circulation, and overall mortality (status at 1 month after cardiac arrest event). Based on the day of the event and the location in which the event occurred, daily minimum and maximum temperatures were obtained from the Japan Meteorological Agency database.A total of 215 eligible cardiac arrest cases were identified, including 25 cases of BRCA. Comparing BRCA and non-BRCA, initial shockable cardiac rhythm (4.0% vs 44.7%), presence of return of spontaneous circulation (8.0% vs 34.7%), and overall mortality (96.0% vs 71.6%) differed significantly (P < .05 each). Daily minimum and maximum temperatures showed no significant relationships with BRCA or non-BRCA. Daily minimum temperature was a risk factor of BRCA occurrence after adjusting for age and temperature difference (risk ratio, 0.937; 95% confidence interval, 0.882-0.995).Daily minimum temperature represents a potential risk factor for BRCA occurrence.
Previous studies have documented the associations between short-term diurnal temperature range (DTR) exposure and cardiovascular disease (CVD) via time-series analyses. However, the long-term impacts of DTR through a population-based prospective cohort have not been elucidated thoroughly. This study aimed to quantify the longitudinal association of DTR exposure with all-cause mortality and CVD in a nationwide prospective cohort and, by extension, project future DTR changes across China under climate change. We included 22,702 adults (median age 56.1 years, 53.7% women) free of CVD at baseline from a nationwide cross-sectional study in China during 2012-2015, and examined three health outcomes during a follow-up survey in 2018-2019. We estimated the chronic DTR exposure as baseline annual mean daily maximum minus minimum temperature. The Cox proportional hazards regression was adopted to assess the multivariable-adjusted hazard ratio and its corresponding 95% confidence interval (95% CI). We employed 31 downscaled global climate models under two shared socioeconomic pathways for future projection. During the median follow-up period of ~5 years, 1096 subjects died due to all causes while 993 and 597 individuals developed fatal or nonfatal CVD and fatal or nonfatal stroke, respectively. The cumulative incidence rates of all-cause mortality, CVD, and stroke were 10.49, 9.45, and 5.64 per 1000 person-years, respectively. In the fully adjusted models, the risks for all-cause mortality, CVD, and stroke would increase by 13% (95% CI: 8-18%), 12% (95% CI: 7-18%), and 9% (95% CI: 2-16%) per 1 °C increment in DTR, respectively. Moreover, linear positive associations for the concentration-response curves between DTR and mortality and CVD were observed. We also found significantly greater DTR-related mortality risks among rural residents than their urban counterparts. The DTR changes featured a dipole pattern across China under a warming climate. The southern (northern) China would experience increased (decreased) DTR exposure by the end of 21st century. The present study indicates that chronic DTR exposure can exert long-term impacts on mortality and CVD risks, which may inform future public health policies on DTR-related susceptible population and regions.
The association between weather-related variables or seasons and the development of Bell’s palsy (BP) is controversial. This study aimed to evaluate the incidence and clinical characteristics of BP and assess the effects of meteorological factors on seasonal and monthly incidence. This retrospective population-based study used data from the Korean Health Insurance claims database (NHICD) from 2010 to 2018, in which annual, seasonal, and monthly incidence rates and age and sex distributions were calculated. A multivariate linear regression and autoregressive integrated moving average (ARIMA) model was used to determine the association between the seasonal and monthly incidence of BP and meteorological factors, including average wind speed, temperature, relative humidity, and atmospheric pressure. We also conducted a scoping review of the literature on epidemiological and seasonality studies of BP in the past 30 years and summarized them in a table for easy comparison with other studies. In this study, the incidence rate of BP increased over 9 years (from 12.86 to 19.92 per 100,000 persons) and was the highest in patients in their 60s (31.6/100,000 persons). The seasonal incidence of BP was the highest in autumn and showed a significant difference compared with spring (coefficient - 0.318, p = 0.003) and summer (coefficient - 0.463, p < 0.001), adjusting the year. In the ARIMA analysis, the autocorrelation of the monthly and seasonal lag in the raw data disappeared after adjustment of the seasonal (or monthly) and longitudinal changes, indicating no additional trends outside the seasonal (or monthly) longitudinal changes. The seasonal and monthly incidence of BP was related to low temperature (p = 0.002), high atmospheric pressure (p = 0.034), and low relative humidity (p < 0.001) in the multivariate linear regression. In contrast, in the ARIMA analysis, after adjusting for seasonality, month, and trends, there were no significant meteorological factors associated with the monthly or seasonal incidence rate. In the past 30 years, 12 studies have reported on the prevalence or incidence of BP, and 14 have reported on the relationship between seasons, weather, and incidence. These results indicate that BP is more common among the elderly, and the incidence of BP is increasing due to an aging society, increased medical accessibility, and lifestyle changes. The data also indicate that the onset of BP is associated with low temperature and humidity; however, in the climate zone with extreme temperature and humidity differences between the coldest and hottest months, it is assumed that the marked decrease in temperature (autumn) has more influence on the outbreak of BP than does the actual cold temperature (winter).
BACKGROUND: Using a population-based stroke registry system, we evaluated the relationship between ambient temperature parameters and stroke incidence in a Japanese population.Methods and Results:We analyzed data from the Takashima Stroke Registry, which records all stroke occurrences in Takashima City, Japan. The study period of 8,401 days was divided into quintiles of daily weather parameters, and the middle quintile was used as the reference category. Incidence rates (IR per 100,000 person-years) were calculated across the quintiles. Poisson regression analysis was used to calculate the effect of temperature parameters on stroke incidence. There were 2,405 first-ever strokes (1,294 men), including 1,625 ischemic, 545 cerebral hemorrhages, 213 subarachnoid hemorrhages, and 22 unclassified strokes. The stroke IR was higher in the middle quintile of average temperature, 357.3 (328.4-388.8), and for other parameters. After adjustment for age and sex, for all stroke, the incidence rate ratio (IRR) in the highest (Q5: IRR 0.81, 95% confidence interval (CI) 0.71-0.92) and the second-highest (Q4: IRR 0.80, 95% CI 0.71-0.91) quintile was lower than that in the middle quintile (Q3: Reference). Analogous results were observed for the minimum, maximum, and lag-days temperatures, also in the subtypes and across ≥65 years of age, also in females. CONCLUSIONS: Higher temperatures, irrespective of the parameter (average, minimum, or maximum), had a protective effect against stroke occurrence in Japan.
OBJECTIVES: To investigate the extent to which temperature and influenza explained seasonality of mortality in Japan and to examine the association of the seasonality with prefecture-specific characteristics. DESIGN: We conducted time-series analysis to estimate the seasonal amplitude before and after adjusting for temperature and/or influenza-like illness (ILI). Next, we applied linear mixed effect models to investigate the association of seasonal amplitudes with each indicator on prefecture-specific characteristics on climate, demographic and socioeconomic factors and adaptations. SETTING: 47 prefectures in Japan PARTICIPANTS: Deaths for all-cause, circulatory, and respiratory disease between 1999 and 2015. OUTCOME MEASURES: Peak-to-trough ratio (PTR, a measure of seasonal amplitude). RESULTS: The nationwide unadjusted-PTRs for all-cause, circulatory and respiratory mortality were 1.29 (95% CIs: 1.28 to 1.31), 1.55 (95% CI: 1.52 to 1.57) and 1.45 (95% CI: 1.43 to 1.48), respectively. These PTRs reduced substantially after adjusting for temperature but very little after a separate adjustment for ILI. Furthermore, seasonal amplitudes varied between prefectures. However, there was no strong evidence for the associations of PTR with the indicators on prefecture-specific characteristics. CONCLUSIONS: Seasonality of mortality is primarily driven by temperature in Japan. The spatial variation in seasonal amplitudes was not associated with prefecture-specific characteristics. Although further investigations are required to confirm our findings, this study can help us gain a better understanding of the mechanisms underlying seasonality of mortality.
This study analyzes how climate change affects the economy, society, and environment in South Korea. Then, the study explores the ways to strengthen capabilities that can alleviate climate change impacts. To find them, the study employs a system dynamics simulation method and builds a model with several sectors including the urban, rural, population, and social-environmental sectors. The study compares the size of climate change damages in rural and urban areas. The results with representative concentration path (RCP) 8.5 show that the size of climate change damage will continue to increase by 2050. The projected damages from the reduced industrial outputs in urban areas will be larger than that in rural areas. The results also show that the service sector will face stronger impacts from climate change than the manufacturing and agricultural sectors. However, the total size of damage in the rural areas will be bigger than that of the urban areas. It is because the size of reduced industrial outputs per capita in the rural areas is twice bigger than that of the urban areas. The climate change damage in the social and environmental sectors (including a loss of biodiversity and an increase in health costs) account for the largest part of the total damage. The study finally provides suggestions and policies that can improve the capabilities to reduce the climate change damages. One of the major suggestions of this study is that the increase in the climate change budget corresponding to the GDP growth can minimize the size of climate change impacts.
This study investigated how changes in weather factors affect the prevalence of conjunctivitis using public big data in South Korea. A total of 1,428 public big data entries from January 2013 to December 2019 were collected. Disease data and basic climate/air pollutant concentration records were collected from nationally provided big data. Meteorological factors affecting eye diseases were identified using multiple linear regression and machine learning analysis methods such as extreme gradient boosting (XGBoost), decision tree, and random forest. The prediction model with the best performance was XGBoost (1.180), followed by multiple regression (1.195), random forest (1.206), and decision tree (1.544) when using root mean square error (RMSE) values. With the XGBoost model, province was the most important variable (0.352), followed by month (0.289) and carbon monoxide exposure (0.133). Other air pollutants including sulfur dioxide, PM(10), nitrogen dioxides, and ozone showed low associations with conjunctivitis. We identified factors associated with conjunctivitis using traditional multiple regression analysis and machine learning techniques. Regional factors were important for the prevalence of conjunctivitis as well as the atmosphere and air quality factors.
This study aimed to analyze the association between temperature and precipitation and the incidence of hepatitis A in Seoul, Korea, as meteorological factors may have different effects on specific diseases depending on the lifestyle in each region. Weekly cases of hepatitis A, weekly mean daily precipitation, and temperature data from 2016 to 2020 were analyzed. Quasi-Poisson-generalized linear models with time variable adjusted by spline function were used considering 0-6-week lags. The association of each variable and hepatitis A incidence was assessed by the single lag and the constrained distributed lag model. Multivariable distributed lag linear and non-linear models were used to develop models with significant independent variables. Weekly mean of daily mean temperature (Tmean) and maximum temperature (Tmax) were negatively associated with hepatitis A in the 6-week lag. Precipitation was negatively associated with hepatitis A in the 5- and 6-week lags. The multivariable model showed the negative association of Tmax, precipitation and hepatitis A in the 5- and 6-week lags. In the non-linear models, the incidence rate ratio (IRR) was the highest at a Tmax of 11 °C and decreased thereafter. IRR was the highest at 12 mm of precipitation and showed decrease pattern to 25 mm and then gradually increased in the 5- and 6-week lags. Identifying the impact of climate factors on hepatitis A incidence would help in the development of strategies to prevent diseases and indirectly estimate the impact of climate change on hepatitis A epidemiology.
Hepatitis A is a water-borne infectious disease that frequently occurs in unsanitary environments. However, paradoxically, those who have spent their infancy in a sanitary environment are more susceptible to hepatitis A because they do not have the opportunity to acquire natural immunity. In Korea, hepatitis A is prevalent because of the distribution of uncooked seafood, especially during hot and humid summers. In general, the transmission of hepatitis A is known to be dynamically affected by socioeconomic, environmental, and weather-related factors and is heterogeneous in time and space. In this study, we aimed to investigate the spatio-temporal variation of hepatitis A and the effects of socioeconomic and weather-related factors in Korea using a flexible spatio-temporal model. We propose a Bayesian Poisson regression model coupled with spatio-temporal variability to estimate the effects of risk factors. We used weekly hepatitis A incidence data across 250 districts in Korea from 2016 to 2019. We found spatial and temporal autocorrelations of hepatitis A indicating that the spatial distribution of hepatitis A varied dynamically over time. From the estimation results, we noticed that the districts with large proportions of males and foreigners correspond to higher incidences. The average temperature was positively correlated with the incidence, which is in agreement with other studies showing that the incidences in Korea are noticeable in spring and summer due to the increased outdoor activity and intake of stale seafood. To the best of our knowledge, this study is the first to suggest a spatio-temporal model for hepatitis A across the entirety of Korean. The proposed model could be useful for predicting, preventing, and controlling the spread of hepatitis A.
To provide a nationwide representative dataset for the study on health impact of air pollution, we combined the data from the Korea National Health and Nutrition Examination Survey with the daily air quality and weather data by matching the date of examination and the residential address of the participants. The database of meteorological factors and air quality as sources of exposure data were estimated using the Community Multiscale Air Quality model. The linkage dataset was merged by three ways; administrative district, si-gun-gu (city, county, and district), and geocode (in latitude and longitude coordinate units) based on the participants’ residential address, respectively. During the study period, the exposure dataset of 85,018 individuals (38,306 men and 46,712 women) whose examination dates were recorded were obtained. According to the definition of exposure period, the dataset was combined with the data on short-term, mid-term, and long-term exposure to air pollutants and the meteorological indices. Calculation of the daily merged dataset’s average air pollution linked by si-gun-gu and geocode units showed similar results. This study generated a daily average of meteorological indices and air pollution exposure dataset for all regions including rural and remote areas in Korea for 11 years. It is expected to provide a platform for the researchers studying the health impact of air pollution and climate change on the representative population and area, which may facilitate the establishment of local health care plans by understanding the residents’ health status at the local as well as national level.
Rapid industrialization of Korea’s economy has brought with it environmental pollution that threatens human health. Among various other pollutants, ambient fine particulate matter known to endanger human health often exceeds air quality standards in Seoul, South Korea’s capital. The goal of this research is to find the impact of meteorological extremes and particle levels on human health. The analysis was conducted using hourly air pollutant concentrations, meteorological variables, and the daily mortality from cerebrovascular disease. Results show that the effect of fine particulate matter on mortality from cerebrovascular disease was more noticeable during meteorological extremes. The linkage between extreme weather conditions and mortality was more apparent in winter than in summer. Comprehensive studies of various causes of diseases should be continued to more accurately analyze the effects of fine particulate matter on human health and meteorological extremes, and to further minimize the public health impact of air pollution and meteorological conditions.
BACKGROUND: Although changes in skin depend on the external environment, researchers have performed only a few studies on effect of the actual environment. Most studies have researched skin characterization based on changes in the humidity or temperature. AIM/OBJECTIVE: This study aimed to evaluate changes in the skin based on the difference in indoor and outdoor temperatures and humidity during summer in South Korea and Southeast Asia. METHODS: Twenty-two female participants aged 25-39 years were included. Skin hydration, sebum (cheek, forehead), colour, transparency and pores of the participants were measured after a 30-min exposure to high temperature and high humidity (HTHH) environment and a 30-min exposure to low temperature and low humidity (LTLH) environment. Subsequently, exposure to HTHH environment for 30 min +LTLH environment for 30 min was performed after a total of 1 h and repeated. RESULTS: Repeated exposure to HTHH and LTLH environments increased the skin’s sebum content and haemoglobin index. Additionally, skin elasticity was significantly reduced, with patients in their 30 s showing greater changes than those in their 20 s. CONCLUSION: Repeated differences in temperature and humidity cause skin ageing, loosen skin vessels and reduce skin elasticity, thereby leading to skin ageing.
For many people living in low-income coastal communities, marine resources provide a crucial source of animal protein and are of major nutritional importance. However, because of various human-induced pressures, such as overfishing and poor resource management, marine resources are deteriorating at an unprecedented rate. Climate change effects this dynamic by contributing directly to marine resource deterioration and acting as an effect multiplier, worsening already-present problems in the systems. This deterioration threatens the viability of marine resources to support future food security demands and presents multiple health implications for coastal communities that rely upon these resources. This research used a narrative review to explore how the impacts of climate change are projected to impact human health and sustainable development throughout subsistence fishing communities. A case study approach focusing on the Pacific Ocean region of Micronesia was conducted to provide a practical indication of the future scenario applicable to other geographical regions across the globe. The results indicate that climate change is likely to exacerbate adverse health outcomes such as food insecurity, ciguatera fish poisoning, heatstroke, and mental health problems and that climate change may lead to the deterioration of traditional cultural practices. As the climate crisis is happening now and will be an issue extending into the foreseeable future, it is necessary to implement adaptation strategies, funding, and governance to limit global emissions, preserve marine resources, and support human well-being. Therefore, this research details adaptation strategies, such as diversifying fish catch and reviving traditional postharvest preservation methods, that may help communities adapt to climate change.
Understanding the impacts of climate on food systems is vital to identifying the most effective food system interventions to support climate-smart agriculture. The study examines how climate change is affecting food systems and what can be done to mitigate its effects. Two methodological approaches were combined in the study. The first was an Asia-wide regional consultation and forum to explore a range of initiatives that transform food systems among stakeholders working in Myanmar. The second method was an in-depth food systems study employing qualitative methods in Htee Pu Village in the Myanmar Central Dry Zone, a research site of IIRR since 2017. Key informant interviews (KII) and focus group discussions (FGD) were conducted to capture insights and data. Food systems consist of components, drivers, actors, and elements that interact with one another and other systems such as social, health, and transportation. The Myanmar food system is complex. Making it sustainable and transformative requires a mix of different approaches implemented at various scales from local to national. It also requires actions that engage various actors in the system from producers to consumers. The study of the local food system of Htee Pu Village indicates that the village has a rural and traditional food system and that climate change is one of its key food system drivers. Climate change negatively impacted farming and agricultural practices and disrupted the input supply of the local food systems. The role of intermediaries such as traders and consolidators is critical in the supply and distribution of food in the Central Dry Zone. Improved and more connected roads are essential for the supply and distribution of food for the village. The informal market outlets serve as the primary food source or sale points for households. Household diets are inadequate in quantity as the population remains highly dependent on their crops for their diets due to relatively low income. Climate adaptation must be embedded in the local level management to mitigate the effect of climate change in food production in the longer term.
BACKGROUND: Haemorrhagic stroke (HS) is a major cause of mortality and disability. Previous studies reported inconsistent associations between ambient air pollutants and HS risk. OBJECTIVE: We evaluated the association between air pollutant exposure and the risk of HS in a cosmopolitan city in the tropics. METHODS: We performed a nationwide, population-based, time-stratified case-crossover analysis on all HS cases reported to the Singapore Stroke Registry from 2009 to 2018 (n = 12,636). We estimated the risk of HS across tertiles of air pollutant concentrations in conditional Poisson models, adjusting for meteorological confounders. We stratified our analysis by age, atrial fibrillation and smoking status, and investigated the lagged effects of each pollutant on the risk of HS up to 5 days. RESULTS: All 12,636 episodes of HS were included. The median (1st-to 3rd-quartile) daily pollutant levels from 22 remote stations deployed across the island were as follows: (PM(2.5) = 15.9 (12.7-20.5), PM(10) = 27.3 (22.7-33.4), O(3) = 22.5 (17.3-29.8), NO(2) = 23.3 (18.8-28.4), SO(2) = 10.2 (5.6-14.4), CO = 0.5 (0.5-0.6). The median (1st-to 3rd-quartile) temperature (°C) was 27.9 (27.1-28.7), that of relative humidity (%) was 79.4 (75.6-83.2), and that of total rainfall (mm) was 0.0 (0.0-4.2). Higher levels of CO were significantly associated with an increased risk of HS (3rd tertile vs 1st tertile: Incidence Rate Ratio (IRR) = 1.06, 95% CI = 1.01-1.12). The increased risk of HS due to CO persisted for at least 5 days after exposure. Individuals under 65 years old and non-smokers had a higher risk of HS when exposed to CO. O(3) was associated with increased risk of HS up to 5 days (3rd tertile vs 1st tertile: IRR(day 1) = 1.07, 95% CI = 1.02-1.12; IRR(day 5) = 1.07, 95% CI = 1.02-1.13). CONCLUSION: Short-term exposure to ambient CO levels was associated with an increased risk of HS. A reduction in CO emissions may reduce the burden of HS in the population.
OBJECTIVES: This study explored the health problems of inhabitants of small South Pacific Islands under the influence of climate change, focusing on three communities in the Solomon Islands. DESIGN: Cross-sectional study of the Solomon Islands’ populations. SETTING: A field survey was conducted in Taro Island, a small, urbanised island with a whole-community relocation plan; Manuopo community of Reef Islands, a small remote island on an atoll environment and Sasamungga, an intermediately urbanised community on a larger island. The Sasamungga community was used for comparison. PARTICIPANTS: Each community’s participants were recruited through local health authorities, and 113, 155 and 116 adults (aged 18+ years) from Taro, Manuopo and Sasamungga, respectively, participated voluntarily. METHODS: Each participant’s body height, weight and body mass index were measured. A drop of blood was sampled for malaria testing; glycated haemoglobin and C reactive protein levels, measured from another drop of blood, were markers for diabetes and inflammation, respectively. The Primary Care Screening Questionnaire for Depression measured depressive mental states. PRIMARY AND SECONDARY OUTCOME MEASURES: Regarding health status, the dependent variables-communicable diseases, non-communicable diseases and mental state-and independent variables-differences in communities and socioeconomic status-were measured through health check-ups and interviews of individual participants. RESULTS: Taro Island inhabitants had a higher risk of obesity (OR 1.13, 95% CI 1.02 to 1.27, p=0.0189), and Manuopo inhabitants had a higher risk of depression (1.25, 95% CI 1.08 to 1.44, p=0.0026) than Sasamungga inhabitants. Manuopo inhabitants recognised more serious problems of food security, livelihood, place to live and other aspects of daily living than other communities’ inhabitants. CONCLUSIONS: The three small island communities’ observation identified different health problems: the urbanised community and remote community had a high risk of non-communicable diseases and mental disorders, respectively. These health problems should be monitored continuously during future climate-related changes.
INTRODUCTION: This focused ethnographic study used qualitative, ethnographic, and participatory methods to explore determinants of maternal, infant, and young child nutrition (MIYCN) during the first 1,000 days of life as part of efforts to address the double burden of malnutrition in Solomon Islands. METHODS: An iterative study design was used to first explore and then confirm findings related to food and nutrition security and social and behavioral determinants of MIYCN in urban and rural settings. The first phase included in-depth interviews, household observations, free lists, and seasonal food availability calendar workshops while the second phase included focus group discussions, pile sorts, participatory community workshops, and repeated household observations. RESULTS AND DISCUSSION: We found that MIYCN is shaped by a complex interaction of factors at the macro- and micro-levels. At the macro-level, globalization of the food system, a shifting economy, and climate change are driving a shift toward a delocalized food system based on imported processed foods. This shift has contributed to a food environment that leaves Solomon Islanders vulnerable to food and nutrition insecurity, which we found to be the primary determinant of MIYCN in this context. At the micro-level, this food environment leads to household- and individual-level food decisions that often do not support adequate MIYCN. Multi-sectoral interventions that address the macro- and micro-level factors shaping this nutrition situation may help to improve MIYCN in Solomon Islands.
Nipah virus (NiV) is a zoonotic virus that can pose a serious threat to human and livestock health. Old-world fruit bats (Pteropus spp.) are the natural reservoir hosts for NiV, and Pteropus lylei, Lyle’s flying fox, is an important host of NiV in mainland Southeast Asia. NiV can be transmitted from bats to humans directly via bat-contaminated foods (i.e., date palm sap or fruit) or indirectly via livestock or other intermediate animal hosts. Here we construct risk maps for NiV spillover and transmission by combining ecological niche models for the P. lylei bat reservoir with other spatial data related to direct or indirect NiV transmission (livestock density, foodborne sources including fruit production, and human population). We predict the current and future (2050 and 2070) distribution of P. lylei across Thailand, Cambodia, and Vietnam. Our best-fit model predicted that central and western regions of Thailand and small areas in Cambodia are currently the most suitable habitats for P. lylei. However, due to climate change, the species range is predicted to expand to include lower northern, northeastern, eastern, and upper southern Thailand and almost all of Cambodia and lower southern Vietnam. This expansion will create additional risk areas for human infection from P. lylei in Thailand. Our combined predictive risk maps showed that central Thailand, inhabited by 2.3 million people, is considered highly suitable for the zoonotic transmission of NiV from P. lylei. These current and future NiV transmission risk maps can be used to prioritize sites for active virus surveillance and developing awareness and prevention programs to reduce the risk of NiV spillover and spread in Thailand.
Conventional local public health planning and monitoring are insufficiently addressing the conjugated impact of urban development change and climate change in the future. The existing checklist and index often ignore the spatial-network interaction determining urban public health services in forward-looking aspects. This study offers and demonstrates a climate-resilient operationalization framework for urban public health services considering the interaction between urban development change and climate change across scales. A combination of collaborative scenario planning and tailor-made composite indicators were applied based on the IPCC Fifth Assessment Report (AR5)’s climate risk concept to adhere to local realities and diverse sets of scenarios. The framework was contested in a medium-sized city with a universal health care coverage setting, Khon Kaen city, Thailand. The results show that the coupling of collaborative scenario planning and composite indicators allows local public health care to operationalize their potential impact and climate-resilient targets in the future(s) in multiple service operation aspects. The scenarios assessment outcomes prove that although public health devotion can be fail-safe, achieving climate-resilient targets requires sectoral integration with urban development and health determining domains. Further exploration and disputation of the framework with a wider scale and diversified settings are recommended to enhance their robustness and universality.
Vietnam is a densely populated country, with the majority of its impoverished people living in rural areas. These people lack facilities and means of self-protection against risks, especially natural disasters related to climate change. Therefore, it is necessary to study the livelihood vulnerability under climate change in rural regions of Vietnam. The study was based on the original Livelihood Vulnerability Index (LVI) and LVI-IPCC (the Intergovernmental Panel on Climate Change) combined with the use of dataset from the Vietnam Access to Resources Household Survey (VARHS) in 2018. by using the dataset from the Vietnam Access to Resources Household Survey (VARHS) in 2018. The database is composed of 1,852 rural households in 12 provinces in Vietnam and considers socio-demographic profile, livelihood, health, food, social networks, water status, natural disasters, and climate variability. The results show that the North Central and South Central Coasts are the most vulnerable regions, with a lower LVI score (0.261) but higher LVI-IPCC score (0.012); this is mainly due to higher exposure to disasters-such as floods, sea storms, and tropical depressions-which heavily affect people’s livelihood. The Red River Delta, the Northern Midlands and Mountains, and the Central Highlands are moderately vulnerable. Moreover, the research outcome indicates that the Red River Delta and the Mekong River Delta were more vulnerable in terms of the sensitivity factor due to a higher vulnerability score on food and water components, especially drought and saltwater intrusions
On recreational sandy beaches, there are guidelines for the management of bacterial pollution in coastal waters regarding untreated sewage, urban wastewater, and industrial wastewater. However, terrestrial plant debris on coastal beaches can be abundant especially after floods and whilst it has rarely been considered a concern, the bacterial population associated with this type of pollution from the viewpoint of public health has not been adequately assessed. In this study, microbes associated with plant debris drifting onto Kizaki Beach in Japan were monitored for 8 months throughout the rainy season, summer, typhoon season, and winter. Here we show that faecal-indicator bacteria in the plant debris and sand under the debris were significantly higher than the number of faecal bacteria in the sand after a 2015 typhoon. When we focused on specific pathogenic bacteria, Brevundimonas vesicularis and Pseudomonas alcaligenes were commonly detected only in the plant debris and sand under the debris during the survey period. The prompt removal of plant debris would therefore help create safer beaches.
Background: Owing to specific working environments, it is important to attain sustainable development goals for the health of fishery workers during climate change. Fishery workers have a hazardous working environment, leading to specific injuries and fatal events. However, limited studies have investigated the health status of fishery workers through long-term longitudinal follow-up and compared it with that of farmers and employed workers with similar socioeconomic status. Methods: The Longitudinal Health Insurance Database 2000, a subset of the Taiwan National Health Insurance Research Database was used for this retrospective cohort study. Only fishery workers, farmers, and employed workers were included. Based on the majority of causes of death and related diseases, participants newly diagnosed with 18 diseases, classified into cardiometabolic diseases, mental illness, chronic kidney disease, infection, and malignancy, were included. Participants with an old diagnosis of these diseases were excluded. All included participants were followed up from 1 July 2000 to the diagnosis and withdrawal date, or 31 December 2012, whichever occurred first. Due to the substantial difference in the baseline demographics, we executed a cohort study with propensity score-matched and applied the Cox model to explore the participants’ health status. Results: After matching, there were negligible differences in the baseline demographics of fishery workers, farmers, and employed workers. Compared to farmers and employed workers, fishery workers were more frequently diagnosed with 11 and 14 diseases, respectively, such as hypertension (hazard ratio [HR]: 1.11, p < 0.01), diabetes (HR: 1.21, p < 0.001), dyslipidemia (HR: 1.18, p < 0.001), depression (HR: 1.38, p < 0.001), peptic ulcer (HR: 1.17, p < 0.001), chronic viral hepatitis (HR: 2.06, p < 0.001), hepatocellular carcinoma (HR: 1.67, p < 0.001), and total malignancy (HR: 1.26, p < 0.001). Conclusions: Compared to farmers and employed workers, fishery workers were more impacted by cardiometabolic diseases, mental illness, infection, and malignancy. Therefore, it is imperative to specifically focus on health policies for fishery workers, such as providing curable antiviral treatment and initiating culture-tailored health promotion programs, to mitigate health inequality.
The impact of temperature variation on health has attracted increasing attention under global climate change. A distributed lag non-linear model (DLNM) was performed to estimate the risk of two indicators of temperature change (diurnal temperature range (DTR) and temperature change between neighboring days (TCN)) on respiratory hospital visits in Lanzhou, a semi-arid climate city in western China from 2012 to 2018. The whole year is divided into two different temperature change periods according to the TCN of each solar term. The results showed that extreme high DTR can apparently enlarge respiratory risk, and it indicated strong cumulative relative risk (RR) in the temperature drop period. Extreme low TCN had strong adverse effects on respiratory diseases especially in temperature rise period, with the greatest RR of 1.068 (95% CI 1.004, 1.136). The effect of extreme high TCN was more obvious in temperature drop period, with a RR of 1.082 (95% CI 1.021, 1.148) at lag 7. Females were more affected by extreme temperature changes. Young people were more vulnerable to DTR, while TCN has a greater impact on the elderly.
OBJECTIVE: To investigate whether seasonal variations and meteorological factors influence pregnancy outcomes in women undergoing in vitro fertilization-embryo transfer (IVF-ET) treatment. DESIGN: Retrospective cohort study. SETTING: University-affiliated reproductive medical center. SUBJECTS: Women aged < 35 years undergoing IVF from June 1, 2015, to June 1, 2019. INTERVENTIONS: Cycles were divided into four groups according to the date of the beginning of ovulation induction: spring (659 cycles), summer (578 cycles), autumn (519 cycles), and winter (534 cycles). RESULTS: The high-quality embryo rate was higher in autumn and winter than in cycles in which ovulation induction occurred in spring and summer (58.70% vs. 58.78% vs. 62.67% vs. 63.42%; P < 0.001). The results of linear regression analysis showed that the high-quality embryo rate was significantly correlated with the daily average temperature of ovulation induction (P = 0.037). The clinical pregnancy rates of cycles starting ovulation induction in spring, summer, and autumn were significantly higher than those starting in winter (70.71% vs. 73.18% vs. 70.13% vs. 65.17%; P = 0.031), while the biochemical pregnancy rate, early abortion rate, and live birth rate were not significantly different (P > 0.050). Multivariate logistic regression analysis showed significant seasonal variation in clinical pregnancy (OR = 1.643, 95% CI = 1.203-2.243; P = 0.002), and that a higher daily average temperature at the time of ovulation induction increased the clinical pregnancy rate (OR = 1.012, 95% CI = 1.001-1.022; P = 0.031). CONCLUSIONS: In women younger than 35 years who undergo IVF treatment, the season and ambient temperature on the date of the beginning of ovulation induction may have an impact on embryo development and clinical pregnancy.
As a significant protein source for humans and animals, soybean (Glycine max) has experienced a fast growth with the rapid development of population and economy. Despite broad interest in energy consumption and CO(2) emissions generated by soybean production, there are few impact-oriented water footprint assessments of soybean production. This study evaluates the fossil energy, carbon, and water footprints of China’s soybean production so that key environmental impacts can be identified. To provide reliable results for decision-making, uncertainty analysis is conducted based on the Monte Carlo model. Results show that the impact on climate change, ecosystem quality, human health, and resources is 3.33 × 10(3) kg CO(2) eq (GSD(2) = 1.87), 6.18 × 10(-5) Species·yr (GSD(2) = 1.81), 3.26 × 10(-3) Disability-adjusted Life Years (GSD(2) = 1.81), and 81.51 $ (GSD(2) = 2.28), respectively. Freshwater ecotoxicity is the dominant contributor (77.69%) to the ecosystem quality category, while climate change (85.22%) is the dominant contributor to the human health category. Key factors analysis results show that diammonium phosphate and diesel, and on-site emissions, are the major contributors to the overall environmental burden of soybean production. Several policy recommendations are proposed, focusing on trade structure optimization, efficient resource use, and technological improvements. Such policy recommendations provide valuable insights to those decision-makers so that they can prepare appropriate mitigation policies.
This study aimed to investigate the seasonal variation of gonorrhea in China, and to analyze the relationship between the incidence of gonorrhea and meteorological factors. Data from gonorrhea cases were obtained from the Disease Prevention and Control Bureau and the Data-Center for China Public Health Science, Chinese Center for Disease Control and Prevention, and the incidence of gonorrhea in China from 1 January 2006 to 31 December 2019 was analyzed. Meteorological data from the same period were obtained from the South China Meteorological Data Sharing Center, including the average monthly temperature, relative humidity, atmospheric pressure, sunshine hours, number of rainy days, and precipitation. The ratio-to-moving average method and seasonal subseries plots were used to analyze the seasonality of gonorrhea cases. The distributed lag non-linear model and attribution risks were used to investigate the effects of meteorological indexes on gonorrhea cases. The number of gonorrhea cases showed seasonal variation, with a peak in the third quarter and a decline in the first quarter. The Spearman assay showed that the reported number of patients with gonorrhea was positively correlated with the monthly temperature, relative humidity, precipitation, and number of rainy days. The risk of gonorrhea onset was highest at 6-11 °C, and the highest risk occurred when the average monthly temperature was 7 °C (resulting in an increase of 14.5% compared with 13 °C); a similar result was found regarding the cumulative risk of gonorrhea onset in relation to temperature. The attribution score of temperature to the onset of gonorrhea was 5.02% (95% confidence interval: - 3.84%, 13.88%). The study findings suggest that increased emphasis should be placed on screening for gonorrhea during summer and autumn, and that education on safe sexual behavior should be promoted during these times.
The throughput of materials fuels the economic process and underpins social well-being. These materials eventually return to the environment as waste or emissions. They can have significant environmental impacts throughout life cycle stages, such as biodiversity loss, adverse health effects, water stress, and climate change. China is the largest resource extractor globally, but the endpoint environmental impacts and the role of possible socioeconomic drivers associated with its resource extraction remain unclear. Here, we account for and analyze the two endpoint environmental impacts associated with China’s resource extraction from 2000 to 2017 and quantify the relative contributions of various socioeconomic factors using structural decomposition analysis. The results show that the environmental impacts of China’s resource extraction peaked in 2010. There was a significant decline from 2010 to 2017, in which human health damage decreased by 32.8 % and ecosystem quality damage decreased by 55.8 %. On the consumer side, the advancement in China’s urbanization process led to an increase in the environmental impacts of urban residents’ consumption, and the effect of investment on the environmental impacts decreased significantly after 2010. Decreases in the intensity of the environmental impacts in most sectors and improvements in production structure could reduce the impacts of resource extraction on human health and ecosystems.
As one of the 100 worst invasive alien species in the world, the red imported fire ant (Solenopsis invicta Buren) is of great concern because of its impact on human health, human health, economic development, and native biodiversity. With the ongoing global climate change situation, there is an increased public health threat from the invasion of S. invicta. To understand the distribution of suitable habitats for S. invicta under current and future climate scenarios in mainland China, nine species distribution models were constructed and compared to which one is more suitable to predict the distribution of S. invicta. The performance of Random Forest (RF) model was the best among all the evaluated models. The results showed that current suitable habitats for S. invicta were predicted to exist in the south of Mainland China. The urban population residing on the southeast coast was primarily exposed to suitable habitats of S. invicta, with an exposed urban area of approximately 130000 km(2). Annual mean temperature and precipitation of the warmest quarter were considered as important predictors among climate variables. Under future climatic scenarios, the suitable habitats originally held by S. invicta will remain stable, and suitable habitats area for expansion will increase over time. The expansion direction of suitable habitats tends to expand towards the north. Our study can provide a reference for understanding the change of S. invicta suitable habitats and exposed urban population distribution.
BACKGROUND: Children are disproportionately affected by climate change while evidence regarding their adaptive behavior and relevant influencing factors is limited. OBJECTIVES: We attempted to investigate health-related adaptive behavior towards climate change for primary school children in China and explore potential influencing factors. METHODS: We conducted a survey of 8322 primary school children in 12 cities across China. Knowledge, attitude, risk perception, and adaptive behavior scores for children were collected using a designed questionnaire. Weather exposures of cities were collected from 2014 to 2018. We applied a multiple linear regression and mixed-effect regression to assess the influencing factors of adaptive behavior. We also used the structural equation model (SEM) to validate the theoretical framework of adaptive behavior. RESULTS: Most children (76.1%) were aware of climate change. They mainly get information from television, smartphones, and the Internet. A 1 score increase in knowledge, attitude, and risk perception was associated with 0.210, 0.386, and 0.160 increase in adaptive behavior scores, respectively. Females and children having air conditioners or heating systems at home were positively associated with adaptive behavior. Exposure to cold and rainstorms increased the adaptive behavior scores, while heat exposure had the opposite effects. The SEM showed that knowledge was positively associated with attitude and risk perception. Knowledge, attitude, and risk perception corresponded to 31.6%, 22.8%, and 26.1% changes of adaptive behavior, respectively. CONCLUSION: Most primary school children in China were aware of climate change. Knowledge, attitude, risk perception, cold, and rainstorm exposure were positively associated with health-related adaptive behavior towards climate change.
Climate change affects public health, and improving eco-efficiency means reducing the various pollutants that are the result of economic activities. This study provided empirical evidence of the quantitative impact analysis of climate change on the health conditions of residents across China due to improvements that have been made to eco-efficiency. First, the indicators that were collected present adequate graphical trends and regional differences with a priori evidence about their relationships to each other; second, the present study applied Sensitivity Evaluation with Support Vector Machines (SE-SVM) to Chinese provincial panel data, taking the Visits to Hospitals, Outpatients with Emergency Treatment, and Number of Inpatients as proxy variables for the health conditions of the residents in each area and temperature, humidity, precipitation, and sunshine as the climate change variables, simultaneously incorporating the calculated eco-efficiency with six controlling indicators; third, we compared in-sample forecasting to acquire the optimal model in order to conduct elasticity analysis. The results showed that (1) temperature, humidity, precipitation, and sunshine performed well in forecasting the health conditions of the residents and that climate change was a good forecaster for resident health conditions; (2) from the national perspective, climate change had a positive relationship with Visits to Hospitals and Outpatients with Emergency Treatment but a negative relationship with the Number of Inpatients; (3) An increase in regional eco-efficiency of 1% increase the need for Visits to Hospitals and Outpatients with Emergency Treatment by 0.2242% and 0.2688%, respectively, but decreased the Number of Inpatients by 0.6272%; (4) increasing the regional eco-efficiency did not show any positive effects for any individual region because a variety of local activities, resource endowment, and the level of medical technology available in each region played different roles. The main findings of the present study are helpful for decision makers who are trying to optimize policy formulation and implementation measures in the cross-domains of economic, environmental, and public health.
In Fiji, low-lying coastal villages are beginning to retreat and relocate in response to coastal erosion, flooding and saltwater intrusion. Planned relocation is considered a last resort as a form of adaptation to the impacts of climatic and environmental change. The health impacts of planned relocation are poorly understood. This paper draws on data from multi-year research with residents of the iTaukei (Indigenous) Fijian village of Vunidogoloa. We used qualitative research methods to examine experiences of planned relocation, including residents’ accounts of their health and quality of life. In-depth interviews and group discussions were conducted with villagers living in a site of relocation, at four points in time (2015, 2016, 2019, and 2020). Twenty-seven people in Vunidogoloa, Fiji, participated in in-depth interviews, several on more than one occasion. Six group discussions with between eight to twelve participants were also conducted. Qualitative analytic software (NVivo) was used to analyse interview transcripts and identify themes. Villagers report both health benefits and challenges following planned relocation. Key facilitators for good health include movement away from some environmental risks to health, adequate drinking water and sanitation, food security including through farms and kitchen gardens, livelihood opportunities, improved access to schools and health services, and appropriate housing design. However, residents also refer to unanticipated risks to health including increased consumption of packaged goods and alcohol, disruptions to social structures and traditional values, and disrupted place attachment following movement away from a coastal site of belonging with consequences for mental wellbeing. Therefore, planned relocation has altered the social determinants of health in complex ways, bringing both health opportunities and risks. These results highlight the need for context-specific planning and adaptation programs that include meaningful involvement of community members in ongoing decision making, and call for an understanding of diverse social determinants of health that emerge and evolve in contexts of planned relocation.
Climate change has compounding effects on development, including direct and indirect impacts on food systems and human health. In the Pacific Islands region, the incidence of non-communicable diseases is among the highest in the world. Additionally, in policy documents, climate change features prominently among the issues most responsible for hindering development in the Pacific. Global discussions are now shifting towards a greater understanding and emphasis on the links between climate change, food systems, nutrition, health, and development. While these links are increasingly appreciated in research and practice, there is a need to understand which types of policy frameworks are best suited to address these issues in an integrated manner. This study was conducted by analyzing policy alignment and coherence in national level strategic planning instruments (policies, plans, and strategies) for two countries in the Pacific Islands region: Fiji and Vanuatu. Documents in the policy domains of development, agriculture, nutrition, health, and climate change were assessed to identify evidence of vertical (national to local), horizontal (between sectors), and integration across different thematic policy approaches (e.g. between economic development sustainable development approaches). By deconstructing the aims of different planning approaches and documents, and by mapping the relationships among them, it is possible to identify opportunities and gaps in the policy architecture that could be addressed in future planning cycles. The study identifies that policy alignment and coherence need to be explicitly addressed in the policy and planning design stage and included in monitoring and evaluation frameworks. The study also highlights the lag in the design and implementation of comprehensive food and nutrition security strategies in both countries and these lags can be linked to policy solutions for agriculture, health, and climate change. Key policy insights There is a need to explicitly consider policy alignment in the design stages of the policy cycle and set policy coherence as an explicit outcome to also be included in monitoring and evaluation frameworks. A lack of consideration of vertical, horizontal, and approach integration in planning and policy processes can lead to failures in the implementation of climate policy, thus delaying countries’ efforts towards achieving the Sustainable Development Goals (SDGs). Pacific Island countries have an opportunity to work towards use of policy frameworks that are able to provide comprehensive responses to the compounding effects of climate change on food systems, diets, health, and, more broadly, on development.
The propagation of antibiotic resistance genes (ARGs) in freshwater reservoirs threatens ecosystem security and human health, and has attracted increasing attention. A series of recent research articles on ARGs provides a unique opportunity for data-driven discoveries in this emerging field. Here, we mined data from a total of 290 samples from 60 reservoirs worldwide with a data-driven framework (DD) developed to discover geographical distribution, influencing factors and pollution hotspots of ARGs in freshwater reservoirs. Most data came from Asia and Europe where nine classes of ARGs were most frequently detected in reservoirs with multi-drug resistance and sulfonamide resistance genes prevailing. Factors driving distribution of reservoir ARGs differed between reservoir waters and sediments, and interactions among these factors had linear or nonlinear enhancement effects on the explanatory power of ARG distribution. During the cold season, small-sized reservoir waters rich in organic carbon, mobile genetic elements (MGEs) and antibiotics had a higher pollution potential of ARGs; during the spring drought, sediments in large reservoirs located in densely populated areas were more conducive to dissemination of ARGs due to their richness in antibiotics and MGEs. Thus, distribution pattern of ARG pollution hotspots in reservoir waters and sediments varies greatly depending on the differences of internal and external factors. From the “One Health” perspective, this widespread contamination of freshwater reservoirs by ARGs we discovered through the DD framework should be a push to promote integrated research across regions and disciplines. Especially the human – food-chain – ecosystem interface needs an improved understanding of ARG contamination mechanisms and targeted monitoring and evaluation systems should be developed to maintain all ecosystem services in freshwater reservoirs as well as to safeguard human health.
In recent years, Indonesia has experienced rapid increases in severe climate-related disasters have dramatically impacted populations unevenly; the poor and the vulnerable populations are most affected, and adaptive measures are urgently needed to protect and mitigate the impact on their health. However, very little is known about the existing measures addressing climate-related disasters and health impacts among vulnerable groups. WHO established a Health Emergency and Disaster Risk Management framework to urge governments and relevant actors to systematically collect evidence to develop science-based feasible adaptive strategies for priority groups. This study used scoping review methods to identify the action areas of Health-EDRM in policy documents in Indonesia, its content, and any potential gaps that require further study. The results from the documents’ review were then reported and discussed at a national stakeholder consultation meeting. This study has identified several achievements, lessons learned, and challenges from strategies and policies for health adaptation in facing climate-related disasters in Indonesia. This study also proposed strategies and recommendations to support mobilizing and accelerating health adaptation actions towards climate-related disasters in Indonesia.
OBJECTIVE: Although several studies have reported that some meteorological factors such as ambient temperature and atmospheric pressure, affect the incidence of spontaneous intracerebral hemorrhage (ICH), the correlation remains unclear. This retrospective time-series analysis was aimed to clarify the effects of meteorological parameters on the incidence of ICH. MATERIALS AND METHODS: Data of patients with ICH were obtained from a population-based survey of acute stroke patients between April 2016 and March 2019. All days during the study period were categorized into “no ICH day” when no ICHs occurred, “single ICH day” when only one ICH occurred, and “cluster day” when two or more ICHs occurred. Meteorological data were compared for among the three categories. RESULTS: 1,691 ICH patients from 19 hospitals were registered. In a total of 1,095 days, 250 were categorized as no ICH days, 361 as single ICH days, and 484 as cluster days. Daily ambient temperature declined in parallel with the daily number of ICHs, and it was a significant predictor for single ICH days and cluster days. Furthermore, the incidence of ICH in patients aged 65 years or above, men, those who emerged at home, those with modified Rankin Scale 3-5; and those with hypertension; and ICHs in the basal ganglia, brain stem, and cerebellum were more likely to be affected by low ambient temperature. CONCLUSION: Daily ambient temperature was significantly associated with ICH incidence. Patients’ activity, history of hypertension, and location of hemorrhage were also related to the impact of low ambient temperature on the incidence of ICH.
We investigated decadal (2010-2019) cardiovascular, cerebrovascular, and respiratory mortality sensitivity to annual warm temperatures in major Japanese cities: Sapporo, Tokyo (23 wards), and Osaka. The summer mortalities (June-August) increased with the monthly mean temperature for acute myocardial infarction, other acute ischemic heart diseases, cerebral infarction, and pneumonia in the three cities. Monthly mean temperatures were an indicator of these disease mortalities in Japan. However, similar responses were not found for cardiac arrhythmia and heart failure (excluding Sapporo), subarachnoid hemorrhage, and intracerebral hemorrhage. The decadal sensitivities and risk ratios between the maximum and minimum monthly mean temperatures were calculated using a linear regression model. In Sapporo, Tokyo, and Osaka, for example, the analyses of acute myocardial infarction showed summer positive responses of 0.19-0.25, 0.13-0.18, and 0.12-0.30, respectively, as the mortality rate (per 100,000 population) per 1 degrees C of monthly mean temperature, which estimated increased risks (between the coolest and hottest months) of 37-65% in Sapporo, 31-42% in Tokyo, and 35-39% in Osaka.
OBJECTIVE: This report tries to capture the impact of the Project for Strengthening the ASEAN Regional Capacity on Disaster Health Management (ARCH Project) in each ASEAN Member State (AMS) and Japan as a result of the ARCH Project implementation since July 2016. METHODS: Impact on AMS: The analysis of the impact on AMS was based on a comparison of the impact of the project on management and coordination of Emergency Medical Teams (EMTs), and application of the project outcome in actual emergency operations compared to the previous status in each AMS.Impact on Japan: The history of the development of disaster medicine in Japan was reviewed, with an aim to analyze the impact of supporting AMS through the ARCH Project on Japan, and the possibility of bi-directional cooperation in the future. RESULTS: Impact on AMS: Since the initiation of the ARCH Project, AMS has made significant progress in WHO EMT accreditation, strengthening EMTCC capacity for receiving international assistance, as well as the development of legislation or strategic plans related to DHM, and application of the Project products such as standard operating procedures or regional tools in actual disasters/emergencies.Impact on Japan: Disaster medicine in Japan originated from the Cambodian refugees’ relief mission in 1979. Since then, the management system has been strengthened including the foundation of the Japan Disaster Relief (JDR) Team, a structure with a legal foundation. The experience gained through international operations has contributed to the development of Japan’s domestic disaster response system. Japan learned the operational effectiveness of the post-disaster health surveillance system through the disaster response operation in 2013 Typhoon Yolanda Disaster in Philippines and introduced a modified system in Japan for domestic disaster response, which was later refined and proposed for an international standard. CONCLUSION: ARCH Project is highly appreciated by AMS as the opportunity to share knowledge and experience among countries and thereby contributing to achieving the “One ASEAN, One Response” concept, as well as the driving force for each AMS to develop its capacity in DHM. While the ARCH Project started to support AMS to strengthen its regional capacity in disaster health management, it is important to build a bi-directional relationship between ASEAN and Japan in terms of mutual learning and support to tackle future disasters.
BACKGROUND: The incidence of acute cholecystitis has a seasonal peak in summer. However, the reason for such seasonality remains unclear. This retrospective cohort study was performed to examine the association between ambient temperature and acute cholecystitis. METHODS: We identified admissions for acute cholecystitis from January 2011 to December 2017 from a nationwide inpatient database in Japan. We performed a Poisson regression analysis to investigate the association between ambient temperature and admission for acute cholecystitis with adjustment for relative humidity, national holidays, day of the week, and year. We accounted for clustering of the outcome within prefectures using a generalized estimating equation. RESULTS: We analyzed 601 665 admissions for acute cholecystitis. With an ambient temperature of 5.0 °C-9.9 °C as a reference, Poisson regression showed that the number of admissions increased significantly with increasing temperature (highest above 30 °C; relative risk, 1.35; 95% confidence interval, 1.34-1.37). An ambient temperature of <5.0 °C was also associated with higher admission for acute cholecystitis than an ambient temperature of 5.0 °C-9.9 °C (relative risk, 1.23; 95% confidence interval, 1.21-1.25). CONCLUSION: The present nationwide Japanese inpatient database study showed that high temperature (≥10.0 °C) and low temperature (<5.0 °C) were associated with increased admission for acute cholecystitis.
AIM: Issuance of the WHO Housing and health guidelines has paralleled growing interest in the housing environment. Despite accumulating evidence of an association between outdoor temperature and serum cholesterol, indoor temperature has not been well investigated. This study examined the association between indoor temperature and serum cholesterol. METHODS: We collected valid health checkup data of 2004 participants (1333 households), measured the indoor temperature for 2 weeks in winter, and divided participants according to whether they lived in a warm (average bedroom temperature ≥ 18℃), slightly cold (12-18℃) or cold house (＜12˚C). The relationship between bedroom temperature and serum cholesterol was analyzed using multivariate logistic regression models, adjusting for demographics, lifestyle habits and the season in which the health checkup was conducted, with a random effect of climate areas in Japan. RESULTS: The sample sizes for warm, slightly cold, and cold houses were 206, 940, and 858, respectively. Compared to those in warm houses, the odds ratio of total cholesterol exceeding 220 mg/dL was 1.83 (95%CI: 1.23-2.71, p=0.003) for participants in slightly cold houses and 1.87 (95%CI: 1.25-2.80, p=0.002) in cold houses. Similarly, the odds ratio of LDL/non-HDL cholesterol exceeding the standard range was 1.49 (p=0.056)/1.67 (p=0.035) for those in slightly cold houses and 1.64 (p=0.020)/1.77 (p=0.021) in cold houses. HDL cholesterol and triglycerides were not significantly associated with bedroom temperature. CONCLUSION: Besides lifestyle modification, improving indoor thermal environment through strategies such as installing high thermal insulation and appropriate use of heating devices may contribute to better serum cholesterol condition.
BACKGROUND: Evidence on whether meteorological conditions affect hip fractures (HFs) is limited. This study aimed to clarify the associations between ambient temperature and sun exposure and HFs in Japan. METHODS: Record of daily hospital admissions for HFs between 2015 and 2018 were extracted from a Japanese nationwide inpatient database. We conducted a time-series quasi-Poisson regression analysis using a distributed lag non-linear model with lag 0-39 days to estimate prefecture-specific relative risks (RRs) of HFs. We also estimated pooled RRs using random-effects meta-analysis. RESULTS: We identified 355,563 HFs. For mean temperature, immediate RRs (lag 0-2 days) were 1.349 (95% confidence interval (CI): 1.305, 1.395) and 0.754 (95% CI: 0.727, 0.782) for low (mean of the 2.5th percentile) and high (mean of the 97.5th percentile) mean temperature, respectively, relative to the reference (mean of medians). For sunshine duration, immediate RRs were 0.929 (95% CI: 0.913, 0.946) and 1.056 (95% CI: 1.029, 1.085) for short (mean of the 2.5th percentile) and long (mean of the 97.5th percentile) sunshine duration, respectively, and delayed RRs (lag 3-39 days) was 0.770 (95% CI: 0.696, 0.851) for long sunshine duration relative to the reference (mean of medians). Immediate RRs were larger for both exposures in patients admitted from home than in those from care facilities. CONCLUSIONS: Lower mean temperature and longer sunshine duration were associated with immediate higher HF risks. Higher mean temperature and shorter sunshine duration were associated with immediate lower HF risks. These associations were modified by admission routes. Longer sunshine duration was also associated with delayed lower HF risks.
BACKGROUND: Most older people with disabilities or illnesses continue to use long-term care (LTC) services for the rest of their lives. However, disasters can cause a discontinuation of LTC services, which usually means tragic outcomes of affected persons. In view of the recent progression of population aging and the increase in natural disasters, this study focuses on the impact of disasters on older people’s discontinuation of LTC services, and those more risk of such discontinuation than others. However, current evidence is scarce. METHODS: We conducted a retrospective cohort study with 259,081 subjects, 2,762 of whom had been affected by disaster and 256,319 who had not been affected during the 2018 Japan Floods. The sample in the three most disaster-affected prefectures was drawn from the Long-term Care Insurance Comprehensive Database and included older people certified with care-need level. The observation period was two months before the disaster and five months after it. We calculated the hazard ratio (HR) of municipality-certified subjects affected by the disaster versus those who were not. Subgroup analyses were conducted for categories of individual-, facility- and region-associated factors. RESULTS: Affected persons were twice as likely to discontinue LTC services than those who were not affected (adjusted HR, 2.06 95% CI, 1.91-2.23). 34% of affected persons whose facilities were closed discontinued their LTC services at five months after the disaster. A subgroup analysis showed that the risk of discontinuing LTC services for affected persons compared to those who were not affected in the relatively younger subgroup (age < 80: adjusted HR, 2.55; 95% CI, 2.20-2.96 vs. age ≥ 80 : 1.91; 1.75-2.10), and the subgroup requiring a lower level of care (low: 3.16; 2.74-3.66 vs. high: 1.71; 1.50-1.96) were more likely to discontinue than the older and higher care level subgroups. CONCLUSIONS: A natural disaster has a significant effect on the older people's discontinuation of LTC services. The discontinuations are supposedly caused by affected persons' death, hospitalization, forced relocation of individuals, or the service provider's incapacity. Accordingly, it is important to recognize the risk of disasters and take measures to avoid discontinuation to protect older persons' quality of life.
Some cardiovascular and respiratory diseases are triggered by changes in ambient temperature or extremes of temperature. This study aimed to clarify the changes in mortality associated with temperature-sensitive diseases in Japan during the COVID-19 pandemic. We used data from three major cities (Sapporo City, Tokyo 23 wards, and Osaka City) from 2010 to 2019 to determine disease mortality rates and monthly mean temperatures from April to December. If the pandemic had not occurred in 2020, the results showed that temperature-sensitive disease death counts would have increased from 324 to 980, based on a 95% confidence interval estimated from the past 10 years in Sapporo (19-56% increase in actual deaths from 2020), from 651 to 2,653 in Tokyo (10-39% increase), and from 235 to 1,343 in Osaka (8-48% increase). Analyses of meshed population data during the COVID-19 pandemic indicated that inhibiting people’s behaviour and outdoor mobility, especially in older men, caused a decrease in mortality.
BACKGROUND: Chronologically meteorological and calendar factors were risks of stroke occurrence. However, the prediction of stroke occurrences is difficult depending on only meteorological and calendar factors. We tried to make prediction models for stroke occurrences using deep learning (DL) software, Prediction One (Sony Network Communications Inc., Tokyo, Japan), with those variables. METHODS: We retrospectively investigated the daily stroke occurrences between 2017 and 2019. We used Prediction One software to make the prediction models for daily stroke occurrences (present or absent) using 221 chronologically meteorological and calendar factors. We made a prediction models from the 3-year dataset and evaluated their accuracies using the internal cross-validation. Areas under the curves (AUCs) of receiver operating characteristic curves were used as accuracies. RESULTS: The 371 cerebral infarction (CI), 184 intracerebral hemorrhage (ICH), and 53 subarachnoid hemorrhage patients were included in the study. The AUCs of the several DL-based prediction models for all stroke occurrences were 0.532-0.757. Those for CI were 0.600-0.782. Those for ICH were 0.714-0.988. CONCLUSION: Our preliminary results suggested a probability of the DL-based prediction models for stroke occurrence only by meteorological and calendar factors. In the future, by synchronizing a variety of medical information among the electronic medical records and personal smartphones as well as integrating the physical activities or meteorological conditions in real time, the prediction of stroke occurrence could be performed with high accuracy, to save medical resources, to have patients care for themselves, and to perform efficient medicine.
This paper aims to study the cumulative lag effect of meteorological factors on brucellosis incidence and the prediction performance based on Random Forest model. The monthly number of brucellosis cases and meteorological data from 2015 to 2019 in Yongchang of Gansu Province, northwest China, were used to build distributed lag nonlinear model (DLNM). The number of brucellosis cases of lag 1 month and meteorological data from 2015 to 2018 were used to build RF model to predict the brucellosis incidence in 2019. Meanwhile, SARIMA model was established to compare the prediction performance with RF model according to R(2) and RMSE. The results indicated that the population had a high incidence risk at temperature between 5 and 13 °C and lag between 0 and 18 days, sunshine duration between 225 and 260 h and lag between 0 and 1 month, and atmosphere pressure between 789 and 793.5 hPa and lag between 0 and 18 days. The R(2) and RMSE of train set and test set in RF model were 0.903, 1.609, 0.824, and 2.657, respectively, and the R(2) and RMSE in SARIMA model were 0.530 and 7.008. This study found significant nonlinear and lag associations between meteorological factors and brucellosis incidence. The prediction performance of RF model was more accurate and practical compared with SARIMA model.
Intestinal infectious disease is one of the most common diseases in China and is prevalent worldwide. The Chinese government launched a toilet improvement campaign to improve sanitation and reduce the incidence of diseases. This study determined the association between sanitary toilet use and intestinal infectious disease incidence in Jiangsu Province, China during 2011-2019. This study adopted an ecological retrospective research design. All secondary data were obtained through government websites and government information disclosure channels. Multiple linear regression was employed to analyze the association between the incidence of intestinal infectious diseases and sanitary toilet coverage rate and other potential predictors. Data suggested that the aggregate annual incidence of Type A and B intestinal infectious diseases showed a downward trend, the aggregate annual incidence of other infectious diarrhea continued to increase, and hand-foot-mouth disease occurred every other year with the highest annual incidence rate. The incidence was higher in coastal cities. Multiple regression results indicated that the usage of three types of sanitary toilets, compliance rate of water quality, and average ambient temperature have an impact on intestinal infectious diseases. The aggregate annual incidence of Type A and B intestinal infectious disease was negatively correlated with the cumulative use of sanitary toilets (β = - 0.036) and surface water quality (β = - 0.135; p < 0.05). Increase in sanitary toilet use and water quality control can reduce the number of new cases, which will be beneficial for the population in the province. Moreover, the toilet improvement interventions should continue to maintain high-quality construction.
Empirical research has shown that climate-related variables, the decline in economic well-being, and the mutual reinforcement of positive checks are the primary drivers of epidemic outbreaks in recent human history. However, their relative importance in causing the outbreak of epidemics is rarely examined quantitatively in a single study. I sought to address this issue by analyzing the 1402 epidemic incidents in China between 1841 and 1911, which partially overlaps partly with the Third Pandemic period. Fine-grained historical big data, multiple regression, and wavelet coherence analysis were employed. Statistical results show that economic fluctuations drove the country-wide epidemics outbreaks in China in inter-annual and decadal time scales. Economic fluctuations could cause short-term hardship and long-term impoverishment to the underprivileged social groups since a large portion of the Chinese population lived at the subsistence level in the past. The fluctuations might have sustained the repeated waves of epidemic outbreaks during the Third Pandemic period. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10745-021-00272-7.
Research at the biophysical level constitutes the main approach to study the path through which climate influences infectious diseases, but the influence of socioeconomic factors on climate change and the spread of infectious diseases also cannot be ignored. In the current context, with its emphasis on carbon emission reduction, countries have begun to adopt “total control and trading” methods to reduce greenhouse gas emissions. This paper is based on the monthly relevant data of various provinces and cities from 2015 to 2019, adds the moderating variable of “carbon emission trading volume” based on current research results, establishes a static model of unbalanced panel fixed effects and a dynamic panel model, and deeply analyzes the impact of climate change on infectious disease popularity and the moderating effect of the carbon trading market. The study found that climate warming, frequent precipitation, and shortened sunshine duration will lead to an increase in the number of infectious disease cases and that the “carbon emission trading volume” variable plays a negative role in the positive correlation between climate change (temperature/precipitation) and the number of infectious disease cases. There are seasonal differences, and the moderating effect in summer/autumn is more obvious than that in winter/spring.
Rubella occurs worldwide, causing approximately 100,000 cases annually of congenital rubella syndrome, leading to severe birth defects. Better targeting of public health interventions is needed to achieve rubella elimination goals. To that end, we measured the epidemiological characteristics and seasonal dynamic patterns of rubella and determined its association with meteorological factors in Shaanxi Province, China. Data on rubella cases in Shaanxi Province from 2005 to 2018 were obtained from the Chinese National Notifiable Disease Reporting System. The Morlet wavelet analysis was used to estimate temporal periodicity of rubella incidence. Mixed generalized additive models were used to measure associations between meteorological variables (temperature and relative humidity) and rubella incidence. A total of 17,185 rubella cases were reported in Shaanxi during the study period, for an annual incidence of 3.27 cases per 100,000 population. Interannual oscillations in rubella incidence of 0.8-1.4 years, 3.8-4.8 years, and 0.5 years were detected. Both temperature and relative humidity exhibited nonlinear associations with the incidence of rubella. The accumulative relative risk of transmission for the overall pooled estimates was maximized at a temperature of 0.23°C and relative humidity of 41.6%. This study found that seasonality and meteorological factors have impact on the transmission of rubella; public health interventions to eliminate rubella must consider periodic and seasonal fluctuations as well as meteorological factors.
The impact of temperature and rainfall on the occurrence of typhoid/paratyphoid fever are not fully understood. This study aimed to characterize the effect of daily ambient temperature and total rainfall on the incidence of typhoid/paratyphoid in a sub-tropical climate city of China and to identify the vulnerable groups for disease prevention. Daily notified typhoid/paratyphoid fever cases and meteorological data for Taizhou from 2005 to 2013 were extracted from the National Notifiable Disease Surveillance System and the Meteorological Data Sharing Service System, respectively. Distributed lag nonlinear model was used to quantify the association between daily mean temperature, total rainfall, and typhoid/paratyphoid fever. Subgroup analyses by gender, age, and occupation were conducted to identify the vulnerable groups. A total of 625 typhoid fever cases and 1,353 paratyphoid fever cases were reported during the study period. An increased risk of typhoid fever was detected with the increase of temperature (Each 2 degree C rise resulted in 6%, 95% [confidence interval] CI: 2-10% increase in typhoid cases), while the increased risk was associated with the higher temperature for paratyphoid (the highest cumulative risk of temperature was 33.40 [95% CI: 12.23-91.19] at 33 degrees C). After the onset of mild precipitation, the relative risk of typhoid fever increased in a short-lasting and with a 13-26 days delay, and the risk was no significant after the continuous increase of precipitation (the highest cumulative risk of rainfall was 24.96 [95% CI: 4.54-87.21] at 100 mm). Whereas the risk of paratyphoid fever was immediate and long lasting, and increase rapidly with the increase of rainfall (each 100 mm increase was associated with 26% increase in paratyphoid fever cases). Significant temperature-typhoid/paratyphoid fever and rainfall-typhoid/paratyphoid fever associations were found in both genders and those aged 0-4 years old, 15-60 years old, farmers, and children. Characterized with a lagged, nonlinear, and cumulative effect, high temperature and rainfall could increase the risk of typhoid/paratyphoid fever in regions with a subtropical climate. Public health interventions such as early warning and community health education should be taken to prevent the increased risk of typhoid/paratyphoid fever, especially for the vulnerable groups.
BACKGROUND: Global climate change could have potential impact on enterovirus (EV)-induced infectious diseases. However, the environmental factors promoting acute hemorrhagic conjunctivitis (AHC) circulation remain inconclusive. This study aimed to quantify the relationship between the environment and AHC. METHODS: We retrieved the monthly counts and incidence of AHC, meteorological variables and air quality in mainland China between 2013 and 2018. Exposure risks were evaluated by multivariate distributed lag nonlinear models. RESULTS: A total of 219,599 AHC cases were reported in 31 provinces of China, predominantly in southern and central China, seasonally increased in summer. AHC incidence increased by 7% between 2013 and 2018, from 2.6873 to 2.7570 per 100,000 people. A moderate positive correlation was seen between AHC and monthly mean temperature, relative humidity (RH) and precipitation. Each unit increment was associated with a relative risk for AHC of 1.058 at 17°-32 °C at lag 0 months, 1.017 at 65-71% RH at lag 1.4 months, and 1.039 at 400-569 mm at lag 2.4 months. By contrast, a negative correlation was seen between monthly ambient NO(2) and AHC. CONCLUSION: Long-term exposure to higher mean temperature, RH and precipitation were associated with an increased risk of AHC. The general public, especially susceptible populations, should pay close attention to weather changes and take protective measures in advance to any AHC outbreak as the above situations occur.
China is one of an increasing number of countries in the world that is suffering from frequent and severe natural disasters, which cause serious loss of life. The Chinese government has set up a special financial fund for natural disaster mitigation and reduction. Therefore, based on the financial expenditure data and disaster losses data obtained from ministries of emergency management and the China Statistical Yearbook, we analyzed the spatio-temporal distribution of natural disaster losses at the economic zonal scale during 2010-2020, and then evaluated the efficiency of disaster mitigation and reduction using a DEA model. The results showed that the natural disaster losses decreased significantly in most provinces from 2010 to 2020. The distribution of precipitation is extremely uneven (more in the southeast and less in the northwest). Moreover, the Central and Western Economic Zones are the most earthquake-prone regions in China, especially Xinjiang, Tibet, Sichuan, Yunnan and Gansu. Among all natural disasters, floods were the leading natural disasters, causing the most severe losses in China on the national scale. Furthermore, the cities with higher comprehensive efficiency, mean the ratio between the effects and funding on disaster mitigation and reduction, were either economically developed or geographically large and sparsely populated. Finally, we used an exponential regression equation model to explore the relationship between financial input and direct economic losses caused by natural disasters in 2019 and 2020; we found that there is a negative correlation between the financial investment and the direct economic losses. In conclusion, it is necessary to improve the technology of natural disaster mitigation and reduction and to adjust the scale of investment according to the actual situation of each region and the different disasters in China. This paper aims to provide relevant experience and basis for China’s comprehensive disaster mitigation and reduction work.
Climate change is increasing the incidence of extreme weather events which have a significant impact on public health. Cardiovascular diseases (CVDs) are the number one cause of death globally (40%). Apparent temperature (AT) and diurnal temperature range (DTR) have been extensively used to evaluate the effects of temperature on cardiovascular disease (CVD). However, the relevant information is quite limited from analysis and comparison of effects and differing pathogenesis of DTR and AT on CVD especially in less-developed, rural areas of China. This is the first attempt to analyze different effects between AT and DTR on CVD using distributed lag nonlinear modeling (DLNM) in rural area. Data on CVD hospital admission in Qingyang (Northwest China) in 2014-2017 originated from the New Rural Cooperative Medical System (NRCMS) of Gansu Province, and meteorological variables were provided by the Meteorological Science Data Sharing Service. Both AT and DTR had significant nonlinear and delayed impacts on hospital admissions for CVD. DTR had a stronger and more persistent effect on CVD incidence than AT. Females were more affected by high AT and low DTR than were males, while males were more vulnerable to low AT and high DTR. Temperature effects were not significantly different between people above and below 65 years of age. These findings provide local public health authorities with reference concerning sensitive temperature indices for susceptible populations with a view to improve CVD preventive strategies in rural areas.
Age-specific discrepancy of mortality burden attributed to temperature, measured as years of life lost (YLL), has been rarely investigated. We investigated age-specific temperature-YLL rates (per 100,000) relationships and quantified YLL per death caused by non-optimal temperature in China. We collected daily meteorological data, population data and daily death counts from 364 locations in China during 2006-2017. YLL was divided into three age groups (0-64 years, 65-74 years, and ≥75 years). A distributed lag non-linear model was first employed to estimate the associations of temperature with age-specific YLL rates in each location. Then we pooled the associations using a multivariate meta-analysis. Finally, we calculated age-specific average YLL per death caused by temperature by cause of death and region. We observed greater effects of cold and hot temperature on YLL rates for the elderly compared with the young population by region or cause of death. However, YLL per death due to non-optimal temperature for different regions or causes of death decreased with age, with 2.0 (95 % CI:1.5, 2.5), 1.2 (1.1, 1.4) and 1.0 years (0.9, 1.2) life loss per death for populations aged 0-64 years, 65-74 years and over 75 years, respectively. Most life loss per death results from moderate temperature, especially moderate cold for all age groups. The effect of non-optimal temperature on YLL rates is smaller for younger populations than older ones, while the temperature-related life loss per death was more prominent for younger populations.
The effect of ambient temperature on dermatologic diseases has received widespread attention. Previous studies have shown that ambient temperature might affect specific dermatologic diseases, but results were inconsistent. This study aims to assess the short-term effect of ambient temperature on outpatient visits due to dermatologic diseases (DMs) in Xinxiang, China. Daily DMs outpatient visits, mean temperature, mean relative humidity, and air pollution data of Xinxiang were retrieved from January 1, 2015, to December 31, 2018. A distributed lag nonlinear model (DLNM) was applied to analyze the effect of ambient temperature on DMs outpatients. We controlled several potential confounding factors such as the long-term trend, public holiday, day of the week, humidity, and air pollutants (NO(2), PM(2.5)). Finally, two more stratification analysis was conducted by age and gender. A total of 164,270 outpatients of DMs were enrolled during our study, and the daily mean visits were 113. The estimated effect of temperature on DMs was nonlinear. Heat temperature would exacerbate outpatients of dermatologic diseases. With a reference median temperature (17 °C), the effect of temperature on DMs was most pronounced at lag0-14; exposure to heat (32 °C, 99th) was associated with 1.565 (95% CI: 1.266-1.934) increased risk of outpatients for DMs. Stratification analysis showed that citizens of young ages were susceptive to heat; both genders had a similar relationship between temperature and DMs risk. This study highlights that ambient temperature was associated with DMs outpatients; heat temperature might aggravate DMs risk. The health hazards of heat temperature required more attention, and more effective prevention measurements should be designed and implemented to curb global warming.
BACKGROUND: Dietary patterns with a high intake of fruits and vegetables (FV) are associated with a reduced risk of various cancers. It is not yet clear where and to what extent a decline in crop productivity caused by climate change may modify the distribution of related cancer burdens through reducing FV consumption in China. To design policies and interventions aimed at improving FV intake, regional monitoring is required on how consumption-changing factors might impact the associated cancer burdens by socio-demographic subpopulations. METHODS: A microsimulation study was conducted from a societal perspective to project the effects of cancers associated with inadequate FV intake attributable to climate change. We linked the International Model for Policy Analysis of Agricultural Commodities and Trade to a health modelling framework for obesity, gastric cancer, lung cancer, and oesophageal cancer in a close-to-reality synthetic population. RESULTS: In the presence of climate constantly change, the relative reduction in FV consumption would induce an additional 9.73 million disability-adjusted life years (DALYs) nationally over the period 2010-2050 ([CrI]: 7.83-12.13). The climate change-induced cancer burden is projected to disproportionately affect socio-demographic index regions from 0.65 to 5.06 million DALYs. CONCLUSIONS: Effects of climate change on FV consumption are anticipated to exacerbate intra-regional inequalities in the associated cancer burdens of China by 2050. By quantitatively analysing the impact of such dietary changes on regional health in light of climate change, our research can inform the design of public health interventions for heterogeneous populations, as health impact assessments based solely on the population as a whole cannot reflect significant differences across subpopulations.
To better evaluate the potential risks of aquatic polycyclic aromatic compounds (PACs), multiple approaches have been implemented in this study to assess the human health and ecological risks of parent, nitrated and oxygenated polycyclic aromatic hydrocarbons (PAHs, NPAHs and OPAHs) in the surface water of Jialing and Yangtze Rivers in downtown Chongqing in southwestern China. The concentrations of ∑PAHs (334 ± 125 ng L(-1)) were much higher than those of ∑OPAHs (20.2 ± 7.49 ng L(-1)) in the two rivers, while NPAHs were barely detected. Concentrations of detected PACs were higher in wet season than dry season, probably resulted from the elevated particle input due to heavy rainfall in wet season. Concentrations of PAHs were higher in the particulate phase than dissolved phase, while OPAHs levels showed a reverse pattern. The partition coefficients (K(p)) of PACs in the water-SPM (suspended particulate matter) system were mainly affected by SPM concentrations and octanol/water partition coefficients of specific PACs. Human health risks calculated from non-probabilistic risk assessment model and probabilistic risk assessment model based on Monte Carlo simulation showed similar data pattern with slight difference in absolute values. Both models revealed potential or even severe human health risks contributed mainly by dermal exposure to aquatic PACs in this study. Furthermore, these models also manifested that infant stage was highly sensitive for PAC exposure. Sensitivity analysis indicated that health risk results was most sensitive to Benzo[a]pyrene equivalent toxic concentration (BaP(eq)), followed by showering time and daily water intake volume. Levels of ecological risks and contributions of individual PACs differed from models based on different quality values. The adequacy of toxicity data was crucial for the reliability of ecological risk assessment.
BACKGROUND: Pulmonary embolism (PE) is a life-threatening condition. Few studies have evaluated the relationship between air pollution and PE, and these results have been inconsistent. Therefore, our study aimed to investigate the association between air pollutant exposure and the risk of hospitalization due to PE. MATERIALS AND METHODS: Daily PE admissions, meteorological data, and ambient pollution data from January 1, 2015, to December 31, 2018, were collected in Beijing. A quasi-Poisson regression model combined with time-stratified case-crossover design and a distributed lag nonlinear model was used to determine the effect of air pollutant exposure on PE admission. To examine the stability of air pollutants’ effects, multi-pollutant analyses were performed. Stratified analyses by age and sex were further conducted. RESULTS: There were 5060 PE admissions during the study period, with an estimated incidence of 6.5 per 100,000. PM(2.5), PM(10), SO(2), O(3) and CO exposures were significantly associated with elevated risk of PE hospitalization. The highest cumulative risks were observed at a lag of 0-28 days for PM(2.5) (relative risk [RR] = 1.056, 95% confidence intervals [CI]: 1.015-1.098), PM(10) (RR = 1.042, 95%CI: 1.010-1.075), and CO (RR = 1.466, 95%CI: 1.127-1.906), at a lag of 0-27 days for SO(2) (RR = 1.674, 95%CI: 1.200-2.335), and at a lag of 0-4 days for O(3) (RR = 1.019, 95%CI: 1.001-1.038). All associations mentioned above except O(3) remained significant in multi-pollutant models. Stratified analyses showed that women and those aged ≥65 years people were more sensitive to PM(10) and CO exposure than men and those aged <65 years. The effect of PM(2.5) exposure was statistically significant in all subgroups. CONCLUSIONS: Exposure to PM(2.5), PM(10), SO(2), and CO showed a positive association with PE hospitalization. High-risk PE groups should take special precautions on days with poor air quality.
BACKGROUND: Dyslipidemia is a key factor causing cardio cerebrovascular diseases, and the total cholesterol (TC) is an important lipid indicator among them. Studies have shown that environmental factors have a strong association with TC levels. Previous studies only focused on the seasonal variation of TC level and the short-term effects of some environmental factors on TC level over time, and few studies explored the geographical distribution of TC level and quantified the impact of environmental factors in space. METHODS: Based on blood test data which was from China Health and Retirement Longitudinal Study (Charls) database, this study selected the TC level test data of middle-aged and elderly people in China in 2011 and 2015, and collected data from 665 meteorological stations and 1496 air pollutant monitoring stations in China. After pretreatment, the spatial distribution map of TC level was prepared and the regional statistics were made. GeoDetector and geographically weighted regression (GWR) were used to measure the relationship between environmental factors and TC level. RESULTS: The TC level of middle-aged and elderly in China was higher in females than in males, and higher in urban areas than in rural areas, showing a clustered distribution. The high values were mainly in South China, Southwest China and North China. Temperature, humidity, PM(10) and PM(2.5) were significant environmental factors affecting TC level of middle-aged and elderly people. The impact of pollutants was more severe in northern China, and TC level in southern China was mainly affected by meteorological factors. CONCLUSIONS: There were gender and urban-rural differences in TC levels among the middle-aged and elderly population in China, showing aggregation in geographical distribution. Meteorological factors and air pollutants may be very important control factors, and their influencing mechanism needs further study.
In this study, the sources of potentially toxic elements (PTEs) from atmospheric deposition in the waters of Guizhou’s Caohai Lake were investigated in addition to the potential risks to human health. Moss bags were used to enrich PTEs from atmospheric deposition, and eight monitoring sites that best represented geographic variation were established around Caohai Lake. Moss bags were collected and examined at every 3 months to identify spatiotemporal patterns of dry and wet atmospheric deposition of PTEs. Zn was the most abundant metal identified from deposition in Caohai (72.07%-95.94%), followed by Pb and Cd, while Hg was the least abundant (0.008%-0.354%). The contributions of wet deposition of PTEs were greater than those of dry deposition, and deposition during the heating season from December to April was greater than that between April to July. Hg was mainly derived from atmospheric dry deposition (65.38%-84.44%). Spatial distribution analysis indicated that atmospheric deposition was associated with the intensity of human activities and heating emissions. Exposure via hand-to-mouth contact accounted for over 99% of the total exposure risk although overall exposure was lower than threshold acceptable levels for carcinogenic and non-carcinogenic metals, indicating an overall lack of risk towards human health. Nevertheless, the health risk from atmospheric deposition of PTEs in Caohai Lake may be reduced by focusing on Zn, Pb, and Cd deposition in rainfall and minimizing the hazards associated with hand-to-mouth exposure to PTEs.
In order to mitigate global warming and improve air quality, the transformation of regional energy structures is the most important development pathway. China, as a major global consumer of fossil fuels, will face great pressure in this regard. Aiming toward achieving the global 2 °C warming target in China, this study takes one of the most developed regions of China, Guangdong Province, as the research area in order to explore a future development pathway and potential air quality attainment until 2050, by developing two energy structure scenarios (BAU_Energy and 2Deg_Energy) and three end-of-pipe scenarios (NFC, CLE, and MTFR), and simulating future air quality and related health impacts for the different scenarios using the WRF-Chem model. The results show that under the energy transformation scenario, total energy consumption in Guangdong rises from 296 Mtce (million tons of coal equivalent) in 2015 to 329 Mtce in 2050, with electricity and clean energy accounting for 45% and 35%. In 2050, the transformation of the energy structure leads to 64%, 75%, and 46% reductions in the emissions of CO(2), NOx, and SO(2) compared with those in 2015. Together with the most stringent end-of-pipe control measures, the emissions of VOCs and primary PM(2.5) are effectively reduced by 66% and 78%. The annual average PM(2.5) and MDA8 (daily maximum 8 h O(3)) concentrations in Guangdong are 33.8 and 85.9 μg/m(3) in 2015, with 63.4 thousand premature deaths (95% CI: 57.1-70.8) due to environmental exposure. Under the baseline scenario, no improvement is gained in air quality or public health by 2050. In contrast, the PM(2.5) and MDA8 concentrations decline to 21.7 and 75.5 μg/m(3) under the scenario with energy structure transformation, and total premature deaths are reduced to 35.5 thousand (31.9-39.5). When further combined with the most stringent end-of-pipe control measures, the PM(2.5) concentrations decrease to 16.5 μg/m(3), but there is no significant improvement for ozone, with premature deaths declining to 20.6 thousand (18.5-23.0). This study demonstrates that the transformation of energy structure toward climate goals could be effective in mitigating air pollution in Guangdong and would bring significant health benefits. Compared with the end-of-pipe control policies, transformation of the energy structure is a more effective way to improve regional air quality in the long term, and synergistic promotion of both is crucial for regional development.
Introduction. Global population has witnessed significant changes in the way food is produced and consumed. Although this has benefitted population health, it has also contributed to climate change and unsustainable use of natural resources. Materials and methods. Comprehensive literature review. Results and discussion. The characteristics of four transition theories related to food are outlined to help explain population behaviour, namely demographic, nutrition/protein, food and sustainability transition. This is followed by a further desktop analysis of the changes occurring in China, the world’s largest demography, and this country’s contribution to a most-needed global sustainability transition. The theoretical framework of transition theories used since the mid-20th century outlines changes in population behaviour impacting relationships between people and more recently with the natural environment. As a multidisciplinary field describing fundamental shifts in human societies, transition theories are very insightful in relation to food and nutrition. The demographic transition links industrialisation with fertility and mortality rates but also with food availability. During the nutrition transition, a change occurs in people’s calorie intakes from different food groups. While the share of protein remains relatively stable, the initial transition from plant- to animal-based foods now changes in reverse with increasing ecological and health awareness. This nutrition/protein transition can result in a better dietary behaviour with reduction in over-consumption, losses and waste. The food transition explains the transformations on the supply side – how food is produced, processed and distributed, reflecting changes in agricultural methods, use of land, soil, water, fertilisers and chemicals, supply and distribution chains. More sustainable farming methods are currently being introduced in response to ecologically threatening trends as a result of land-use changes and use of chemicals. As distinct from the other concepts, sustainability transition does not describe an evolutionary pattern of changes but only the current most necessary transformation in development. It requires radical transformation and action towards reduced environmental footprints of all human activities, including food. China’s development has experienced similar transitions although with unique features. Its demographic transition has been influenced by the “one child policy” while the nutrition/protein transition has been fuelled by increasing income levels. Industrialisation of food production with application of chemicals is widespread but more recently, organic methods of farming are gaining momentum. Food security and production are recognised as a challenge and opportunity in China’s sustainability transition with state-driven dietary efforts to contain domestic meat consumption. Conclusion. China has the opportunity to play a prominent role in the global transition to improved food choices, as required by the current environment and climate emergency, by shifting its own eating habits and also contributing to the burgeoning field of new alternatives to livestock products.
With China’s rapid economic development, particularly its accelerated urbanization, air pollution has been one of the serious environmental issues across China. Most major cities in China expand their subway systems to handle this problem. This study takes both long- and short-term effects of subway expansions on air quality and its corresponding health implications into account based on a network density-based time series analysis and a distance-based difference-in-differences analysis. The daily and hourly monitor-level air quality data on Nanjing from 13 May 2014 to 31 December 2018, combining with corresponding weather variables, are used to quantify the effect of subway expansions on local air pollution caused by eight new subway lines in Nanjing. The results reveal that subway expansions result in a statistically significant decrease in the air pollution level; specifically, the air pollution level experiences a 3.93% larger reduction in the areas close to subway lines. Heterogeneous analysis of different air pollutants indicates that the air pollution reduction effect of subway expansions is more significant in terms of Particulate Matter (PM(2.5)) and CO. A back-of-the-envelope analysis of the health benefits from this air improvement shows that the total number of yearly averted premature deaths is around 300,214 to 443,498. A set of alternative specifications confirm the robustness of our results. These results provide strong support for putting more emphasis on the environmental effect of subway expansions in the cost-benefit analysis of subway planning.
Air pollution has posed serious threats to human health. Based on the microdata of a large tertiary hospital in Shandong Province from 2016 to 2021, combined with the macro data such as air quality monitoring data, meteorological data, and city-level regional socio-economic data, this paper empirically tests the impact of air pollution instrumented by thermal inversions on the cardiovascular health of patients with type 2 diabetes mellitus (T2DM) and its group differences. The results show that: (1) Air pollution has a negative impact on the cardiovascular health of patients with T2DM, that is, the cardiovascular health of patients with T2DM will decline in regions with high air pollution; (2) The impact of air pollution on cardiovascular health in T2DM patients is heterogeneous, with males and older patients bearing greater air pollution health losses; (3) From the perspective of the external environment, the negative effects of environmental pollution on patients’ health were significantly reduced in areas with higher environmental regulation intensity and better public health conditions, indicating the necessity of strengthening environmental governance and increasing public health expenditure.
Groundwater is the major source of water for drinking and irrigation purposes in and around Hua County, Shaanxi Province, China. The main purposes of this research is to evaluate the groundwater quality in the rainy and dry seasons of Hua County and analyze the causes of seasonal differences and determine the areas with serious pollution. Groundwater quality was assessed in this study using entropy water quality index (EWQI) and some graphical approaches such as Gibbs and Piper diagrams. The contour maps of groundwater quality were drawn by Geographical Information System (GIS). According to the obtained results, the locations where groundwater quality was rated as excellent or good in both wet and dry seasons were mainly in the north and east of the research area. COD and NO3- are the parameters that have the most serious negative effect on water quality. The dominant factors influencing groundwater chemical evolution in the study area were rock weathering and dissolution, and the precipitation and evaporation during the wet and dry seasons do not cause significant changes in groundwater chemistry. Adults’ health risks results revealed that 27.69% and 52.31% of the groundwater samples exceeded the acceptable limit for non-carcinogenic risk in the wet and dry season, respectively, while for children the ratios are 30.16% and 47.62%, respectively. The contributive percentages of nitrate, fluoride and nitrate to the total risk are 61.29%, 28.71% and 10.00% in the wet season and 68.84%, 20.85% and 10.31% in the dry season. The risk is higher in the south than in the north of the study area, and is especially high in the southwest of the study area.
Climate change is one of the most severe threats to human survival and a significant factor influencing financial stability. Different from previous studies, this paper investigates the economic impact of climate change at the micro level based on data from China Meteorological Administration database, and China Household Finance Survey (CHFS) 2017 released in 2019. The empirical findings indicate that climate change contributes to the financial vulnerability of farmers’ households, which is confirmed following robustness tests. The mechanism analysis reveals that climate change has effects on rural households’ financial vulnerability via farmers’ health, credit availability, and agricultural output. Furthermore, the effect of climate change on farmers’ household financial vulnerability (HFV) is more pronounced in farmers with lower education levels. The changes in temperature and precipitation show different intensity effects in different areas, but all of them provide reasonable heterogeneity mechanisms. This paper’s policy value is demonstrated by the fact that it uncovers the effects of climate change on farmers’ HFV, information that may be useful for addressing climate change and rural financial stability.
Extreme temperature is strongly associated with human health, but few studies are available for the effects of extreme temperatures on respiratory disease (RD) in rural villages in Jiuquan, China over 2018-2019. In this study, we evaluate the effect of daily mean temperature on RD hospitalizations in suburban rural villages. A distribution lag non-linear model was constructed to analyze the relationship between the temperature and the daily risk of RD hospitalizations; and stratified analysis by sex and age group was performed. The effect of daily mean temperature on RD hospitalizations was non-linear and lagging. With a reference 25th percentile of temperature (-1.8 °C), exposure to extremely low temperature (-15.8 °C, 1st percentile), or moderate low temperature (-8.3 °C, 10th percentile) were associated with 1.396 (95% CI: 1.251, 1.558) and 1.216 (95% CI: 1.180, 1.253) increased risks of RD hospitalizations over lag 0-21 days. For RD morbidity, the effects of moderate high temperature (90th percentile of temperature, 22.5 °C) appeared at on the exposed day (lag 0), with the largest hot effect (RR 1.008, 95% CI 1.001, 1.020), while the effects of extremely high temperature (99th percentile of temperature, 27.0 °C) were insignificant. The effect of ambient temperature varied with gender and age. Both cold and high temperatures have more serious influence on males than females. In contrast, the elderly (age ≥ 65) seemed to be more sensitive in extremely low temperature (RR = 3.471; 95% CI, 2.183, 5.518; lag 0-21). The effect of moderate high temperature on the < 65 years group appeared for the first time at lag 0 (RR = 1.012; 95% CI, 1.001, 1.029). Both high temperature and low temperature increased the RD hospitalization risk; the harmful effect and duration of low temperature were greater than that of high temperature; the ≥ 65-year group and male were more sensitive to low temperature.
Recently, indoor thermal comfort has received more scholarly attention than ever due to the COVID-19 pandemic and global warming. However, most studies on indoor thermal comfort in China concentrated on urban buildings in the east and north. The indoor thermal comfort of rural dwellers in southwest China is insufficiently investigated. Hence, this study assesses residents’ indoor thermal comfort in a rural dwelling in Linshui, obtains the thermal neutral temperature of the rural area, and analyzes the thermal adaptation behavior of rural dwellers. The results reveal that the thermal neutral temperature of rural dwellers is 29.33°C (operative temperature), higher than that presented in previous studies based on the same climate region. Indoor thermal conditions in rural dwellings are relatively harsh, but various thermal adaptation behavior of rural dwellers significantly improve their ability to withstand the harsh conditions. When people live in an environment with a (relatively) constant climate parameter (e.g., humidity), their perception of that parameter seems compromised. Most rural dwellers are unwilling to use cooling equipment with high energy consumption. Therefore, more passive cooling measures are recommended in the design and renovation of rural dwellings.
BACKGROUND: Climate change exacerbates temperature-related mortality, but effects may vary by geographic characteristics. We hypothesize that higher greenness may mitigate temperature-related mortality, and that the effect may vary in different areas. OBJECTIVE: We examined how mortality among older adults in China was associated with temperature for 2000-2014, and how geolocation and residential greenness may modulate this association. METHODS: We used health data from the China Longitudinal Healthy Longevity Survey (CLHLS), and meteorological data from the Global Surface Summary of Day (GSOD) product by National Climate Data Center. We used a case-crossover study design with distributed nonlinear modeling to estimate mortality risks in relation to temperature, and stratified analysis by quartile of greenness. Greenness was estimated by Normalized Difference Vegetation Index (NDVI) from remote-sensed imagery. In addition to the national analysis, we also assessed three provinces (Jiangsu, Guangdong, and Liaoning) to examine differences by climatic regions. RESULTS: Extreme temperatures had a significant association with higher mortality, with regional differences. Findings from the national analysis suggest that individuals in the lowest quartile of greenness exposure had a ratio of relative risks (RRR) of 1.38 (0.79, 2.42) for mortality risk on extreme hot days at the 95th percentile compared to those at the 50th percentile, compared to those in the highest quartile, which means those residing in the lowest quartile of greenness had a 38% higher RR than those residing in the highest quartile of greenness, where RR refers to the risk of mortality on days at the 95th percentile of temperature compared to days at the 50th percentile. The RRR for the highest to lowest quartiles of greenness for mortality risk on extreme cold days at the 5th percentile compared to the 50th percentile was 2.08 (0.12, 36.2). In Jiangsu and Guangdong provinces, both the heat effects and cold effects were the lowest in the highest greenness quartile, and the results in Liaoning province were not statistically significant, indicating different regional effects of greenness on modulating the temperature-mortality relationship. DISCUSSION: We elucidated one pathway through which greenness benefits health by decreasing impact from extreme high temperatures. The effects of greenness differed by climatic regions. Policymakers should consider vegetation in the context of climate change and health.
OBJECTIVE: Gout is a chronic disease caused by the deposition of sodium urate (MSU) crystals. Available data on the association between environmental hazards and gout are scarce. The present study was present to investigate the relationship between short-term exposure to air pollution and hospitalizations for acute gout from 2016 to 2020 in Anqing City, China. METHODS: Daily records of hospital admissions for acute gout in Anqing from 1 January 2016 to 31 December 2020 were retrieved from the tertiary first-class hospitals in Anqing. Air pollutants and meteorological data were obtained from the China Environmental Monitoring Station and China Meteorological Data Service Center respectively. We used a time-series analysis to explore the association between air pollution (NO(2), O(3), and CO) and hospitalizations for acute gout, and conducted stratified analyses by gender, age and season. RESULTS: We observed an association between NO(2) and hospitalizations for gout (lag 0, relative risk (RR):1.022, 95% confidence interval (CI):1.004-1.041). For every 1 mg/m(3) increase in CO concentration, hospitalizations for gout increased by 3.9% (lag 11 days, RR=1.039, 95% CI: 1.004-1.076). Intriguingly, there was a negative association between O(3) and hospitalizations for gout (lag0, RR=0.986, 95% CI: 0.976-0.996). Stratified analyses showed that exposure to high levels of NO(2) was considered to be more vulnerable to gout in cold season. CONCLUSION: Our study showed that short-term exposure to NO(2) and CO has a significant effect on hospitalizations for acute gout.
BACKGROUND: In the context of global climate changes, increasing extreme weather events have aroused great public concern. Limited evidence has focused on the association between extreme precipitation and hospitalizations for acute myocardial infarction (AMI). Our study aimed to examine the effect of extreme precipitation on AMI hospitalizations. METHODS: Daily AMI hospitalizations, weather variables and air pollution data in Beijing from 2013 to 2018 were obtained. We used a time-series analysis with a distributed lag model to evaluate the association of extreme precipitation (≥95th percentile of daily precipitation) with AMI hospitalizations. Subgroup analysis was conducted to identify the vulnerable subpopulations and further assessed the attributable burden. RESULTS: Extreme precipitation increased the risk of AMI hospitalizations with significant single-day effects from Lag 4 to Lag 11, and the maximum cumulative effects at Lag 0-14 (CRR = 1.177, 95% CI: 1.045, 1.326). Older people (≥65 years) and females were more vulnerable to extreme precipitation. The attributable fraction and numbers of extreme precipitation on AMI hospitalizations were 0.68% (95% CI: 0.20%, 1.12%) and 854 (95% CI: 244, 1,395), respectively. CONCLUSION: Extreme precipitation is correlated with a higher risk of AMI hospitalizations. The elderly (≥65 years) and females are more susceptible to AMI triggered by extreme precipitation.
BACKGROUND: Studies on the associations between ambient temperature and asthma hospitalizations are limited, and the results are controversial. We aimed to assess the short-term effects of ambient temperature on the risk of asthma hospitalizations and quantify the hospitalization burdens of asthma attributable to non-optimal temperature in adults in Beijing, China. METHODS: We collected daily asthma hospitalizations, meteorological factors and air quality data in Beijing from 2012 to 2015. We applied a time-stratified case-crossover design and fitted a distributed lag non-linear model with a conditional quasi-Poisson regression to explore the association between ambient temperature and adult asthma hospitalizations. The effect modifications of these associations by gender and age were assessed by stratified analyses. We also computed the attributable fractions and numbers with 95% empirical confidence intervals (eCI) of asthma hospitalizations due to extreme and moderate temperatures. RESULTS: From 2012 to 2015, we identified a total of 18,500 hospitalizations for asthma among adult residents in Beijing, China. Compared with the optimal temperature (22 °C), the cumulative relative risk (CRR) over lag 0-30 days was 2.32 with a 95% confidence interval (CI) of 1.57-3.42 for extreme cold corresponding to the 2.5th percentile (- 6.5 °C) of temperature distribution and 2.04 (95% CI 1.52-2.74) for extreme heat corresponding to the 97.5th percentile (29 °C) of temperature distribution. 29.1% (95% eCI 17.5-38.0%) of adult asthma hospitalizations was attributable to non-optimum temperatures. Moderate cold temperatures yielded most of the burdens, with an attributable fraction of 20.3% (95% eCI 9.1-28.7%). The temperature-related risks of asthma hospitalizations were more prominent in females and younger people (19-64 years old). CONCLUSIONS: There was a U-shaped association between ambient temperature and the risk of adult asthma hospitalizations in Beijing, China. Females and younger patients were more vulnerable to the effects of non-optimum temperatures. Most of the burden was attributable to moderate cold. Our findings may uncover the potential impact of climate changes on asthma exacerbations.
Prior research has shown that environmental hazards, such as limited green space, air pollution, and harmful weather, have the strong adverse impact on older adults’ cognitive function; however, most of the studies were conducted in developed countries and limited to cross-sectional analyses. China has the largest aging population in the world so the research evidence from it can offer an insight to the study in other developing countries facing similar issues and inform future public health policy and disease control. This study examined the long-term impact of environmental factors, namely, green space coverage, air pollution, and weather conditions on cognitive function using a nationally representative sample consisting of adults aged 45 years and older selected from the China Health and Retirement Longitudinal Study (CHARLS 2011-2018), the China City Statistical Yearbook, and other sources. Multilevel growth curve models were utilized for analysis and the mediator effects of physical activity and social engagement on the relationship between environmental factors and cognitive function were examined. Findings of this study showed that after controlling for sociodemographic characteristics, annual precipitation of 80 cm or more, living in areas with July temperature of 28°C or higher, urban community, and green space coverage were positively associated with cognition score at the baseline and lower precipitation, urban community, and greater green space coverage were associated with slower cognitive decline over a 7-year period. The impact of gross domestic product (GDP) seemed to take into effect more and more over time. These effects did not substantially change after weekly total hours of physical activities and levels of social engagement were added. More research on the mechanisms of the effect of environmental factors on cognition is needed such as the subgroup analyses and/or with more aspects of environmental measures.
Gradually increasing durations of high temperature caused by climate change harm the health of individuals and then lead to death. This study aimed to investigate the relationship between durations of different daily mean air-temperature categories and mortality in China and forecast future mortality changes in China for 2020-2050 under Representative Concentration Pathways (RCP)4.5 and RCP8.5 scenarios. The daily mean air temperature was divided into 10 categories, and the days under each air-temperature category were counted during the period of 2000-2015. Then, the connection between the days of each of the 10 air-temperature categories and mortality was established using the semi parametric regression model. Results indicate that the days of the >32 degrees C category have the largest impact on mortality in China, with the death rate increasing by 23 parts per thousand for one additional day. Predictions reveal that mortality in China will increase 25.48% and 26.26% under the RCP4.5 and RCP8.5 scenarios, respectively. Moreover, the mortality of 86 regions in western China will increase 30.42%. Therefore, in the future, the increasing duration of days of high temperatures will raise the mortality rate in China and aggravate the mortality gap between developed and underdeveloped regions.
OBJECTIVES: Short-term temperature variability (TV) is associated with the exacerbation of asthma, but little is known about the relative effects of intra- and inter-day TV. We aimed to assess the relative impacts of intra- and inter-day TV on childhood asthma and to explore the modification effects by season. METHODS: A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was adopted to evaluate the nonlinear and lagged effects of TV on childhood asthma in Shanghai from 2009 to 2017. Intra- and inter-day TV was measured with diurnal temperature range (DTR) and temperature changes between neighboring days (TCN), respectively. RESULTS: Increased DTR was associated with the elevated relative risk (RR) of daily outpatient visits for childhood asthma (DOVCA) in both the whole year (RR(lag0-14) for the 99th percentile: 1.264, 95% confidence interval (CI): 1.052, 1.518) and cold season (RR(lag0-12) for the 99th percentile: 1.411, 95% CI: 1.053, 1.889). Higher TCN in the warm season was associated with the increased RR of DOVCA (RR(lag0-14) for the 99th percentile: 2.964, 95% CI: 1.636, 5.373). The number and fraction of DOVCA attributed to an interquartile range (IQR) increase of TCN were higher than those attributed to DTR in both the whole year period and warm season. However, the number and fraction of DOVCA attributed to an IQR increase of DTR were greater than those attributed to TCN in the cold season. CONCLUSIONS: Our results provide novel evidence that both intra- and inter-day TV might be a trigger of childhood asthma. Higher DTR appeared to have greater impacts on childhood asthma in the cold season while an increase in TCN seemed to have bigger effects in the warm season.
Epidemiological studies have revealed associations between several temperature parameters and allergic rhinitis (AR). However, few studies have reported the association of AR with daily temperature variability, which indicates both short-term intra- and interday temperature changes. This study aimed to analyze associations between temperature variability and initial outpatient visits for AR. The analysis was conducted with an over-dispersed Poisson model using daily time-series data on temperature and the number of initial AR outpatients from 2013 to 2015 in Changchun, China. The composite index of temperature variability was derived by calculating the standard deviation of daily minimum temperature and maximum temperature over exposure days. Stratified analysis by season was also conducted. There were 23,344 AR outpatients during the study period. In the total period, per 1 °C increase in temperature variability at 0-2 days (TV(0-2)), 0-3 days (TV(0-3)), and 0-4 days (TV(0-4)) was associated with a 4.03% (95% CI: 0.91-7.25%), 4.40% (95% CI: 0.95-7.97%), and 4.12% (95% CI: 0.38-8.01%) increase in the number of AR outpatients, respectively. When stratified by season, the strongest effect was shown in spring. Our results suggested that temperature variability was associated with increased initial outpatient visits for AR, which may provide helpful implications for formulating public health policies to reduce adverse health impacts of unstable temperature.
OBJECTIVE: By exploring the exposure-response relationships between meteorological factors and rupture of intracranial aneurysm (IA) to reveal the influence of meteorological variation on IA rupture under the specific climate in Fujian, China. METHOD: 7515 cases of IA rupture from several municipal medical institutions in Fujian Province as well as local meteorological data during the same period were collected from 2013 to 2017. Poisson regression and Spearman correlation analysis were applied to explore the distribution characteristics of IA rupture and how it is associated with meteorological parameters. Poisson generalized additive model was established to further analyze the exposure-response relationships between meteorological factors and IA rupture, and its hysteresis effects. RESULT: The IA rupture exhibited a negative correlation with temperature (r(s) = -0.323, 95% CI: -0.539 ~ -0.068) and a positive correlation with atmospheric pressure (r(s) = 0.397, 95% CI: 0.152-0.597) or pressure difference (r(s) = 0.296, 95% CI: 0.038-0.517), 21.05 ℃ and 1000.14 hPa were the risk thresholds for the onset ascribed to variation in temperature and atmospheric pressure, respectively. Temperature and atmospheric pressure also exerted hysteresis effects on IA rupture. Cold will increase the rupture risk in the subsequent 1-3 days, and high pressure will raise the morbidity in the next 1-2 days. Besides, drastic variations in temperature and atmospheric pressure were also associated with the higher risk of IA rupture in the next 2 days and 1 day, respectively. CONCLUSION: Temperature and atmospheric pressure have a negative and positive correlation with IA rupture in Fujian, China, respectively. Variation in temperature and atmospheric pressure exert different degrees of hysteresis effects on IA rupture.
BACKGROUND: Considering the serious health burden caused by adverse weather events, increasing researches focused on the relationship between temperature variability (TV) and cause-specific mortality, but its association with cancer was not well explored. We aimed to investigate the impacts of TV on cancer mortality and examine the modifying effects of weather type and geographical location as well as other characteristics. MATERIALS AND METHODS: Daily city-specific data of cancer deaths, mean temperature (Tmean), maximum and minimum temperatures (Tmax and Tmin), relative humidity (RH), rainfall, and air pollutants were collected during 2016-2017 in 13 cities in Jiangsu Province, China. TV(0-t) was defined as the standard deviation of the daily Tmax and Tmin on the exposure 0-t days. A two-stage analysis was applied. First, a time-stratified case-crossover design was used to examine the odds ratio (OR) and attributable fraction of cancer mortality per 1 °C increase in TV by adjusting for potential confounders. Random effect meta-analysis was used to summarize the pooled ORs. Second, stratified analysis was performed for weather type, geographical location, demographics, and other city-level characteristics. The weather was defined as four types according to days during warm or cold season combined with high or low RH. RESULTS: A total of 303670 cases were included in our study. Meta-analysis showed that the ORs of cancer mortality per 1 °C increase in TV(0-t) significantly increased and peaked in TV(0-2) (OR=1.0098, 95% CI: 1.0039-1.0157). The attributable fraction of TV(0-2) on cancer mortality was 4.74%, accounting for 14395 deaths in the study period. Significant ORs of TV-related cancer mortality were found during the warm season combined with high RH and in the northern region of Jiangsu. Susceptible groups of TV-related cancer mortality were identified as female patients, patients aged 45-65 years, and those living in cities with lower per capita green area. CONCLUSIONS: TV can significantly increase the risk of cancer mortality, especially during warm and humid days and in the northern region of Jiangsu. Findings are of great significance to formulate urban planning, resource allocation, and health intervention to prolong the life of cancer patients.
Global climate change has resulted in an increase in the frequency, intensity, and duration of extreme events. However, we know very little about the associations between large temperature changes lasting for several days (LTCD) and CVD, particularly in less-developed, rural areas. We collected daily data on cardiovascular-related diseases and weather conditions from 119 villages in seven counties between 2010 and 2016. A distributed lag non-linear model was used to investigate the association between LTCD and relative risk (RR) of hospital admissions for CVD. Analyses were stratified by the duration and intensity of LTCD, age, and sex. The RR of CVD increases with the intensity and duration of LTCD. Men and young people were more vulnerable to LTCD of longer duration and higher intensity than women and old. Our findings may help local public health authorities develop adaptive preventive strategies targeting inhabitants of villages.
Diurnal temperature range (DTR) is an appropriate indicator for reflecting climate change. Many previous studies have examined the relationship between DTR and mortality. Cerebrovascular disease (CVD) have a higher mortality than other diseases, with mortality from CVD higher in rural areas than in urban areas. A distributed lag non-linear model (DLNM) was used to analyze the exposure-effect relationship between DTR and hospital admissions for CVD from 2018 to 2020 in the population living in rural areas of Tianshui, Gansu Province, China. We investigated the effects of extreme DTR in groups stratified according to gender and age. A U-shape relationship was observed between DTR and hospital admissions for CVD. Both high DTR (19 °C) and low DTR (3 °C) were significantly associated significantly with CVD hospital admissions. When the lag period was 0-21 days, the impact of high DTR (1.595 [95% CI 1.301-1.957]) was slightly more significant than that of a low DTR (1.579 [95% CI – 1.202 to 2.075]). The effect of DTR on CVD varied in different populations. Males and adults were more sensitive to DTR than females and elderly people. It is necessary to make preventive measures to protect vulnerable populations from the adverse effects of extreme DTR.
BACKGROUND: Several studies have investigated the associations between temperature variability (TV) and death counts. However, evidence of TV-attributable years of life lost (YLL) is scarce. OBJECTIVES: To investigate the associations between TV and YLL rates (/100,000 population), and quantify average life loss per death (LLD) caused by TV in China. METHODS: We calculated daily YLL rates (/100,000 population) of non-accidental causes and cardiorespiratory diseases by using death data from 364 counties of China during 2006-2017, and collected meteorological data during the same period. A distributed lag non-linear model (DLNM) and multivariate meta-analysis were used to estimate the effects of TV at national or regional levels. Then, we calculated the LLD to quantify the mortality burden of TV. RESULTS: U-shaped curves were observed in the associations of YLL rates with TV in China. The minimum YLL TV (MYTV) was 2.5 °C nationwide. An average of 0.89 LLD was attributable to TV in total, most of which was from high TV (0.86, 95% CI: 0.56, 1.16). However, TV caused more LLD in the young (<65 years old) (1.87, 95% CI: 1.03, 2.71) than 65-74 years old (0.85, 95% CI: 0.40-1.31) and ≥75 years old (0.40, 95% CI: 0.21-0.59), cerebrovascular disease (0.74, 95% CI: 0.36, 1.11) than respiratory disease (0.54, 95% CI: 0.21, 0.87), South (1.23, 95% CI: 0.77, 1.68) than North (0.41, 95% CI: -0.7, 1.52) and Central China (0.40, 95% CI: -0.02, 0.81). TV-attributed LLD was modified by annual mean temperature, annual mean relative humidity, altitude, latitude, longitude, and education attainment. SIGNIFICANCE: Our findings indicate that high and low TVs are both associated with increases in premature death, however the majority of LLD was attributable to high TV. TV-related LLD was modified by county level characteristics. TV should be considered in planning adaptation to climate change or variability. IMPACT: (1) We estimated the associations of TV with YLL rates, and quantified the life loss per death (LLD) caused by TV. (2) An average of 0.89 years of LLD were attributable to TV, most of which were from high TVs. (3) TV caused more LLD in the young, cerebrovascular disease, and southern China. (4) The mortality burdens were modified by county level characteristics.
We aimed to estimate the non-accidental and cause-specific mortality burden attributed to diurnal temperature range (DTR) and the relative contributions of low, high, and extremely low and extremely high DTR in Yunnan, southwest China. Furthermore, we explored the possible effect modification of the DTR-mortality association by season, sex, age, ethnicity, marital status, and occupation. A standard time-series quasi-Poisson regression model combined with a distributed lag nonlinear model was used to derive estimates of city-specific DTR-mortality associations, then random effects meta-analysis was used to pool the estimated city-specific overall cumulative DTR-mortality association, estimating empirical confidence intervals (eCIs). The overall fraction of non-accidental mortality caused by DTR was 11.00% (95% eCI 3.40-17.28): high DTR accounted for most of burden (total estimate 10.03%, 95% eCI 2.59-16.32). The estimated mortality risk attributable to DTR was significantly associated with cardiovascular and respiratory mortality, with attributable fractions of 13.61% (95% eCI 3.91-21.13) and 14.32% (95% eCI 0.47-21.44), respectively. The estimated risk attributable to DTR was slightly greater for males, people ≥75 years old, married people, and non-farmers than their corresponding categories. Most of the DTR-related mortality burden was attributable to high DTR, and the mortality risk attributable to DTR might be modified by specific causes, sex, age, marital status, and occupation.
Rheumatoid arthritis (RA) is an autoimmune disease, mainly characterized by erosional arthritis. The proportion of adults suffering from RA is about 0.5%-1%. There have been reports on the association of rainfall and traffic-related air pollutants with RA hospitalization rates. However, there have been no studies on the association of diurnal temperature range (DTR) and relative humidity (RH) with RA hospitalization rates. This study aimed to examine the short-term association of DTR, RH and other meteorological factors with the hospital admission rate of RA patients, while excluding the interference of PM(2.5), SO(2), NO(2), CO and O(3) atmospheric pollutants. We collected daily RA occupancy rate and meteorological factor data in Hefei city from 2015 to 2018 and used the generalized additive model (GAM) combined with the distributed lag nonlinear model (DLNM) for time series analysis, and further stratified analysis by gender and age. Single-day and cumulative-day risk estimates of RA admissions were expressed as relative risk (RR) and its 95% confidence interval (95% CI). For the cumulative-day lag model, high RH was statistically significant after cumulative lag 0-8 days, and the effect gradually increases. Stratified analysis shows that females seem to be more susceptible to high or extremely high DTR and RH exposure, and extremely high DTR exposure may increase the risk of RA admission in all populations. In conclusion, this study found that high DTR and high RH exposure increased the risk of hospitalization in RA patients and provided clues to the potential association between other meteorological factors and RA.
OBJECTIVE: Ambient temperature extremes due to heat exposure was an established risk factor for preterm birth (<37 gestational weeks). However, there is insufficient epidemiological evidence on the effects of temperature variation(TV), although TV is also associated with heat exposure and can influence human health risk. This study aimed to investigate the relationship between inter- and intraday TV and preterm birth (PTB). METHOD: A total of 1,388,994 live singleton births were collected from January 2003 to December 2012, from the Shenzhen Birth registry system. Daily temperature range (DTR) was defined as the difference between the highest and lowest recorded daily temperature. Intraday TV was defined as the maximum daily diurnal temperature range in a given week (Max-DTR). Inter-day TV was defined as the maximum increase or decrease in daily mean temperature between days t and t-1in a given week; either an increase (Temp-inc) or a decrease (Temp-dec). We used Cox proportional hazards models to estimate TV-related PTB risks during the first trimester, the second trimester, and in late pregnancy. RESULTS: The maximum values for DTR, Temp-inc, and Temp-dec were 17 °C, 8 °C and 11 °C, respectively. The greatest TV-related PTB risk occurred in the second trimester, with 5.8% (95%CI: 3.3%, 8.3%), 23.7% (95%CI: 19.6%, 27.9%), and 4.4% (95%CI: 1.8%, 7.1%) differences per 1 °C increase in Max-DTR, Temp-inc, and Temp-dec, respectively. Greater TV was associated with elevated PTB risk during the warm season. The association between TV and PTB was modified by seasons, maternal education and chronic conditions. CONCLUSIONS: Sharp TV is a likely risk factor for PTB. Policy makers and clinicians should recognize the potential role of TV in the etiology of PTB so that interventions can be designed to protect pregnant women and their fetuses against extreme temperatures.
BACKGROUND: The New Environmental Health is an approach to environmental health adopted in 1999. The new approach was in response to emerging health risks from the pressures that development placed on the environment, climate change, and increasing vulnerabilities of local communities. The new approach heralded a change in perception and roles within environmental health. Twenty years on, it seems these changes have not been embraced by local government. METHODS: To determine whether this was the case, we assessed the use of the term “environmental health” in local government annual reports, and where environmental health functions sit within the organisational structure of councils. RESULTS: We found that the New Environmental Health has not been adopted by councils and environmental health relates solely to the delivery of statutory services and legislative compliance. CONCLUSIONS: One result of this is local environmental health practitioners, who constitute the major health protection capability of councils, are defined by the narrow legislative obligations imposed on councils. This represents a significant lost opportunity as public health is not protected in the way that was envisaged with the adoption of the New Environmental Health.
The importance of a safe climate for human health is recognised by healthcare professionals, who need to be equipped to deliver environmentally sustainable healthcare and promote the health of natural systems on which we depend. The inclusion of climate-health in Australian and New Zealand accredited master-level public health training and medical programs is unclear. Educators identified by their coordination, convenorship, or delivery into programs of public health and medicine at universities in Australia and New Zealand were invited to participate in a cross-sectional, exploratory mixed methods study to examine the design and delivery of climate change content in the curricula, and the barriers and opportunities for better integration. Quantitative surveys were analysed using descriptive statistics and qualitative interview content was analysed via a modified grounded theory approach. The quantitative survey had 43.7% (21/48) response rate, with 10 survey respondents completing qualitative interviews. Qualitative interviews highlighted the minimal role of Indigenous-led content in this field, the barriers of time and resources to develop a coherent curriculum and the role of high-level champions to drive the inclusion of climate change and planetary health. Building pedagogical leadership in in the area of climate change and health teaching at universities through stronger partnerships with policymakers, community stakeholders and advocacy organisations will be important for future health workforce training amid increasing climate risks. Supplemental data for this article is available online at https://doi.org/10.1080/13504622.2022.2036325 .
Background: Climate change contributes to the increasing incidence of AD, diurnal temperature range (DTR) is a pivotal indicator for monitoring climate change, however, the effects of DTR on AD remains unknown in regions with a temperate continental climate. Objective: This study aims to explore effects of DTR on AD in Lanzhou, China. Method: A Poisson generalized linear regression model combined with a distributed lag non-linear model (DLNM) was used to analyze data. Results: The effect of DTR on AD outpatient visits is nonlinear and presents J-shaped. For every 1 degrees C increase in DTR, the risk of AD outpatient visits increased by 2.6% (95% CI: 0.2%, 5.2%) at lag 21 when DTR was 17 degrees C. Harmful effect of extremely high DTR is significant, it is observed on lag 9 days and lasted for 12 days. The maximum effect of extremely high DTR emerged on lag 0-21 days and the relative risk was 1.470 (95% CI: 1.119, 1.932). Females and children aged 0-14 years were vulnerable to extremely high DTR. Conclusion: The present study suggests that high DTR is a risk factor for AD outpatient visits and provides a theoretical basis and practical guidelines for the prevention of AD.
It is known that air pollution is harmful to creatures, though until now most of the human thermal comfort indices that existed were calculated only with meteorological conditions. Therefore, a new index – meteorology and environment comfort (MEC) – was given out in this paper that considers both meteorology and air pollution conditions and presents the comprehensive and synergistic effects of meteorological and air pollution. The meteorology and air pollution data were used to establish the influence function of the five air pollutants (PM(2.5), PM(10), O(3), NO(2), and SO(2)) according to Fechner’s law; then, we calculated the somatosensory temperature (ST, a class of human thermal comfort indices) and MEC values of five typical cities (Beijing, Xining, Nanjing, Kunming, and Guangzhou). The results showed average improvements of five cities on MEC as a new comprehensive human comfort index to new ST. In spring, the MEC comfort proportion fell by 29.25%. Besides, the extreme heat discomfort ratio in Nanjing and Kunming has increased over 20%. In summer, the comfort proportion fell 12.54%; the extreme heat discomfort proportion of Beijing increased 37.86% and Kunming increased 24.09%. Air pollution significantly raised discomfort stress in Beijing. In fall, the comfort proportion fell by 20.87%; and the extreme heat discomfort of Nanjing increased 23.67% caused by poor air quality. About winter, the comfort ratio decreased 12.72%, and the cold discomfort proportion of Nanjing increased 30.30%, signifying awful air quality in winter. Air pollution levels significantly affect the comfort levels in all seasons, which is more evident with good weather patterns. MEC can offer early warnings of extreme weather events and provide a basis for the better prevention and control of air pollution to protect human health basing on the predictions of meteorological and environmental impact factors.
BACKGROUND: In the context of ongoing climate change, temperature variability (TV) has been considered as an important trigger of death. However, evidence of association between mortality and hourly temperature variability (HTV) is scarce at the multi-city level, and the time window of health effects of HTV is lack of investigation. This study aims at quantifying the mortality risk and burden of HTV and exploring subpopulations susceptible to HTV from a large-scale multi-city perspective. METHODS: Data on daily number of deaths and meteorology were collected for 31 Chinese major cities during 2007-2013. HTV was calculated as the standard deviation of hourly temperature within a few days. The optimal exposure period of HTV was chosen according to multiple scientific criteria. A quasi-Poisson regression combined with distributed lag nonlinear model was used to assess the city-specific HTV-mortality associations. Then, meta-analysis was further applied to pool city-specific effect estimates. Finally, we calculated the fraction of mortality attributable to HTV. Stratification analyses were conducted by individual characteristics (i.e. age, sex, and educational attainment), season, and region. RESULTS: HTV calculated in a relatively long-time window like 18 d (HTV(0-17)) could capture the impact of HTV adequately. Per 1 °C raise of HTV(0-17) associated with 1.38% (95%CI: 0.77, 1.99) increase of non-accidental mortality. During the study period, 5.47% (95%CI: 1.06, 9.64) of non-accidental mortality could be attributed to HTV. The females, the elderly, and individuals with low education level were more susceptible to HTV than their counterparts, respectively. Moreover, a stronger HTV-mortality association was observed in individuals who live in warmer season and temperature zone. CONCLUSION: HTV is associated with a considerable mortality burden, which may be modified by season, geographic and individual-level factors. Our findings highlight the practical importance of establishing early warning systems and promoting health education to mitigate the impacts of temperature variability.
The Chinese government attaches great importance to climate change adaptation and has issued relevant strategies and policies. Overall, China’s action to adapt to climate change remains in its infancy, and relevant research needs to be further deepened. In this paper, we study the future adaptive countermeasures of Shenzhen city in the Pearl River Delta in terms of climate change, especially urban flood risk resilience. Based on the background investigation of urban flood risk in Shenzhen, this paper calculates the annual precipitation frequency of Shenzhen from 1953 to 2020, and uses the extreme precipitation index as a quantitative indicator to analyze the changes in historical precipitation and the impact of major flood disasters in Shenzhen city in previous decades. Based on the six kinds of model data of the scenario Model Inter-comparison Project (MIP) in the sixth phase of the Coupled Model Inter-comparison Project (CMIP6), uses the Taylor diagram and MR comprehensive evaluation method to evaluate the ability of different climate models to simulate extreme precipitation in Shenzhen, and the selected models are aggregated and averaged to predict the climate change trend of Shenzhen from 2020 to 2100. The prediction results show that Shenzhen will face more severe threats from rainstorms and floods in the future. Therefore, this paper proposes a resilience strategy for the city to cope with the threat of flood in the future, including constructing a smart water management system and promoting the development of a sponge city. Moreover, to a certain extent, it is necessary to realize risk transfer by promoting a flood insurance system.
Lung cancer (LC) mortality, as one of the top cancer deaths in China, has been associated with increased levels of exposure to ambient air pollutants. In this study, different lag times on weekly basis were applied to study the association of air pollutants (PM2.5, PM10, and NO2) and LC mortality in Ningbo, and in subpopulations at different age groups and genders. Furthermore, seasonal variations of pollutant concentrations and meteorological variables (temperature, relative humidity, and wind speed) were analysed. A generalised additive model (GAM) using Poisson regression was employed to estimate the effect of single pollutant model on LC mortality in Yangtze River Delta using Ningbo as a case study. It was reported that there were statistically significant relationships between lung cancer mortality and air pollutants. Increases of 6.2% (95% confidence interval [CI]: 0.2% to 12.6%) and 4.3% (95% CI: 0.1% to 8.5%) weekly total LC mortality with a 3-week lag time were linked to each 10 μg/m(3) increase of weekly average PM(2.5) and PM(10) respectively. The association of air pollutants (PM(2.5), PM(10) and NO(2)) and LC mortality with a 3-week lag time was also found statistically significant during periods of low temperature (T < 18 °C), low relative humidity (H < 73.7%) and low wind speed (u < 2.8 m/s), respectively. The female population was found to be more susceptible to the exposure to air pollution than the male population. In addition, the population with an age of 50 years or above was shown to be more sensitive to ambient air pollutant. These outcomes indicated that increased risk of lung cancer mortality was evidently linked to exposure to ambient air pollutant on a weekly basis. The impact of weekly variation on the LC mortality and air pollutant levels should be considered in air pollution-related health burden analysis.
Older people are main susceptible group affected by non-optimal temperature. The aim of the study was to determine how mortality of older people with different ages are affected by temperatures. For this study, we collected data of all-cause death of 256,037 people aged between 65 and 104 years of age from a prefecture located in the north subtropical area with most serious aging rate in 2000, 2010 and 2020 in China. A distributed lag nonlinear model under different age groups was used to estimate non-optimal temperature associations to mortality. The results revealed: (1) With increasing age, older people were more likely to die during moderate low temperature, the proportion of attributable fraction of moderate low temperature in all temperature gradually increased with age. (2) Moderate low temperature could be divided into two parts, the lower part caused most death at age 65-79 and the higher part was not so dangerous, while for age 80+, preventive actions should be taken for both parts. (3) A leveling-off and deceleration phenomenon was observed at age 95-99 for low temperature, but not 100-104, it may be virtually a consequence of “harvesting effect” in that susceptible and common people have died before age 95, it was coincidence with mortality deceleration at extreme old ages found by demographic scholars over the past 200 years. (4) Heat wave had much higher relative risk than cold spell compared with moderate high and low temperature because of steeper slope of relative risk at the period of moderate-extreme conversion of high temperature, the older people should pay more attention to weather with moderate-extreme conversion of high temperature. Furthermore, our findings could help improve the understanding of non-optimal temperature on health of older people and support the development of response strategies for different seasons at different ages.
OBJECTIVES: This study aimed to investigate the seasonality of paediatric intussusception and the associations between meteorological factors and paediatric intussusception in Hangzhou, as well as aimed to compare the variance in sex and disease type. DESIGN: An 8-year retrospective study was conducted from January 2014 to December 2021 in the Children’s Hospital of Zhejiang University, Hangzhou, China. SETTING: This was a single-centre retrospective study review of intussusception cases in a large Children’s Hospital in Hangzhou. PARTICIPANTS: There were 17 674 patients with intussusception in this study. METHODS: A Spearman correlation analysis and Poisson regression analysis were used to determine the association between weekly intussusception cases and meteorological factors. The seasonality of paediatric intussusception was demonstrated via the t-test and visualised. RESULT: In January, May and December, there were relatively more intussusception patients. In February, there was a trough in the number of intussusception patients. Both the Spearman correlation analysis and Poisson regression analysis proved that weekly intussusception cases had significant associations with temperature (λ=-0.205, p<0.01; β=-0.080, p<0.01), feels-like temperature (λ=-0.214, p<0.01; β=-0.012, p<0.01), dew (λ=-0.249, p<0.01; β=0.095, p<0.01), humidity (λ=-0.230, p<0.01; β=-0.037, p<0.01), precipitation (λ=-0.148, p<0.01; β=-0.001, p<0.01), windspeed (λ=-0.135, p<0.01; β=0.005, p<0.01), visibility (λ=-0.206, p<0.01; β=-0.066, p<0.01), sea level pressure (λ=0.171, p<0.01; β=-0.004, p<0.01) and a total of 20 of 25 dynamic meteorological factors (p<0.05). These associations reflected gender differences but showed stronger associations in groups that were prone to recurrence. CONCLUSIONS: Paediatric intussusception in Hangzhou showed a seasonal tendency. Additionally, intussusception was significantly associated with certain meteorological factors in all of the cases. These findings suggest that parents and paediatricians should be more vigilant about the occurrence of intussusception in children regarding seasonal change times and climate change times.
This study aimed to investigate the association between relative humidity (RH) and various cause of mortality, and then quantify the RH-related mortality fraction of low and high RH under the assumption that causal effects exist. Daily cause-specific mortality counts from 2008 to 2011, and contemporaneous meteorological data in three Chinese cities were collected. Distributed lag nonlinear models were adopted to quantify the nonlinear and delayed effects of RH on mortality risk. Low and high RH were defined as RH lower or higher than the minimum mortality risk RH (MMRH), respectively. Corresponding RH-related mortality fractions were calculated in the explanatory analysis. From the three cities, 736,301 deaths were collected. RH (mean ± standard deviation) were 50.9 ± 20.0 for Beijing, 75.5 ± 8.6 for Chengdu, and 70.8 ± 14.6 for Nanjing. We found that low RH in Beijing and high RH (about 80-90%) in Chengdu was associated with increased all-cause mortality risk. Both low and high RH may increase the CVD mortality risk in Beijing. Both low and high (about 80-85%) RH may increase the COPD mortality risk in Chengdu. Low RH (about < 45%) was associated with increased diabetes mortality risk in Nanjing. Effects of extreme low and extreme high RH were delayed in these cities, except that extreme low effects on COPD mortality appeared immediately in Chengdu. The effects of extreme low RH are higher than that of the extreme high RH in Beijing and Nanjing, while contrary in Chengdu. Finally, under the causal effect assumption, 6.80% (95% eCI: 2.90, 10.73) all-cause mortality and 12.48% (95% eCI: 7.17, 16.80) CVD deaths in Beijing, 9.59% (95% eCI: 1.38, 16.88) COPD deaths in Chengdu, and 23.79% (95% eCI: 0.92, 387.93) diabetes mortality in Nanjing were attributable to RH. Our study provided insights into RH-mortality risk, helped draw relative intervention policies, and is also significant for future predictions of climate change effects under different scenarios.
Climate variability driven by El Niño-Southern Oscillation (ENSO) is a significant public health concern in parallel with global population aging; however, its role in healthy aging is less studied. We examined the longitudinal impacts of ENSO exposure on excess mortality and related medical costs in the elderly from 23 provinces of China. A total of 27,533 non-accidental all-cause deaths were recorded in 30,763 participants during 1998-2018. We found that both low and high levels of ENSO metrics over lags of 0-12 months were associated with increased mortality risks. Specifically, comparing the 10th percentile (-1.8) and 90th percentile (2.0) multivariate El Niño index (MEI) levels to the reference level with the minimum effect of MEI exposure, the risk of mortality was 1.87 (95 % confidence interval [CI], 1.75, 2.00) and 4.89 (95 % CI, 4.36, 5.49), respectively. ENSO exposure was also positively related to medical costs. Further, the associations were stronger among drinkers, lower-income participants, and those with higher blood pressure and heart rate measured at the most recent follow-ups. Our results suggested that ENSO exposure was capable of heightening mortality risks and medical burden among older elderly adults, highlighting that climate variability driven by ENSO could be a crucial determinant of healthy aging.
BACKGROUND: Associations of acute glycemic complications with season and ambient temperature have been reported in general population with diabetes. However, little is known about the risks of acute glycemic complications in relation to season and ambient temperature in pregnant women, who are likely to be even more vulnerable. This work aimed to investigate the associations of season and ambient temperature with pregnancies complicated with hyperglycemia emergency or severe hypoglycemia. METHODS: Two separate case-control studies were nested within 150,153 pregnancies by women with type 1, type 2, or gestational diabetes between 2009 and 2014 in Taiwan. Hyperglycemia emergency (mainly diabetic ketoacidosis and hyperosmolar hyperglycemic state) and severe hypoglycemia occurred in 77 and 153 diabetic pregnancies (cases), respectively. Ten control pregnancies were randomly selected for each case by matching each case pregnancy on type of diabetes (i.e., T1DM, T2DM, or GDM), maternal age on the date of acute glycemic complication occurrence (i.e., index date), and “length of gestation at risk” (i.e., period between conception and index date). Meteorological parameters were retrieved from 542 meteorological monitoring stations across Taiwan during 2008-2014. Conditional logistic regression analysis with generalized estimation equation was separately performed to estimate the covariate adjusted odds ratios (ORs) of each of the two acute glycemic complications in association with season and ambient temperature within 30 days prior to the index date. RESULTS: Compared to summer, winter season was associated with a significantly elevated risk of severe hypoglycemia with an OR of 1.74 (95% confidence interval (CI) 1.08-2.79). The OR of hyperglycemic emergency was also elevated in winter season at OR of 1.88, but the significance is only marginal (95% CI 0.97-3.64, p = 0.0598). Subgroup analyses further noted that such seasonal variation was also observed in pregnancies with pre-pregnancy type 1 diabetes and gestational diabetes. On the other hand, ambient temperature was not significantly associated with the two acute glycemic complications. CONCLUSIONS: A moderately but significantly elevated risk of severe hypoglycemia was found in pregnant women with diabetes during winter season, and such increased risk was more evident in pregnancies with T1DM.
This study focused on the extreme heavy rainstorm that occurred in Zhengzhou in July 2021; approximately 380 people were killed or missing as a result of this storm. To investigate the evolution behaviors of this rainstorm and take corresponding prevention measures, several methods and models were adopted, including cloud modeling, preliminary hazard analysis (PHA), fault tree analysis (FTA), bow-tie modeling, and chaos theory. The main reasons for this rainstorm can be divided into the following three aspects: force majeure, such as terrain and extreme weather conditions, issues with city construction, and insufficient emergency rescue. The secondary disasters caused by this rainstorm mainly include urban water logging, river flooding, and mountain torrents and landslides. The main causes of the subway line-5 accident that occurred can be described as follows: the location of the stabling yard was low, the relevant rules and regulations of the subway were not ideal, insufficient attention was given to the early warning information, and the emergency response mechanism was not ideal. Rainstorms result from the cross-coupling of faults in humans, objects, the environment, and management subsystems, and the evolution process shows an obvious butterfly effect. To prevent disasters caused by rainstorms, the following suggestions should be adopted: vigorously improve the risk awareness and emergency response capabilities of leading cadres, improve the overall level of urban disaster prevention and mitigation, reinforce the existing reservoirs in the city, strengthen the construction of sponge cities, and improve the capacity of urban disaster emergency rescue.
BACKGROUND: Childhood atopic dermatitis (AD) is an inflammatory skin disease which sometimes predisposes to allergies. Environmental factors (low humidity, irritants, etc.) are prominent causative triggers of AD. OBJECTIVES: This study aims to explore the effects of both meteorological factors and air pollutants on childhood AD, and the modification effects by season in Shanghai, China. METHODS: Quasi-Poisson generalized linear regression model, combined with a distributed lag nonlinear model was used to examine the nonlinear and lagged effects of environmental factors on childhood AD from 2009 to 2017 in Shanghai. We also performed a season-stratified analysis to determine the modification effects of environmental exposure by season on childhood AD. RESULTS: There were 1,043,240 outpatient visits for childhood AD in total, at 3 major pediatric hospitals. Low temperature and relative humidity (RH), and high daily temperature difference (DTD) and air pollutants (i.e., NO2) increased the relative risks (RRs) of outpatient visits for childhood AD in the whole year. In the cold season, an increased risk of outpatient visits for childhood AD was associated with low RH (RR 2.26, 95% CI 1.69-3.02) and high NO2 (1.11, 95% CI 1.06-1.17). In the warm season, outpatient visits for childhood AD were associated with low temperature (3.49, 95% CI 3.22-3.77), low RH (1.89, 95% CI 1.74-2.06), high DTD (1.41, 95% CI 1.31-1.53), and high NO2 (1.05, 95% CI 1.03-1.06). CONCLUSIONS: This study suggests that environmental exposure may be a key trigger for outpatient visits for childhood AD with apparent seasonal effects. Tailored preventive strategies to avoid environmental triggers of childhood AD should be developed.
PURPOSE: To assess the correlation between meteorological factors and spinal disease admissions. METHODS: Data was obtained from the electronic medical records of a tertiary general hospital. Meteorological data was collected from China Meteorological Science Data Sharing Service. Distributed lag nonlinear models were used to evaluate the impact of meteorological variables on weekly spinal disease admissions. RESULTS: A total of 2739 spinal cases were documented. Compared with estimates at the 50(th), the cumulative relative risk (RR) for extremely high temperatures at the 97.5(th) over lag week 18 to lag week 20 increased by 75.7%. When the weekly maximum temperature reached 38°C during lag week 20, the maximum RR was 1.96 (95% CI:1.095-3.506). Moreover, the effects of extremely high temperatures on spinal disease admissions were more obvious in females and the age group ≥65 years old compared with males and the age group<65 years old. CONCLUSIONS: Extremely high temperatures were significantly associated with higher risks of spinal disease admissions.
To meet the carbon neutrality target and Beautiful China goal, the co-control strategy of carbon emission and air pollution is crucial. The Beijing-Tianjin-Hebei region is a prominent cooperative development zone, which faces dual challenges of CO2 emission reduction and air pollution control. This study aims to find the co-benefit pathway for achieving both targets in Beijing-Tianjin-Hebei. Based on an innovative and integrated framework by linking the computable general equilibrium model, atmospheric environment analysis model and health impact assessment model, we analyze the mutual co-benefits of carbon reduction and air quality improvement by climate and environmental policies. The results show significant mutual effects of CO2 emission mitigation and air pollution reduction. From the regional view, air pollutants control and CO2 mitigation policies have a relatively higher synergistic emission reduction effect in Beijing and Tianjin than in Hebei. From the sector perspective, the energy supply and transport sectors have much higher co-effects with CO2 reduction, while climate change mitigation policies have the best co-effects with air pollution reduction in the energy supply and residential sectors. Moreover, the health benefits in the air pollution control scenario (6.0 BUSD) are higher than in the decarbonization scenario (5.7 BUSD). In addition, climate mitigation policies could have tremendous synergistic air pollution reductions, even the health benefits (5.7 BUSD) may be insufficient to offset the cost (18.7 BUSD) of climate policy in the current situation. In order to better achieve the dual climate and air quality targets at lower costs, two types of policies should be better coordinated in the decision-making process.
BACKGROUND: Two cervical cancer screening (CCS) projects have been ongoing for years in Guangxi Zhuang autonomous region (Guangxi), and some Trichomonas vaginalis infection (TVI) cases have been found as an opportunistic finding. This study aimed to identify the high-risk population and expound the spatial epidemiological features of TVI in Guangxi. METHODS: This study was based on CCS from 2012 to 2019. Adjusted odds ratio (AOR), and spatial analyses were used to identify the high-risk subgroups, as well as to depict the spatial epidemiological feature and its relationship with meteorological factors. RESULTS: The infection rate of TVI was 0.38% in 873,880 samples. Significant association with a high risk of TVI was found in the following: females aged 40-49 years (aOR=4.464; 95% CI, 3.359-5.932; p<0.001), aged 50-59 years (aOR=3.169; 95% CI, 2.370-4.237; p<0.001), from urban (aOR=1.577; 95% CI, 1.471-1.691; p<0.001), from minority areas (aOR=1.183; 95% CI, 1.060-1.320; p=0.003), areas with GPD <41,500 CNY (aOR=1.191; 95% CI, 1.106-1.282; p<0.001), and inland areas (aOR=1.520; 95% CI, 1.339-1.726; p<0.001). Counties with higher infection rate were concentrated in northwest Guangxi's mountainous area (Z-score=3.9656, p<0.001), in the upper reaches of the Hongshui River and Yu River, and with a significant spatial autocorrelation (Moran's I=0.581, p=0.002). Spatial error model showed significantly negative regressions among temperature (B=-0.295, p=0.002), annual temperature range (B=-0.295, p=0.002), and TVI spatial distribution. CONCLUSION: The spatial clustering and disparity of TVI in northwest Guangxi warrant further study, and meteorological conditions may play an important role in TVI in northwest Guangxi.
BACKGROUND: Diurnal temperature range (DTR) has been widely applied in exploring its effect on cardiovascular disease (CVD). However, few studies have investigated the correlations between DTR and CVD in poor rural areas in China. This study aimed to examine the association between DTR and CVD in rural China. METHODS: A distributed lag nonlinear model was used to evaluate the relationship between DTR and CVD risk among farmers living in the city of Dingxi (Northwest China) in the period from January 1, 2016 to December 31, 2019. RESULTS: We observed nonlinear M-patterns between the relative risk (RR) of DTR (reference: median DTR, 12 °C) and CVD hospitalizations in all subgroups. The peak RR of CVD was noticed at DTR of 6 °C (total: 1.418; men: 1.546; women: 1.403; young: 1.778; old: 2.549) and 17 °C (total: 1.781; men: 1.937; women: 1.712; young: 2.233; old: 1.798). The adverse effect of DTR on CVD risk was more pronounced in females (RR 1.438) and elderly (RR 2.034) than males (RR 1.141) and younger adults (RR 1.852) at the extremely low (5th, 4 °C) DTR. The reverse was observed at the extremely high DTR (95th, 19 °C) (male: 1.267; females: 0.993; young: 1.586; old: 1.212). CONCLUSIONS: DTR is associated with CVD morbidity. This association was more pronounced in women and elderly, but men and younger peoples at extremely high DTR (19 °C). Future measures should take DTR into account to prevent CVD among susceptible populations.
BACKGROUND: A number of studies have explored the association between ambient temperature and preterm birth (PTB), but rarely among adolescent mothers. OBJECTIVES: To estimate the effects of ambient temperature on the risk of PTB and gestational age of newborns delivered by adolescent mothers in rural areas of Henan province. METHODS: We obtained 5394 medical records of adolescent mothers with results of pre-pregnancy physical examination and pregnancy outcomes from the National Free Preconception Health Examination Project (NFPHEP) in Henan province. Meteorological information was obtained from the China Meteorological Data Sharing Service System. Individual exposure levels were evaluated with an inverse distance-weighted model. A multiple logistic regression model and multiple linear regression model were used to estimate the effects of ambient temperature on the risk of PTB and gestational age, respectively. Stratified and interaction analyses were also performed. RESULTS: Of newborns in this study, 3.45% (186/5394) were PTB. Mean, maximum and minimum temperature during the entire pregnancy, especially the last 1-4 weeks of pregnancy, were positively associated with the risk of PTB and negatively associated with gestational age (P < 0.05). Nevertheless, a masking effect was observed that gestational age was positively associated with ambient temperature during the first trimester of pregnancy, due to the strongly inverse correlation between ambient temperature during the early and late stages of pregnancy. Stratified analyses showed that increasing temperature during the last 1-4 weeks of pregnancy increased the risk of PTB and decreased gestational age in newborns born in the cold season (P < 0.05). Furthermore, interaction analyses showed that birth season modified the effects of temperature on the gestational age (P(interaction) < 0.10). CONCLUSIONS: Elevated ambient temperature can decrease gestational age and increase the risk of PTB in offspring of adolescent mothers in rural areas. The birth season may modify the effects of temperature on gestational age.
Climate variability exerts severe threats to farmers and agriculture related activities and farmers. A growing number of studies have paid attention to mitigating carbon emission and adapting to climate change. Very few studies, however, have investigated farmers’ health risk management associated with climate change. This study, therefore, proposed a hybrid theoretical model to explore the roles of farmers’ climate risk perceptions and facilitating conditions in farmers’ health risk management, both theoretically and empirically. Using a sample of 1499 rice farmers in China, the partial least squares structural equation modeling (PLS-SEM) was adopted for empirical analysis, and the Multi-group Analysis (MGA) was employed to examine the heterogeneity among farmers’ socio-economic status. This study found that farmers’ perceived severity of climate change and perceived benefits of addressing climate change have significant impacts on their resources and technical facilitating conditions, in turn, those two types of facilitating conditions significantly impact their health risk management intentions. Subjective norms are also identified as predictors of resources facilitating condition and technical facilitating condition. In addition, farmers with lower income are more likely to suffer from health risks induced by climate change. They have fewer resources for resilience and maintaining health. Based on the findings identified above, strategies for coping with the negative impacts of climate change on farmers’ health were proposed for climate adaptation from the perspective of health risk management.
No abstract available.
Zoonoses impart a significant public health burden in Australia particularly in Queensland, a state with increasing environmental stress due to extreme weather events and rapid expansion of agriculture and urban developments. Depending on the organism and the environment, a proportion of zoonotic pathogens may survive from hours to years outside the animal host and contaminate the air, water, food, or inanimate objects facilitating their transmission through the environment (i.e. environmentally transmitted). Although most of these zoonotic infections are asymptomatic, severe cases that require hospitalisation are an important indicator of zoonotic infection risk. To date, no studies have investigated the risk of hospitalisation due to environmentally transmitted zoonotic diseases and its association with proxies of sociodemographic and environmental stress. In this study we analysed hospitalisation data for a group of environmentally transmitted zoonoses during a 15-year period using a Bayesian spatial hierarchical model. The analysis incorporated the longest intercensal-year period of consistent Local Government Area (LGA) boundaries in Queensland (1996-2010). Our results showed an increased risk of environmentally transmitted zoonoses hospitalisation in people in occupations such as animal farming, and hunting and trapping animals in natural habitats. This risk was higher in females, compared to the general population. Spatially, the higher risk was in a discrete set of north-eastern, central and southern LGAs of the state, and a probability of 1.5-fold or more risk was identified in two separate LGA clusters in the northeast and south of the state. The increased risk of environmentally transmitted zoonoses hospitalisations in some LGAs indicates that the morbidity due these diseases can be partly attributed to spatial variations in sociodemographic and occupational risk factors in Queensland. The identified high-risk areas can be prioritised for health support and zoonosis control strategies in Queensland.
BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is endemic in Zhejiang Province, China, while few studies have concentrated on the influence of meteorological factors on HFRS incidence in the area. METHODS: Data on HFRS and meteorological factors from January 1, 2008 to December 31, 2020 in Taizhou City, Zhejiang Province were collected. Multivariate analysis was conducted to the relationship between meteorological factors including minimum temperatures, relative humidity, and cumulative rainfall with HFRS. RESULTS: The HFRS incidence peaked in November and December and it was negatively correlated with average and highest average temperatures. Compared with median of meteorological factors, the relative risks (RR) of weekly average temperature at 12 ℃, weekly highest temperature at 18 ℃relative humidity at 40%, and cumulative rainfall at 240 mm were most significant and RRs were 1.41 (95% CI: 1.09-1.82), 1.32 (95% CI: 1.05-1.66), 2.18 (95% CI: 1.16-4.07), and 1.91 (95% CI: 1.16-2.73), respectively. Average temperature, precipitation, relative humidity had interactions on HFRS and the risk of HFRS occurrence increased with the decrease of average temperature and the increase of precipitation. CONCLUSION: Our study results are indicative of the association of environmental factors with the HFRS incidence, probable recommendation could be use of environmental factors as early warning signals for initiating the control measure and response.
Hemorrhagic fever with renal syndrome (HFRS) is caused by hantavirus (HV) infection, and is prevalent across Europe and Asia (mainly China). The genetic variation and wide host range of the HV family may lead to vaccine failure. In this study, we analyzed the gene sequences of HV isolated from different regions of China in order to trace the molecular evolution of HV and the epidemiological trends of HFRS. A total of 16,6975 HFRS cases and 1,689 HFRS-related deaths were reported from 2004 to 2016, with the average annual incidence rate of 0.9674 per 100,000, 0.0098 per 100,000 mortality rate, and case fatality rate 0.99%. The highest number of cases were detected in 2004 (25,041), and after decreasing to the lowest numbers (8,745) in 2009, showed an incline from 2010. The incidence of HFRS is the highest in spring and winter, and three times as many men are affected as women. In addition, farmers account for the largest proportion of all cases. The main hosts of HV are Rattus norvegicus and Apodemus agrarius, and the SEOV strain is mainly found in R. norvegicus and Niviventer confucianus. Phylogenetic analysis showed that at least 10 HTNV subtypes and 6 SEOV subtypes are endemic to China. We found that the clustering pattern of M genome segments was different from that of the S segments, indicating the possibility of gene recombination across HV strains. The recent increase in the incidence of HFRS may be related to climatic factors, such as temperature, relative humidity and hours of sunshine, as well as biological factors like rodent density, virus load in rodents and genetic variation. The scope of vaccine application should be continuously expanded, and surveillance measures and prevention and control strategies should be improved to reduce HFRS infection in China.
BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a severe public health threat. Previous studies have discovered the influence of meteorological factors on HFRS incidence, while few studies have concentrated on the stratified analysis of delayed effects and interaction effects of meteorological factors on HFRS. OBJECTIVE: Huludao City is a representative area in north China that suffers from HFRS with primary transmission by Rattus norvegicus. This study aimed to evaluate the climate factors of lag, interaction, and stratified effects of meteorological factors on HFRS incidence in Huludao City. METHODS: Our researchers collected meteorological data and epidemiological data of HFRS cases in Huludao City during 2007-2018. First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. We then constructed a generalized additive model (GAM) to explore the interaction effect between temperature and the other two meteorological factors on HFRS incidence and the stratified effect of meteorological factors. RESULTS: During the study period, 2751 cases of HFRS were reported in Huludao City. The incidence of HFRS showed a seasonal trend and peak times from February to May. Using the median WAT, median WTP, and median WARH as the reference, the results of DLNM showed that extremely high temperature (97.5th percentile of WAT) had significant associations with HFRS at lag week 15 (RR = 1.68, 95% CI: 1.04-2.74) and lag week 16 (RR = 2.80, 95% CI: 1.31-5.95). Under the extremely low temperature (2.5th percentile of WAT), the RRs of HFRS infection were significant at lag week 5 (RR = 1.28, 95% CI: 1.01-1.67) and lag 6 weeks (RR = 1.24, 95% CI: 1.01-1.57). The RRs of relative humidity were statistically significant at lag week 10 (RR = 1.19, 95% CI: 1.00-1.43) and lag week 11 (RR = 1.24, 95% CI: 1.02-1.50) under extremely high relative humidity (97.5th percentile of WARH); however, no statistically significance was observed under extremely low relative humidity (2.5th percentile of WARH). The RRs were significantly high when WAT was -10 degrees Celsius (RR = 1.34, 95% CI: 1.02-1.76), -9 degrees Celsius (1.37, 95% CI: 1.04-1.79), and -8 degrees Celsius (RR = 1.34, 95% CI: 1.03-1.75) at lag week 5 and more than 23 degrees Celsius after 15 weeks. Interaction and stratified analyses showed that the risk of HFRS infection reached its highest when both temperature and precipitation were at a high level. CONCLUSIONS: Our study indicates that meteorological factors, including temperature and humidity, have delayed effects on the occurrence of HFRS in the study area, and the effect of temperature can be modified by humidity and precipitation. Public health professionals should pay more attention to HFRS control when the weather conditions of high temperature with more substantial precipitation and 15 weeks after the temperature is higher than 23 degrees Celsius.
BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is a serious public health problem in China. The geographic distribution has went throughout China, among which Zhejiang Province is an important epidemic area. Since 1963, more than 110,000 cases have been reported. METHODS: We collected the meteorological factors and socioeconomic indicators of Zhejiang Province, and constructed the HFRS ecological niche model of Zhejiang Province based on the algorithm of maximum entropy. RESULTS: Model AUC from 2009 to 2018, is 0.806-0.901. The high incidence of epidemics in Zhejiang Province is mainly concentrated in the eastern, western and central regions of Zhejiang Province. The contribution of digital elevation model ranged from 2009 to 2018 from 4.22 to 26.0%. The contribution of average temperature ranges from 6.26 to 19.65%, Gross Domestic Product contribution from 7.53 to 21.25%, and average land surface temperature contribution with the highest being 16.73% in 2011. In addition, the average contribution of DMSP/OLS, 20-8 precipitation and 8-20 precipitation were all in the range of 9%. All-day precipitation increases with the increase of rainfall, and the effect curve peaks at 1,250 mm, then decreases rapidly, and a small peak appears again at 1,500 mm. Average temperature response curve shows an inverted v-shape, where the incidence peaks at 17.8(°)C. The response curve of HFRS for GDP and DMSP/OLS shows a positive correlation. CONCLUSION: The incidence of HFRS in Zhejiang Province peaked in areas where the average temperature was 17.8(°)C, which reminds that in the areas where temperature is suitable, personal protection should be taken when going out as to avoid contact with rodents. The impact of GDP and DMSP/OLS on HFRS is positively correlated. Most cities have good medical conditions, but we should consider whether there are under-diagnosed cases in economically underdeveloped areas.
Hemorrhagic fever with renal syndrome (HFRS), caused by hantavirus, is a serious public health problem in China. Despite intensive countermeasures including Patriotic Health Campaign, rodent control and vaccination in affected areas, HFRS is still a potential public health threat in China, with more than 10,000 new cases per year. Previous epidemiological evidence suggested that meteorological factors could influence HFRS incidence, but the studies were mainly limited to a specific city or region in China. This study aims to evaluate the association between monthly HFRS cases and meteorological change at the country level using a multivariate distributed lag nonlinear model (DLNM) from 2004 to 2018. The results from both univariate and multivariate models showed a non-linear cumulative relative risk relationship between meteorological factors (with a lag of 0-6 months) such as mean temperature (Tmean), precipitation, relative humidity (RH), sunshine hour (SH), wind speed (WS) and HFRS incidence. The risk for HFRS cases increased steeply as the Tmean between - 23 and 14.79 °C, SH between 179.4 and 278.4 h and RH remaining above 69% with 50-95 mm precipitation and 1.70-2.00 m/s WS. In conclusion, meteorological factors such as Tmean and RH showed delayed-effects on the increased risk of HFRS in the study and the lag varies across climate factors. Temperature with a lag of 6 months (RR = 3.05) and precipitation with a lag of 0 months (RR = 2.08) had the greatest impact on the incidence of HFRS.
Hemorrhagic fever with renal syndrome (HFRS), a serious threat to human health, is mainly transmitted by rodents in Eurasia. The risk of disease differs according to sex, age, and occupation. Further, temperature and rainfall have some lagging effects on the occurrence of the disease. The quantitative data for these factors in the Tai’an region of China are still unknown. We used a forest map to calculate the risk of HFRS in different populations and used four different mathematical models to explain the relationship between time factors, meteorological factors, and the disease. The results showed that compared with the whole population, the relative risk in rural medical staff and farmers was 5.05 and 2.00, respectively (p < 0.05). Joinpoint models showed that the number of cases decreased by 33.32% per year from 2005 to 2008 (p < 0.05). The generalized additive model showed that air temperature was positively correlated with disease risk from January to June, and that relative humidity was negatively correlated with risk from July to December. From January to June, with an increase in temperature, after 15 lags, the cumulative risk of disease increased at low temperatures. From July to December, the cumulative risk decreased with an increase in the relative humidity. Rural medical staff, farmers, men, and middle-aged individuals were at a high risk of HFRS. Moreover, air temperature and relative humidity are important factors that affect disease occurrence. These associations show lagged and differing effects according to the season.
Climate variability and anomalies are known drivers of the emergence and outbreaks of infectious diseases. In this study, we investigated the potential association between climate factors and anomalies, including El Niño Southern Oscillation (ENSO) and land surface temperature anomalies, as well as the emergence and spillover events of bat-borne viral diseases in humans and livestock in the Asia-Pacific region and the Arabian Peninsula. Our findings from time series analyses, logistic regression models, and structural equation modelling revealed that the spillover patterns of the Nipah virus in Bangladesh and the Hendra virus in Australia were differently impacted by climate variability and with different time lags. We also used event coincidence analysis to show that the emergence events of most bat-borne viral diseases in the Asia-Pacific region and the Arabian Peninsula were statistically associated with ENSO climate anomalies. Spillover patterns of the Nipah virus in Bangladesh and the Hendra virus in Australia were also significantly associated with these events, although the pattern and co-influence of other climate factors differed. Our results suggest that climate factors and anomalies may create opportunities for virus spillover from bats to livestock and humans. Ongoing climate change and the future intensification of El Niño events will therefore potentially increase the emergence and spillover of bat-borne viral diseases in the Asia-Pacific region and the Arabian Peninsula.
Australia has experienced an astonishing increase in liver cancer over the past few decades and the epidemiological reasons behind this are puzzling. The existing recognized risk factors for liver cancer, viral hepatitis, and alcohol consumption, are inconsistent with the trend in liver cancer. Behind the effects of migration and metabolic disease lies a potential contribution of climate change to an increase in liver cancer. This study explored the climate-associated distribution of high-risk areas for liver cancer by comparing liver cancer to lung cancer and finds that the incidence of liver cancer is more pronounced in hot and humid areas. This study showed the risk of liver cancer was higher in the equatorial region and tropical regions. These results will extend the study on the health consequences of climate change and provide more ideas and directions for future researchers.
BACKGROUND: Temperature fluctuations can affect human health independent of the effect of mean temperature. However, no study has evaluated whether short-term temperature fluctuations could affect DNA methylation. METHODS: Peripheral blood DNA methylation for 479 female siblings of 130 families were analysed. Gridded daily temperatures data were obtained, linked to each participant’s home address, and used to calculate nine different metrics of short-term temperature fluctuations: temperature variabilities (TVs) within the day of blood draw and preceding one to seven days (TV 0-1 to TV 0-7), diurnal temperature range (DTR), and temperature change between neighbouring days (TCN). Within-sibship design was used to perform epigenome-wide association analyses, adjusting for daily mean temperatures, and other important covariates (e.g., smoking, alcohol use, cell-type proportions). Differentially methylated regions (DMRs) were further identified. Multiple-testing comparisons with a significant threshold of 0.01 for cytosine-guanine dinucleotides (CpGs) and 0.05 for DMRs were applied. RESULTS: Among 479 participants (mean age ± SD, 56.4 ± 7.9 years), we identified significant changes in methylation levels in 14 CpGs and 70 DMRs associated with temperature fluctuations. Almost all identified CpGs were associated with exposure to temperature fluctuations within three days. Differentially methylated signals were mapped to 68 genes that were linked to human diseases such as cancer (e.g., colorectal carcinoma, breast carcinoma, and metastatic neoplasms) and mental disorder (e.g., schizophrenia, mental depression, and bipolar disorder). The top three most significantly enriched gene ontology terms were Response to bacterium (TV 0-3), followed by Hydrolase activity, acting on ester bonds (TCN), and Oxidoreductase activity (TV 0-3). CONCLUSIONS: Short-term temperature fluctuations were associated with differentially methylated signals across the human genome, which provides evidence on the potential biological mechanisms underlying the health impact of temperature fluctuations. Future studies are needed to further clarify the roles of DNA methylation in diseases associated with temperature fluctuations.
The health impacts of climate are widely recognised, and extensive modelling is available on predicted changes to climate globally. The impact of these changes may affect populations differently depending on a range of factors, including geography, socioeconomics and culture. This study reviewed current evidence on the health risks of climate change for Australian Aboriginal populations and linked Aboriginal demographic data to historical and projected climate data to describe the distribution of climate-related exposures in Aboriginal compared to non-Aboriginal populations in New South Wales (NSW), Australia. The study showed Aboriginal populations were disproportionately exposed to a range of climate extremes in heat, rainfall and drought, and this disproportionate exposure was predicted to increase with climate change over the coming decades. Aboriginal people currently experience higher rates of climate-sensitive health conditions and socioeconomic disadvantages, which will impact their capacity to adapt to climate change. Climate change may also adversely affect cultural practices. These factors will likely impact the health and well-being of Aboriginal people in NSW and inhibit measures to close the gap in health between Aboriginal and non-Aboriginal populations. Climate change, health and equity need to be key considerations in all policies at all levels of government. Effective Aboriginal community engagement is urgently needed to develop and implement climate adaptation responses to improve health and social service preparedness and secure environmental health infrastructure such as drinking water supplies and suitably managed social housing. Further Aboriginal-led research is required to identify the cultural impacts of climate change on health, including adaptive responses based on Aboriginal knowledges.
Australia experienced two public health emergencies in 2020 – the catastrophic bushfires and the global coronavirus (COVID-19) pandemic. Whilst these were separate events, both have similar drivers arising from human pressures on the natural environment. Here we report on relative personal concerns of Australians in a survey implemented during the global COVID-19 pandemic. The study design was a cross sectional online survey administered between 11 August and 11 November 2020. The setting was an Australia-wide online population involving 5483 individuals aged ≥18 residing in Australia. Recruitment occurred in two stages: unrestricted self-selected community sample through mainstream and social media (N = 4089); and purposeful sampling using an online panel company (N = 1055). The sample was predominantly female (N = 3187); mean age of 52.7 years; and approximately representative of adults in Australia for age, location, state and area disadvantage (IRSD quintiles). Climate change was very much a problem for 66.3% of the sample, while COVID-19 was ranked at the same level by only 25.3%. Three times as many participants reported that climate change was very much a problem than COVID-19, despite responding at a time when Australians were experiencing Stage 2 through 4 lockdowns. Demographic differences relating to relative personal concerns are discussed. Even in the midst of the uncertainty of a public health pandemic, Australians report that climate change is their most significant personal problem. Australia needs to apply an evidence-based public health approach to climate change, like it did for the pandemic, which will address the climate change concerns of Australians.
BACKGROUND: Climate change is a rapidly progressing threat to global health and well-being. For general practitioners (GPs) currently in training, the effects of climate change on public health will shape their future professional practice We aimed to establish the prevalence and associations of Australian GP registrars’ (trainees’) perceptions of climate change as it relates to public health, education, and workplaces. METHODS: A cross-sectional questionnaire-based study of GP registrars of three Australian training organizations. The questionnaire assessed attitudes regarding adverse health effects of climate change (over the next 10-20 years), and agreement with statements on (i) integrating health impacts of climate change into GP vocational training, and (ii) GPs’ role in making general practices environmentally sustainable. RESULTS: Of 879 registrars who participated (response rate 91%), 50.4% (95% CI 46.8%, 54.0%) perceived a large or very large future health effect of climate change on their patients, and 61.8% (95% CI 58.6%, 65.0%) agreed that climate health impacts should be integrated within their education programme. 77.8% (95% CI 74.9%, 80.4%) agreed that GPs should have a leadership role in their practices’ environmental sustainability. Multivariable associations of these attitudes included female gender, training region, and (for the latter two outcomes) perceptions of future impact of climate change on patient health. CONCLUSIONS: GP registrars are motivated to receive climate health education and engage in environmentally sustainable practice. This may primarily reflect concern for future practice and patient care.
The study assessed the environmental impacts of landfilling, anaerobic digestion and incineration technologies and investigated the effect of the replaced source of electricity on the environmental impacts of these waste to energy (WtE) technologies. Data published in the national pollutant inventories and ReCiPe impact assessment method were employed in this study. The study showed that electricity generation through incineration had the highest impacts on human health and ecosystems, followed by landfilling. Compared to the electricity of the Australian national grid, electricity generated from all three WtE technologies have a lower environmental impact. The results revealed that global warming and fine particulate matter formation with more than 97.6% contribution were the main impact factors for human health, while terrestrial acidification, global warming and ozone formation were contributing to more than 99% of the impacts to ecosystems. Global warming was the most impactful category on human health and ecosystems from incineration with over 85% contribution to both endpoint categories. Incineration revealed significantly higher avoided global warming impacts to human health and ecosystems than landfilling from the treatment of one tonne of solid waste by replacing electricity from brown coal, black coal or the Australian power grid. The growing share of renewable energy in the Australian power grid is expected to decrease the grid GHG emissions and the effect of the avoided impacts of replaced electricity. The results revealed that if the GHG emissions from the Australian power grid (757 kg CO2 eq/MWh) decrease to break-even point (621 kg CO2 eq/MWh), incineration loses the climate advantage over landfilling.
Aeromonas species can cause severe bloodstream infection (BSI) however, few studies have examined their epidemiology in non-selected populations. The objective of this study was to describe the incidence and determinants of Aeromonas species BSI in Queensland, Australia. A retrospective population-based cohort study was conducted during 2000-2019. Aeromonas species BSI were identified by laboratory surveillance and clinical and outcome information through data linkages to statewide databases. A total of 407 incident Aeromonas species BSI were identified with an age- and sex-standardized incidence of 5.2 per million residents annually. No trend in annual incidence rate during two decades of surveillance was demonstrated. Significant variable monthly occurrences were observed with highest rates during warmer, wetter months, and lowest rates during winter and dry periods. There was significant variability in incidence accordingly to region and climate zones, with higher rates observed in tropical north regions and lowest in southeastern corner. The highest incidence was observed in very remote and hot areas in Queensland. Cases were infrequent in children and risk was highest in elderly and males. Seventy-eight patients died within 30 days with a case-fatality rate of 19%. Older age, non-focal infection, higher Charlson score, and monomicrobial bacteremia were independent risk factors for death. Demographic and climatic changes may increase the burden of these infections in future years.
Disasters resulting from climate change and extreme weather events adversely impact crop and livestock production. While the direct impacts of these events on productivity are generally well known, the indirect supply-chain repercussions (spillovers) are still unclear. Here, applying an integrated modelling framework that considers economic and physical factors, we estimate spillovers in terms of social impacts (for example, loss of job and income) and health impacts (for example, nutrient availability and diet quality) resulting from disruptions in food supply chains, which cascade across regions and sectors. Our results demonstrate that post-disaster impacts are wide-ranging and diverse owing to the interconnected nature of supply chains. We find that fruit, vegetable and livestock sectors are the most affected, with effects flowing on to other non-food production sectors such as transport services. The ability to cope with disasters is determined by socio-demographic characteristics, with communities in rural areas being most affected. The complex nature of food supply chains makes it a crucial exercise to estimate the impacts of disruptions caused by climate disasters. By applying an integrated modelling framework to Australia and considering heatwaves, cyclones and other climate events, this study presents novel ways of quantifying regional and sectoral spillover effects-including job and income losses, food and nutrient availability, and diet quality.
Social housing stock worldwide can be characterised by poor indoor environmental quality and building thermal performance, which along with the increasing urban overheating put the low-income population at higher health risk. The dwellings’ thermal performance and the indoor environmental quality are often overlooked in the context of social housing compared to the general building stock in Australia. In the present study, the synergies between urban microclimate, indoor air temperature, housing characteristics and quality of life of residents have been investigated by employing subjective and objective assessment of indoor environmental quality in 106 low-income dwellings during the winter and summer of 2018- 2019 in New South Wales. It further examines the impact of urban overheating and levels of income on indoor thermal conditions. The subjective method involved assessing the links between the type of housing in which low-income people live, energy bills, self-reported thermal sensation, health and well-being, and occupants’ behaviours. The results show that many dwellings operated outside the health and safety temperature limits for substantial periods. Indoor air temperatures reached 39.8 degrees C and the minimum temperature was about 5 degrees C. While the upper acceptability limit for indoor air temperature was 25.6 degrees C for 80 % satisfaction, periods of up to about 997 and 114 continuous hours above 26 degrees C and 32 degrees C were found in overheated buildings, respectively. Indoor overheating hours above 32 degrees C were recorded up to 238 % higher in Sydney’s western areas compared to eastern and inner suburbs. Similarly, residents in westerns suburbs and regions experience more outdoor overheating hours than those living near the eastern suburbs. This study highlights the interrelationships between ambient temperature, housing design, income, thermal comfort, energy use, and health and well-being in the context of social housing. The evidence of winter underheating and summer overheating suggests that improvements in building quality and urban heat mitigation are required to minimise the impacts of poor-performing housing and local climate. Crown Copyright (c) 2022 Published by Elsevier B.V. All rights reserved.
Consumption of healthy and sustainable diets (HSD) provides opportunities to co-benefit human health and adapt to and mitigate climate change. Despite robust evidence and policy recommendations from authoritative groups to reorientate the food system to favour consumption of HSD there has been limited policy action. This study investigated potential barriers and enablers for successful HSD policies in Australia. A review of HSD policy recommendations and of current Australian policies was undertaken. Results from the reviews informed a Delphi study, which investigated Australian stakeholder opinions on the effectiveness of HSD policy recommendations and barriers and enablers to creating successful HSD policies. Nine participants completed two Delphi iterations. A lack of consensus was reached on the effectiveness of policy recommendations. Consensus was reached on the effect of five barriers and three enablers. Key barriers were: the complex nature of the food system, competing interests of stakeholders, pressure from industry, government silos and lack of political will. Key enablers were: building relationships with key stakeholders across multiple disciplines and sectors, understanding the policy making process and developing a clear and coherent solution. Most of the identified barriers fall under the broad category of lack of political will. Interrelationships between barriers are likely worsening the impact of inadequate political will. There is a need to act on the identified barriers and enablers to secure the HSD policies that are required. Interactions between barriers may present an opportunity to address them simultaneously.
The MJA-Lancet Countdown on health and climate change in Australia was established in 2017, and produced its first national assessment in 2018, its first annual update in 2019, and its second annual update in 2020. It examines indicators across five broad domains: climate change impacts, exposures and vulnerability; adaptation, planning and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. Our special report in 2020 focused on the unprecedented and catastrophic 2019-20 Australian bushfire season, highlighting indicators that explore the relationships between health, climate change and bushfires. For 2021, we return to reporting on the full suite of indicators across each of the five domains and have added some new indicators. We find that Australians are increasingly exposed to and vulnerable to excess heat and that this is already limiting our way of life, increasing the risk of heat stress during outdoor sports, and decreasing work productivity across a range of sectors. Other weather extremes are also on the rise, resulting in escalating social, economic and health impacts. Climate change disproportionately threatens Indigenous Australians’ wellbeing in multiple and complex ways. In response to these threats, we find positive action at the individual, local, state and territory levels, with growing uptake of rooftop solar and electric vehicles, and the beginnings of appropriate adaptation planning. However, this is severely undermined by national policies and actions that are contrary and increasingly place Australia out on a limb. Australia has responded well to the COVID-19 public health crisis (while still emerging from the bushfire crisis that preceded it) and it now needs to respond to and prepare for the health crises resulting from climate change.
Background The purpose of this study was to explore the impact of extreme precipitation on the risk of outpatient visits for depression and to further explore its associated disease burden and vulnerable population. Methods A quasi-Poisson generalized linear regression model combined with distributed lag non-linear model (DLNM) was used to investigate the exposure-lag-response relationship between extreme precipitation (>= 95th percentile) and depression outpatient visits from 2017 to 2019 in Suzhou city, Anhui Province, China. Results Extreme precipitation was positively associated with the outpatient visits for depression. The effects of extreme precipitation on depression firstly appeared at lag4 [relative risk (RR): 1.047, 95% confidence interval (CI): 1.005-1.091] and lasted until lag7 (RR = 1.047, 95% CI: 1.009-1.087). Females, patients aged >= 65 years and patients with multiple outpatient visits appeared to be more sensitive to extreme precipitation. The attributable fraction (AF) and numbers (AN) of extreme precipitation on outpatient visits for depression were 5.00% (95% CI: 1.02-8.82%) and 1318.25, respectively. Conclusions Our findings suggested that extreme precipitation may increase the risk of outpatient visits for depression. Further studies on the burden of depression found that females, aged >= 65 years, and patients with multiple visits were priority targets for future warnings. Active intervention measures against extreme precipitation events should be taken to reduce the risk of depression outpatient visits.
Disasters and climate-related risks displace millions of people each year. Planned relocation is one strategy used to address displacement and is increasingly being analyzed for the potential opportunities and challenges it creates for relocated people. However, little attention has been paid to the secondary impacts of planned relocations, and how they influence the risk, vulnerability and well-being of other groups, particularly people who live on the land that is selected for relocation sites, or in neighboring areas. This paper explores how current and potential future planned relocations in Fiji and the Philippines redistribute vulnerabilities to non-target communities who previously lived on, or alongside, relocation site land. The notion of cascading displacement is introduced to illustrate a serious consequence of planned relocations in which insecurity and displacement are re-created and perpetuated due to a failure to consider the needs of non-target groups who are directly disadvantaged by relocation processes. Insights from this paper may be used to inform future relocation policy and practice for more equitable and sustainable outcomes for all involved. This article is protected by copyright. All rights reserved.
Impacts of climate change in the Pacific are far reaching and include effects on mental health and wellbeing. Pacific concepts around the interrelation of these global giants are yet to be described. The aim of this study was to seek consensus amongst Pacific mental health and/or climate change experts on key principles underpinning mental health and wellbeing, and climate change, and the intersection of the two, for Pacific peoples. The Delphi method included forming a panel of 70 experts. Two rounds of online questionnaires sought their views on mental health and wellbeing, and climate change and the impact upon Pacific peoples. Of the panel 86% identified with one or more Pacific ethnicities. Six themes emerged, 92% of items reached consensus and 36% reached strong consensus of >95%. Recurring subthemes included culture and spirituality, family and community, connection to ancestors, connection to the environment, resilience, disasters, livelihoods, government, education, workforce, migration and stigma. This is the first time these concepts have been explored and described for, and by Pacific peoples in this format. It is a necessary first step towards development of responses in preparedness of mental health services, in the Pacific region, and Aotearoa New Zealand.
Climate disasters pose a risk to residents’ well-being globally. However, information about the impact of climate disasters among urban and rural residents remains lacking, especially in Indonesia. This study aims to fill the gap by investigating the impact of climate disaster on subjective well-being based on urban and rural typology model. The data were cross-sectional, involving 7110 Indonesian residents who had experienced climate disasters, 3813 from urban areas and 3297 from rural areas. An ordered probit model was employed to estimate the impact of climate disasters on subjective well-being (i.e., happiness and life satisfaction). In general, the empirical results show that climate disasters do not significantly affect the happiness of Indonesian residents, but they significantly and negatively impact their life satisfaction. Further analysis reveals that climate disasters impact urban and rural residents differently. The subjective well-being of rural residents is more severely affected than those living in urban areas. Further estimation also indicated that climate disaster significantly reduces residents’ subjective well-being at the lowest income level for both rural and urban residents. Our finding confirms that rural residents remain the most vulnerable to the impacts of climate change.
This study analyzed the support activities that the Disaster Psychiatric Assistance Team (DPAT) in Japan provided following four previous disasters (a volcanic eruption, a mudslide, a flood, and an earthquake) to identify links between the disaster type and the characteristics of acute stage mental disorders observed. Using Disaster Mental Health Information Support System database records of consultations with patients supported by the DPAT during the survey period from 2013 (when DPAT was launched) to 2016, we performed cross-tabulations and investigated significant differences using chi-squared tests. For expected values less than 5, Fisher’s exact test was performed. Frequently occurring acute-stage symptoms after a disaster include anxiety, sleep problems, mood and affect, and physical symptoms. The affected population characteristics, victim attributes, severity of damage sustained, and evacuation status were the chief factors that influenced acute-stage mental health symptoms. The psychiatric symptoms detected in our study together with the results of diagnoses are important for determining the types of early interventions needed during the acute stage of a disaster. By sharing baseline mental health information, together with disaster-related characteristics highlighted in this study, mental health providers are better able to predict future possible mental disorders and symptoms.
BACKGROUND: Although substantial evidence suggests that high and low temperatures are adversely associated with nonaccidental mortality, few studies have focused on exploring the risks of temperature on external causes of death. OBJECTIVES: We investigated the short-term associations between temperature and external causes of death and four specific categories (suicide, transport, falls, and drowning) in 47 prefectures of Japan from 1979 to 2015. METHODS: We conducted a two-stage meta-regression analysis. First, we performed time-stratified case-crossover analyses with a distributed lag nonlinear model to examine the association between temperature and mortality due to external causes for each prefecture. We then used a multivariate meta-regression model to combine the association estimates across all prefectures in Japan. In addition, we performed stratified analyses for the associations by sex and age. RESULTS: A total of 2,416,707 external causes of death were included in the study. We found a J-shaped exposure-response curve for all external causes of death, in which the risks increased for mild cold temperatures [20th percentile; relative risk (RR) = 1.09 (95% confidence interval [CI]: 1.05,1.12)] and extreme heat [99th percentile; RR = 1.24 (95% CI: 1.20, 1.29)] compared with those for minimum mortality temperature (MMT). However, the shapes of the exposure-response curves varied according to four subcategories. The risks of suicide and transport monotonically increased as temperature increased, with RRs of 1.35 (95% CI: 1.26, 1.45) and 1.60 (95% CI: 1.35, 1.90), respectively, for heat, whereas J- and U-shaped curves were observed for falls and drowning, with RRs of 1.14 (95% CI: 1.03, 1.26) and 1.95 (95% CI: 1.70, 2.23) for heat and 1.13 (95% CI: 1.02, 1.26) and 2.33 (95% CI: 1.89, 2.88) for cold, respectively, compared with those for cause-specific MMTs. The sex- and age-specific associations varied considerably depending on the specific causes. DISCUSSION: Both low and high temperatures may be important drivers of increased risk of external causes of death. We suggest that preventive measures against external causes of death should be considered in adaptation policies. https://doi.org/10.1289/EHP9943.
As climate change accelerates, adaptive social protection programmes are becoming increasingly more popular than conventional social assistance programmes, since they are seen to enhance people’s resilience and well-being outcomes. Despite this upsurge, little is known about the impacts of adaptive programmes on resilience and well-being outcomes as compared to conventional programmes. This paper examines the economic functions that both types of social protection programmes offer through empirical studies in two climate-vulnerable zones in Bangladesh. By operationalising a simplified analytical framework to comprehend subjective resilience, the qualitative data reveal that the adaptive programme is more effective in enhancing beneficiaries’ perceived resilience to climate risks. Regrettably, neither programme is found to contribute much significantly in terms of enabling beneficiaries to achieve the desired well-being outcomes that one might expect to see. The paper offers rich insights into the design components of the programmes, affording an on-the-ground understanding of their implications for resilience and well-being.
Although active transport contributes to environmental and human health, only limited research has been conducted on what makes people participate in active transport in tourism-related contexts. To fill this gap, research was conducted on theoretically conceptualized relationships between pro-social behavior on active transport, air quality, climate change mitigation, and health with a moderator of leisure and tourism activity. In order to collect data, an online survey was conducted targeting Korean cyclists and walkers, and PLS-SEM and deep learning were applied for data analysis. Results revealed that pro-social behavior on active transport has a great effect on perceived air quality. Health is strongly influenced by pursuing climate change mitigation and a strong impact of active transport on health was identified. There were greater effects between pro-social behavior and air quality as well as pro-social behavior and climate change mitigation for those engaged in active transport for tourism than for leisure, while the leisure group has a stronger relationship between pro-social behavior and health than for tourism. The results are valuable for encouraging active transport behavior.
Public health is threatened by air pollution and high temperature, especially in urban areas and areas impacted by climate change. Well-designed urban forms have co-benefits on promoting human health and mediating atmospheric environment-related threats (e.g., high temperature and air pollution). Previous studies overlooked these mediating effects of urban form on suicide mortality. This study used partial least squares modeling and countywide data in Taiwan to identify the crucial influences and pathways of urban environment, socioeconomic status, and diseases on suicide mortality. The model considered the impact of the characteristics of urban form (i.e., urban development intensity, land mix, and urban sprawl), urban industrial status (i.e., industrial level), urban greening (i.e., green coverage), disease (i.e., important diseases morbidity of human immunodeficiency virus [HIV], cerebrovascular disease [CVD], chronic liver disease and cirrhosis [CLDC], nephritis, nephrotic syndrome and nephrosis [NNSN], malignant tumor [MT]), socioeconomic status (i.e., income level and aging population rate), and the atmospheric environment (i.e., air pollution and high temperature) on suicide mortality. Optimizing land mix and minimizing urban development intensity and urban sprawl have been found to reduce suicide mortality. The mediating effect of urban form on suicide mortality originated from air pollution and high temperature, and mediating air pollution was greater than high temperature. Furthermore, industrial level, important diseases (HIV, CVD, CLDC, NNSN, and MT) morbidity, an aging population rate, air pollution, and high temperature were associated with an increase in suicide mortality, whereas green coverage and income level were associated with a reduction in suicide rates. The findings demonstrate that appropriate urban policy and urban planning may lower suicide mortality, be useful strategies for suicide prevention, and be a foundation for building a healthy city. Moreover, this study provides clarity on the complex relationship of suicide and the urban environment while identifying crucial factors.
Anthropogenic climate change poses huge challenges to humanity. The frequency and magnitude of extreme weather is increasing. As more attention turns to disaster preparedness and recovery, it is worth recognising that many communities have a long history of living with the flux of planetary dynamism. They are experienced in negotiating collective well-being with one another and with the earth. Other communities have less experience and know-how and have had to adopt more experimental approaches. In this paper we draw on planetary social thought and critical disaster studies to re-think disaster recovery. We present stories of communities in the Philippines differently negotiating collective well-being in the face of climate uncertainty.
Non-economic loss and damage induced by climate change in the Pacific Islands region has been reported as fears of cultural loss, deterioration of vital ecosystem services, and dislocation from ancestral lands, among others. This paper undertakes an in-depth systematic review of literature from the frontlines of the Pacific Islands to ascertain the complexities of non-economic loss and damage from climate change. We synthesise knowledge to date on different but inter-connected categories of non-economic loss and damage, namely: human mobility and territory, cultural heritage and Indigenous knowledge, life and health, biodiversity and ecosystem services, and sense of place and social cohesion. Identifying gaps and possibilities for future research agendas is presented. Synthesising knowledge to date and identifying remaining gaps about non-economic loss and damage is an important step in taking stock of what we already know and fostering action and support for addressing loss and damage in the years to come.
Air pollution has negative impact on health status of the population. Several previous studies have been assessed the short-term and/or long-term effect of air pollutants on different diseases. An important sign of increasing the number of new people suffering from a disease or worsening the disease among the persons is increasing the hospitalization rate due to the disease. Increasing the incidence rate or severity of mental disorders which leads to patient hospitalization due to these types of diseases have negative impacts on the socio-economic aspects on the affected countries. Therefore, predicting the hospitalization rate due to mental disorders in advance may be helpful for health institutions to be prepared for dealing with these situations. Thus, the main aim of this study is proposing a novel stacked ensemble of Deep Convolutional neural network model and long short-term memory model (SEDCMLM) to predict the number of hospitalizations due to psychological disorders from the air pollutants and weather condition descriptors. This study considers all mental disorders included in International Statistical Classification of Diseases and Related Health Problems (ICD-10). Previous studies have shown that weather descriptors are highly correlated with air pollution. Therefore, we consider both of them as input variables in this study. Input variables include air pollutant indices and weather condition descriptors gathered in range of March 21, 2014 to 1/18/2017 from Tehran Air Quality Control Company (AQCC) and Meteorological Organization of Iran, respectively. The experimental results show that SEDCMLM outperforms the compared models for psychological hospitalization prediction and it leads to desirable performance with Root Mean Square Error (RMSE) of 1.62, Mean Absolute Error (MAE) of 1.48 and Mean R-2 of 0.91. The short-term effect of air pollution on the number of admissions due to mental disorders are investigated for 1 to 10 previous days. It is shown that the best performance of the prediction models is obtained while considering data of 2e4 previous days. Moreover, considering air pollutants, weather descriptors and the number of psychological hospitalization in the previous days can lead to the best performance for predicting the number of psychological patient admissions in the current day. According to the experimental results, air pollutants are good predictors for number of patient admissions due to mental disorders per day Therefore, it is recommended to use policies for reducing the level of air pollutants. (c) 2020 Elsevier Ltd. All rights reserved.
Communities throughout the Pacific Islands region have experienced, and will continue to experience, extensive non-economic loss and damage (NELD) from climate change. Assessments of loss and damage, however, often fall short on their coverage of these non-economic dimensions, which can distort our understanding of climate change impacts, discount the experiences of some and skew future decision-making. This paper explores how stakeholders in the Pacific Islands understand NELD and what they perceive to be the best ways of responding to it. An open-ended questionnaire was used to collect qualitative and quantitative data from representatives from governments, donors and development partners, civil society, intergovernmental organisations, and relevant others. This study found that NELD in the Pacific Islands is understood, perceived and experienced through the lens of intangible values, identity and cultural landscapes, and this is encapsulated by a typology with eight interconnected core dimensions. These eight dimensions include: health and wellbeing, ways of being, future ways of being, cultural sites and sacred places, Indigenous and local knowledge, life sustaining tools, biodiversity and ecosystem services, and connection to land and sea. NELD is complex, entangled and interconnected, thereby significantly undermining entire socio-ecological systems. Moving forward, responding to NELD in the Pacific Islands region will require a comprehensive approach that protects, conserves and restores complex socio-ecological systems, and provides opportunities to work through loss and damage by means of education and training, safeguarding knowledge systems, community activities, cultural connection and maintenance, and strong relationships with land and sea.
Australians have experienced repetitive exposure to climate change adversity (either in-person or through televised exposure from media and internet sources). As these events become more prevalent and severe, developing, and implementing strategies to enhance emotional resilience at individual, community, and government levels is beneficial. This literature review examines one way of addressing this issue: enhancement of societal emotional resilience capabilities that can minimize negative impacts of climate change adversity upon emotional wellbeing. The study also offers an initial exploration of climate change adversity and emotional resilience. A systematic literature review identified key research themes. Subsequent findings identified policy and framework recommendations aimed at supporting emotional resilience in communities. Such strategies should focus on community preparedness through needs-based assessments and community engagement, fostering knowledge-building pathways and ongoing collaboration among system levels to address a diversity of community needs. These systematic approaches would ensure the accessibility and appropriateness of relevant supports by establishing frameworks that are regularly monitored, evaluated, and promoted.
Being intrinsically associated with death-related themes (e.g. decay, destruction, lack of control, chaos), communicating climate change risks may elicit thoughts in an audience about their own mortality – potentially invoking terror management responses. This study examined individual differences in death-thought accessibility (DTA) amongst Australian university students (N=241) after exposure to information about climate change impacts, to predict climate change risk perceptions. It was posited that information about the impacts of climate change would lead to worldview defence (a terror management strategy) via increasing death-related thoughts. Although climate change salience did not invoke DTA, there was evidence that choosing not to complete word-fragments in a death-related manner reflected a high death-defensive response, rather than low-DTA. Compared with a control condition, climate change salience participants’ risk perceptions shifted liberally. The function of death-related thoughts depended on the individual’s climate change beliefs. Climate-deniers with high-DTA in the climate change salience condition showed greater risk perceptions compared to those with high-DTA in the control condition. Risk perceptions did not change as a function of DTA amongst climate-acceptors. A general implication was that climate change communications, may not produce counterproductive terror management outcomes as has been previously hypothesized. Rather they may motivate more realistic attitudes, such as perceiving climate change as high-risk, even amongst climate-deniers. From a policy perspective, to maximise acceptance, climate change information may benefit from being presented within frameworks that support individuals important personal worldviews.
The process of learning about climate change is not simply cognitive. It is also an emotional encounter that may have enduring effects. To date, little research has attended to the emotional significance of childhood learning experiences of climate change in adult lives and in social responses to climate change. We report a qualitative study exploring the variety, complexity, and the post-school significance of affective experiences of climate change schooling. We interviewed 21 young adults (18-24 years) in Tasmania, Australia, with diverse educational backgrounds and diverse levels of interest in and opinions about climate change. Applying an interpretivist framework, we analysed the tangled and interrelated emotions evident in participant reflections on educational encounters with climate change. Three overarching themes were identified: ‘stripped of power’, ‘stranded by the generation gap’ and ‘daunted by the future’. In contrast to discourses of education as empowering, a majority of participants (n = 16) told of feeling disempowered by their educational encounters with climate change. They described being overwhelmed by an experience of limited agency and power. Participants also identified a generational gap that left them feeling abandoned by older adults, with associated feelings of anger and betrayal. Finally, affective experience of climate change schooling had ongoing significance for participants as they sought to make life choices in the shadow of a frightening future. These findings provide insight into the interaction of facts and feelings in public engagements with climate change. A lack of integration of cognitive and affective experience in climate change schooling may have lasting effects in adult attitudes and behaviours, and related social dynamics of distrust and division, related to this issue. In this study, young adult participants recounted childhood experiences of being powerless, betrayed and afraid in learning about climate change as significant formative encounters in their ongoing understanding of climate change.
As human activities have destabilised life on Earth, a new geological era is upon us. While there is a myriad of challenges that have emerged because of such human-driven planetary changes, one area of investigation that requires ongoing scholarly attention and scientific debate is the emotions of the Anthropocene. The emotional, mental, and psychological burdens induced by rapid and unprecedented change must be understood to better reflect the experiences of people around the globe and to initiate conversations about how emotions may be used for transformative change and effective politics. This paper aims to provide insights into the types of emotions that are emerging in Oceania as the Anthropocene unfolds. To do this, we draw on several data sets: questionnaire results with visitors of Mt Barney Lodge in the World Heritage Gondwana area in Queensland, Australia; another questionnaire with Pacific Island “experts” engaged in climate change, development, and disaster risk management work; interviews with locals living in the Cook Islands; and various spoken, written, and visual art from the Pacific. Bringing these data sets together allows us to explore a diversity of experiences, perspectives, and emotional responses to the Anthropocene from participants across Oceania. We found that acute and slow-onset weather events, experiences of direct loss and change, a perceived lack of agency or control over futures, and a sense of injustice triggered emotions including fear, stress, anxiety, exhaustion, sadness, grief, anger, frustration, helplessness, worry, but also empowerment. These results are critical for the first step of acknowledging and naming the emotions that are emerging in Oceania, such that they can then be worked through, and may be used for transformative change, effective politics, and agency over futures.
Climate change and environmental degradation caused by human activities are having an irrefutable impact on human health, particularly mental health. People working in the environment sector are confronted with these impacts daily. This exploratory study was conducted as a response to concern in the sector about rising levels of worry and distress, and a need for organizational knowledge about effective workplace mental health strategies. Using evidenced-based frameworks for workplace mental health and wellbeing, the study focused on the relationship between climate change, environmental degradation and mental health issues for this sector. This Australian-based exploratory qualitative study was guided by participatory research approaches. Maximum variation and criterion sampling strategies were applied to engage environmental sector senior managers (n = 8) in individual/paired interviews, followed by online focus group sessions with frontline employees (n = 9). Qualitative thematic analysis techniques were used in an iterative process, combining inductive and deductive strategies. Data was triangulated and interpretation was finalized with reference to literature and a workplace mental health promotion framework. Interview data provided new perspectives on the interconnectivity between risk and protective factors for mental health. Workers were motivated by commitment and values to continue their work despite experiencing increasing levels of trauma, ecological grief, and stress due to overwork and ecological and climate change crises. The findings highlight the need for integrated health promotion approaches that acknowledge the complex interactions between risk and supportive factors that influence mental health in this sector.
Concerns about the effects of climate change are mainstream, and the climate crisis might have greater psychological impact on younger people. We hypothesise that climate concern will have detrimental links with psychological wellbeing over time, and that this association will be more pronounced among younger adults. We test our pre-registered predictions using two waves of an annual national probability panel study-the New Zealand Attitudes and Values Survey (N = 13,453). Cross-lagged models examining effects within the same individuals over time indicated that climate concern predicted a small residual increase in psychological distress, but not in life satisfaction, one year later. However, there was no evidence that the associations varied across age. These longitudinal findings indicate a novel link between climate concern and psychological distress, which is apparent across the adult lifespan.
Recent super-typhoons and torrential rains triggered by global warming have had disproportionately large effects on medically vulnerable people in Japan. This study aimed to identify factors associated with intention to evacuate to the nearest public shelter among family caregivers of pediatric patients receiving home medical care. The study included family caregivers of these patients from the Department of Pediatrics, Fukuoka University Hospital, Japan, including family caregivers of young adults with special healthcare needs. An original questionnaire was prepared drawing on previous studies and used for an interview survey. Overall, 57 individuals provided valid data and were included in the analysis. Factors associated with evacuation intention were non-use of a home ventilator (odds ratio [OR] 3.99, 95% confidence interval [CI]: 1.13-14.03) and not having made arrangements to use a non-public shelter (OR 7.29 95% CI: 1.62-32.88). This means that those who use mechanical ventilation or have secured alternative places to go if they need to evacuate their homes may not use the nearest public shelter in a disaster. We recommend that policy makers consider the use of mechanical ventilation and the availability of non-public shelters as predictors of evacuation behavior when considering disaster preparedness for these patients.
OBJECTIVE: This paper correlated the Meniere attack with meteorological parameters i.e. atmospheric pressure, temperature, relative humidity and rainfall, to investigate which parameters that trigger the Meniere attack. METHODS: During the past three years, totally 283 (2015), 351 (2016) and 319 (2017) patients with Meniere’s disease (MD) were encountered at a clinic of the university hospital, accounting for 13%, 17% and 16% incidence in relation to overall annual neurotological cases, respectively. The onset of Meniere attack was then correlated with meteorological parameters. RESULTS: The mean seasonal incidence of Meniere attack in relation to overall seasonal neurotological cases in 2015-2017 were 14.8 ± 2.8% (spring), 17.5 ± 2.2% (summer), 16.0 ± 1.8 % (autumn) and 12.8 ± 2.0% (winter), indicating that summer season had a higher incidence of Meniere attacks than winter season. Onset of Meniere attacks correlated significantly with the atmospheric pressure (r = -0.4484, p = 0.0061) and temperature (r = 0.4736, p = 0.0035), and the atmospheric pressure was highly negatively correlated with the temperature (r = -0.9421, p < 0.0001). In contrast, no correlation was identified between the onset of Meniere attacks and relative humidity or rainfall. The atmospheric pressure in the same month with typhoon compared with that without typhoon revealed a median reduction of 13.1 hectopascal. CONCLUSION: Atmospheric pressure and temperature are correlated with the onset of Meniere attack. Summer season has a higher incidence of Meniere attack than winter season, likely because low atmospheric pressure in summer may aggravate endolymphatic hydrops, especially when accompanied by typhoons in the northwest Pacific region.
As the fifth-largest super tropical cyclone landed on Mainland China in history, typhoon Lekima occurred in August 2019 caused at least 71 deaths, 14 million disaster victims, and cost RMB 65.37 billion in damages. Here we use six latest GPM-based near-real-time satellite precipitation estimates (IMERG-Early, IMERG-Late, GSMaP-NOW, GSMaP-NRT, GSMaP-MVK, and CMORPH-RT) to quantify the spatiotemporal pattern of typhoon rainfall and meanwhile the potentials of these satellite precipitation products in detecting heavy storms are systematically investigated. Retrieval results indicate that the expansive rain belt of typhoon Lekima brought approximately 93.2 billion m(3) water in total onto the Chinese mainland during the typhoon period and the precipitation process maintained higher intensities on the earlier two days (August 10 and 11). Specifically, it is found that a “precipitation window” with higher precipitation intensities appeared between 5:00 a.m. and 10:00 a.m., implying that a greater probability of rainstorms may occur during this period. Moreover, at the storm center around the Dongying City of Shandong Province, the dual-frequency precipitation radar of GPM (GPM-DPR) successfully revealed the existence of precipitation columns with the peak value of 121 mm.h(-1), which seem to play a key role in the regional torrential rainfall. Additionally, our evaluation shows IMERG-Late and CMORPH-RT perform better under higher rain rates relative to other satellite precipitation estimates. This can be primarily attributed to their sufficient inputs from PMW sensors and, respectively, the former benefits well from both DPR and GMI while the latter significantly reduces its IR inputs. This study illustrates an example of monitoring the extreme heavy precipitation storms by the latest GPM-based near-real-time satellite precipitation estimates and highlights future possible improvements for algorithm developers.
OBJECTIVES: To examine the association between the number of visits to the emergency department (ED) by children for night-time headaches and exposure to multifaceted factors, such as meteorological conditions and air pollution. DESIGN: We conducted a clinical observational time-series analysis study. SETTING: We reviewed consecutive patients younger than 16 years of age at the primary ED centre in Kobe city, Japan, during the night shift (19:30-7:00 hours) between 1 January 2011 and 31 December 2019. PARTICIPANTS: In total, 265 191 children visited the ED; 822 presented with headache during the study period. PRIMARY OUTCOME MEASURES: We investigated the effects of meteorological factors and air pollutants by multivariate analysis of Poisson regression estimates. A subanalysis included the relationship between the number of patients with night-time headaches and the above factors by sex. Furthermore, the effect of typhoon landing on patient visits for headache was also analysed. Headache was not classified because examinations were performed by general paediatricians (non-specialists). RESULTS: The number of patients with night-time headaches displayed distinct seasonal changes, with peaks during the summer. Multivariate analysis of Poisson regression estimates revealed a significant positive relationship between the number of patients for headache and mean temperature. Subanalysis by sex indicated a positive relationship between the number of patients with headache and mean temperature in both sexes; however, it was significant only for females. No relationship was found between the number of patients with headache and air pollution. There was no change in the number of patients for night-time headaches 3 days before and after typhoon landing. CONCLUSIONS: High temperature is the main factor for visiting ED for night-time headaches among children in Kobe city. Our results suggest that preventive measures against night-time headaches may be possible by reducing time spent outside during summer.
To derive deeper insight into the dynamic thermal comfort demands of the elderly in response to the seasonal climate shift, 213 people aged above 60 years in nursing homes were surveyed in a long-term field investigation conducted in Xi’an, China. A subjective questionnaire of thermal comfort and objective physical environment tests was administered, and 834 valid questionnaires were collected. Human thermal responses to seasonal climate shift, and their correlations with indoor operative temperatures were analyzed. Seasonal and yearly adaptive thermal comfort models for the elderly were then developed. Results show that clothing regulation during the transition season was most sensitive to temperature changes. Neutral temperatures during winter, transition season, and summer were 19.4 ?, 22.6 ?, and 24.1 ?, respectively. The acceptable temperature ranges that 80% and 90% respondents accepted were 14.9?-30.4 ? and 17.7?-27.7 ?, respectively. Nearly half the older respondents expected indoor temperature to remain unchanged during all seasons, but the percentage of respondents who wanted warmer or cooler indoor temperatures varied in different seasons. The yearly adaptive comfort model for elderly differed from models in ASHRAE 55 and EN 15251, as well as the models for elderly in Shanghai and young people in Xi’an. The results indicate that elderly in Xi’an actively adapt to the indoor thermal environment through behavioral adjustment. Moreover, they have higher acceptability and lower psychological expectations on the thermal environment. The model established in this study may have some limitations for the sample size, but can serve as references while designing comfortable and healthy indoor thermal environments for nursing homes.
WHAT IS ALREADY KNOWN ABOUT THIS TOPIC? An increasing number of studies have projected temperature-related mortality, but few consider the change of population’s adaptability to future temperature and mortality burden from cold and heat effects. WHAT IS ADDED BY THIS REPORT? This study offers a comprehensive characterization of human adaptability and excess mortality burden of temperature across various regions of China. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE? The temperature-related excess mortality was projected to increase in the 2050s and decrease in the 2080s. Heat adaptability was projected to increase in the future, but along with the rising temperatures, the heat-related excess mortality continuously rose, except for the low-speed rising scenario. Although the excess mortality of cold was projected to decrease in the nearer future, it might not keep declining in the long run, due to the decreasing cold-adaptability, which deserves more attention.
China, with its growing population and economic development, faces increasing risks to health from climate change, but also opportunities to address these risks and protect health for generations to come. Without a timely and adequate response, climate change will impact lives and livelihoods at an accelerated rate. In 2020, the Lancet Countdown Regional Centre in Asia, led by Tsinghua University, built on the work of the global Lancet Countdown and began its assessment of the health profile of climate change in China with the aim of triggering rapid and health-responsive actions. This 2021 report is the first annual update, presenting 25 indicators within five domains: climate change impacts, exposures, and vulnerability; adaptation, planning, and resilience for health; mitigation actions and health co-benefits; economics and finance; and public and political engagement. The report represents the contributions of 88 experts from 25 leading institutions in, and outside of, China. From 2020 to 2021, five new indicators have been added and methods have been improved for many indicators. Where possible, the indicator results are presented at national and provincial levels to facilitate local understanding and policy making. In a year marked by COVID-19, this report also endeavours to reflect on China’s pathway for a green recovery, ensuring it aligns with the carbon neutrality goal, for the health of the current and future generations.
Climate change is almost unanimously perceived to be one of the greatest environmental and developmental challenges of this century. Implementing climate change response requires not just huge and prudent utilization of financial resources, but also highly efficient financing institutions and systems especially in developing countries where underlying development issues such as poverty, health, etc. exist. This paper attempts to evaluate the operationalization of the Indonesian Climate Change Trust Fund (ICCTF) as a climate financing prototype in terms of fund mobilization, nature of projects, equity and inclusion, alignment and mainstreaming. This study was conducted through review of relevant and recent literature on climate change governance and financing, supported with information retrieved from relevant official documents as well as interviews of key persons. Our study found the ICCTF most effective in alignment with national development plans and Sustainable Development Goals (SDGs). It has implemented climate change adaptation programmes with the principles of equity and inclusion of various stakeholders. The ICCTF has however struggled to efficiently mobilize funds owing largely to technical ambiguities especially in its legal and institutional frameworks, it therefore yet to be utilized to its maximum potentials.
As climate change increasingly interacts with socioeconomic development factors to contribute to migration, understanding how climate and migration can coalesce to exacerbate health risks is urgent. Our study examines how migration influences the health of Mekong Delta migrants in Ho Chi Minh City and explores the role of weather and climate variability in the migration experience and health status of migrants before and after migration. Using a qualitative approach, we conducted 43 in-depth semi-structured interviews. We found migration is a strategy to cope with livelihood insecurity in the Mekong Delta. Livelihood trade-offs in Ho Chi Minh City produce precarious living and working conditions contributing to changes in the self-reported health status of migrants after migration, while climate variability is a threat multiplier for migrants’ health and livelihoods in both the Mekong Delta region and Ho Chi Minh City. Our findings illustrate the intersections of climate, migration and health where migrants make strategic health trade-offs to pursue better livelihoods, whilst weather and climate variability exacerbate the health risks and livelihood insecurity of migrants. This study supports the need to implement policies that reduce trade-offs, strengthen migrants’ adaptive capacity, and address underlying socioeconomic and political factors shaping vulnerability across the rural-urban continuum.
Support for rural livelihoods to adapt to climate change is a top policy priority around the world. We advance the concept of ‘self-organized adaptation’ to analyze how long-term pathways of transformation come about as the organic outcome of farmers’ incremental and continuous responses to climate and other challenges. Through an analysis of four decades’ responses to changing climate conditions in an agricultural system of the Indian Himalayas, we show how several key policy interventions-institutional support for the dissemination of agricultural knowledge, investments in infrastructure, and strengthening of market linkages-have produced favorable conditions for successful, long-term self-organized adaptation to climate change. This has led to the transformation of an agricultural system specialized in apple production to one with a great diversity of fruit, vegetable, and food grain crops. We find that farmers growing these crops cluster into five distinct agricultural portfolios that reflect the constraints and opportunities that different farmers face, and which are patterned by interaction with rural institutions and household social networks. We highlight the role of distributed decision-making in shaping broader trajectories of systemic transformation, and we argue for the need to move beyond pre-defined climate interventions toward the identification of policy mechanisms that can support more effective self-organization over the long-term.
Climate change impacts the urban environment and landscape changes worldwide. To understand how South Korean citizens perceive these changes and what they expect for the future landscape, this study analyzed urban residents’ perceptions through text mining. Data related to the keywords “future landscape”, “future environment”, “well-being”, and “climate change” were collected from July 2020 to July 2021 from the Korean search engines Naver, Daum, and Google using the tool TEXTOM. Keywords, importance, and related words were derived through word frequency, TF-IDF, and N-gram analysis. CONCOR analysis was used to derive the meaning and relevance of the words. In “future landscape”, results showed a high frequency of the words “complex”, “apartment”, “future value”, and “sale”, and the connection strength was higher between “complex”, “landscape”, and “future value”. In “future environment”, “eco-friendly” showed the highest word frequency, and the words “New Deal”, “hydrogen” and “mobility” showed a high frequency and correlation. For “well-being”, “Green Cross” (a well-being-related company) showed the highest frequency, and the connection strength between satisfaction indexes was high. For “climate change”, “response” showed the highest frequency, and the connection strength between “carbon-neutral”, “UN-convention”, and “plan-establishment” was high. These results showed that South Koreans associate landscaping with the value of apartment complexes, that they expect solutions to mitigate climate change impacts with green and eco-friendly strategies, and lastly that well-being-related companies are receiving a great deal of public attention. Thus, it is expected that the results will help plan effective landscaping approaches to respond to environmental changes.
From the microperspective, climate change restricts human life in many aspects, and it affects the regional economic system from the macroperspective. The paper presents an inoperability input-output model (IIM) that is an extension approach of the Leontief input-output model. The IIM is able to provide a feasible methodology for measuring the impact of vulnerable economic factors on the whole economic system and identifying the key adaptation trajectory of the economic system. The IIM is applied in Tianjin to explore its dilemmas facing the increased demand for electricity, water, and public health service sectors under the RCP2.5, RCP4.5, and RCP8.5 climate scenarios. The results indicated that the inoperability ranking of all economic sectors is the same under the three climate scenarios. The key adaptation trajectory in Tianjin is S40, S27, S25, S17, S12, S02, S21, S16, S09, S24, S29, S33, S19, S13, and S15 sector in order. The costs required by the key adaptation trajectory to adapt to climate change account for more than 90% of that required by the whole economic system. These results can be helpful for policy-makers to prioritize sectors in terms of climate adaptation and understand the efficacy of climate change risk mitigation strategies.
The spatial form of a village can affect human comfort by changing microclimatic conditions, which in turn can affect the health of residents. The architectural forms of traditional Jiangnan villages have been adapted to local environmental and landscape characteristics, creating optimal thermal comfort conditions. However, these traditional forms are being lost in China’s rapid drive toward urbanization and modernization, resulting in built environments that offer far less thermal comfort. To explore the elements of traditional adaptation, we conducted microclimate research in Shecun Village, Nanjing, and examined how the form of the surrounding landscape influenced the spatial layout of village streets and public spaces. Air temperature, relative humidity, and average wind speed were measured at locations around the village and were compared to similar data collected from a meteorological station in urban Nanjing. Based on these data, ENVI-met software was used to create a numerical simulation to demonstrate the relationship between the spatial forms of traditional Jiangnan villages and local microclimate factors. We found that the average physiological equivalent temperature (PET) values of all measurement points in the village in the summer were between 42? and 48?, and those in the winter were between 17? and 20?. In general, the thermal comfort in the winter was better than that in the summer, and the overall middle-level climate environment of the village in the winter and summer was comfortable. The PET values at different points followed the order of building complex space (MP1, 3 and 5) > vegetation space (MP2) > water space (MP4). The PET value was positively correlated with comfort sensation in winter, but this value had the opposite correlation in the summer. The average value of PET at the vegetation space was 3.18? higher than that at the water space in the winter, which showed that the water body was beneficial for thermal comfort in the summer, but was the opposite in the winter. These results showed that the traditional village site selection in accordance with local conditions, made use of the surrounding landscape environment to provide villages with a more comfortable and pleasant living environment. This information provides a useful reference for the design of modern public spaces.
BACKGROUND: Worry about climate change may be associated with poorer mental health but also with greater political engagement. We determined trajectories of climate change-related worry over adolescence and whether these were associated with depression symptoms and greater engagement with news and politics in late adolescence. METHODS: At ages 10-11, 12-13, 16-17 and 18-19 years, adolescents participating in the Kindergarten cohort of the Longitudinal Study of Australian Children rated their worry about climate change. At age 18-19 years, participants reported on depression symptoms and engagement with news and politics. Latent profile analysis determined trajectories of climate change-related worry across all time points (N=2244). Linear regression analyses examined the association between trajectories and outcomes at 18-19 years. RESULTS: Thirteen per cent (n=290) of adolescents had high persistent worry. The largest proportions had moderate (n=559, 24.9%) or increasing worry (n=546, 24.3%), followed by persistent low worry (n=376, 16.8%), slightly decreasing worry (n=297, 13.2%) and steeply decreasing worry (n=176, 7.8%). Adolescents with high persistent worry had higher depression symptoms at age 18-19 years compared to the moderate group, while those with increasing worry did not. The high persistent and increasing worry groups reported greater engagement with news and politics across several measures. CONCLUSION: This is the first study to track climate-related worry and outcomes in young people across adolescence. A substantial number of Australian adolescents experience high or increasing worry about climate change, which is associated with greater societal engagement.
Scientists caution against ignoring human-induced climate change and related health repercussions, with a growing body of literature highlighting the mental health effects of climate change and the importance of understanding coping and adaptation strategies. Less is known, however, about sustainable personal practices fortifying mental health in the context of climate change. The present study sought to investigate how long-term yoga practitioners (yoga therapists or yoga teachers) in Australia with a lived experience of climate change-related events are coping and adapting. The aim was to better understand participants’ reports of climate change-related experiences and how yoga influences their mental health and choices in the face of climate change. Eleven in-depth telephone interviews were conducted and analyzed using an interpretive phenomenological methodology. Participants reported that their ongoing relationship with yoga influences how they cope with climate change-related stressors and their being-in-the-world, and how concern for all life bolsters their responses to climate change. The results illustrate the part yoga may play in supporting long-term practitioners to prepare for, cope with, and respond to climate change events and impacts. Offering inclusive, interdisciplinary yoga therapy and community-based networks fostering ethical living and response flexibility may prove beneficial not only for the mental health and coping ability of participants, but for the planet.
(1) Background: In Australia, young people are one of the most vulnerable populations to the mental health impacts of climate change. The aim of this article was to explore mental health promotion issues related to climate change for young people in Australia. (2) Methods: An exploratory mixed-method approach, co-led by young people, was used to engage young people living in Australia aged 18-24 years in semi-structured interviews (N = 14) and an online survey (N = 46). Data were analysed thematically and with descriptive statistics. (3) Results: Findings indicated that negative impacts included worry, eco-anxiety, stress, hopelessness/powerlessness and feelings of not having a voice. Several mediating factors, in particular social media engagement, highlighted the duality of mental health impacts for young people’s mental health. Positive impacts of climate action included feeling optimistic and in control. (4) Conclusions: This exploratory study contributes to an emerging field of public health research on young people’s mental health in a climate-impacted Australia. Climate change is a significant concern for young people, and it can negatively affect their mental health. The findings can inform the design of public health interventions that raise awareness of climate change-related mental health issues among young people and promote their participation in nature-based interventions, climate action and empowering social media engagement.
OBJECTIVE: Prior to coronavirus disease (COVID-19), many Australians experienced extreme bushfires, droughts, and floods. A history of experiencing these events might be a risk factor for increased psychological distress during COVID-19. This study aimed to provide insight into the mental health of Australian workers during the initial COVID-19 outbreak, with an additional focus on whether previous disaster exposure and impact from that disaster is a risk factor for increased psychological distress. METHODS: A snowball recruitment strategy was used. Participants (n = 596) completed an online survey, which included the Depression Anxiety Stress Scales-21, and questions related to mental health and disaster exposure. RESULTS: Overall, 19.2%, 13.4%, and 16.8% of participants were experiencing moderate to extremely severe depression, anxiety, and stress symptoms, respectively. Multiple regression found that higher depression, anxiety, and stress symptoms were associated with a pre-existing mental health diagnosis; only higher stress symptoms were associated with having experienced a disaster, with impact, in addition to COVID-19. CONCLUSIONS: People who have experienced impact from an additional disaster might need additional support to protect their mental health during COVID-19. A focus on the cumulative mental health impacts of multiple disasters and the implications for organizational communities where recovery work is undertaken, such as schools and workplaces, is needed.
BACKGROUND: Evidence of immediate and delayed effects of climatic drivers on hospital admissions for schizophrenia is limited and inconsistent. We aimed to assess the association between climatic factors and daily hospital admissions for schizophrenia in Queensland, Australia. METHODS: Daily hospital admissions for schizophrenia from January 1, 1996 to December 31, 2015 in all private and public hospitals of Queensland were obtained from Queensland Health. The association between climatic factors and hospital admissions for schizophrenia were analysed using Generalised Linear Models with Poisson distribution (GLM) and Distributed Lag non-linear Models (DLNM) across different climatic zones. RESULTS: In South East Queensland, only daily mean temperature showed an immediate negative effect on schizophrenia admissions (RR 0.93, 95%CI 0.90-0.98, p value < 0.001). For other regions, the adverse effect of temperature on hospital admissions was not significant, however, relative humidity (North: RR 1.01, 95%CI 1.00-1.02, p = 0.05) and air pressure (North: RR 1.03, 95%CI 1.00-1.05, p = 0.04; South West: RR 1.01, 95%CI 1.00-1.02, p = 0.05) had an immediate and positive effect on hospital admissions. Moreover, climatic factors had some delayed effects on schizophrenia admissions in different regions of Queensland, i.e. temperature over 0-4 lag days (South East: RR 0.97, 95%CI 0.94-0.98, p = 0.05; South West: RR 0.96, 95%CI 0.94-0.98, p = 0.01), relative humidity over 0-7 lag days (North: RR 0.95, 95%CI 0.92-0.98, p = 0.01; Central: RR 1.02, 95%CI 1.00-1.03, p = 0.05) and rainfall over 0-21 lag days (North: RR 1.03, 95%CI 1.01-1.04, p = 0.01). Meta-analysis showed significant pooled delayed effects of temperature (0-15 days lag: RR 0.95, 95% CI 0.93-0.98, p value < 0.001), relative humidity (0-7 days: RR 0.96, 95%CI 0.92-0.99, p < 0.001); rainfall (0-21 lag days: RR 1.03, 95%CI 1.01-1.04, p < 0.001) and air pressure (0-7 days lag: RR 1.02, 95%CI 1.00-1.04, p < 0.001) on schizophrenia admissions in Queensland. DISCUSSION: As this is the largest study from Australia and also internationally to extensively examine both short term and delayed association between climatic factors and daily admissions for schizophrenia, the results of the study indicate that climate plays an important role in the sudden exacerbation of acute episodes of schizophrenia. Thus, preventive measures could be taken to reduce the severity of symptoms as well as hospital admissions due to schizophrenia during vulnerable periods.
Epidemiological studies have revealed the associations of air pollutants and meteorological factors with a range of mental health conditions. However, little is known about local explanations and global understanding on the importance and effect of input features in the complex system of environmental stressors – mental disorders (MDs), especially for exposure to air pollution mixture. In this study, we combined deep learning neural networks (DLNNs) with SHapley Additive exPlanation (SHAP) to predict the illness risk of MDs on the population level, and then provided explanations for risk factors. The modeling system, which was trained on day-by-day hospital outpatient visits of two major hospitals in Nanjing, China from 2013/07/01 through 2019/02/28, visualized the time-varying prediction, contributing factors, and interaction effects of informative features. Our results suggested that NO(2), SO(2), and CO made outstanding contributions in magnitude of feature attributions under circumstances of mixed air pollutants. In particular, NO(2) at high concentration level was associated with an increase in illness risk of MDs, and the maximum and mean absolute SHAP value were approximated to 10 and 2 as a local and global measure of feature importance, respectively. It presented a marginally antagonistic effect for two pairs of gaseous pollutants, i.e., NO(2) vs. SO(2) and CO vs. NO(2). In contrast, CO and SO(2) displayed the opposite direction of feature effects to the rise of observed concentrations, but an apparent synergistic effect was obviously captured. The primary risk factors driving a sharp increase in acute attack or exacerbation of MDs were also identified by depicting prediction paths of time-series samples. We believe that the significance of coupling accurate predictions from DLNNs with interpretable explanations of why a prediction is completed has broad applicability throughout the field of environmental health.
Since recent climate change has caused more natural disasters (NDs) than ever before, there is a worldwide concern that this could have both short-term and long-term economic and health consequences. This is perhaps the first attempt to explore the effects of natural capital (NC) and NDs on the human health and wellbeing of China over the period 1993-2020. The study has compiled data from World Bank, World Value Survey, UNDP, EM-DAT, and IMF for analysis. The empirical analysis is done by using the autoregressive distributed lag model. Empirical results prove that NC has a positive and significant effect on happiness, health, and human wellbeing in the long run. The results also show that NDs significantly reduce happiness and human wellbeing in the long run. The results recommend some important policy implications.
Coastal hazards, particularly cyclones, floods, erosion and storm surges, are emerging as a cause for major concern in the coastal regions of Vijayawada, Andhra Pradesh, India. Serious coastal disaster events have become more common in recent decades, triggering substantial destruction to the low-lying coastal areas and a high death toll. Further, women living in informal and slum housing along the Vijayawada coastline of Andhra Pradesh (CAP), India, suffer from multiple social, cultural and economic inequalities as well. These conditions accelerate and worsen women’s vulnerability among this coastal population. The existing literature demonstrates these communities’ susceptibility to diverse coastal disasters but fails to offer gender-specific vulnerability in urban informal housing in the Vijayawada area. Accordingly, the current study developed a novel gender-specific Women’s Coastal Vulnerability Index (WCVI) to assess the impact of coastal disasters on women and their preparedness in Vijayawada. Field data was collected from over 300 women through surveys (2) and workshops (2) between November 2018 and June 2019, and Arc-GIS tools were used to generate vulnerability maps. Results show that women are more vulnerable than men, with a higher death rate during coastal disaster strikes. The current study also found that gender-specific traditional wear is one of the main factors for this specific vulnerability in this area. Furthermore, the majority of the women tend to be located at home to care for the elders and children, and this is associated with more fatalities during disaster events. Homes, particularly for the urban poor, are typically very small and located in narrow and restricted sites, which are a barrier for women to escape from unsafe residential areas during disasters. Overall, the research reveals that most of the coastal disaster events had a disproportionately negative impact on women. The results from this present study offer valuable information to aid evidence-based policy- and decision-makers to improve existing or generate innovative policies to save women’s lives and improve their livelihood in coastal areas.
Floods due to heavy rains or typhoons are frequent annual hazards in Japan. This study aims to reduce disaster fatalities and contribute to disaster risk reduction. This retrospective observational study analyzed fatalities caused by heavy rains or typhoons. In Japan, 578 fatalities, related to seven occurrences of heavy rains and 16 typhoons, occurred between 2016 and 2020. Moreover, 13,195 houses collapsed due to hazards. Furthermore, 334 (73.2%) of the 456 fatalities were > 60 years old. Heavy rains caused more local area destruction due to floods and landslides than typhoons although wind- and disaster-related mortalities were found to be caused by typhoons. Human damage was eminent in older people because of their vulnerabilities and possibly dangerous behavior. Many fatalities were due to floods (46.9%) and landslides (44.1%). Indoor and outdoor mortalities due to heavy rains or typhoons were 157 (55.9%) and 124 (44.1%), respectively, and 24 (21.8%) of 124 outdoor mortalities occurred in vehicles. The number of recent flood mortalities in Japan correlates with the number of destroyed houses. Analyzing the victim’s locations in the 2020 Kumamoto Heavy Rain using hazard and inundation maps suggested the difficulty of ensuring the safety of people living in dangerous areas. This study showed the characteristics of flood damage by heavy rains and typhoons in Japan and reports that flood damage is increasing because of the hazard size and community aging. Disaster risk reduction, disaster education, and evacuation safety plans for the elderly using hazard maps were important for strengthening disaster resilience.
Floods can be devastating in densely populated regions along rivers, so attaining a longer forecast lead time with high accuracy is essential for protecting people and property. Although many techniques are used to forecast floods, sufficient validation of the use of a forecast system for operational alert purposes is lacking. In this study, we validated the flooding locations and times of dike breaking that had occurred during Typhoon Hagibis, which caused severe flooding in Japan in 2019. To achieve the goal of the study, we combined a hydrodynamic model with statistical analysis under forcing by a 39-h prediction of the Japan Meteorological Agency’s Meso-scale model Grid Point Value (MSM-GPV) and obtained dike-break times for all flooded locations for validation. The results showed that this method was accurate in predicting floods at 130 locations, approximately 91.6% of the total of 142 flooded locations, with a lead time of approximately 32.75 h. In terms of precision, these successfully predicted locations accounted for 24.0% of the total of 542 locations under a flood warning, and on average, the predicted flood time was approximately 8.53 h earlier than a given dike-break time. More warnings were issued for major rivers with severe flooding, indicating that the system is sensitive to extreme flood events and can issue warnings for rivers subject to high risk of flooding.
Because of Taiwan’s specific geographical location, disastrous weather phenomena such as typhoons, extreme rainfall, flooding, and regional flooding occur frequently, resulting in devastating casualties and property loss. The losses caused by flooding are NT$5.5 billion per year. This study used insurance claims data on flood damage in Taiwan’s transportation construction projects (from 1996 to 2007) as a sample space. Statistical actuarial model analysis was performed to normalize the loss factors, thereby enabling loss model testing and quantitative analysis of the normalized loss factors. To evaluate the risk in transportation construction, two models were separately applied in the analysis: the value at risk and riskiness models. The results may aid in estimating flooding damage losses in transportation construction projects.
Floods are known to increase the level of allergens such as molds in the environments. Under climate change, the frequency of floods could be increased, which highlights the importance of understanding the impacts of floods on atopic diseases. However, there was a lack of studies. This study examines whether floods induce attacks of childhood atopic dermatitis (AD). A retrospective population-based study was conducted in Taiwan Island using Taiwan’s National Health Insurance Research Database. Emergency room (ER) visits for AD were identified among children aged 0-12 years. Weekly data of flood occurrence, number of flood sites, temperature, and air pollution were obtained for each township of the identified cases. A time-stratified case-crossover design was used. The relationship between ER visits for AD and floods was assessed by conditional logistic regression, adjusting for weekly mean temperature, PM(2.5) and NO(2). There were a total of 55,488 ER visits due to AD during the study period. Such visits increased when flood occurred, and then declined. The effects of floods at the week of flood remained robust, with OR of 1.14 (95% CI = 1.01-1.28) for flood occurrence and 1.31 (95% CI = 1.10-1.55) for the number of flood sites, after adjusting for covariates. Such effects were slightly higher in boys and children aged 1-12 years. This study demonstrated the impact of floods on flare-up of childhood AD, and the effect was most prominently at the week of flood. Healthcare workers should be alarmed for potential increase of AD flare ups after flood events.
OBJECTIVES: This study aimed to examine the effects of flooding due to Typhoon Hagibis on the incidence of cardiovascular/cerebrovascular events in Nagano City. METHODS: The SAVE trial retrospectively enrolled 2426 patients hospitalized for cardiovascular/cerebrovascular disease in 5 hospitals in Nagano City from October 1 to December 31 in 2017 and 2018 (pre-disaster period) and in 2019 (post-disaster period). From these, 280 patients who were hospitalized in a district flooded in 2019 were recruited for the same period (October 12 to December 31) over the 3 years. The baseline characteristics of and the incidence of cardiovascular/cerebrovascular disease in cases from the flooded district in 2019 were compared with those of cases in the flooded district in 2017 and 2018. RESULTS: The total number of patients with acute myocardial infarction did not differ significantly between the post- and pre-disaster periods. The incidence of unstable angina pectoris was significantly higher in 2019 (n = 4, 5.1%) than in 2017 and 2018 (n = 0, 0.0%) (P = 0.001). CONCLUSIONS: This study did not prove the impact of flood due to a typhoon on the incidence of cardiovascular/cerebrovascular events.
Landslides are natural hazards that cause severe damage and human losses. Japan has succeeded in reducing the number of landslide fatalities and is one of the few countries with long-term databases of landslide fatalities. In this study, we identified the factors that contributed to the decrease in fatalities associated with rainfall-triggered landslides in Japan between 1945 and 2019. We examined trends in landslide fatalities and six factors for Periods I, II, III, IV, and V-each period spans 15 years of the study period-and for Periods I-II, II-III, III-IV, and IV-V. We examined the trends in the number of landslides (N(L)) and in the ratio between the number of fatalities (N(F)) and the number of landslides (N(F)/N(L)), and considered fatalities as the product of the number of landslides and the probability of fatalities. The number of fatalities decreased continuously between Periods I and IV; the rate of the decrease declined over time. During Period I-II, N(F)/N(L) decreased, whereas N(L) remained unchanged. Decreases in the average number of household members, changes in building structure, and increases in the number of people evacuated may have contributed to the decrease in N(F)/N(L). During Periods II-III and III-IV, N(L) also decreased. During Period II-III, the area of mature forests increased slowly. During Period III-IV, the implementation of structural measures (i.e., hard measures) was aggressively pursued. The factors that contributed to the decrease in landslide fatalities changed with time, suggesting that measures for reducing landslide fatalities changed according to the degree of maturity of the nation. Furthermore, we identified increases in rainfall and N(L) in Period V, which might indicate a future increase in landslide fatalities.
The proliferation of algal blooms (ABs) in lakes and reservoirs (L&Rs) poses a threat to water quality and the ecological health of aquatic communities. With global climate change, there is a concern that the frequency and geographical expansion of ABs in L&Rs could increase. China has experienced rapid economic growth and major land-use changes over the last several decades and therefore provides an excellent context for such an analysis. About 289,600 Landsat images were used to examine the spatiotemporal distribution of ABs in L&Rs (>1 km(2)) across China (1983-2017). Results showed significant changes in the temporal slope of the sum of normalized area (0.26), frequency (2.28), duration (6.14), and early outbreak (-3.48) of AB events in L&Rs across China. Specifically, AB-impacted water bodies expanded longitudinally, and the time range of AB observation has expanded starting in the 2000s. Spearman correlation and random forest regression analyses further indicated that, among climatic factors, wind speed and temperature contributed the most to AB expansion. Overall, anthropogenic forces have overridden the imprints of climatic factors on the temporal evolution of ABs in China’s L&Rs and therefore could inform policy decisions for the management of these resources.
Research has demonstrated that posttraumatic stress disorder (PTSD) is associated with internet-related problematic behaviors. However, studies have not explored the linkage between PTSD symptoms and internet gaming disorder (IGD) symptoms. The current study aimed to investigate the relationship between posttraumatic stress symptoms (PTSS) and IGD symptoms via network analysis. We conducted a cross-sectional study with 341 Chinese young adults directly exposed to a typhoon and examined the network structure of PTSS and IGD symptoms, along with bridge symptoms, to elucidate how they co-occur. Results indicated that ‘avoiding external reminders’ and ‘anhedonia’ were identified as the most central symptoms in the PTSD network, whereas ‘preoccupation,’ ‘gaming despite harms’, and ‘loss of control’ ranked highest on centrality in the IGD network. Two bridge symptoms emerged within the combined PTSD and IGD network model: ‘concentration difficulties’ and ‘conflict due to gaming’ from among the PTSS and IGD symptoms, respectively. These findings reveal novel associations between PTSS and IGD symptoms and provide an empirically-based hypothesis for how these two disorders may co-occur among individuals exposed to natural disasters.
This study focuses on an arts-based mental health and psychosocial support (MHPSS) intervention in the form of TOT (training of trainers) conducted under the auspices of IsraAID in the aftermath of the Yolanda typhoon in the Philippines in 2013. Interviews were conducted with 10 female education and healthcare professionals, who also made drawings of their experiences. The goal was to better understand how they evaluated the training program, both for themselves and their communities. Analysis of the interviews and drawings, based on the principles of Consensual Qualitative Research (CQR), identified three main domains: (1) Supportive and inhibiting factors for participants in the training course; (2) Supportive and inhibiting factors with respect to the participants’ implementation of the training goals in their local communities; (3) Perceptions of the benefits of the training program for the participants and their communities. The discussion centers on the value of the creative process, the importance of the group in the training course and in the context of multiculturalism, and the impact these factors in interventions applying the TOT model.
The present study examined the measurement and antecedents of positive mental health in people who concurrently experienced two disasters of different nature (i.e., typhoons and COVID-19 crisis), focusing on the survivors of typhoons Vamco and Goni that hit the Philippines in November 2020, during the COVID-19 pandemic. First, we investigated the psychometric prop-erties of Mental Health Continuum-Short Form (MHC-SF), a well-validated measure of positive mental health dimensions (i.e., emotional, social, and psychological well-being) by: 1) comparing the structural validity of three measurement models including a single-factor, bifactor, and three-factor solutions of positive mental health; 2) looking into the criterion validity through corre-lating the MHC-SF subscales with relevant measures; and 3) calculating for item reliability. Second, we examined the mediating role of social responsibility in the positive influence of community resilience on the three dimensions of positive mental health. Using 447 participants, with ages ranging from 18 to 70 years old, confirmatory factor analysis showed that compared to the single-factor and the bifactor models, the intercorrelated three-factor model of MHC-SF has the best model fit and most stable factor loadings. MHC-SF subscales correlated with relevant measures indicating criterion validity and yielded excellent internal consistency for all subscales. Additionally, results showed that social responsibility mediated the positive impact of community resilience on emotional, social, and psychological well-being of Filipinos in times of great ad-versities. The findings were discussed within the context of extreme weather events and the COVID-19 crisis in the Philippines, highlighting implications on disaster preparedness and mental health policies at the community level.
The strongest storm in Philippines history, super-typhoon Haiyan, barreled through central Philippines in 2013 and left a high death toll and extensive destruction in its wake. Past studies have investigated Fading Affect Bias (FAB) in extremely negative situations like the death of a loved one and found that the FAB generally occurs in those extreme situations, but this study is the first to assess FAB in first-hand memories for a natural disaster survival situation. The FAB phenomenon is the tendency for emotional intensity associated with negative memories for events to fade over time and emotional intensity for positive events stays relatively stable over time. Researchers collected memories for the super-typhoon from survivors three years after the event. Results showed that negative emotional intensity for the event faded after the event. Emotion in comparison positive memories for non-typhoon events did not fade, and emotion in comparison negative memories faded, following results in several other FAB studies. The Positive and Negative Affect Scale (PANAS) was used as an initial assessment of mood before the study began, and PANAS scores reliably predicted current emotional intensity scores. Memory vividness and emotional intensity in first-hand accounts of a natural disaster experience behave like vividness and intensity in flashbulb memories, but details in first-hand accounts are similar to the amount of details in memories of near-death experiences. How memory rehearsal behaves in relation to time elapsed since event has yet to be captured for first-hand survival experiences.
OBJECTIVES: Environmental hazards are part of the Earth’s natural cycle and are ongoing within human history. When vulnerable situations meet environmental hazards, disasters occur where human and natural costs could be enormous. This study aimed to explore the experiences of the victims of coastal erosion during the monsoon season. METHODS: Seven victims of catastrophic coastal erosion in the Kollam District of Kerala, India, were interviewed from December 2013 to February 2014. The study followed Edmond Husserl’s descriptive phenomenological method. RESULT: These interviews constituted the primary data source. Three main themes with eleven subthemes emerged from these data. The main themes were impact, consequences and recovery. The subthemes were living in constant fear, escaping from the catastrophe; cataclysmic sea waves and their tumultuous behaviour, instant damage and destruction, the epoch of losses; agony and suffering; homelessness-helplessness-sleeplessness mixed with fear; government aid only in dreams; haunting memories; never-ending daily needs; first home and native land; and the desire to go back to the site of the disaster. CONCLUSION: From the derived themes, a phenomenon associated with coastal erosion evolved. The phenomenon is termed “Catastrophic coastal erosion: A cycle of impact, consequences, and recovery.”
Super typhoons can lead to post-traumatic stress disorder (PTSD), which can adversely affect a person’s mental health after a disaster. Neuroimaging studies suggest that patients with PTSD may have post-exposure abnormalities of the white matter. However, little is known about these defects, if they are localized to specific regions of the white matter fibers, or whether they may be potential biomarkers for PTSD. Typhoon survivors with PTSD (n = 27), trauma-exposed controls (TEC) (n = 33), and healthy controls (HCs) (n = 30) were enrolled. We used automated fiber quantification (AFQ) to process the participants’ DTI and compared diffusion metrics among the three groups. To evaluate diagnostic value, we used support vector machine (SVM) and a random forest (RF) classifier to build a machine learning model. White matter fiber segmentation between the three groups was found to be statistically significant for the fractional anisotropy (FA) value of the right anterior thalamic radiation (ATR) (26-50 nodes) and right uncinate fasciculus (UF) (60-72 nodes) (FDR correction, p < 0.05). By analyzing the characteristics of the machine learning model, the two most important variables were the right ATR and right UF for differentiating PTSD and trauma-exposed controls (TEC) from the healthy controls (HC). In addition, the left cingulum cingulate and left UF were the most critical variables in the differentiation of PTSD and TEC. AFQ with machine learning can localize abnormalities in specific regions of white matter fibers. These regions may be used as a diagnostic biomarker for PTSD.
BACKGROUND: The structural changes recent-onset posttraumatic stress disorder (PTSD) subjects were rarely investigated. This study was to compare temporal and causal relationships of structural changes in recent-onset PTSD with trauma-exposed control (TEC) subjects and non-TEC subjects. METHODS: T1-weighted magnetic resonance images of 27 PTSD, 33 TEC and 30 age- and sex-matched healthy control (HC) subjects were studied. The causal network of structural covariance was used to evaluate the causal relationships of structural changes in PTSD patients. RESULTS: Volumes of bilateral hippocampal and left lingual gyrus were significantly smaller in PTSD patients and TEC subjects than HC subjects. As symptom scores increase, reduction in gray matter volume began in the hippocampus and progressed to the frontal lobe, then to the temporal and occipital cortices (p < 0.05, false discovery rate corrected). The hippocampus might be the primary hub of the directional network and demonstrated positive causal effects on the frontal, temporal and occipital regions (p < 0.05, false discovery rate corrected). The frontal regions, which were identified to be transitional points, projected causal effects to the occipital lobe and temporal regions and received causal effects from the hippocampus (p < 0.05, false discovery rate corrected). CONCLUSIONS: The results offer evidence of localized abnormalities in the bilateral hippocampus and remote abnormalities in multiple temporal and frontal regions in typhoon-exposed PTSD patients.
This study examined the effects of parents’ posttraumatic stress symptoms (PTSS) and parenting behaviors, children’s feelings of safety, and children’s self-disclosure on children’s PTSS, to elucidate the mechanisms underlying intergenerational effect of PTSS. Three months after the Super Typhoon Lekima occurred in China, August 2019, self-report questionnaires were used to investigate 866 Chinese parent-child dyads (children’s mean age was 10.55 years, 52.2% were boys; parents’ mean age was 37.99 years, 23.2% were fathers) in the area most affected by the typhoon. The results found that parents’ PTSS may have disrupted the provision of emotionally warm parenting, in turn reducing children’s feelings of safety and limiting their self-disclosure, ultimately increasing the severity of children’s PTSS. This suggested that the mechanisms underlying the intergenerational effect of PTSS between parents and children involve the combined role of parents’ emotionally warm parenting, children’s feelings of safety, and children’s self-disclosure.
OBJECTIVE: Investigate an association between severe tropical cyclones (TCs) and birth outcomes in an Australian population. METHODS: We analysed over 600,000 singleton livebirths collected through the Queensland Perinatal Data Collection between 2008 and 2018. We estimated the odds ratios (ORs) of adverse birth outcomes using logistic multi-level modelling. RESULTS: Exposure to TCs in early pregnancy was associated with significantly higher odds of preterm births in affected compared to unaffected areas during the TC year [OR=1.28, 95%CI=1.11, 1.49, p=0.001] and slightly significant higher odds in affected areas during TC years compared to non-TC years. Significantly higher odds of low birthweight births were associated with mid-pregnancy exposure to cyclone Marcia [OR=1.62, 95%CI=1.00, 2.40, p=0.016] . CONCLUSIONS: Findings aligned with studies demonstrating an association between exposure to environmental stressors in early to mid-pregnancy and adverse birth outcomes. IMPLICATIONS FOR PUBLIC HEALTH: There is limited research into TCs and perinatal health in Australia despite most of the population residing along coastlines and TCs presenting one of the nation’s most devastating weather events. This study will inform public health practice and contribute to further research into mitigating environmental risks faced by pregnant women.
The Miyako Islands (with a population of approximately 50,000) are located in southwestern Japan, with a subtropical oceanic climate. This isolated location permitted a retrospective population-based epidemiological study of subarachnoid hemorrhage. We retrospectively enrolled 110 consecutive patients from 2010 to 2019 using the subarachnoid hemorrhage database at Okinawa Miyako Hospital, which is the only local facility with neurosurgeons. We calculated the incidence of subarachnoid hemorrhage standardized to the entire Japanese population. The seasonal distribution of subarachnoid hemorrhage onset and patients’ epidemiological characteristics were also investigated. The standardized annual incidence of subarachnoid hemorrhage was 21.4 per 100,000 population, as reported previously in Japan. The patients’ mean age was 62.1 ± 15.4 years, and women constituted 60.9%. Anterior communicating artery aneurysms were most common. The endovascular treatment for ruptured aneurysms was increasing as standard levels in Japan. The rates of symptomatic vasospasm and secondary hydrocephalus requiring additional neurosurgical treatment were 2.7% and 19.1%, respectively. The mortality rate was 23.6%. The percentage of patients with a modified Rankin scale score of 0-2 at discharge was 55.5%. There were no differences in the frequency of subarachnoid hemorrhage associated with seasonal distribution or climatic factors. The incidence, baseline characteristics, and clinical outcomes of subarachnoid hemorrhage in the Miyako Islands were similar to those in other regions of Japan. There are preferable epidemiological backgrounds for further practical clinical research.
BACKGROUND: The Reiwa First Year East Japan Typhoon of 2019 caused a torrential flood in Japan. In Nagano City, a large area was flooded due to the collapse of the Chikuma River embankment. After large-scale disasters, an increase in cardiovascular and cerebrovascular events has been reported on account of the stressful conditions. However, few reports of disaster-related diseases associated with flood damage have been described. Thus, our aim was to elucidate the effect of floods on the incidences of cardiovascular and cerebrovascular diseases in Nagano City. METHODS: The Shinshu Assessment of Flood Disaster Cardiovascular Events (SAVE) trial enrolled 2,426 patients admitted for cardiovascular or cerebrovascular diseases at all five hospitals with an emergency department in Nagano City from October 1 to December 31 in the years 2017, 2018, and 2019. The occurrence of these diseases was calculated in every 2 weeks and the findings of 2019 (year of the flood) were compared with those of 2017 and 2018. RESULTS: Cardiovascular and cerebrovascular diseases significantly increased during the 2 weeks immediately after the flood disaster (149 in 2019 vs average of 116.5 in the previous 2 years, p < 0.05). Unstable angina cases significantly increased 1.5-2 months after the flood disaster, and cerebral hemorrhage cases significantly increased in the 2 weeks after the flood disaster. CONCLUSIONS: Cardiovascular and cerebrovascular events increased significantly during the 2 weeks immediately after the large-scale flood disaster caused by the Reiwa First Year East Japan typhoon. Because of the increasing frequency of flood disasters, it is necessary to predict the occurrences of cardiovascular and cerebrovascular diseases and to implement guidelines for their appropriate and timely management.
Assessment of urban river sediment quality is paramount to understanding the impacts of urbanization on aquatic ecosystems and public health. The study evaluated the health impacts and sources of heavy metal pollutants in the Mangonbangon river, Tacloban City. With the abundance of heavy metal contaminants in the river sediment (Fe>Mn>Zn>Cu>Cr>Ni>Co), Hazard indices (HIs) ranged from 0.04 to 0.10 for adults and 0.31 to 0.90 for children suggesting little or no non-carcinogenic effects to the population. Lifetime cancer risk (LCR) is below the tolerable threshold of 10(-4), with Co contributing 61% of the cancer risk. Using unconstrained ordination and the GIS-based method (UOGM), we showed two non-multidimensional scaling groups of pollutants distributed based on dwelling density, presence of informal settlers, and types of activity at the sample sites. Given that sampling was performed three years after the city-wide destruction by Typhoon Haiyan (Yolanda), our analysis indicated the return of anthropogenic activities and pollution-related health problems in Tacloban. Our results reinforce the urgent need for proper river management and economic zoning to help curb the rapidly growing heavy metal pollution problem at its earliest stage.
Background: Floods are the most common natural disaster which may have substantial impacts on the human health and life and the environment. In recent years, Iran have faced many floods and it seems that increasing impacts of floods in Iran are attributed to inadequate preparation and no well-established strategies and guidelines for response by health sector and other related response organizations. So, this study was conducted to review the current plans in the world to identify the required elements of the flood emergency response plan to prevent its consequences on the health sector in Iran. Methods: A comprehensive review was performed through search on electronic data bases, including, Medline, Scopus, ProQuest, and e-journals which were accessible during 2010-2020. The keywords were response plan, flood, requirements, guidelines, and health sector. Data were collected using data extraction form and analyzed through content analysis. Results: In the initial search, 960 possible sources of flood response were identified. After excluding duplicate papers and the documents that did not contribute to the flood response plan, 64 articles and programs or guidelines that all them has been reviewed, were obtained. The findings were divided into two groups, response prerequisites and response activities. Conclusion: This review provided a complete view of the flood consequences for the health sector and allows professionals to incorporate facets of the health effect of floods into a flood response plan. The flood response plan was divided into two general categories: Initial and specific, each of which plays an important role in preventing the negative effects of the floods.
Floods occur when a body of water overflows and submerges normally dry terrain. Tropical cyclones or tsunamis cause flooding. Health and safety are jeopardized during a flood. As a result, proactive flood mitigation measures are required. This study aimed to increase flood disaster preparedness among Selangor communities in Malaysia by implementing a Health Belief Model-Based Intervention (HEBI). Selangor’s six districts were involved in a single-blinded cluster randomized controlled trial Community-wide implementation of a Health Belief Model-Based Intervention (HEBI). A self-administered questionnaire was used. The intervention group received a HEBI module, while the control group received a health talk on non-communicable disease. The baseline variables were compared. Immediate and six-month post-intervention impacts on outcome indicators were assessed. 284 responses with a 100% response rate. At the baseline, there were no significant differences in ethnicity, monthly household income, or past disaster experience between groups (p>0.05). There were significant differences between-group for intervention on knowledge, skills, preparedness (p<0.001), Perceived Benefit Score (p = 0.02), Perceived Barrier Score (p = 0.03), and Cues to Action (p = 0.04). GEE analysis showed receiving the HEBI module had effectively improved knowledge, skills, preparedness, Perceived Benefit Score, Perceived Barrier Score, and Cues to Action in the intervention group after controlling the covariate. Finally, community flood preparedness ensured that every crisis decision had the least impact on humans. The HEBI module improved community flood preparedness by increasing knowledge, skill, preparedness, perceived benefit, perceived barrier, and action cues. As a result, the community should be aware of this module. Clinical trial registration: The trial registry name is Thai Clinical Trials Registry, trial number TCTR20200202002.
The evacuation of the population from flood-affected regions is a non-structural measure to mitigate flood hazards. Shelters used for this purpose usually accommodate a large number of flood evacuees for a temporary period. Floods during a pandemic result in a compound hazard. Evacuations under such situations are difficult to plan as social distancing is nearly impossible in the highly crowded shelters. This results in a multi-objective problem with conflicting objectives of maximizing the number of evacuees from flood-prone regions and minimizing the number of infections at the end of the shelter’s stay. To the best of our knowledge, such a problem is yet to be explored in literature. Here we develop a simulation-optimization framework, where multiple objectives are handled with a max-min approach. The simulation model consists of an extended Susceptible-Exposed-Infectious-Recovered-Susceptible model. We apply the proposed model to the flood-prone Jagatsinghpur district in the state of Odisha, India. We find that the proposed approach can provide an estimate of people required to be evacuated from individual flood-prone villages to reduce flood hazards during the pandemic. At the same time, this does not result in an uncontrolled number of new infections. The proposed approach can generalize to different regions and can provide a framework to stakeholders to manage conflicting objectives in disaster management planning and to handle compound hazards.
The elderly population is of utmost importance amongst vulnerable populations during disasters because they experience reduced functional abilities, cognitive disturbance, dementia, weak physical conditions and various degenerative diseases. This study aimed to assess the effect of disaster preparedness training on knowledge regarding flood disaster preparedness and management in families with older people. This study was conducted using a quasi-experimental pre-post design with 30 participants in natural hazard preparedness training using purposive sampling. The results of this study showed a significant change in general knowledge on disaster and flood (12.9 and 20 points, respectively). Disaster preparedness practice was good, as reflected in actions performed before, during and after disaster. Before a flood occurs, families prepare a disaster preparedness bag for important documents as well as logistics (e.g. food) for emergencies and equipment for evacuation whilst also storing valuable goods in a safe place. During floods, families prioritise older people’s evacuation whilst seeking information about the flood through neighbours, walkie-talkies, handphones, television and radio as well as ensuring that the necessary logistics are taken care of. After the disaster, families clean their properties, provide clean water and toilet facilities for the family, check the health of family members that may be impacted by the flood and make sure that all electrical panels are safe. It is concluded that disaster training affects the knowledge of flood management in families with older people.
The concept of resilience has been rapidly accepted across multiple disciplines and spheres of applied work, but operationalizing resilience poses several methodological challenges. Issues associated with complexity due to system dynamics, nonlinearity, and self-organization render traditional evaluation methods insufficient and often speculative. Focusing on system actors, processes and structures, and the scales of the system involved, we provide a framework and methodology to establish evidence and evaluate resilience. We take the case of two transboundary communities situated in the Gangetic plains of South Asia, i.e., Paklihawa (Nepal) and Shivpur (India), that are affected by annual monsoonal floods. Using an accessibility-based livelihood framework, we identified key indicators contributing to resilience and measured them in select households, pre- and post-monsoon, over three consecutive years. Focusing on the variation in well-being and coping capacity, we recommend two propositions that must simultaneously be satisfied for increased resilience. Over time, first, the well-being of the communities should increase, and second, the magnitude of recovery from shocks by the communities should decrease, approaching zero. We used a repeated measures analysis of variance to evaluate the significance of changes in well-being and recoveries over time. Our analysis shows that the resilience of Paklihawa increased significantly while Shivpur’s remained inconclusive. The two propositions and the methodology are robust to a wide range of shocks and social-ecological systems. This study contributes to the growing need for approaches toward measuring resilience and the monitoring and evaluation of resilience-focused interventions.
BACKGROUND: Armed forces hospitals are often called upon to provide medical aid to civilians during natural calamities. Though children are often the most vulnerable segment of population in these events, research that addresses their unique needs and the role of armed forces hospitals remains sparse. OBJECTIVES: We examined pediatric morbidity and mortality at a flooded armed forces hospital. Factors that affected outcomes were identified. METHODS: 158 patients were evacuated en masse from a children’s hospital in northern India that was submerged by flood to an adjacent partially inundated armed forces hospital specializing in military medicine and adult trauma. The children were provided case-based clinical care as per existing disaster management protocol. Geoclimatic vulnerability factors, morbidity/mortality, and medical and logistical challenges for future intervention were investigated. RESULTS: One pediatrician who provided initial triage was joined by two others after 48 hours. A limited load of adult patients permitted more resources for the children, majority (49 percent) of whom were neonates. Intensive care was necessitated for 32 (20.2 percent) cases, with half managed in adult ICU. Overall in-hospital mortality was 5.7 percent. Experienced staff, cross-specialty multitasking, and innovative and noncensorious leadership were identified as assets amidst resources compromised by flooding. Clear delineation of primary caregiver role of pediatrician at outset, pediatric emergency care training, pediatric triage, resource allocation for thermoregulation, oxygen therapy and ventilation, earmarking centers for transfer of cases, and safe transportation to the centers were identified as areas meriting further attention. CONCLUSION: Armed forces hospitals in vulnerable geoclimatic zones must address pediatric concerns in disaster management plans.
The upper Brahmaputra floodplain (UBF) is highly enriched with geogenic contaminants, mostly the Arsenic (As), owing to its sensitive geomorphology, aquifer groundwater (GW) dynamics, huge sediment deposition along with natural and anthropogenic disturbance significantly accelerate the As leaching rate into the groundwater, leading to an increase the health risk. Concerning the above active processes in the Lakhimpur district of UBF, current work aims to investigate seasonal dynamics of As contamination and associated health hazard for local community. To carry out this study, 51 GW samples analyzed which reveal the seasonal variation in As concentrations with the minimum average concentration in the monsoon season (4.7 μg.L(-1)) and the maximum in the post-monsoon season (18.5 μg.L(-1)) with 50% of the samples exceeding permissible limits. The differences in the local geological conditions and the GW flow may contribute to the spatial variations in mean As concentration in the study area. Also, the active GW recharge process identified in post-monsoon season accelerates the As leaching in the area’s aquifers. Further, results indicate higher As levels associated with a pH range of 6-7 favours As desorption from minerals under reducing conditions. The hazard index indicates that the children population has high carcinogenic risk compared to adult populations. Furthermore, the study highlights the social risk potential arising from public health crises due to As exposure. Overall, results indicate high As concentrations in region with moderate seasonal variability and demand a dire attention for long-term monitoring to provide sustainable water resources to safeguard the people at risk.
Recent years recorded an increasing number of short duration – high-intensity rainfall events in the Indian subcontinent consequent with urban and riverine flash floods. Rapid assessments of flooded areas are key for effective mitigation strategies and disaster risk plans, as well as to prepare operative policies for future events. Herein, we present an integrated methodology for rapidly mapping the flood extent, and depths based on Synthetic Aperture Radar (SAR) images and a digital elevation model (DEM). Incessant rain during August 2019 brought heavy riverine flooding in southern India, killed at least 280 people, and displaced about one million inhabitants from low-lying areas. We used SAR images by Sentinel-1 before, and during the flooding, and the MERIT DEM which enabled us to map the flood extent and flood depth of the inundation zones. Because the coverage of Sentinel-1 scene was limited to the Kabini river section during the flood period, flood extent and depth maps for the adjacent basin was generated by mapping the susceptibility for flooding using the training set obtained from the flood time Sentinel-1 images, and a set of predictive variables derived from DEM using random forest model. Qualitative analysis and cross-comparison with a numerical flood model proved the proposed approach is highly reliable with an accuracy value of 90% and 86% respectively for training and validation data, thus allowing a precise, simple, and fast flood mapping. The methodology presented here could be applied to other flooded areas having incomplete inventory in the context of flood risk assessment.
During the first half of 2019, many provinces of Iran were affected by floods, which claimed the lives of 82 people. The present study aimed to investigate the behavioral, health related and demographic risk factors associated with deaths due to floods. We measured the odds ratio and investigated the contribution and significance of the factors in relation to mortality. This case-control study was conducted in the cities affected by flood in Iran. Data were collected on the flood victims using a questionnaire. Survivors, a member of the flood victim’s family, were interviewed. In total, 77 subjects completed the survey in the case group, and 310 subjects completed the survey in the control group. The findings indicated that factors such as the age of less than 18 years, low literacy, being trapped in buildings/cars, and risky behaviors increased the risk of flood deaths. Regarding the behavioral factors, perceived/real swimming skills increased the risk of flood deaths although it may seem paradoxical. This increment is due to increased self confidence in time of flood. On the other hand, skills and abilities such as evacuation, requesting help, and escape decreased the risk of flood deaths. According to the results, the adoption of support strategies, protecting vulnerable groups, and improving the socioeconomic status of flood-prone areas could prevent and reduce the risk of flood deaths.
Event scenarios serve as the basis for emergency decision making after sudden disasters, and the accuracy of scenario deduction directly determines the effectiveness of emergency management implementation. On July 20, 2021, an exceptionally heavy rainstorm disaster occurred in Zhengzhou, Henan Province, China, causing serious urban waterlogging, river floods, flash floods and landslides and resulting in major casualties and property losses:14.79 million people affected, 398 people killed or missing (380 people in Zhengzhou) and a direct economic loss of 120.06 billion RMB. In order to investigate the complex evolution process of this disaster, a dynamic Bayesian network, evidence theory and emotion update mechanism are integrated to develop an efficient and effective scenario deduction model, with an emphasis on combining subjective and objective factors. In this model, more attention is given to subjective factors such as decision makers’ emotions. The elements of scenario deduction are classified into the situation status, meteorological factor, emergency activities, decision makers’ emotions and emergency goals, the coupling relationship between the elements are comprehensively analyzed, and the influence of these elements on the evolution mechanism of the rainstorm disaster is investigated, so as to facilitate targeted emergency management measures for the rescue operations. The empirical results show that the proposed dynamic Bayesian network can effectively simulate the dynamic change process of scenario deduction, the improved Dempster-Shafer evidence theory can reduce the subjectivity of the model in dealing with the uncertainty of the evolution process, and the emotion update mechanism can adequately quantify and decrease the influence caused by the emotional changes of decision makers. The model may better replicate actual events, and it may apply to the scenario deduction of other disasters, making an impact on the study of sudden catastrophes.
BACKGROUND: Adequate nutrition before and during pregnancy is necessary to maintain women’s reproductive health and to ensure healthy foetal outcome. Pregnant women are at high risk of acute malnutrition specifically during humanitarian crisis leading to adverse effects in foetal outcomes and women’s health. This study aimed to assess the factors associated with acute malnutrition among pregnant women visiting Antenatal Clinics in two hospitals and a Primary Health Care Centre of Siraha district in the south-eastern plains of Nepal immediately after 2017 flash flood. METHODS: A health-institution based cross-sectional study was conducted among 444 pregnant women of reproductive age (15-49 years) in second and third trimester in three health institutions. Data collection was done in the aftermath of 2017 flash floods through face to face interview. Multiple logistic regression analysis was used to identify the factors associated with acute malnutrition defined as Mid Upper Arm Circumference less than or equals to 21 centimetres. RESULTS: Out of 444 participants, 9.9% were found to be acutely malnourished. Participant’s education (AOR[Adjusted Odds Ratio]: 3.09, 95% CI[Confidence Interval]: 1.43-6.70), occupation (AOR: 3.16, 95% CI: 1.08-9.22), husband’s occupation (AOR: 6.61, 95% CI: 2.17-20.12), household food security (AOR: 3.39, 95% CI: 1.36-8.49) and participant’s dietary diversity (AOR:10.06, 95% CI: 3.35-30.27) were found to be statistically significant factors associated with acute malnutrition among pregnant women. CONCLUSIONS: Participants’ silliteracy, unemployment, husband not employed for cash, household food insecurity and low dietary diversity were found to be statistically significant predictors of acute malnutrition among pregnant women during flash floods.
The present work has been oriented to the qualitative and quantitative assessments of the aftermath effects of 2014 flood tragedy on the organic, inorganic and microbial contaminants in the floodwater, with a particular emphasis on their relative health risks and microbial infectious hazards to the flood-affected population, using average daily dose, hazard quotient, hazard index (HI), cancer risk (CR) and quantitative microbial risk assessment. Statistical comparison of the organic and inorganic contents was performed using the paired t-tests, while the predominant socio-demographic profiles and health attributes of the respondents to flood-induced health risks (HI) were verified by the chi-square test and binary logistic regression analysis. Among all, Fe, Cu, Pb, Ni, Zn, Cr, Cd, chlorpyrifos, diazinon, polycyclic aromatic hydrocarbons, estriol, 17α-ethinylestradiol, estrone, β-estradiol and bisphenol A were detected at the study area after flooding. The microbiological quality of the floodwater samples has been tracked positive for Escherichia coli, Salmonella typhimurium and Shigella flexneri, with the mean concentrations of 6500, 50 and 180 CFU/100 mL, respectively. Exposure and health risk assessments revealed that the overall HI value for organic and inorganic contaminants in the water samples was 1.19, exceeding the USEPA maximum limit of 1, after the flood incidence. The largest CR contributors were Ni, Cr and Cd, while the infection risks (P(inf,single)) associated with the exposure of E. coli, Salmonella spp. and Shigella spp. were identified to be 3.1 × 10(-2), 1.2 × 10(-4) and 3.2 × 10(-5) for incidental scenario; and 8.3 × 10(-1), 3.9 × 10(-1) and 1.9 × 10(-1) for intentional scenario, respectively. The findings of these integrated tools are critically important to provide a more reliable quantitative assessment of human health hazards and microbial risks for different environmental settings, to safeguard water resource, and preservation of public health and the overall river ecosystem.
The present study aimed to investigate the concentrations of potentially toxic metals (PTMs) in the drainages, rivers, and coast of Malacca in Peninsular Malaysia. The ranges of total PTM concentrations (mg/kg dry weight) were 1.88-7.01 for Cd, 18.9-1689 for Cu, 26.0-850 for Ni, 56.5-307 for Pb, and 75.4-312 for Zn. Based on an ecological risk assessment and geochemical fractions, it was concluded that heavy metals pollute the drainages and the Malacca River. The potential ecological risk index (PERI) categorised the drainage and river sites as a “very high ecological risk”. Therefore, it was shown that elevated levels of PTMs in the drainages near Malacca Industrial Area and in the Malacca River sediment were most probably attributed to untreated (or incomplete treatment of) industrial effluents. The drainage sediments were found to have higher hazard quotient (HQ) values for the three pathways of the PTMs for children and adults. Although in general, the non-carcinogenic risks of the PTMs for children and adults indicated no significant detrimental health effects, the hazard index (HI) for Pb in children at drainage locations surpassed 1.0, suggesting a non-carcinogenic risk (NCR), which is a cause for worry. Consequently, the ecological health risk assessments offered critical information for PTM pollution reduction and environmental management in future sustainable development initiatives in Peninsular Malaysia’s drainages and rivers. The present findings on the ecological health risks of PTMs based on 2006 samples can serve as an important baseline for future reference and comparison. This work should encourage future investigations on the direct impact of the risks to the residents during floods in Malaysia, as part of mitigation and risk assessments of the contaminated drainage and river sediments in an attempt to lower the hazards for the surrounding residents.
Assessments of vulnerability to flooding can generate useful data for planners and policy makers. To the best of the authors knowledge, no flood-vulnerability study has combined geophysical modelling of floods with socioeconomic assessments of vulnerability at finer municipal or household scale. In addition, the extent to which vulnerability assessments actually feed into flood adaptation policies remains largely unknown. A new flood vulnerability index, and associated methodology, is proposed, combining high-resolution hydrological-hydraulic modelling with built-environment and socio-economic indicators at the smallest spatial scale at which socio-economic data is available. The main advantage of the methodology is its ability to incorporate place-specific data, hence yielding more refined simulations of floods and the capacity to make projections into climate futures at local scale. The index is built and applied to the inter-city suburb of Marrickville in Sydney and used to assess the effects of future climate change on vulnerability mapping in the suburb. Finally, the results of the assessment are presented to, and discussed with, the local government authority responsible for implementing flood adaptation policies for Marrickville. Locally specific modelling of floods, combined with socio-economic and built-environment mapping, has yielded a rich set of information on flood vulnerability and significant variability within a single suburb. Flood duration is projected to increase by more than 100% under some climate change scenarios, as a result of reduced drainage caused by sea level rise. Feedback from municipal council has highlighted the potential usefulness of the knowledge generated by the assessment, especially for emergency services.
During flood events, warnings issued by emergency service agencies serve to communicate risk and guide community behavior. Yet research shows that while warnings convey operational details, they may not always be understood and appropriately actioned in a timely manner by the public. Such maladaptive behavior can place multiple parties at risk of injury and fatality. Few studies empirically consider and compare the effectiveness of traditional agency-designed oper-ational warnings with other designs such as behavior-oriented warnings. The former typically contain technical and operational detail while the latter provide immediate priority and greater emphasis on translating the situation into specific behavioral actions to be undertaken by the public. Using operational versus newly developed behavior-oriented warnings from New South Wales State Emergency Service in Australia, a total of 774 community members rated each type of scaled warning and their likelihood to engage in adaptive and maladaptive behaviors following exposure to warnings designed to convey one of five levels of an unfolding flooding scenario from its beginning to conclusion (‘Prepare for flooding’, ‘Be ready to evacuate’, ‘Evacuate’, ‘Too late to evacuate’ and ‘Safe to return’). Findings showed positive response to both types of warnings, with behavior-oriented warnings offering greater benefit for perception factors (e.g., risk and comprehension) and adaptive behavioral intentions.
BACKGROUND: Exposure to adverse experiences during pregnancy, such as a natural disaster, can modify development of the child with potential long-term consequences. Elemental hair analysis may provide useful indicators of cellular homeostasis and child health. The present study investigated (1) if flood-induced prenatal maternal stress is associated with altered hair elemental profiles in 4-year-old children, and (2) if hair elemental profiles are associated with behavioural outcomes in children. METHODS: Participants were 75 children (39 boys; 36 girls) whose mothers were exposed to varying levels of stress due to a natural disaster (2011 Queensland Flood, Australia) during pregnancy. At 4 years of age, language development, attention and internalizing and externalizing problems were assessed and scalp hair was collected. Hair was analyzed by inductively coupled plasma mass spectrometry (ICP-MS) for 28 chemical elements. RESULTS: A significant curvilinear association was found between maternal objective hardship and copper levels in boys, as low and high maternal objective hardship levels were associated with the highest hair copper levels. Mediation analysis revealed that low levels of maternal objective hardship and high levels of copper were associated with lower vocabulary scores. Higher levels of maternal objective hardship were associated with higher magnesium levels, which in turn were associated with attention problems and aggression in boys. In girls, high and low maternal objective hardship levels were associated with high calcium/potassium ratios. CONCLUSION: Elemental hair analysis may provide a sensitive biomonitoring tool for early identification of health risks in vulnerable children.
Research conducted in 2018 documented the disaster experiences of 56 women and men in Australia aged between 18 and 93 years. This paper draws out the gendered factors that affected their resilience, and in so doing, begins to address the dearth of research related to gendered aspects of long-term disaster resilience. It is unique in capturing the voices of survivors who spoke of events 9 years after the 2009 Black Saturday fires and of earlier fires and floods in Victoria more than 50 years ago, including the 1983 Ash Wednesday fires. Over decades, gendered expectations of men and women significantly hindered resilience. Men spoke of the long-term cost to them of demands to ‘be strong’ in the worst of disasters and reasons they were reluctant to seek help afterwards. Women spoke of their contributions holding a lesser value and of discrimination. Discussions of violence against women and children after disaster, and suicide ideation in anticipation of future disasters offered critical insights. Protective factors identified by informants were not wholly intrinsic to their character but were also physical, such as essential resources provided in the immediate aftermath, and psychological and community support offered in the long-term. Factors that helped resilience departed from the ‘masculine’ model of coping post-disaster by moving away from a refusal to admit trauma and suffering, to community-wide resilience bolstered by widespread emotional, social and psychological support. Genuine community planning for disasters before they strike builds trust and offers insights for emergency management planners.
OBJECTIVE: This study aimed to investigate the effects of disaster trauma, disaster conflict, and economic loss on posttraumatic stress disorder (PTSD), and to verify the moderating effect of personal and community resilience in these relationships. The data of 1914 people, aged 20 or above, who had experienced natural disasters (earthquake, typhoon, flooding) were used. METHODS: Hayes’s (2013) PROCESS macro (Model 1) was conducted to verify the moderation effect of personal and community resilience between PTSD and disaster trauma, disaster conflict, and economic loss. RESULTS: Disaster trauma, disaster conflict, and economic loss were found to be positively related to PTSD. Personal and community resilience were negatively related to PTSD. Resilience had a moderating effect on the relationship between disaster trauma, economic loss, and PTSD. However, there was no moderating effect on the relationship between disaster conflict and PTSD. Community resilience had a moderating effect on the relationship between economic loss and PTSD. However, there was no moderating effect on the relationship between disaster trauma, disaster conflict, and PTSD. CONCLUSIONS: The results suggest that personal and community resilience could be used for prevention and therapeutic interventions for disaster victims who experience PTSD.
By the 2050s, more than 120 million people are predicted to settle in the Pearl River Delta (PRD), which covers large coastal cities such as Guangzhou, Shenzhen and Hong Kong. Cities in the PRD are vitally important to China in relation to their socio-economic contributions. From recent evidence, this strongly urbanized area is vulnerable to, and currently facing bigger incidences of, coastal and urban flooding. Flood risk is growing in low-lying coastal areas due to rapid urbanization and increasing flood hazards exacerbated by climate change. Frequent intensive rainstorms, sea-level rise, typhoons and surges threaten large populations and their economic assets, causing severe socio-economic and ecological impacts in the PRD cities. Current flood risk management (FRM) in the delta is still predominately focused on using traditional techno-fixes and infrastructure paradigms, lacking sufficient strategic planning and flood protection to develop adequate flood resilience. Recent urban floods, enhanced by storm surges and intensive rainstorms, have affected multiple PRD cities and drawn attention to flood risk as a major challenge in the PRD’s coastal cities. This review encourages development of long-term FRM practices with provincial and municipal authorities working together more closely to develop better-integrated regional FRM strategies for the PRD.
OBJECTIVE: Typhoon Hagibis struck Japan on October 12, 2019. This study documents and characterizes deaths caused by Hagibis and helps identify strategies to reduce mortality in future disasters. METHODS: Japanese residents, who were killed by Typhoon Hagibis, as reported by Japan’s Fire and Disaster Management Agency, were considered for the study. Details were collected from mainstream Japanese media, and flooding data from hazard maps published by local municipalities. RESULTS: Out of the 99 total fatalities, 65 (73.0%) were aged 65 years or above. Among those who drowned indoors (20), 18 (90.0%) lived in high-risk areas of flooding, and their bodies were found on the first floor of their residences. A total of 10 (55.6%) out of the 18 fatalities lived in homes with 2 or more floors, indicating that they could have moved upstairs to avoid the floodwater. However, 6 (33.3%) could not do so due to existing health issues. CONCLUSIONS: Relatively elderly people, particularly those in areas at high risk of flooding, were most affected. Seeking higher ground is a standard safety measure in times of flooding, but this may not be possible for everyone depending on their health status, structure of their residence, and the depth of floodwaters.
This is a one-page summary of findings from EPA’s report Climate Change and Social Vulnerability in the United States: A Focus on Six Impacts related to disproportionate risks of climate change to Asian individuals and Pacific Islanders.
BACKGROUND: The intense interactions between people, animals and environmental systems in urban informal settlements compromise human and environmental health. Inadequate water and sanitation services, compounded by exposure to flooding and climate change risks, expose inhabitants to environmental contamination causing poor health and wellbeing and degrading ecosystems. However, the exact nature and full scope of risks and exposure pathways between human health and the environment in informal settlements are uncertain. Existing models are limited to microbiological linkages related to faecal-oral exposures at the individual level, and do not account for a broader range of human-environmental variables and interactions that affect population health and wellbeing. METHODS: We undertook a 12-month health and environmental assessment in 12 flood-prone informal settlements in Makassar, Indonesia. We obtained caregiver-reported health data, anthropometric measurements, stool and blood samples from children < 5 years, and health and wellbeing data for children 5-14 years and adult respondents. We collected environmental data including temperature, mosquito and rat species abundance, and water and sediment samples. Demographic, built environment and household asset data were also collected. We combined our data with existing literature to generate a novel planetary health model of health and environment in informal settlements. RESULTS: Across the 12 settlements, 593 households and 2764 participants were enrolled. Two-thirds (64·1%) of all houses (26·3-82·7% per settlement) had formal land tenure documentation. Cough, fever and diarrhoea in the week prior to the survey were reported among an average of 34.3%, 26.9% and 9.7% of children aged < 5 years, respectively; although proportions varied over time, prevalence among these youngest children was consistently higher than among children 5-14 years or adult respondents. Among children < 5 years, 44·3% experienced stunting, 41·1% underweight, 12.4% wasting, and 26.5% were anaemic. There was self- or carer-reported poor mental health among 16.6% of children aged 5-14 years and 13.9% of adult respondents. Rates of potential risky exposures from swimming in waterways, eating uncooked produce, and eating soil or dirt were high, as were exposures to flooding and livestock. Just over one third of households (35.3%) had access to municipal water, and contamination of well water with E. coli and nitrogen species was common. Most (79·5%) houses had an in-house toilet, but no houses were connected to a piped sewer network or safe, properly constructed septic tank. Median monthly settlement outdoor temperatures ranged from 26·2 °C to 29.3 °C, and were on average, 1·1 °C warmer inside houses than outside. Mosquito density varied over time, with Culex quinquefasciatus accounting for 94·7% of species. Framed by a planetary health lens, our model includes four thematic domains: (1) the physical/built environment; (2) the ecological environment; (3) human health; and (4) socio-economic wellbeing, and is structured at individual, household, settlement, and city/beyond spatial scales. CONCLUSIONS: Our planetary health model includes key risk factors and faecal-oral exposure pathways but extends beyond conventional microbiological faecal-oral enteropathogen exposure pathways to comprehensively account for a wider range of variables affecting health in urban informal settlements. It includes broader ecological interconnections and planetary health-related variables at the household, settlement and city levels. It proposes a composite framework of markers to assess water and sanitation challenges and flood risks in urban informal settlements for optimal design and monitoring of interventions.
OBJECTIVE: To determine the impact of the 2018 Japan Floods, one of the largest water disasters in Japan, on the number of prescriptions for triptans and ergotamine (acute treatment). BACKGROUND: Natural disasters frequently occur worldwide and may cause psychological stress-related diseases. Acute migraine attacks can be triggered by psychological stress. Disaster victims are likely to experience tremendous psychological stress; however, the relationship between natural disasters and migraine attacks is not well investigated. METHODS: A retrospective longitudinal cohort study was conducted using the National Database of Health Insurance Claims in the hardest-hit areas of the disaster 1 year before and after the disaster. We included people between the ages of 15 and 64 years. Those who had a victim code that was certificated by a local government were assigned to the victim group, and others to the nonvictim group. For those who were not prescribed acute treatment before the disaster (i.e., group without previous acute treatment), the cumulative incidence of new prescriptions for acute treatment at 12 months of follow-up was calculated and compared between victims and nonvictims with survival analysis. RESULTS: Of 3,475,515 people aged 15 to 64 years enrolled in the study, 16,103 (0.46%) were assigned to the victim group. In the group without previous acute treatment, 111 (0.70%) of 15,933 victims and 14,626 (0.43%) of 3,431,423 nonvictims were newly prescribed acute treatment after the disaster, and new prescriptions for acute treatment were significantly more likely to occur in victims than in nonvictims (adjusted hazard ratio, 1.68; 95% CI, 1.39-2.02). CONCLUSIONS: The 2018 Japan Floods increased the number of prescriptions for acute migraine medications among victims, suggesting that acute migraine attacks occurred more frequently after a natural disaster.
INTRODUCTION: Rainfall-induced floods and landslides accounted for 20.7% of all disaster events in Japan from 1985 through 2018 and caused a variety of health problems, both directly and indirectly, including injuries, infectious diseases, exacerbation of pre-existing medical conditions, and psychological issues. More evidence of health problems caused by floods or heavy rain is needed to improve preparedness and preventive measures; however, collecting health data surrounding disaster events is a major challenge due to environmental hazards, logistical constraints, political and economic issues, difficulties in communication among stakeholders, and cultural barriers. In response to the West Japan Heavy Rain in July 2018, Emergency Medical Teams (EMTs) used Japan – Surveillance in Post-Extreme Emergencies and Disasters (J-SPEED) as a daily reporting template, collecting data on the number and type of patients they treated and sending it to an EMT coordination cell (EMTCC) during the response. STUDY OBJECTIVE: The aim of the study was to conduct a descriptive epidemiology study using J-SPEED data to better understand the health problems during floods and heavy rain disasters. METHODS: The number and types of health problems treated by EMTs in accordance with the J-SPEED (Ver 1.0) form were reported daily by 85 EMTs to an EMTCC, where data were compiled during the West Japan Heavy Rain from July 8 through September 11, 2018. Reported items in the J-SPEED form were analyzed by age, gender, area (prefecture), and time period. RESULTS: The analysis of J-SPEED data from the West Japan Heavy Rain 2018 revealed the characteristics of a total of 3,617 consultations with the highest number of consultations (2,579; 71.3%) occurring between Day 5 and Day 12 of the 65-day EMT response. During the response period, skin disease was the most frequently reported health event (17.3%), followed by wounds (14.3%), disaster stress-related symptoms (10.0%), conjunctivitis (6.3%), and acute respiratory infections (ARI; 5.4%). CONCLUSION: During the response period, skin disease was the most frequently reported health event, followed by wounds, stress, conjunctivitis, and ARIs. The health impacts of a natural disaster are determined by a variety of factors, and the current study’s findings are highly context dependent; however, it is expected that as more data are gathered, the consistency of finding will increase.
BACKGROUND: The frequency and intensity of natural disasters are increasing worldwide, which makes our understanding of disaster-related diseases more important than ever. Natural disasters cause mental stress and infectious diarrhea, but the causal relationship between disasters and a potential consequence of these conditions, irritable bowel syndrome (IBS), is unreported. The 2018 Japan Floods, which took place in July 2018 was one of the largest water disasters in Japan’s recorded history. We investigate the change of drug prescriptions for IBS between disaster-suffers and non-sufferers throughout the disaster period to examine the relationship. METHODS: This is a retrospective cohort study based on the Japanese National Database of Health Insurance Claims and Specific Health Checkups in flood-stricken areas between July 2017 and June 2019. We included subjects older than 15 years of age who had visited a medical institution or been hospitalized in the hardest-hit areas of the disaster. Ramosetron, polycarbophil calcium, and mepenzolate bromide (IBS drugs) approved solely for the treatment of IBS in Japan were analyzed. The monthly rate of prescriptions for IBS drugs was compared between municipality-certified disaster victims and non-victims using a controlled interrupted time series analysis. For those who were not prescribed IBS drugs before the disaster (non-users), the occurrence of an IBS drug prescription after the disaster was evaluated using a multivariable logistic regression analysis adjusted for gender and age. RESULTS: Of 5,287,888 people enrolled, 32,499 (0.61%) were certified victims. The prescription rate for IBS drugs among victims increased significantly by 128% immediately after the disaster, while it was stable among non-victims. The trend for the post-disaster prescription rate among victims moved upward significantly when compared to non-victims (0.01% per month; 95% confidence interval (CI) 0.004-0.015; P = 0.001). Among non-users, the occurrence of an IBS drug prescription for victims was 0.71% and was significantly higher than non-victims (0.35%, adjusted odds ratio 2.05; 95% CI 1.81-2.32). CONCLUSIONS: The 2018 Japan Floods increased the rate of prescriptions for IBS drugs, suggesting that the disaster caused or worsened IBS among victims.
BACKGROUND: The July 2018 Japan Floods caused enormous damage to western Japan. Such disasters can especially impact elderly persons. Research has shown that natural disasters exacerbated a decline in cognitive function, but to date, there have been no studies examining the effects of this disaster on the elderly. The object of this study was to reveal the effect of this disaster in terms of cognitive decline among the elderly. METHODS: Study participants were certified users of the long-term care insurance (LTCI) system in Hiroshima, Okayama, and Ehime prefectures from May 2018 to June 2018. The observation period was from July 2018 to December 2018. Our primary outcome was cognitive decline after the disaster using a dementia symptomatology assessment. In addition to a crude model, a multivariate Cox proportional hazards model was used to assess the cognitive decline of victims, adjusting for age classification, gender, the level of dementia scale before the disaster occurred, residential environment, whether a participant used facilities shut down after the disaster, and population density. After we confirmed that the interaction term between victims and residential environment was statistically significant, we stratified them for the analysis. RESULTS: The total number of participants was 264,614. Victims accounted for 1.10% of the total participants (n = 2,908). For the Cox proportional hazards model, the hazard ratio of the victims was 1.18 (95% confidential interval (CI): 1.05-1.32) in the crude model and 1.12 (95% CI: 1.00-1.26) in the adjusted model. After being stratified by residential environment, the hazard ratio of home victims was 1.20 (95% CI: 1.06-1.36) and the hazard ratio of facility victims was 0.89 (95% CI: 0.67-1.17). CONCLUSIONS: This study showed that elderly living at home during the 2018 Japan Floods were at risk for cognitive decline. Medical providers, care providers, and local governments should establish a system to check on the cognitive function of elderly victims and provide necessary care support.
Managing information at city level has become increasingly important owing to the introduction of smart cities and the increasing severity of disasters due to climate change. A data collection framework, model construction, and information management must be established to systematically manage information at the city level. This study developed an urban model generation method using detailed attributes within the City Geography Markup Language (CityGML), a standard data schema for 3D representation of cities based on different types of publicly available information within Korea. The generated model was used to develop a method for simulating flooding status, degree of flooding, and level of building damage after heavy rainfall, in Korea. Furthermore, we developed a method to estimate the loss of human life and property damage by combining the results of the flood analysis with the city model. The proposed methodology supports the creation of standard-based models for flood analysis and exhibits strong interoperability for application to different areas of analysis.
Households living in the close vicinity of shoreline are constantly threatened by various climate change impacts. Community awareness towards climate change is a subject of considerable study as adequate knowledge is a preliminary step for adaptation decision making. An important question is how coastal communities perceive climatic variation, sea level rise and coastal hazard impacts and the socio-economic factors that affect their level of awareness. Thus, this research measures the level of awareness and the factors influencing it based on a household survey (n = 1016) that was conducted 10 critically eroded coastal areas in Selangor. Descriptive statistical analysis reveals that more than half of the households have high level of awareness about climatic variation and sea level, however, there is moderate awareness about the coastal hazard impacts such as human causalities and disease transmission. Even though households are more aware of direct coastal hazard impact such as damages to properties and disruption of daily activities. An independent sample T test indicates that respondents who are male, at working age, educated, involve in natural resource dependent occupations, and had prior exposure to extreme coastal hazards have higher levels of awareness. Research indicated about 55% of all sampled households reflected awareness of climate change, 60% households were aware of sea level rise and 47% households were aware of coastal hazard impact. This study recommends that households in Selangor coast need capacity building and climate change awareness initiatives which would assist household to build adaptive capacity, increase resilience and reduce vulnerability to climate change.
The east coast of Malaysia is frequently hit by monsoon floods every year that severely impact people, particularly those living close to the river bank, which is considered to be the most vulnerable and high-risk areas. We aim to determine the most vulnerable area and understand affected residents of this community who are living in the most sensitive areas caused by flooding events in districts of Temerloh, Pekan, and Kuantan, Pahang. This study involved collecting data for vulnerability index components. A field survey and face-to-face interviews with 602 respondents were conducted 6 months after the floods by using a questionnaire evaluation based on the livelihood vulnerability index (LVI). The findings show that residents in the Temerloh district are at higher risk of flooding damage compared to those living in Pekan and Kuantan. Meanwhile, the contribution factor of LVI-Intergovernmental Panel on Climate Change (IPCC) showed that Kuantan is more exposed to the impact of climate change, followed by Temerloh and Pekan. Among all the principal components shown, food components were considered to be the most vulnerable. Meanwhile, water components were categorised as the most invulnerable. Preventive planning involves preserving human life, minimising damage to household products, preserving crops and animals, adequate supply of clean water and food, good health and ensuring financial sustainability as an indication of changing livelihoods, sustainable food-storing systems, and other protective steps to curb damage and injury caused by annual flood strikes. Information generated on LVI assessment and adaptation procedures will help policymakers reduce people’s vulnerability in the face of floods and ensure proper plans are put in place in all relevant areas.
The need for an emergency disaster management related to dam has risen up in recent years. This is due to uncertainties in global weather predictions which also affect local Malaysian area. With unpredictable prolonged rainy weather, concerns on events that could lead to flooding has triggered the authority to review the evacuation strategies in critical locations. This paper describes an investigation on the effect of early warning system and people response delay to the rate of fatality in the event of flooding due to dam breach. The Life Safety Model is utilized as a tool for the simulation of people vehicle and building response to 2D hydraulic flow of the river originated from the dam. The study area is based on Kenyir Dam and its surrounding vicinity. A number of scenarios are simulated namely cases with and without early warning system. For the case with early warning system, different triggering time is also investigated. On top of that, the effect of people response delay to the warning system is simulated. It was found that early warning system plays a critical role in reducing the number of fatalities due to flooding. Equally important is the time taken for the community to start evacuating when triggered by the early warning system. From the result LSM, optimum evacuation parameters could be identified and used for the purpose of design, planning and implementation of local emergency evacuation plan in the event of dam-related flooding.
This research aimed at assessing flood hazard areas and flood literacy of the elderly population in Bangkok, Thailand and analyzing their flood preparedness through SWOT analysis. Expert interviews and a community survey were conducted. Using the analytic hierarchy process (AHP) and GIS technique, the results indicated that land-use, drainage density, and annual maximum rainfall were the most heavily weighted factors in flood hazard mapping in Bangkok. About half (50.32%) of Bangkok’s total area was defined as high flood hazard area. A total of 736 questionnaires were distributed in flood-prone areas and in the areas with the highest percentage of elderly population. The results of both SWOT and survey analysis found that many senior citizens have low digital and media literacy and limited experience in using information technology for flood preparedness. Lack of integration of disaster risk reduction and aging population policy, ineffective warning system, and lack of access to disaster preparedness training were the key barriers in reducing vulnerability to flood hazard. The survey revealed that the majority of elderly respondents (75%) have neither used online applications for their flood hazard management both before and during flood disaster nor shared/communicated information via online platforms. Some respondents (13%) used Facebook and Line applications to obtain information before a flood event. Very few of the elderly respondents (<2%) accessed the national/provincial web-based platform to find out flood-related information. Almost all respondents, especially who are living in high-risk flood zones, had never participated in the community training of flood preparedness and management. Therefore, effective strategies in enhancing social engagement of the elderly and their literacy skills in flood risk preparedness and management are urgently needed.
OBJECTIVE: This study explored the approaches for community-based flood disaster management for older adults in Southern Thailand. It sought to understand community culture for supporting older adults and promoting community strength in case of flood disaster. METHOD: This was a qualitative content analysis study using data from observation, in-depth interviews, secondary data, and focus group discussion. One hundred and twenty-seven people in total were selected specifically for the study, including Local Administration Organization (LAO), community leaders, public sector officers, civil groups, and older adult groups and family caregivers. RESULTS: The results of this study were two main themes, focusing on 1) approaches to community-based flood disaster management for older adults as follows: eight approaches in the phase of prevention and preparedness in flood disaster management for older adults, eight approaches in the phase of response in flood disaster management for older adults, and six approaches in the phase of recovery and rehabilitation in flood disaster management for older adults; and 2) factors contributing to success in flood disaster management for older adults has four factors, including the human factor, the work factor, the data factor, and the resource factor. CONCLUSION: The findings showed significant roles in improving the potential and strength in community-based flood disaster management for older adults and providing suggestions for community nurses and health practice personnel involving in flood disaster management to mitigate the potential influence on older adults in the community.
BACKGROUND: Floods cause not only damage but also public health issues. Developing an application to simulate public health problems during floods around the Loei River by implementing geographic information system (GIS) and structural equation model (SEM) techniques could help improve preparedness and aid plans in response to such problems in general and at the subdistrict level. As a result, the effects of public health problems would be physically and mentally less severe. METHODS: This research and development study examines cross-sectional survey data. Data on demographics, flood severity, preparedness, help, and public health problems during floods were collected using a five-part questionnaire. Calculated from the population proportion living within 300 m of the Loei River, the sample size was 560 people. The participants in each subdistrict were recruited proportionally in line with the course of the Loei River. Compared to the empirical data, the data analysis examined the causal model of public health problems during floods, flood severity, preparedness, and help. The standardized factor loadings obtained from the SEM analysis were substituted as the loadings in the equations for simulating public health problems during floods. RESULTS: The results revealed that the causal model of public health problems during floods, flood severity, preparation, and help agreed with the empirical data. Flood severity, preparedness, and aid (χ(2) = 479.757, df = 160, p value <.05, CFI = 0.985, RMSEA = 0.060, χ(2)/df = 2.998) could explain 7.7% of public health problems. The computed values were applied in a GIS environment to simulate public health problem situations at the province, district, and subdistrict levels. CONCLUSIONS: Flood severity and public health problems during floods were positively correlated; in contrast, preparedness and help showed an inverse relationship with public health problems. A total of 7.7% of the variance in public health problems during floods could be predicted. The analysed data were assigned in the GIS environment in the developed application to simulate public health problem situations during floods.
OBJECTIVE: To examine the relationship between flood severity and risk of hospitalisation in the Vietnam Mekong River Delta (MRD). METHODS: We obtained data on hospitalisations and hydro-meteorological factors during 2011-2014 for seven MRD provinces. We classified each day into a flood-season exposure period: the 2011 extreme annual flood (EAF); 2012-2014 routine annual floods (RAF); dry season and non-flood wet season (reference period). We used province-specific Poisson regression models to calculate hospitalisation incidence rate ratios (IRRs). We pooled IRRs across provinces using random-effects meta-analysis. RESULTS: During the EAF, non-external cause hospitalisations increased 7.2% (95% CI 3.2% to 11.4%); infectious disease hospitalisations increased 16.4% (4.3% to 29.8%) and respiratory disease hospitalisations increased 25.5% (15.5% to 36.4%). During the RAF, respiratory disease hospitalisations increased 8.2% (3.2% to 13.5%). During the dry season, hospitalisations decreased for non-external causes and for each specific cause except injuries. CONCLUSIONS: We observed a gradient of decreasing risk of hospitalisation from EAF to RAF/non-flood wet season to dry season. Adaptation measures should be strengthened to prepare for the increased probability of more frequent extreme floods in the future, driven by climate change.
This study develops and assesses the application of a livelihood vulnerability index (LVI), LVI-IPCC and livelihood effect index for the natural and agricultural resources in Northwestern Pakistan. By using structured questionnaire, primary data were collected from the targeted households in the study region. Data on socio-demographics, water security, health, social networks and climate variability were collected from the targeted respondents in this study area, and combined into indices. The IPCC framework was utilized that characterizes vulnerability into exposure, sensitivity and its adaptive capacity. Findings of our study showed that tehsil Shabqadar was more vulnerable among three studied tehsils particularly in natural disasters, health, water and land holding status. Tehsil Tangi was the second high vulnerable tehsil followed by tehsil Charsadda relative to other LVI components with the exclusion of livelihood strategies and financial constraints. Findings of this study provide a better understanding of the social and behavioral trends as well as an integrated and holistic view of the agriculture, climate change and livelihoods process in assessing the vulnerability. The findings and this pragmatic approach will be helpful in intending specific strategies and policy effectiveness to lessen susceptibility of households to climatic variations.
Emergency medical service (EMS) is important for rescuing victims suffering from life-threatening illnesses or accidents, and is highly time-sensitive by nature. Many uncertain contexts in the urban environment can prolong EMS response time and deteriorate its performance. Using the enhanced two-step floating catchment area (E2SFCA) method, this study measures EMS accessibility with the effect of a regular uncertain context (i.e., the city dynamics like time-varying population and traffic) and an irregular uncertain context (i.e., an extreme pluvial flood event which can cause extensive road closures). The results indicate that, in the central urban area of Shanghai, mid-west areas with denser populations have higher accessibility than eastern peripheral areas. Flooding can cause a remarkable decline of accessibility which falls to the lowest point slightly earlier than the time when the worst road connectivity emerges. The night time exhibits better accessibility than especially the peak hours during the daytime. The GWR results reveal that increasing facility richness and road density while decreasing flood-induced road closures have a positive effect on EMS accessibility. The study indicates that both regular and irregular uncertain contextual factors can influence EMS accessibility in a highly complex manner. Carefully taking these uncertainties into account would enable EMS planning in other contexts and regions to face the enormous challenges posed by the changing climate and increasingly complex urban environment.
In recent years, the rainstorm and flood disasters frequently happened in cities and posed increasingly wide challenges. Therefore, the whole development process of urban rainstorm and flood disaster should be carried out for the reasonable and quantitative assessment on cities’ ability to respond to rainstorm and flood disasters, and the index system of risk assessment on regional flood disaster is constructed based on the three attributes of vulnerability, adaptability and restorability. 3 first-class and 14 s-class indexes are set up accordingly. The weight of each index is calculated by weighting methods which are both subjective and objective based on entropy-weight order relation. Then, the theoretical model for risk assessment is established by weighted clustering assessment. Finally, the empirical analysis was conducted on the current situation of rainstorm and flood disaster in 8 regions of a city in China. The results show that among the risk grade of rainstorm and flood disaster in 8 regions, there are 2 regions with grade-II higher risk, 5 regions with grade-III general risk and 1 region with grade-IV low risk. The consistency between assessment results and actual operation of cities indicates this model can be applied and effective to some extent.
People are always susceptible to a loss of stability in urban floodwaters that leads to serious casualties. Thus, the safety criterion for the instability of people in floodwaters must be determined. In this study, the hydrodynamic criterion of the instability of people in floodwaters in terms of the incipient velocity and water depth is derived using the probability method based on Shannon entropy theory. The derived model can characterize variations in the incipient velocity of people in floodwaters with respect to the inundating water depth. Furthermore, a comparison with seven experimental datasets available in the literature shows the validity of the proposed entropy-based model considering data scattering. A sensitivity analysis of the derived model to some of the incorporated parameters was performed, and the qualitative results are in accordance with our understanding of the physical mechanism of the instability of people in floodwaters. Taking the physical parameters (height and mass) of Chinese adults and children as a representative example, this study also showed the vulnerability degree of Chinese adults and children subject to floodwaters. These findings could provide a reference for administrators and stakeholders for flood hazard mitigation and flood strategy management. This study shows that an entropy-based method could be a valuable addition to existing deterministic models for characterizing the instability criterion of people in an urban flooding event.
The evaluation of emergency response capability under different pluvial flooding scenarios is an essential approach to improve the emergency response capability of flood disasters. A new evaluation method of emergency response capacity of urban public services is proposed based on urban pluvial flooding scenario simulation. Firstly, inundation area and depth under different pluvial flooding scenarios are simulated based on the SCS-CN model. Following that, space densities of all indicators include inundation area and depth, road network and the emergency public service institutions. Then, the indicator weight is determined by the combined weighting method of entropy weight and coefficient of variation. Finally, the emergency response capacity index (of each pixel) is calculated based on the graph stacking method. Taking Erqi District, Zhengzhou City as an example, the emergency response capacity of public service under different urban flooding scenarios is evaluated. The results show that the spatial distribution difference of public service emergency response capacity in Erqi District, Zhengzhou City is obvious, and with the increase of the precipitation return period, the high value area of public service emergency response capability decreases gradually and the low value area increases gradually. This method takes into account the specific urban flooding scenario and the layout of public service institutions and road networks that have strong practicability. the results of the evaluation can provide a reference for the construction of urban flood emergency response capacity and provide support for emergency decision-making.
Billions of people live in urban poverty, with many forced to reside in disaster-prone areas. Research suggests that such disasters harm child nutrition and increase adult morbidity. However, little is known about impacts on mental health, particularly of people living in slums. In this paper we estimate the effects of flood disasters on the mental and physical health of poor adults and children in urban Indonesia. Our data come from the Indonesia Family Life Survey and new surveys of informal settlement residents. We find that urban poor populations experience increases in acute morbidities and depressive symptoms following floods, that the negative mental health effects last longer, and that the urban wealthy show no health effects from flood exposure. Further analysis suggests that worse economic outcomes may be partly responsible. Overall, the results provide a more nuanced understanding of the morbidities experienced by populations most vulnerable to increased disaster occurrence.
In this study, tweets related to fires in Riau, Sumatra, were identified using carefully selected keywords for the 2014-2019 timeframe. The TAGGS algorithm was applied, which allows for geoparsing based on the user’s nationality and hometown and on direct referrals to specific locations such as name of province or name of city in the message itself. Online newspapers covering Riau were analyzed for the year 2019 to provide additional information about the reasons why fires occurred and other factors, such as impact on people’s health, animal mortality related to ecosystem disruption, visibility, decrease in air quality and limitations in the government firefighting response. Correlation analysis between meteorological information, Twitter activity and satellite-derived hotspots was conducted. The existing approaches that BMKG and other Indonesian agencies use to detect fire activity are reviewed and a novel approach for early fire detection is proposed based on the crowdsourcing of tweets. The policy implications of these results suggest that crowdsourced data can be included in the fire management system in Indonesia to support early fire detection and fire disaster mitigation efforts.
INTRODUCTION: Global climate change (global warming) has been identified as the primary factor responsible for the observed increase in frequency and severity of wildfires (also known as bushfires in some countries) throughout the majority of the world’s vegetated environments. This trend is predicted to continue, causing significant adverse health effects to nearby residential populations and placing a potential strain on local emergency departments (EDs). STUDY OBJECTIVE: The aim of this literature review was to identify papers relating to wildfires and their impact on EDs, specifically patient presentation characteristics, resource utilization, and patient outcomes. METHOD: This integrative literature review was guided by the Preferred Reporting Items of Systematic Reviews and Meta-Analysis (PRISMA) guidelines for data collection, and Whittemore and Knafl’s framework for data analysis. Data were collected from OvidSP, MEDLINE, DARE, CINAHL, PubMed, and Scopus databases. Various Medical Subject Headings (MeSH) and keywords identified papers relevant to wildfires/bushfires and EDs. RESULTS: Literature regarding the relationship between ED presentations and wildfire events, however, is primarily limited to studies from the United States and Australia and indicates particulate matter (PM) is principally linked to adverse respiratory and cardiovascular outcomes. Observable trends in the literature principally included a significant increase in respiratory presentations, primarily with a lag of one to two days from the initial event. Respiratory and cardiovascular studies that stratified results by age indicated individuals under five, over 65, or those with pre-existing conditions formed the majority of ED presentations. CONCLUSION: Key learnings from this review included the need for effective and targeted community advisory programs/procedures, prior to and during wildfire events, as well as pre-event planning, development, and robust resilience strategies for EDs.
The depletion of air quality is a major problem that is faced around the globe. In Australia, the pollutants emitted by bushfires play an important role in making the air polluted. These pollutants in the air result in many adverse impacts on the environment. This paper analysed the air pollution from the bushfires from November 2019 to July 2020 and identified how it affects the human respiratory system. The bush fires burnt over 13 million hectares, destroying over 2400 buildings. While these immediate effects were devastating, the long-term effects were just as devastating, with air pollution causing thousands of people to be admitted to hospitals and emergency departments because of respiratory complications. The pollutant that caused most of the health effects throughout Australia was Particulate Matter (PM) PM(2.5) and PM(10). Data collection and analysis were covered in this paper to illustrate where and when PM(2.5) and PM(10,) and other pollutants were at their most concerning levels. Susceptible areas were identified by analysing environmental factors such as temperature and wind speed. The study identified how these pollutants in the air vary from region to region in the same time interval. This study also focused on how these pollutant distributions vary according to the temperature, which helps to determine the relationship between the heatwave and air quality. A computational model for PM(2.5) aerosol transport to the realistic airways was also developed to understand the bushfire exhaust aerosol transport and deposition in airways. This study would improve the knowledge of the heat wave and bushfire meteorology and corresponding respiratory health impacts.
Australia often experiences natural disasters and extreme weather conditions such as: flooding, sandstorms, heatwaves, and bushfires (also known as wildfires or forest fires). The proportion of the Australian population aged 65 years and over is increasing, alongside the severity and frequency of extreme weather conditions and natural disasters. Extreme heat can affect the entire population but particularly at the extremes of life, and patients with morbidities. Frequently identified as a vulnerable demographic in natural disasters, there is limited research on older adults and their capacity to deal with extreme heat and bushfires. There is a considerable amount of literature that suggests a significant association between mental disorders such as dementia, and increased vulnerability to extreme heat. The prevalence rate for dementia is estimated at 30%by age 85 years, but there has been limited research on the effects extreme heat and bushfires have on individuals living with dementia. This review explores the differential diagnosis of dementia, the Australian climate, and the potential impact Australia’s extreme heat and bushfires have on individuals from vulnerable communities including low socioeconomic status Indigenous and Non-Indigenous populations living with dementia, in both metropolitan and rural communities. Furthermore, we investigate possible prevention strategies and provide suggestions for future research on the topic of Australian bushfires and heatwaves and their impact on people living with dementia. This paper includes recommendations to ensure rural communities have access to appropriate support services, medical treatment, awareness, and information surrounding dementia.
In Malaysia, floods are often considered a normal phenomenon in the lives of some communities, which can sometimes cause disasters to occur beyond expectations, as shown during the flood of 2014. The issue of flood disasters, which particularly impacts SDG 13 of the integrated Sustainable Development Goals (SDGs), still lacks widespread attention from sociology researchers in Malaysia. Similarly, questions related to the welfare of victims, especially in regards to aspects of disaster management from a humanitarian perspective, are still neglected. This study aims to identify the adaptive actions through a solution from a humanitarian perspective in managing flood disaster risks. For the purpose of obtaining data, this study used a qualitative approach with a case study design. Data were collected using in-depth interviews and non-participant observation methods. A total of ten experts, consisting of the flood management teams involved in managing the 2014 flood disaster in Hulu Dungun, Terengganu, Malaysia, were selected through a purposive random sampling method. The results showed that adaptive actions in managing flood disaster risks from a humanitarian point of view include the provision of social support, collective cooperation from the flood management teams, and adaptation efforts after the floods.
OBJECTIVES: In this paper, we explore the exposure to risk and experiences of people with disability and carers during a flooding event and the subsequent mental health impacts. DESIGN: A cross-sectional survey between September and November 2017. Binary logistic regression models were used to investigate associations between the mental health of people with disability and carers and their exposure to the flood. Inductive content analysis was used to analyse qualitative data. SETTING: Flood-affected communities in the rural area of Northern Rivers, New South Wales, Australia, 6 months after river flooding in 2017. PARTICIPANTS: People over 16 years and a resident in the Northern Rivers at the time of the flood were invited to participate. Using a purposive, snowballing sampling technique participants were drawn from a wide range of socioeconomic backgrounds and had experienced different degrees of flood exposure. RESULTS: Of 2252 respondents, there were 164 people with disability and 91 carers. Both groups had increased odds of having their home flooded (people with a disability: OR 2.41 95% CI 1.71 to 3.39; carers: OR 1.76 95% CI 1.10 to 2.84). On evacuation, respondents reported inaccessible, conflicting and confusing information regarding flood warnings. Essential services such as healthcare and social services were disrupted (people with a disability: OR 3.98 95% CI 2.82 to 5.60; carers 2.17 95% CI 1.33 to 3.54) and access to safe and mould free housing post flood event was limited. After taking sociodemographic factors into account, respondents with a disability and carers had greater odds of probable post-traumatic stress disorder compared with other respondents (people with a disability: 3.32 95% CI 2.22 to 4.96; carers: 1.87 95% CI 1.10 to 3.19). CONCLUSION: Our findings show the profound impact and systemic neglect experienced by people with disability and carers during and after the 2017 flood event in the Northern Rivers. As people with disability will take longer to recover, they will require longer-term tailored supports and purposeful inclusion in flood preparedness and recovery efforts.
Flood events can be dramatic and traumatic. People exposed to floods are liable to suffer from a variety of adverse mental health outcomes. The adverse effects of stressors during the recovery process (secondary stressors) can sometimes be just as severe as the initial trauma. Six months after extensive flooding in rural Australia, a survey of 2530 locals was conducted focusing on their flood experiences and mental health status. This mixed methods study analysed (a) quantitative data from 521 respondents (21% of total survey respondents) who had insurance coverage and whose household was inundated, 96 (18%) of whom reported an insurance dispute or denial; and (b) qualitative data on insurance-related topics in the survey’s open comments sections. The mental health outcomes were all significantly associated with the degree of flood inundation. The association was strong for probable PTSD and ongoing distress (Adjusted Odds Ratios (AORs) with 95% confidence intervals 2.67 (1.8-4.0) and 2.30 (1.6-3.3), respectively). The associations were less strong but still significant for anxiety and depression (AORs 1.79 (1.2-2.7) and 1.84 (1.2-2.9)). The secondary stressor of insurance dispute had stronger associations with ongoing distress and depression than the initial flood exposure (AORs 2.43 (1.5-3.9) and 2.34 (1.4-3.9), respectively). Insurance was frequently mentioned in the open comment sections of the survey. Most comments (78% of comments from all survey respondents) were negative, with common adverse trends including dispute/denial, large premium increases after a claim, inconsistencies in companies’ responses and delayed assessments preventing timely remediation.
There is substantial evidence that in the aftermath of a disaster, an individual’s sense of coherence (SOC) plays an important role in promoting one’s sense of well-being. The SOC is regarded as a core component of the salutogenic model of mental health. Disaster survivors are frequently subjected to traumatic experience and have higher psychological distress prevalence rates than people in the general population. The present study aimed to investigate possible socio-demographic differences (gender and age) on the sense of coherence (SOC) among disaster survivors in Indonesia. A total of 194 respondents (71 male and 123 females) from across the country participated in the online survey. A factorial ANOVA using JASP was conducted to investigate the main effects of gender and age groups and the interaction effect of these variables on the SOC level. The findings were two folds, age group variance was significantly associated with the SOC, while gender did not significantly associate with the SOC. The main effect of Age groups was F (2, 962.773) = 4.307, p = 0.005, indicating a significant difference of SOC between young adult, middle adult, and late adult groups.
OBJECTIVE: The impact of the 2018 Japan Floods on prescriptions of Yokukansan was evaluated. METHODS: This was a retrospective cohort study based on the National Database of Health Insurance Claims which covers all the prescriptions issued in Japan. Participants were patients aged 65 or older who received any medical care at medical institutions located in the three most-severely affected prefectures between 1 year before and after the disaster. We analyzed the number of new prescriptions of Yokukansan and other Kampo drugs among those who had not been prescribed any Kampo for 1 year before the disaster. Kaplan-Meier analysis and a Cox proportional hazards model were used to evaluate the risk of the disaster for a new prescription. RESULTS: Subjects comprised 1,372,417 people (including 12,787 victims, 0.93%). The hazard ratio (HR) of the disaster for Yokukansan prescriptions was 1.49 [95% confidence intervals (CI): 1.25-1.78], and 1.54 (95% CI: 1.29-1.84) in the crude and age-sex adjusted model, respectively. The HR of the disaster for prescription of other Kampo drugs in the crude and adjusted model was 1.33 (95% CI: 1.27-1.39), and 1.32 (95% CI: 1.27-1.38), respectively. The magnitude of increase of victims prescribed Yokukansan (31.4%) was statistically higher than for those prescribed other Kampo drugs (19.3%) (p < 0.001). CONCLUSION: The disaster increased prescriptions of both Yokukansan and other Kampo drugs among elderly victims. The increase was more remarkable in Yokukansan than other Kampo drugs. Clinicians and policymakers should be aware of the increased need for Yokukansan in times of natural disaster.
PURPOSE: Natural disaster has an impact on mental health. The 2018 Japan Floods, which took place in July 2018 were one of the largest water disasters in Japan’s recorded history. We aimed to evaluate the change in the number of benzodiazepine prescriptions by physicians before and after the disaster. METHODS: A retrospective cohort study based on the National Database of Health Insurance Claims was conducted in the flood-stricken areas between July 2017 and June 2019. The subjects were divided between victims and non-victims according to certification by local governments. Members of both groups were then categorized into three groups based on their pre-flood use of benzodiazepines: non-user, occasional user, and continuous user. Difference-in-differences (DID) analysis with a logistic regression model was conducted to estimate the effect of the disaster among victims by comparing the occurrence of benzodiazepine prescriptions before and after the disaster. RESULTS: Of 5,000,129 people enrolled, 31,235 were victims. Among all participants, the mean prescription rate for benzodiazepines in victims before the disaster (11.3%) increased to 11.8% after the disaster, while that in non-victims (8.3%) decreased to 7.9%. The DID analysis revealed that benzodiazepine prescription among victims significantly increased immediately after the disaster (adjusted ratio of odds ratios (ROR) 1.07: 95% confidence interval 1.05-1.11), and the effect of the disaster persisted even 1 year after the disaster (adjusted ROR 1.2: 95% confidence interval 1.16-1.24). CONCLUSION: The flood increased the number of benzodiazepines prescriptions among victims, and the effect persisted for at least 1 year.
Thailand has faced many flooding crises, especially in 2011, which caused widespread damage to indus-trial parks and community zones. However, the nega-tive consequences of flooding on the local people and workers in industrial zones have been little studied. This study focuses on the impacts of flooding after 2011 on the well-being of residents in industrial zones in terms of their work and livelihoods. Community -based research was used to explore the effects of floods on 647 respondents who worked in Rojana Indus-trial Park (N = 247) and those who lived around the park (N = 400). A questionnaire survey was con-ducted in February 2020. The results showed adverse impacts on the economy, accommodation, and well-being of both the local inhabitants and workers, whose monthly incomes and overtime jobs decreased signif-icantly compared to before the disaster. However, lo-cal people suffered more from low incomes than work-ers of the company, as the employees’ work status was maintained during the crisis. Japanese company cul-ture is investigated as a factor in the higher resilience and recovery levels of company employees than the Rojana community. In addition, the workers were evacuated to other accommodations until the com-pany recovered, while locals remained in their flooded homes. In addition, most respondents reported that mental health impacts were more likely to affect their mental health. For effective recovery and flood risk management, the government should follow up on em-ployment, accommodation, and livelihood after a sud-den flood, especially for the local people. A greater understanding of community risk, community engage-ment, and awareness-raising activities can enhance readiness, response, recovery, and resilience in disas-ter management by government, businesses, and local communities.
Developing countries are increasingly impacted by floods, especially in Asia. Traditional flood risk man-agement, using structural measures such as levees, can have negative impacts on the livelihoods of social groups that are more vulnerable. Ecosystem-based adaptation (EbA) provides a complementary approach that is potentially more inclusive of groups that are commonly described as more vulnerable, such as the poor and women. However, there is a lack of disaggregated and quantitative information on the potential of EbA to support vulnerable groups of society. This paper provides a quantitative analysis of the differ-ences in vulnerability to flooding as well as preferences for EbA benefits across income groups and gen -der. We use data collected through a survey of households in urban and rural Central Vietnam which included a discrete choice experiment on preferences for ecosystem services. A total of 1,010 households was surveyed during 2017 through a random sampling approach. Preferences are measured in monetary and non-monetary terms to avoid issues that may arise from financial constraints faced by respondents and especially the more vulnerable groups. Our results reveal that lower income households and women are overall more vulnerable than their counterparts and have stronger preferences for the majority of the EbA benefits, including flood protection, seafood abundance, tourism, and recreation suitability. These findings strongly indicate that EbA is indeed a promising tool to support groups of society that are espe-cially vulnerable to floods. These results provide crucial insights for future implementation of EbA pro-jects and for the integration of EbA with goals targeted at complying with the Sendai Framework and Sustainable Development Goals. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
The 2014 flood disaster has brought physical destruction, damage as well as social disruption that caused normal life to become less stable. A state of social equilibrium needs to be restored through effective restoration solutions to normalise life after the disaster. This qualitative research aims to identify two main issues, namely social disruption and social resilience, by utilising a case study of the 2014 flood disaster in Hulu Dungun, Terengganu. A total of 15 victims were selected using the purposive sampling method based on a set of defined criteria-the data collection method comprised of in-depth interviews and non-participant observation. The data were analysed through thematic analysis techniques. The results showed that the disruption suffered by the victims included disruption of social roles, the uncertainty of employment, instability of social routine, and collective trauma. However, the availability of social resilience had enabled the victims to rebuild their lives after flood disasters and restore the ‘normal’ or ‘stable’ situations of social equilibrium. The research is expected to contribute to environmental sociology that has yet to receive widespread attention from sociological researchers in Malaysia. This research is a meaningful effort towards promoting and increasing the environmental sociology study, which to date, remains disoriented.
Floods have become the most prevalent natural disaster in the world. Understanding the emotional impact of floods on people helps reduce negative mass incidents and contributes to the implementation of disaster prevention and mitigation. This study collected online discussions related to the great flood in the middle and lower reaches of the Yangtze River basin in China in 2020. Then, we obtained the sentiments of people and the deep thoughts behind their negative sentiment through the dictionary sentiment analysis and the LDA topic modeling, counting them according to the regions. The overall sentiment of Internet users during this flood was neutral, and the posts showing negative sentiment were mostly from the affected areas. People in the affected areas were highly concerned about personal safety and property, whose negative emotions were directed towards the flood prevention work and the relocation of affected people.
With extreme weather events on the rise, the question of how witnessing adverse weather events may affect individuals’ perception, and consequently their subjective well-being, gains in relevance. To identify events that have been witnessed, i.e., tangential exposure to a weather shock, satellite-based data on flooding is linked to an extensive household panel survey from rural Southeast Asia. Contrasting direct shock experience with tangential shock exposure, we find that mere proximity to a potentially adverse shock, without reporting any actual direct shock experience, could be sufficient to reduce subjective well-being. This effect is not only restricted to the present but can also impinge on expected future well-being dynamics. Eventually, such a persistent effect from witnessing a weather shock may have further politico-economic repercussions, for instance, by altering support for redistribution policies.
Since the outbreak of coronavirus disease 2019 (COVID-19), adolescents in 70 countries have suffered the COVID-19 pandemic and flood disasters simultaneously. Although antecedent cyberbullying variables have attracted significant research attention, the effects of psychological distress and the potential mechanisms of cyberbullying among adolescents under multiple disasters remains unclear. Based on social-ecological system theory, this study examines the moderating effects of parent-child relationships and the negotiable fate on the relationship between psychological distress and cyberbullying. A total of 1204 middle school students (52.4% boys) who suffered from floods and the COVID-19 pandemic from Zhengzhou City, China, are the participants. The results reveal that psychological distress was positively related to adolescent cyberbullying during a disaster. Parent-child relationships and negotiable fate significantly moderate the relationship between psychological distress and cyberbullying. Specifically, high parent-child relationships and a high negotiable fate could protect adolescents from the negative effects of psychological distress of cyberbullying. For adolescents with low or high parent-child relationships and low negotiable fate, the links between psychological distress and cyberbullying are stronger. These findings underline the significance of considering the interaction of psychological distress, parent-child relationships, and negotiable fate when examining adolescents’ cyberbullying during disasters.
Due to climate change and rapid urbanization, contemporary cities face the dual challenges of providing sufficient stormwater management and adequate park services, which potentially conflict over limited space and resources. To solve these problems, cities are increasingly combining stormwater infrastructure with park space in ways that create new efficiencies. To date, most research has focused on the stormwater management performance aspect of these combinations and not the techniques employed to achieve the combined goals. To fill this gap, 23 sponge city parks in Shanghai were investigated to examine the combination of stormwater and park services. Our findings show that stormwater techniques were primarily combined with the park facilities of water areas, paved open spaces, and pathways. Additionally, we found that larger parks employed a wider range of techniques for managing stormwater runoff and supported broader sets of park activities, while those at smaller scales prioritized infiltration, detention, and purification measures, as well as concentrated on social and economic activities. This study is the first to explore SPC parks that integrate stormwater management and park services, thereby providing implications for SPC development in China and insights into the ways that the two properties can be combined in other cities.
BACKGROUND: /Objective: Flooding risk is a global issue, and various approaches have been established to prevent flooding risk around the world. China is one of the heavily flood-affected countries and has been implementing the Sponge City program since 2015 to defend against flooding. Unfortunately, flooding has been common in China in recent years, causing severe health risks to citizens. This research mainly focuses on (a) evaluating the implementation of China’s Sponge City program and the associated impacts on human health and (b) exploring the future improvement of the Sponge City program in China. METHODS: The Interpretive Document Approach was used to explore an inclusive review of the Sponge City program and its implications on human health. RESULTS: /Findings: The Sponge City program in China is still insufficient to prevent flooding risks effectively. In the past eight years, 24/34 provinces have recorded flooding, which caused a total of 4701 deaths and over 525.5 billion RMB (around 72.9 billion US$) in economic loss. Till now, only 64/654 cities have promulgated local legislation to manage sponge city construction, although the Sponge City was implemented in 2015. Besides, the completed Sponge City program constructions cannot fully prevent flooding risks, the flood prevention capacity is limited. The Sponge City program is not granted priority, lacking national legislation hinders Sponge City program implementation in China. CONCLUSIONS: China needs to make national legislation on the Sponge City program and update the Sponge City program technology guidelines. Local governments should implement Sponge City construction according to local geographic environments.
Background: Children’s flood risk perceptions that include their awareness and behaviors, can be cultivated through disaster education, which is crucial for improving disaster resilience and adaptation to climate extremes. However, education’s co-influencing effect along with family and society was unclear. This study investigated a three-year disaster education program conducted in schools in Sichuan Province, China. Method: In three pilot counties, we used stratified duster sampling in 2016 and 2018 to separately survey the risk perceptions of 2,105 children (baseline) and 1710 children (post-intervention), respectively, aged 8-12, in 45 primary schools. The Ordinary Least Squares Regression and Propensity Score Matching Method (PSM) were used to assess the effectiveness of classroom education, propaganda poster, professional guidance, social education (television, radio, friends, and internet), and risk-related parent-child interactions. Interaction items and Structure Equation Model (SEM) were performed to identify their co-influencing mechanisms. Finally, the intervention effect was assessed by categorizing different levels of parent-child interactions and left-behind status. Result: The classroom education (Coeff = 0.040; P < 0.05), propaganda poster (Coeff = 0.024; P < 0.05), and professional guidance (Coeff = 0.016; P < 0.1) had significantly positive effects on children's flood risk perception. But these effects were found to be underestimated using PSM. Interaction effects between disaster education and parent-child interaction were statistically significant, and parent-child interaction was a moderating factor for improving risk perception (standardized indirect effect = 0.055, p < 0.001). Additionally, the mean score of risk perception increased by 118% in 2018 compared with the baseline. It was found that the higher the level of risk-related parent-child interaction, the higher the mean scores of risk perception (Coeff = 0.055; P < 0.001) irrespective whether they are left-behind children. Conclusion: To improve disaster resilience and climate change adaptation, risk-related parent-child interaction should be considered in disaster education, which is an effective way to promote children's risk perceptions. (C) 2020 Published by Elsevier B.V.
In this study, we investigated the flooding accident that occurred on Metro Line 5 in the capital city of Zhengzhou, Henan Province, China. On 20 July 2021, owing to an extreme rainstorm, serious inundation occurred in the Wulongkou parking lot of Zhengzhou Metro Line 5 and its surrounding area. Flooding forced a train to stop during operation, resulting in 14 deaths. Based on our preliminary investigation and analysis of this accident, we designed three main control measures to reduce the occurrence of similar accidents and mitigate the impact of similar accidents in the future, given the increasing number of extreme storm weather events in recent years: (1) to conduct subway flood risk assessments and to establish an early warning system, involving real-time monitoring of meteorological information during subway operation and construction; (2) to improve subway flood control emergency plans and to establish a response mechanism for subway flooding; and (3) to strengthen safety awareness training to ensure the orderly evacuation of people after accidents.
Air pollution and extreme heat have been responsible for more than a million deaths in China every year, especially in densely urbanized regions. While previous studies intensively evaluated air pollution episodes and extreme heat events, a limited number of studies comprehensively assessed atmospheric hot-and-polluted-episodes (HPE) – an episode with simultaneously high levels of air pollution and temperature – which have potential adverse synergic impacts on human health. This study focused on the Pearl River Delta (PRD) region of China due to its high temperature in summer and poor air quality throughout a year. We employed geostatistical downscaling to model meteorology at a spatial resolution of 1 km, and applied a machine learning algorithm (XGBoost) to estimate a high-resolution (1 km) daily concentration of particulate matter with an aerodynamic diameter ≤2.5 μm (PM(2.5)) and ozone (O(3)) for June to October over 20 years (2000-2019). Our results indicate an increasing trend (∼50%) in the frequency of HPE occurrence in the first decade (2000-2010). Conversely, the annual frequency of HPE occurrence reduced (16.7%), but its intensity increased during the second decade (2010-2019). The northern cities in the PRD region had higher levels of PM(2.5) and O(3) than their southern counterparts. During HPEs, regional daily PM(2.5) exceeded the World Health Organization (WHO) and Chinese guideline levels by 75% and 25%, respectively, while the O(3) exceeded the WHO O(3) standard by up to 69%. Overall, 567,063 (95% confidence interval (CI): 510,357-623,770) and 52,231 (95%CI: 26,116-78,346) excessive deaths were respectively attributable to exposure to PM(2.5) and O(3) in the PRD region. Our findings imply the necessity and urgency to formulate co-benefit policies to mitigate the region’s air pollution and heat problems.
INTRODUCTION: There is a large body of epidemiological evidence showing significantly increased mortality risks from air pollution and temperature. However, findings on the modification of the association between air pollution and mortality by temperature are mixed. METHODS: We used a varying coefficient distributed lag model to assess the complex interplay between air temperature and PM(2.5) on daily mortality in Guangzhou City from 2013 to 2020, with the aim of establishing the PM(2.5)-mortality association at different temperatures and exploring synergetic mortality risks from PM(2.5) and temperature on vulnerable populations. RESULTS: We observed near-linear concentration-response associations between PM(2.5) and mortality across different temperature levels. Each 10 μg/m³ increase of PM(2.5) in low, medium, and high temperature strata was associated with increments of 0.73% [95% confidence interval (CI): 0.38%, 1.09%], 0.12% (95% CI: -0.27%, 0.52%), and 0.46% (95% CI: 0.11%, 0.81%) in non-accidental mortality, with a statistically significant difference between low and medium temperatures (P=0.02). There were significant modification effects of PM(2.5) by low temperature for cardiovascular mortality and among individuals 75 years or older. CONCLUSIONS: Low temperatures may exacerbate physiological responses to short-term PM(2.5) exposure in Guangzhou, China.
Background: Preterm birth contributes to the morbidity and mortality of newborns and infants. Recent studies have shown that maternal exposure to particulate matter and extreme temperatures results in immune dysfunction, which can induce preterm birth. This study aimed to evaluate the association between fine particulate matter (PM(2.5)) exposure, temperature, and preterm birth in Seoul, Republic of Korea. Methods: We used 2010-2016 birth data from Seoul, obtained from the Korea National Statistical Office Microdata. PM(2.5) concentration data from Seoul were generated through the Community Multiscale Air Quality (CMAQ) model. Seoul temperature data were collected from the Korea Meteorological Administration (KMA). The exposure period of PM(2.5) and temperature were divided into the first (TR1), second (TR2), and third (TR3) trimesters of pregnancy. The mean PM(2.5) concentration was used in units of ×10 µg/m(3) and the mean temperature was divided into four categories based on quartiles. Logistic regression analyses were performed to evaluate the association between PM(2.5) exposure and preterm birth, as well as the combined effects of PM(2.5) exposure and temperature on preterm birth. Result: In a model that includes three trimesters of PM(2.5) and temperature data as exposures, which assumes an interaction between PM(2.5) and temperature in each trimester, the risk of preterm birth was positively associated with TR1 PM(2.5) exposure among pregnant women exposed to relatively low mean temperatures (<3.4 °C) during TR1 (OR 1.134, 95% CI 1.061-1.213, p < 0.001). Conclusions: When we assumed the interaction between PM(2.5) exposure and temperature exposure, PM(2.5) exposure during TR1 increased the risk of preterm birth among pregnant women exposed to low temperatures during TR1. Pregnant women should be aware of the risk associated with combined exposure to particulate matter and low temperatures during TR1 to prevent preterm birth.
This study aims to quantitatively identify the economic value of the comprehensive improvement of environmental degradations caused by climate change. The research method applied to that is the choice experiment. Fine particulate matter, algae bloom, and heat waves were selected as individual attributes constituting environmental problems. It was found that the willingness to pay could not be induced for any level of improvement in algal bloom. It was concluded that if heat waves improved to the medium level where the number of heat-related illnesses and estimated deaths decreased by 50% compared to the current level, there would be a loss in value by USD 13.33. The value of improving environmental problems is USD 7.69 per household per year, and the improvement of fine particulate matter was the highest value attributed by consumers. This study is significant in that it comprehensively evaluates severe environmental problems, reflects their priorities and importance, and assesses the value for each level. It provides important foundational data for establishing effective budget input strategies to maximize consumer benefits and aids in the preparation of effective policies by establishing more detailed goals to achieve net-zero carbon emissions and the Sustainable Development Goals.
Mounting studies have associated asthma with environmental and climatic factors, but their interaction during pregnancy on childhood asthma are unclear. This study aims to investigate the interaction of in utero air pollution and environmental temperature exposure on childhood asthma, to identify key timing windows for exposure. A retrospective cohort study with 2,598 pre-schoolers was conducted during 2011-2012 in Changsha, China. Maternal exposure to three critical ambient air pollutants (PM10, SO2 and NO2, as proxies of industrial and vehicular air pollution) and temperature (T), was assessed for the 40 gestational weeks, three trimesters of gestation, and entire pregnancy by an inverse distance weighted (IDW) method. Logistic regression analysis was used to examine the association of childhood asthma with air pollution and temperature exposure. Our results showed that pre-schooler’s asthma was significantly associated with SO2 and NO2 exposure in utero, ORs = 1.46 (95% CI: 1.12-1.89) and 1.67 (95% CI: 1.24-2.26) by inter quartile range (IQR) increase of their exposure respectively. Significant risk was observed for exposure of SO2 and NO2 particularly during the 1st and 2nd trimesters and their specific gestational weeks. Pre-schooler’s asthma was related with high temperature expo-sure during 1st trimester, OR = 2.33 (95% CI: 1.11-4.90) by IQR increase of T exposure. Low T and high T respectively increased the asthma risk of NO2 exposure in the 1st and 3rd trimester. Boys were more susceptible to the temperature-pollution interaction on asthma development. Our study indicates that low and high tem-perature respectively during early and late pregnancy significantly increased the impact of air pollution exposure in utero on pre-schooler’s asthma.
BACKGROUND: Although low temperature and air pollution exposures have been associated with the risk of anxiety, their combined effects remain unclear. OBJECTIVE: To investigate the independent and interactive effects of low temperature and air pollution exposures on anxiety. METHOD: Using a case-crossover study design, the authors collected data from 101,636 outpatient visits due to anxiety in three subtropical Chinese cities during the cold season (November to April in 2013 through 2018), and then built conditional logistic regression models based on individual exposure assessments [temperature, relative humidity, particulate matter (PM(2.5), PM(10)), sulfur dioxide (SO(2)), and nitrogen dioxide (NO(2))] and twelve cold spell definitions. Additive-scale interactions were assessed using the relative excess risk due to interaction (RERI). RESULTS: Both cold spell and air pollution were significantly associated with outpatients for anxiety. The effects of cold spell increased with its intensity, ranging from 8.98% (95% CI: 2.02%, 16.41%) to 15.24% (95% CI: 6.75%, 24.39%) in Huizhou. Additionally, each 10 μg/m(3) increase of PM(2.5), PM(10), NO(2) and SO(2) was associated with a 1.51% (95% CI: 0.61%, 2.43%), 1.58% (95% CI: 0.89%, 2.28%), 13.95% (9.98%, 18.05%) and 11.84% (95% CI: 8.25%, 15.55%) increase in outpatient visits for anxiety. Synergistic interactions (RERI >0) of cold spell with all four air pollutants on anxiety were observed, especially for more intense cold spells. For particulate matters, these interactions were found even under mild cold spell definitions [RERI: 0.11 (95% CI: 0.02, 0.21) for PM(2.5), and 0.24 (95% CI: 0.14, 0.33) for PM(10)]. Stratified analyses yielded a pronounced results in people aged 18-65 years. CONCLUSIONS: These findings indicate that both cold spell and air pollution are important drivers of the occurrence of anxiety, and simultaneous exposure to these two factors might have synergistic effects on anxiety. These findings highlight the importance of controlling air pollution and improving cold-warning systems.
BACKGROUND: The extreme thermal environment driven by climate change disrupts thermoregulation in pregnant women and may threaten the survival of the developing fetus. OBJECTIVES: To investigate the acute effect of maternal exposure to thermophysiological stress (measured with Universal Thermal Climate Index, UTCI) on the risk of stillbirth and modification of this effect by sociodemographic disparities. METHODS: We conducted a space-time-stratified case-crossover analysis of daily UTCI and 2835 singleton stillbirths between 1st January 2000 and 31st December 2015 across multiple small areas in Western Australia. Distributed lag non-linear models were combined with conditional quasi-Poisson regression to investigate the effects of the UTCI exposure from the preceding 6 days to the day of stillbirth. We also explored effect modification by fetal and maternal sociodemographic factors. RESULTS: The median UTCI was 13.9 °C (representing no thermal stress) while the 1st and 99th percentiles were 0.7 °C (slight cold stress) and 31.7 °C (moderate heat stress), respectively. Relative to median UTCI, we found positive associations between acute maternal cold and heat stresses and higher risks of stillbirth, increasing with the intensity and duration of the thermal stress episodes. The cumulative risk from the preceding 6 days to the day of stillbirth was stronger in the 99th percentile (RR = 1.19, 95% CI: 1.17, 1.21) than the 1st percentile (RR = 1.14, 95% CI: 1.12, 1.15), relative to the median UTCI. The risks were disproportionately higher in term and male stillborn fetuses, smoking, unmarried, ≤19 years old, non-Caucasian, and low socioeconomic status mothers. DISCUSSION: Acute maternal exposure to both cold and heat stresses may contribute to the risk of stillbirth and be exacerbated by sociodemographic disparities. The findings suggest public health attention, especially for the identified higher-risk groups. Future studies should consider the use of a human thermophysiological index, rather than surrogates such as ambient temperature.
Qinghai-Tibet Plateau (QTP) is one of the most sensitive regions to climate change in the world. As a result, people in the QTP are more likely to be sensitively affected by climate change than those in other regions, particularly in the poverty area. Using the Universal Thermal Climate Index (UTCI) derived from ERA5 and population data, changes in annual thermal comfort condition and population under such condition in the QTP are systematically analyzed. The results reveal that there is considerable regional heterogeneity in the distribution of UTCI and the number of comfortable days (CDs), mainly due to the complex geographic features. In most areas of the QTP, the increase in UTCI leads to an increased number of comfortable days. Spatial distribution and temporal change in the number of comfortable days are found to be principally related to altitude. In areas within altitudes of 3000-4500 m, the number of comfortable days increases by up to 6 d per decade, which is faster than that in higher elevation areas above 4500 m. Results also indicate that thermal comfortable condition has improved in areas of 2500-5000 m (medium to high altitude), particularly in spring and autumn. Further research indicates that population distribution also shows a regional clustering feature, with the majority of residents residing in cities and their vicinities, where a higher number of comfortable days were observed. Most areas with a greater number of comfortable days have experienced a more significant increase in population under thermal comfortable conditions. It implies that climate change more likely has a large influence on population in the QTP. These findings are expected to enhance tourism development and the assessment of the impact on the living environment. The findings can be helpful for optimizing of tourism development and better understanding how climate change affects population distribution.
Thermal comfort and environmental health in scenic open spaces, a communication bridge between tourists and their environment, are prerequisites for tourism activities. In this study, scenic open spaces in an urban area of Xi’an, China were selected. Thermal perception (thermal sensation, comfort and acceptability) of residents and tourists were investigated through meteorological measurement and questionnaire survey. Physiological equivalent temperature (PET) was used to determine thermal benchmarks of all visitors to the site. Variables that influence individual thermal perception assessment (physical, individual, society and psychology) were measured and compared. Finally, a series of strategies and suggestions were proposed based on meteorological characteristics and influencing factors of thermal perception from perspectives of designers and scenic spot managers. Results show that: 1) Neutral PET (NPET) of respondents were 17.3 °C (residents) and 15.5 °C (tourists). Neutral PET ranges (NPETR) were 8.9-25.8 °C (residents) and 7.2-23.8 °C (tourists). Preferred PET values were 20.1 °C (residents) and 19.7 °C (tourists). Thermal acceptability ranges (TAR) were 6.3-37.8 °C (residents) and 0.5-39.9 °C (tourists). 2) In winter, physical factors were primary influencers of residents’ thermal perception, followed by social factors, while tourists’ thermal perception was mainly influenced by physical factors. In spring, physical factors were still the primary influencers for residents, followed by individual factors. Physical factors were also dominant for tourists, followed by psychological. In summer, physical factors were the major influencing factors for residents and tourists’ thermal perceptions.
The study aims to investigate the thermal comfort requirements in residential buildings and to establish an adaptive thermal comfort model in the cold zone of China. A year-long field study was conducted in residential buildings in Xi’an, China. A total of 2069 valid questionnaires, along with indoor environmental parameters were obtained. The results indicated occupants’ thermal comfort requirements varied with seasons. The neutral temperatures were 17.9, 26.1 (highest), 25.2, and 17.4 degrees C (lowest), and preferred temperatures were 23.2, 25.6 (highest), 24.8, and 22.4 degrees C (lowest), respectively for spring, summer, autumn, and winter. The neutral temperature and preferred temperature in autumn are close to the neutral temperature in summer, while the neutral temperature and preferred temperature in spring are close to that in winter. Besides, the 80% and 90% acceptable temperature ranges, adaptive thermal comfort models, and thermal comfort zones for each season were established. Human’s adaptability is related to his/her thermal experience of the current season and the previous season. Therefore, compared with the traditional year-round adaptive thermal comfort model, seasonal models can better reflect seasonal variations of human adaptation. This study provides fundamental knowledge of the thermal comfort demand for people in this region.
BACKGROUND: Given that low income worsens health outcomes, income differences may affect health disparities in weather-related illnesses. The aim of this study was to investigate the association between income levels and prevalence of heat- and cold-related illnesses among Korean adults. METHODS: The current study comprised 535,186 participants with all variables on income and health behaviors. Patients with temperature-related illnesses were defined as individuals with outpatient medical code of heat- and cold-related illnesses. We categorized individual income into three levels: “low” for the fourth quartile (0-25%), “middle” for the second and the third quartiles (25-75%), and “high” for the first quartile (75-100%). To examine income-related health disparities, Cox proportional hazard regression was performed. Hazard ratios (HRs) and 95% CI (confidence interval) for heat- and cold-related illnesses were provided. The model adjusted for age, sex, smoking status, alcohol drinking, exercise, body mass index, hypertension, hyperglycemia, and local income per capita. RESULTS: A total of 5066 (0.95%) and 3302 (0.62%) cases identified patients with heat- and cold-related illnesses, respectively. Compared with high income patients, the adjusted HR for heat-related illnesses was significantly increased in the low income (adjusted HR = 1.103; 95% CI: 1.022-1.191). For cold-related illnesses, participants with low income were likely to have 1.217 times greater likelihood than those with high income (95% CI: 1.107-1.338), after adjusting for other covariates. In the stratified analysis of age (20-64 years and over 65 years) and sex, there was no difference in the likelihood of heat-related illnesses according to income levels. On the other hand, an HR for cold-related illnesses was higher in patients aged 20 to 64 years than in those aged over 65 years. Male with low income had also a higher HR for cold-related illnesses than female with low income. CONCLUSIONS: Our results showed that heat- or cold-related illnesses were more prevalent in Koreans with low income than those with high income. Strategies for low-income subgroups were needed to reduce greater damage due to the influence of extreme temperature events and to implement effective adaptation.
Changes of thermal environment can lead to unfavorable impacts such as a decrease of thermal stratification, increase of energy consumption, and increase of thermal health risk. Investigating changes in outdoor thermal environments can provide meaningful information for addressing economic and social issues and related challenges. In this study, thermal environment changes in South Korea were investigated using a nonstationary two-component Gaussian mixture model (NSGMM) for air temperature and two thermal comfort indices. For this, the perceived temperature (PT) and universal thermal climate index (UTCI) were employed as the thermal comfort index. Thermal comfort indices were computed using observed meteorological data at 26 weather stations for 37 years in South Korea. Meanwhile, trends of thermal comforts in the warm and cool seasons were simultaneously modeled by the NSGMM. The results indicate significant increasing trends in thermal comfort indices for South Korea. The increasing trends in thermal comfort indices both the warm and cool seasons were detected while the magnitudes of the trends are significantly different. This difference between the magnitude of trends led to an increase in mean and inter-annual variability of thermal comfort indices based on PT, while an increase of mean and decrease of inter-annual variability were observed based on the UTCI. Moreover, the annual proportion of the category referring to days in comfort based on the results of PT has decreased due to the different trends of thermal comfort indices in the warm and cool seasons. This decrease may lead to an increase of thermal health risk that is larger than what would be expected from the results considering the increasing trend of the annual mean temperature in South Korea. From this result, it can be inferred that the thermal health risk in South Korea may be more adverse than what we originally expected from the current temperature trend.
Determining the thresholds for risk assessment is critical for the successful implementation of thermal health warning systems. A risk assessment methodology with multiple thresholds must be developed to provide detailed warning information to the public and decision makers. This study developed a new methodology to identify multiple thresholds for different risk levels for heat or cold wave events by considering simultaneously impact on public health. A new objective function was designed to optimize segmented Poisson regression, which relates public health to temperature indicators. Thresholds were identified based on the values of the objective functions for all threshold candidates. A case study in identifying thresholds for cold and heat wave events in Seoul, South Korea, from 2014 to 2018, was conducted to evaluate the appropriateness of the proposed methodology. Daily minimum or maximum air temperature, mortality, and morbidity data were used for threshold identification and evaluation. The proposed methodology can successfully identify multiple thresholds to simultaneously represent different risk levels. These thresholds show comparable performance to those using the relative frequency approach.
Individual and meteorological factors are associated with cognitive function in older adults. However, how these two factors interact with each other to affect cognitive function in older adults is still unclear. We used mixed effects models to assess the association of individual and meteorological factors with cognitive function among older adults. Individual data in this study were from the database of China Family Panel Studies. A total of 3448 older adults from 25 provinces were included in our analysis. Cognitive functions were measured using a memory test and a logical sequence test. We used the meteorological data in the daily climate dataset of China’s surface international exchange stations, and two meteorological factors (i.e., average temperature and relative humidity) were assessed. The empty model showed significant differences in the cognitive scores of the older adults across different provinces. The results showed a main impact of residence (i.e., urban or rural) and a significant humidity-residence interaction on memory performance in older adults. Specifically, the negative association between humidity and memory performance was more pronounced in urban areas. This study suggested that meteorological factors may, in concert with individual factors, be associated with differences in memory function in older adults.
The aim of this study was to investigate coping styles, posttraumatic stress, and mental health symptoms among a sample of community members affected by 2019-20 Australian bushfires. Using a convenience sampling approach, an online survey was used to assess a range of coping strategies, posttraumatic stress and symptoms of depression, anxiety, and stress among the affected community members of Black Summer bushfires. The results revealed that study participants reported moderate symptoms of depression and stress, and severe levels of anxiety. Additionally, participants reported use of both approach and avoidance coping strategies following the bushfire event as well as experiencing symptoms of posttraumatic stress, such as having intrusive thoughts and symptoms of avoidance and hyperarousal. Despite the durability of many individuals, others remain affected by the event and there is evidence there may be longer term mental health consequences of the bushfires for some people. Given these findings, it is imperative that mental health services be readily available for people in the bushfire-affected areas. Mental health nurses have an important role to play in supporting individuals affected by disasters. Awareness of the short- and long-term impacts of disasters on the mental health of people is paramount for mental health nurses.
BACKGROUND: The April 2019 wildfires in Gangwon Province, South Korea forced the evacuation of 1500 individuals and cost more than $100 million in damages, making it the worst wildfire disaster in Korean history. The purpose of this paper was to investigate the mental health effects on survivors following the wildfires. METHODS: Between April and May 2019, outreach psychological support services were delivered to people impacted by the wildfires. Post-disaster psychological responses using a checklist and the Clinical Global Impression Scale-Severity (CGI-S) were evaluated for 206 wildfires survivors. The CGI-S was administered consequently at 1, 3, and 6 months after baseline measurement. RESULTS: Among four response categories, somatic responses (76.2%) were most frequently observed among the wildfire survivors. Specifically, insomnia (59.2%), anxiety (50%), chest tightness (34%), grief (33%), flashbacks (33%), and depression (32.5%) were reported by over 30% of the participants. The mean CGI-S scores were significantly decreased at 1 month (mean score = 1.94; SE = 0.09) compared to baseline (mean score = 2.94; SE = 0.08) and remained at the decreased level until 6 months (mean score = 1.66; SE = 0.11). However, participants with flashbacks showed significantly higher CGI-S scores compared to those without flashback at 6 months. CONCLUSIONS: Wildfire survivors have various post-disaster responses, especially somatic responses. While most participants’ mental health improved over time, a few of them may have experienced prolonged psychological distress after 6 months. Flashbacks were particularly associated with continuing distress. These results suggest that the characteristics of responses should be considered in early phase intervention and in follow-up plans for disaster survivors.
This paper estimates the wellbeing effects of the 2009 Black Saturday Bushfires, the deadliest wildfire event in Australia’s known history. Using subjective wellbeing data from a nationally representative longitudinal study and adopting an individual fixed-effects approach, our results identify a significant reduction in life satisfaction for individuals residing in close proximity of the wildfires. The negative wellbeing effect is valued at A$52,300. This corresponds to 80% of the average annual income of a full-time employed adult in the state of Victoria. The satisfaction domain most negatively affected is how safe the person feels, and the group most affected are people with low social support. A delayed adverse mental health effect is also identified.
INTRODUCTION: Mortality attributed to fire and flame for children (0-14 years) over a fifty-year period has not been previously analyzed in Australia. The literature has focused on these deaths over a shorter time period or disaggregated with other causes of burns or deaths in one burns center. However, mortality associated with fire/flames affects this age group the greatest. The aims of this study are to: (1) develop a trends analysis of fire and flames mortality between1968 to 2016, using the Australian Bureau of Statistics (ABS) mortality database and, (2) determine the association of interventions with fire and flames mortality using the Haddon’s categorical intervention framework. METHODS: International Classification of Disease (ICD) codes were extracted and code equivalencies between ICD 8, 9, 10 and the Australian Bureau of Statistics for fire/flames data between 1968–2016 were assessed. To determine whether population changes affected the risks of mortality, the frequency and, rates per 100,000 were used. A literature review was conducted that summarized the current knowledge of interventions associated with the major decreases in the fire and flames mortality rate. RESULTS: In Australia, we found was a downward trend for the period although with significant variation from year to year when compared to external cause mortality. Additionally, there were multiple successful interventions associated with a sustained decrease in mortality. After 2016, child fire-related mortality remains a problem particularly in low socioeconomic groups and indigenous peoples. A combination of research, public awareness, engineering, legal enforcement, advancements in burns care and, evidence-based policy development all have a role to play in future injury prevention initiatives. Although direct causation to an individual is not possible, associations can be drawn from interventions on a population level to decreases in mortality. CONCLUSION: We found was a steady decline in both rates and frequency of childhood fire and flames mortality from 1968 to 2016 associated with multiple interventions.
The health effects of the unprecedented bushfires in Australia in 2019-20 have not been fully examined. We aimed to examine the excess emergency department (ED) visits related to the 2019-20 bushfires in New South Wales (NSW). We obtained weekly data of ED visits for cardiovascular and respiratory diseases in all the 28 Statistical Area Level 4 (SA4) regions in NSW during the bushfire seasons from 2017 to 2020. A two-stage interrupted time-series analysis was applied to quantify the excess risk for ED visits in 2019-20. The total number of excess ED visits, excess percentages, and their empirical confidence intervals (eCIs) were calculated to estimate the impacts of the bushfire season. A total of 416,057 records of cardiorespiratory ED visits were included in our analysis. The bushfire season in 2019-20 was significantly associated with a 6.0% increase (95% eCI: 1.9, 10.3) in ED visits for respiratory diseases and a 10.0% increase (95% eCI: 5.0, 15.2) for cardiovascular diseases, corresponding to 6177 (95% eCI: 1989, 10,166) and 3120 (95% eCI: 1628, 4544) excess ED visits, respectively. The percentage of excess ED visits was higher in regions with lower SES and high fire density. In the context of climate change, more targeted strategies should be developed to prevent adverse bushfire effects and recover from such extreme environmental events.
Wildfires pose a significant risk to people and property, which is expected to grow with urban expansion into fire-prone landscapes and climate change causing increases in fire extent, severity and frequency. Identifying spatial patterns associated with wildfire activity is important for assessing the potential impacts of wildfires on human life, property and other values. Here, we model the probability of fire ignitions in vegetation across Victoria, Australia, to determine the key drivers of human- and lightning-caused wildfire ignitions. In particular, we extend previous research to consider the role that fuel moisture has in predicting ignition probability while accounting for environmental and local conditions previously identified as important. We used Random Forests to test the effect of variables measuring infrastructure, topography, climate, fuel and soil moisture, fire history, and local weather conditions to investigate what factors drove ignition probability for human- and lightning-caused ignitions. Human-caused ignitions were predominantly influenced by measures of infrastructure and local weather. Lightning-sourced ignitions were driven by fuel moisture, average annual rainfall and local weather. Both human-and lightning-caused ignitions were influenced by dead fuel moisture with ignitions more likely to occur when dead fuel moisture dropped below 20 %. In future, these models of ignition probability may be used to produce spatial likelihood maps, which will improve our models of future wildfire risk and enable land managers to better allocate resources to areas of increased fire risk during the fire season.
Accumulating studies have been focused on the independent effects of air pollutants and ambient heat exposure on congenital heart defects (CHDs) but with inconsistent results, and their interactive effect remains unclear. A case-control study including 921 cases and 9210 controls was conducted in Changsha, China in warm season in 2015-2018. The gravidas were assigned monthly averages of daily air pollutants and daily maximum temperature using the nearest monitoring station method and city-wide average method, respectively, during the first trimester of pregnancy. Multivariate logistic regression models were used to estimate the independent effects of each air pollutant and different ambient heat exposure indicators. Their additive joint effects were quantified using attribute proportions of interaction (API). Increasing SO(2) consistently increased the risk of CHDs in the first trimester of pregnancy, with aORs ranging from 1.78 to 2.04. CO, NO(2) and PM(2.5) exposure in the first month of pregnancy, and O(3) exposure in the second and third month of pregnancy were also associated with elevated risks of CHDs, with aORs ranging from 1.04 to 1.15. Depending on the ambient heat exposure indicator used, air pollutants showed more apparent synergistic effects (API > 0) with less and moderately intense heat exposure. Maternal exposure to CO, NO(2), SO(2), PM(2.5) and O(3) during early pregnancy increased risk of CHDs, and ambient heat exposure may enhance these effects. Our findings help to understand the interactive effect of air pollution with ambient heat exposure on CHDs, which is of vital public health significance.
Air pollution and high temperatures can increase kidney disease rate, especially under climate change. A well-designed urban environment has mediating effects on atmospheric environmental threats and promoting human health, but previous studies have overlooked these effects. This study used partial least squares modeling and urban-scale data from Taiwan to identify the crucial effects (i.e., direct, indirect, and total effects) and pathways of urban form (i.e., urban development intensity, land-use mix, and urban sprawl), urban greening (i.e., green coverage), urban industrial status (e.g., industrial level), atmospheric environment (i.e., high temperature and air pollution), and socioeconomic status (i.e., elderly ratio, medical resources, and economic status) on kidney disease rate. Maximizing land-use mix and green coverage and minimizing urban development intensity, urban sprawl, and industrial levels could help reduce kidney disease rate. Air pollution and high temperature had a mediation effect of built environment on kidney disease rate; with the mediation effect of air pollution was greater than that of high temperature. Furthermore, air pollution, high temperature, and elderly ratio increased kidney disease rate, whereas medical resources decreased kidney disease rate. This study is the first to consider the impact (i.e., direct, indirect, and total effects) and pathways of built environment characteristics on kidney disease rate. The findings revealed that an appropriate urban policy might be a practical strategy and lower kidney disease rate for a healthy city development. Moreover, this study provides a new approach for clarifying complex relationships and identifying crucial factors.
The Yellow River, with a developmental and historical significance to China, is now facing several emerging pressures, which are degrading the river status and creating challenges for high-quality development in the basin. Numerous studies on such emerging pressures, present scattered outcomes, and trigger uncertainties and deficient assumptions on the river’s problems. This review integrated such scattered information and investigated the emerging pressures, their drivers and integrated impacts at the basin level. The study intended to prioritize those pressures needing expeditious consideration, and carried a discussion on the alternative pathways to the solution. To determine the critical emerging pressures, a literature review was conducted and experts’ opinion was sought. The outcome further led to a comprehensive review, data collection, and analysis of three groups of emerging pressures. The review recognized ‘Water Stress’ in the lower reach, primarily caused by an abated flow, as the most distressing emerging pressure inflicting social, ecological, and economic consequences. Such decline in flow was mostly induced by a recent increase in ‘Anthropogenic activities’, such as intensive water withdrawal for irrigation (≥27 BCM), and construction of check dams in the Loess Plateau region (trapping~5 BCM water). The increasing ‘Pollution’ in the river, besides threatening public health and ecology, also contributed to the water stress by rendering certain stretches of the river biologically dead and unsuitable for any use. The ‘Climate Change’, with its key negative effect on precipitation in the middle sub-basin, overall contributed small (8-11 %) to the observed reduction in river flow. With increasing challenges for the adopted engineering solutions tackling the water stress, the study suggested the use of a demand management approach, employing adaptive policy measures, as an alternative or supplementary solution to the current approach. In addition, the study highlights that regular reviewing and reforming the key decisions based on evidence and updated information, and taking a participatory approach, may offer a sustainable pathway to the environment as well as socio-economic goals.
Human exposure to a hot environment may result in various heat-related illnesses (HRIs), which range in severity from mild and moderate forms to life-threatening heatstroke. The Hajj is one of the largest annual mass gatherings globally and has historically been associated with HRIs. Hajj attracts over two million Muslim pilgrims from more than 180 countries to the holy city of Makkah, Kingdom of Saudi Arabia. Several modifiable and non-modifiable factors render Hajj pilgrims at increased risk of developing HRIs during Hajj. These include characteristics of the Hajj, its location, population, and rituals, as well as pilgrims’ knowledge of HRIs and their attitude and behavior. Makkah is characterized by a hot desert climate and fluctuating levels of relative humidity. Pilgrims are very diverse ethnically and geographically, with different adaptations to heat. Significant proportions of the Hajj population are elderly, obese, and with low levels of fitness. In addition, many have underlying health conditions and are on multiple medications that can interfere with thermoregulation. Other factors are inherent in the Hajj and its activities, including crowding, physically demanding outdoor rituals, and a high frequency of infection and febrile illness. Pilgrims generally lack awareness of HRIs, and their uptake of preventive measures is variable. In addition, many engage in hazardous behaviors that increase their risk of HRIs. These include performing rituals during the peak sunshine hours with no sun protection and with suboptimal sleep, nutrition, and hydration, while neglecting treatment for their chronic conditions. HRIs preventive plans for Hajj should incorporate measures to address the aforementioned factors to reduce the burden of these illnesses in future Hajj seasons. Lessons from the Hajj can be used to inform policy making and HRIs preventive measures in the general population worldwide.
Most heat-health studies identified thresholds just outside human comfort zones, which are often too low to be used in heat-warning systems for reducing climate-related health risks. We refined a generalized additive model for selecting thresholds with substantial health risk enhancement, based on Taiwan population records of 2000-2017, considering lag effects and different spatial scales. Reference-adjusted risk ratio (RaRR) is proposed, defined as the ratio between the relative risk of an essential health outcome for a threshold candidate against that for a reference; the threshold with the highest RaRR is potentially the optimal one. It was found that the wet-bulb globe temperature (WBGT) is a more sensitive heat-health indicator than temperature. At lag 0, the highest RaRR (1.66) with WBGT occurred in emergency visits of children, while that in hospital visits occurred for the working-age group (1.19), presumably due to high exposure while engaging in outdoor activities. For most sex, age, and sub-region categories, the RaRRs of emergency visits were higher than those of hospital visits and all-cause mortality; thus, emergency visits should be employed (if available) to select heat-warning thresholds. This work demonstrates the applicability of this method to facilitate the establishment of heat-warning systems at city or country scales by authorities worldwide.
This study was conducted as a planning stage for development of wearable devices capable of managing the thermal diseases by applying the ICT (Information Communication Technology) in an endeavor to meet the urgent needs for countermeasures amid rapid increase in the number of patients with the thermal diseases caused as a result of global warming. The purpose of this study was to provide the basic data for development of wearable devices allowing the patients to be transported expeditiously to hospitals based on synchronization with medical institutions or enabling the prevention of diseases through the response system for each stage according to the reference values based on the data reflecting physical characteristics of individuals by applying the ICT, so that the thermal diseases can be managed effectively. For that, basic study will be conducted on expanding the role of the devices capable of protecting human lives from various thermal diseases caused by the scorching heat waves, which are affecting countries worldwide and expected to persist in the period ahead, by setting the goals of each stage for the thermal disease management platform and collecting necessary information. Based on the accumulated data, the functions of precise diagnosis and treatment can be expected through more accurate evidences pertaining to the thermal diseases.
Previous studies have suggested an association between air pollution and lung disease. However, few studies have explored the relationship between chronic lung diseases classified by lung function and environmental parameters. This study aimed to comprehensively investigate the relationship between chronic lung diseases, air pollution, meteorological factors, and anthropometric indices. We conducted a cross-sectional study using the Taiwan Biobank and the Taiwan Air Quality Monitoring Database. A total of 2889 participants were included. We found a V/U-shaped relationship between temperature and air pollutants, with significant effects at both high and low temperatures. In addition, at lower temperatures (<24.6 °C), air pollutants including carbon monoxide (CO) (adjusted OR (aOR):1.78/Log 1 ppb, 95% CI 0.98-3.25; aOR:5.35/Log 1 ppb, 95% CI 2.88-9.94), nitrogen monoxide (NO) (aOR:1.05/ppm, 95% CI 1.01-1.09; aOR:1.11/ppm, 95% CI 1.07-1.15), nitrogen oxides (NO(x)) (aOR:1.02/ppm, 95% CI 1.00-1.05; aOR:1.06/ppm, 95% CI 1.04-1.08), and sulfur dioxide (SO(2)) (aOR:1.29/ppm, 95% CI 1.01-1.65; aOR:1.77/ppm, 95% CI 1.36-2.30) were associated with restrictive and mixed lung diseases, respectively. Exposure to CO, NO, NO(2), NO(x) and SO(2) significantly affected obstructive and mixed lung disease in southern Taiwan. In conclusion, temperature and air pollution should be considered together when evaluating the impact on chronic lung diseases.
The Asia-Pacific contains over half of the world’s population, 21 countries have a Gross Domestic Product <25% of the world's largest economy, many countries have tropical climates and all suffer the impact of global warming. That 'perfect storm' exacerbates the risk of occupational heat illness, yet first responders must perform physically demanding work wearing personal-protective clothing and equipment. Unfortunately, the Eurocentric emphasis of past research has sometimes reduced its applicability to other ethnic groups. To redress that imbalance, relevant contemporary research has been reviewed, to which has been added information applicable to people of Asian, Melanesian and Polynesian ancestry. An epidemiological triad is used to identify the causal agents and host factors of work intolerance within hot-humid climates, commencing with the size dependency of resting metabolism and heat production accompanying load carriage, followed by a progression from the impact of single-layered clothing through to encapsulating ensembles. A morphological hypothesis is presented to account for inter-individual differences in heat production and heat loss, which seems to explain apparent ethnic- and gender-related differences in thermoregulation, at least within thermally compensable states. The mechanisms underlying work intolerance, cardiovascular insufficiency and heat illness are reviewed, along with epidemiological data from the Asia-Pacific. Finally, evidence-based preventative and treatment strategies are presented and updated concerning moisture-management fabrics and barriers, dehydration, pre- and post-exercise cooling, and heat adaptation. An extensive reference list is provided, with >25 recommendations enabling physiologists, occupational health specialists, policy makers, purchasing officers and manufacturers to rapidly extract interpretative outcomes pertinent to the Asia-Pacific.
Tasks performed by search and rescue (SAR) teams can be physically demanding. SAR organizations are faced with mounting challenges due to increased participation in recreation in remote locations and more frequent extreme weather. We sought to describe the physiological response and the methods for data collection during helicopter emergency medical service (HEMS) winch rescue from remote wilderness in extreme heat. A flight paramedic sustained 81% of maximum heart rate (VO₂ ~44.8 mL/kg/min) for ~10 minutes at a rate of perceived exertion of 19/20, and a relative heart rate of 77.5% in 37.1°C. Maximal acceptable work time for this task was calculated at 37.7 minutes. Our data collection methods were feasible, and the data captured demonstrated the level of physiological strain that may be encountered during HEMS SAR operations in austere environments and hot climate. It is essential that SAR teams that perform physically demanding tasks use a scientific approach to adapt and evolve. This is necessary to ensure personnel are appropriately selected, trained, and equipped to respond in an era of increasing demand and extreme environments.
INTRODUCTION: It is well-established that heatwaves increase demand for emergency transport in metropolitan areas; however, little is known about the impact of heat events on demand for prehospital retrieval services in rural and remote areas, or how heatwaves are defined in this context. INCLUSION CRITERIA: Papers were eligible for inclusion if they reported on the impact of a heat event on the activity of a prehospital and retrieval service in a rural or remote area. METHODS: A search of PubMed, Cochrane, Science Direct, CINAHL, and Google Scholar databases was undertaken on August 18, 2020 using search terms related to emergency medical transport, extreme heat, and rural or remote. Data relevant to the impact of heat on retrieval service activity were extracted, as well as definitions of extreme heat. RESULTS: Two papers were identified, both from Australia. Both found that heat events increased the number of road ambulance call-outs. Both studies used the Excess Heat Factor (EHF) to define heatwave periods of interest. CONCLUSIONS: This review found almost no primary literature on demand for prehospital retrieval services in rural and remote areas, and no data specifically related to aeromedical transport. The research did recognize the disproportionate impact of heat-related increase in service demand on Australian rural and regional health services. With the effects of climate change already being felt, there is an urgent need for more research and action in this area.
An innovative bioclimatic metric based on the Universal Thermal Climate Index (UTCI) is developed to quantify human thermal physiological heat stress. The Heat Stress Exposure (HSE) metric includes both duration and intensity dimensions of heat exposure, and in this paper it is applied to the Sydney Australia climatology. Geographic Information Systems (GIS) were used to spatially represent and visualize Sydney’s HSE. The first stage of the analysis collated observed meteorological data from 10 weather stations across the Sydney metropolitan region, extending from coastal Sydney to approximately 50 km inland in 2017. The second stage of the analysis integrated the radiative meteorological data into estimates of hourly Mean Radiant Temperature which were then applied to UTCI. In the final stage, a threshold UTCI value of 26 degrees C was selected for the calculation of HSE, which was then cumulated to represent the duration of heat exposure throughout the year. The difference between each UTCI hourly reading and the 26 degrees C threshold defined a UTCI exceedance (Delta UTCI; degrees C). The cumulative total of all Delta UTCI throughout the year defined n-ary sumation Delta UTCI in units of degree hours (degrees C.hr), thereby capturing both intensity and duration of exposure to heat stress. Weather systems driving westerly winds from the Australian continent’s central deserts brought the highest HSE to Sydney’s inland western suburbs, with values ranging between 4,000-6,000 n-ary sumation Delta UTCI (degrees C.hr). Coastal eastern Sydney experienced considerably lower HSE values ranging from 1,600-3,000 n-ary sumation Delta UTCI (degrees C.hr), reflecting the moderating influences of sea breezes and evaporative cooling.
Extreme heat and hot weather has a negative impact on human health and society. Global warming has resulted in an increase in the frequency and duration of heatwaves. Heat-related illnesses are a significant negative consequence of high temperatures and can be life-threatening medical emergencies. The severity of the symptoms can depend on the pre-existing medical conditions and vary from mild headaches to severe cases that can lead to coma and death. The risk of heat-related illness may be higher for people experiencing homelessness due to a lack of access to cool places and water, and the complex interactions between mental illness, medications and substance use disorder. This paper presents two cases of people experiencing homelessness who were admitted to the emergency department of a hospital in Sydney, Australia during a heatwave in November 2020. Both cases were adult males with known risk factors for heat-related illness including hypertension and schizophrenia (Case One) and hepatitis C, cirrhosis, and alcohol use disorder (Case Two). These cases show that severe weather can not only be detrimental to homeless people’s health but can also cause a significant economic toll, evident by the $70,184 AUD expenditure on the care for these two cases. This case report highlights the requirement to determine the risk of heat-related illness to people experiencing homelessness and need to protect this vulnerable population from weather-related illness and death.
Public health risks resulting from urban heat in cities are increasing due to rapid urbanisation and climate change, motivating closer attention to urban heat mitigation and adaptation strategies that enable climate-sensitive urban design and development. These strategies incorporate four key factors influencing heat stress in cities: the urban form (morphology of vegetated and built surfaces), urban fabric, urban function (including human activities), and background climate and regional geographic settings (e.g. topography and distance to water bodies). The first two factors can be modified and redesigned as urban heat mitigation strategies (e.g. changing the albedo of surfaces, replacing hard surfaces with pervious vegetated surfaces, or increasing canopy cover). Regional geographical settings of cities, on the other hand, cannot be modified and while human activities can be modified, it often requires holistic behavioural and policy modifications and the impacts of these can be difficult to quantify. When evaluating the effectiveness of urban heat mitigation strategies in observational or traditional modelling studies, it can be difficult to separate the impacts of modifications to the built and natural forms from the interactions of the geographic influences, limiting the universality of results. To address this, we introduce a new methodology to determine the influence of urban form and fabric on thermal comfort, by utilising a comprehensive combination of possible urban forms, an urban morphology data source, and micro-climate modelling. We perform 9814 simulations covering a wide range of realistic built and natural forms (building, roads, grass, and tree densities as well as building and tree heights) to determine their importance and influence on thermal environments in urban canyons without geographical influences. We show that higher daytime air temperatures and thermal comfort indices are strongly driven by increased street fractions, with maximum air temperatures increases of up to 10 and 15 ? as street fractions increase from 10% (very narrow street canyons and/or extensive vegetation cover) to 80 and 90% (wide street canyons). Up to 5 ? reductions in daytime air temperatures are seen with increasing grass and tree fractions from zero (fully urban) to complete (fully natural) coverage. Similar patterns are seen with the Universal Thermal Climate Index (UTCI), with increasing street fractions of 80% and 90% driving increases of 6 and 12 ?, respectively. We then apply the results at a city-wide scale, generating heat maps of several Australian cities showing the impacts of present day urban form and fabric. The resulting method allows mitigation strategies to be tested on modifiable urban form factors isolated from geography, topography, and local weather conditions, factors that cannot easily be modified.
Historically, heat waves have resulted in more Australian deaths than any other natural hazard and continue to present challenges to the health and emergency management sectors. While people experiencing homelessness are particularly vulnerable to adverse effects of heat waves, little research has been reported about their hot weather experiences. This paper reports findings from interviews with 48 homeless people sleeping rough in Adelaide CBD on very hot days. While the majority reported drinking a litre or more of water in the previous 24 hours, 79% reported experiencing one or more heat stress symptoms. The research highlights that the protective actions people sleeping rough can take during hot weather are limited by their circumstances and may not be sufficient to prevent dehydration and heat stress. The levels of dehydration and heat stress symptoms suggest that immediate responses could include making drinking water more readily available. It may be helpful to provide information which highlights heat stress symptoms including indicators of dehydration. The role of outreach in providing connections, support and advice is most likely to ameliorate the risk of heat stress. However, the long-term response to protect people from heat stress is access to housing.
OBJECTIVES: To conduct a document analysis of sports and leisure activity heat-related injury prevention resources in Australia and develop an understanding of the content within those resources. DESIGN & METHODS: Heat resources were included if they dealt specifically with, or could be extrapolated to, prevention of heat-related injuries. Collating strategies for the catalogue included: (1) a detailed search of the organisation’s website and (2) an online search for sport specific heat resources. A content analysis of each resource was first performed, and descriptive codes were assigned to the data using qualitative data analysis software. Every coded text was recorded as an individual data point (n). Common sub-categories were identified by thematic analysis and collated under three broader categories. RESULTS: A total of 468 data points were identified within the 64 heat resources found. Guidelines (n = 20) and policies (n = 18) were the most common type of resources followed by factsheets (n = 9), webpages (n = 8), laws and by-laws (n = 2). Three overarching categories emerged through the data analysis process: preventive strategies (n = 299, 63.9%), risk factors (n = 94, 20.1%), treatment (n = 75, 16.0%). Activity modification, which included information on rescheduling games and extra breaks, was the most common intervention. Cricket, soccer, swimming and triathlon had the most complete set of heat resources. CONCLUSIONS: The findings of this study provide an insight into the composition of heat-related sports injury prevention resources within Australia and identify areas for development. As the resources were incomplete for many sports, the development of more comprehensive heat safety resources is required to ensure the safety of participants.
Anthropogenic climate change and related sea level rise will have a range of impacts on populations, particularly in the low lying Pacific island countries (PICs). One of these impacts will be on the health and well-being of people in these nations. In such cases, access to medical facilities is important. This research looks at the medical facilities currently located on 14 PICs and how climate change related impacts such as sea level rise may affect these facilities. The medical infrastructure in each country were located using information from a range of sources such as Ministry of Health (MoH) websites, World Health Organization, Doctors Assisting in South Pacific Islands (DAISI), Commonwealth Health Online, and Google Maps. A spatial analysis was undertaken to identify medical infrastructure located within 4 zones from the coastline of each country: 0 to 50 m, 50 to 100 m, 100 to 200 m, and 200 to 500 m. The findings indicate that 62% of all assessed medical facilities in the 14 PICs are located within 500 m of the coast. The low-lying coral atoll countries of Kiribati, Marshall Islands, Nauru, Palau, Tokelau, and Tuvalu will be highly affected as all medical facilities in these countries fall within 500 m of the coast. The results provide a baseline analysis of the threats posed by sea-level rise to existing critical medical infrastructure in the 14 PICs and could be useful for adaptive planning. These countries have limited financial and technical resources which will make adaptation challenging.
In recent years, climate changeability, hydrologic regime conditions, and human interventions have become crucial issues to be assessed. In this research, two annually recorded datasets were collected to analyse the change in the trend. The first set is comprised of precipitation, streamflow, and water quality variables including Total Dissolved Solids (TDS), pH, cation, and anion and the second one contains the mean groundwater level and agricultural water demand of four main stations of Shahpour River basin in the south of Iran. To recognize the fluctuating patterns, the Mann-Kendall Trend Test (MKTT), KPSS Stationary Test, and Pettit Homogeneity Test (PHT) of statistical methods were utilized at a 5% significance level. The Standardized Precipitation Index (SPI) and Streamflow Drought Index (SDI) were subsequently employed to detect the hydrological drought patterns. According to the statistical analysis, the streamflow and water quality depicted intensive varying trends, while there were slight decreasing trends for the precipitation series. Afterward, the abrupt changing points were identified in the first and second datasets between the years 2004 to 2007. The results of this study clarified that human activity effects (as a major factor) and climate variability (as a minor factor) have been affecting the Shahpour River basin. These effects disrupt the water chemical balance (the relationship between cations and anions) and hydrological regimes (increasing drought drivers) and consequently menace the health of the watershed.
Urban overheating (UO) may interact with synoptic-scale weather conditions. The association between meteorological parameters and UO has already been a subject of considerable research, however, the impact of synoptic-scale weather conditions on UO magnitude, particularly in a coastal city that is also near the desert landmass (Sydney) has never been investigated before. The present research examines the influence of synoptic-scale weather conditions on UO magnitude in Sydney by utilizing the newly developed gridded weather typing classification (GWTC). The diurnal, and seasonal variations in suburban-urban temperature contrast (ΔT) in association with synoptic-scale weather conditions, and ΔT response to synoptic air-masses during extreme heat events are investigated in three zones of Sydney. Generally, an exacerbation in UO magnitude was reported at daytime over the years, whereas the nocturnal UO magnitude was alleviated over time. The humid warm (HW), and warm (W) air-masses were found primarily responsible for exacerbated daytime UO during extreme heat events and in all other seasons, raising the mean daily maximum ΔT to 8-10.5 °C in Western Sydney, and 5-6.5 °C in inner Sydney. The dry warm (DW), and W conditions were mainly responsible for urban cooling (UC) at nighttime, bringing down the mean daily minimum ΔT to – 7.5 to – 10 °C in Western Sydney, and – 6 to – 7.5 °C in inner Sydney. The appropriate mitigation technologies can be planned based on this study to alleviate the higher daytime temperatures in the Sydney suburbs.
BACKGROUND: Though inconsistent, acute effects of ambient nitrogen oxides on cardiovascular mortality have been reported. Whereas, interactive roles of temperature on their relationships and joint effects of different indicators of nitrogen oxides were less studied. This study aimed to extrapolate the independent roles of ambient nitrogen oxides and temperature interactions on cardiovascular mortality. METHODS: Data on mortality, air pollutants, and meteorological factors in Shenzhen from 2013 to 2019 were collected. Three indicators including nitric oxide (NO), nitrogen dioxide (NO(2)), and nitrogen oxides (NO(X)) were studied. Adjusted generalized additive models (GAMs) were applied to analyse their associations with cardiovascular mortality in different groups. RESULTS: The average daily concentrations of NO, NO(2), and NO(X) were 11.7 μg/m^3, 30.7 μg/m^3, and 53.2 μg/m3, respectively. Significant associations were shown with each indicator. Cumulative effects of nitrogen oxides were more obvious than distributed lag effects. Males, population under 65 years old, and population with stroke-related condition were more susceptible to nitrogen oxides. Adverse effects of nitrogen oxides were more significant at low temperature. Impacts of NO(2) on cardiovascular mortality, and NO on stroke mortality were the most robust in the multi-pollutant models, whereas variations were shown in the other relationships. CONCLUSIONS: Low levels of nitrogen oxides showed acute and adverse impacts and the interactive roles of temperature on cardiovascular mortality. Cumulative effects were most significant and joint effects of nitrogen oxides required more attention. Population under 65 years old and population with stroke-related health condition were susceptible, especially days at lower temperature.
BACKGROUND: The concentration of air pollutants is affected by changes in climatic conditions. Air temperature is a main factor affecting the concentration of air pollutants. This study sought to examine the relationship between air temperature, air pollutants, and their interactions in elderly patients with coronary heart disease (CHD) in Liaoning Province, China. METHODS: The population data primarily comprised data on daily hospitalizations due to CHD between January 1, 2015 and December 31, 2019 at the Shengjing Hospital of China Medical University. A total of 25,461 patients, who were permanent residents of Liaoning Province, were included in the study. The meteorological data included data on the average daily temperature and air pollutant data of the average daily concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) over the hospitalization period. A multiple linear regression model was constructed to analyze the relationship between meteorological factors and CHD. RESULTS: The interaction between air temperature and SO2, NO2, and O3 concentrations was related to the number of daily CHD-related hospitalizations in elderly patients aged ≥65 years (P=0.0023); however, this correlation was lower than that of the interaction between SO2 and NO2 concentrations (P=0.0026). Additionally, age exerted a greater effect than air temperature and air pollutants. CONCLUSIONS: The incidence of CHD in elderly patients aged ≥65 years was found to be related to the interaction of SO2 and NO2 concentrations, and the interaction of air temperature and the concentrations of SO2, NO2, and O3.
Hot extremes are anticipated to be more frequent and more intense under climate change, making the Indo-Gangetic Plain of India, with a 400 million population, vulnerable to heat stress. Recent studies suggest that irrigation has significant cooling and moistening effects over this region. While large-scale irrigation is prevalent in the Indo-Gangetic Plain during the two major cropping seasons, Kharif (Jun-Sep) and Rabi (Nov-Feb), hot extremes are reported in the pre-monsoon months (Apr-May) when irrigation activities are minimal. Here, using observed irrigation data and regional climate model simulations, we show that irrigation effects on heat stress during pre-monsoon are 4.9 times overestimated with model-simulated irrigation as prescribed in previous studies. We find that irrigation increases relative humidity by only 2.5%, indicating that irrigation is a non-crucial factor enhancing the moist heat stress. On the other hand, we detect causal effects of aerosol abundance on the daytime land surface temperature. Our study highlights the need to consider actual irrigation data in testing model-driven hypotheses related to the land-atmosphere feedback driven by human water management.
BACKGROUND: Improving the level of knowledge, attitude and practices of workers exposed to heat stress using a suitable tool can be a cheap and effective method. This requires the consideration of personal, environmental and social factors, which, the PRECEDE model is highly applicable for. Thus, the aim of the present study is the development of a tool assessment for measuring the knowledge, attitude and practices of workers in outdoor occupations regarding heat stress exposure using the PRECEDE model. METHODS: In the present study, a tool was designed and constructed using the PRECEDE model by analyzing the relevant literature and expert opinion. The face validity of the tool was determined based on the opinion of ten experts with experience in the field of occupational weather conditions. The content validity of the tool was determined using the Content Validity Ratio (CVR) and the Content Validity Index (CVI). Cronbach’s alpha reliability coefficient was used to determine the reliability of the tool’s internal consistency. SPSS version 23 was used for statistical analysis. RESULTS: A PRECEDE based questionnaire was designed with a total of 55 questions consisting of predisposing factors (28 questions for knowledge and 14 questions for attitude), enabling factors (5 questions), reinforcing factors (3 questions) and preventive behaviors (5 questions). The Content Validity Index (CVI) of all questions was above 0.79. The Content Validity Ratio (CVR) of all questions was above 0.62 (Lawshe method). The Cronbach’s alpha reliability coefficient of all PRECEDE domains were above the 0.7 acceptable value. Based on the results obtained, all 55 questions were approved and thus the content validity and reliability of this tool was deemed acceptable. CONCLUSION: Considering the reliability and validity of this tool, its application is recommended in all health and safety inspections within various industries for measuring the heat stress knowledge, attitude and practices of workers engaged in outdoor occupations and also for presenting suitable solutions or preventive measures.
OBJECTIVE: The purpose of this study is to evaluate the factors involved in the early stage of exertional heat stroke (EHS) that are associated with mortality. METHODS: In this retrospective, case-control study, patients from 11 tertiary medical centers in China were enrolled from January 1, 2012, to December 31, 2019. Demographic information, underlying diseases, ambient temperature, and relative humidity, clinical manifestations, initial body temperature, time from onset to diagnosis of EHS (including suspected), and the duration of body temperature > 38°C of all enrolled patients were recorded. The occurrence of organ dysfunction within 72 h was evaluated, and in-hospital deaths were recorded. The patients were subsequently divided into a survival group and a non-survival group. The “case” refers to patients in the non-survival group, while the “control” refers to patients without death. RESULTS: Of the 214 hospitalized patients with EHS, 183 survived and 31 died, and the overall mortality was 14.49% (31/214). A binary logistic regression showed that only the duration of body temperature > 38°C (OR 1.80, 95% CI 1.34-2.42) and the number of organs damaged within 72 h of onset (OR 6.54, 95% CI 2.31-18.56) were statistically significant in terms of risk of death in hospital (p < 0.05). A goodness of fit test produced a p-value of 0.76. According to receiver operating characteristic curve (ROC) analysis, the areas under the curve (AUC) were 0.989 (95% CI 0.978-1.000; p < 0.05) and 0.936 (95% CI 0.896-0.976; p < 0.05). CONCLUSION: Of the various factors involved in the early stage of the disease, the duration of high body temperature and the number of organs damaged within 72 h of onset were independent risk factors and predictors associated with death.
The net effective temperature (NET), an index that includes the combined effects of temperature, humidity, and wind, was used along with temperature to assess the impacts of climate change on the heat stress perception in East Asia, one of the regions considered most vulnerable to heat stress. The need for dynamic downscaling has been emphasized because the regional effects of climate change do not follow the global levels linearly. In this study, daily maximums calculated from the 3-hourly data downscaled by five different regional climate models from four coupled general circulation models participating in Coordinated Regional Climate Downscaling Experiment-East Asia phase 2 were utilized. To account for the fact human beings acclimate to their environments, 95th percentile of the maximum temperature and maximum NET was used along with the average boreal summer maximum temperatures/NETs. The performance of the models was assessed first, which showed that the models reproduced the current climate well. Future projections revealed an increase in both average and 95th percentile of the maximum temperature and NET over the entire domain for both the RCP8.5 and SSP5-8.5 scenarios. The increase in heat stress (NET) was slightly larger than the temperature itself, with an increase of up to 7/10 degrees C for temperature and 8/11 degrees C for NET in RCP8.5/SSP5-8.5, respectively. The overall increases in temperature and NET were projected to be higher in the higher latitudes, while the increase in the frequency of the temperature and NET extremes was predicted to be higher in the already vulnerable regions in the southern part of the domain.
Background: One of the biggest global occupational threats, especially in the outdoor workplace, is climate change and global warming, as workers are exposed to the heat stress leading to reduced performance. The aim of this study was to investigate the effect of workplace climate on labor productivity index in the agricultural sector. Methods: In this study, data related to environmental variables of 215 synoptic meteorological stations in Khuzestan province were collected from three climatic regions (hot, mild, and cold). Using MATLAB R 2018b mathematical software based on ASHRAE/ISO7730 standard values by designing some scenarios, predicted mean vote (PMV) index, and then, labor productivity index (P) were estimated. The data were analyzed using SPSS version 25 software. Results: The results showed that in the hot regions, there is a significant inverse relationship between P index and the main environmental variables (ta, tr, pa). In the cold regions, increasing the amount of ta and tr in light and medium workload improved the P index, but for heavy workload, it reduced productivity, and the most effective factor was increasing air vapor pressure. In the mild regions, the most effective factor in productivity was air vapor pressure. In addition, the results of Spearman’s correlation coefficient showed that PMV index has a direct and significant relationship with P index. Conclusion: Regarding the increasing trend of climate change and its effect on the desired thermal comfort and productivity, well structure and planning is needed to manage farm workers health.
The number of patients experiencing heat-related illnesses has gradually increased due to global warming. Owing to an aging society, 50% of patients with heat-related illnesses in Japan are elderly. Core temperature is one key parameter for health care; however, its monitoring is virtually impossible. Internet of Things (IoT) devices for healthcare have been proposed; however, the vital parameters to be monitored remain controversial. Here, we assessed the core temperature of elderly patients who were transported to hospitals by ambulance from their homes. The patients’ core temperatures were recorded by the Fire Department of Nagoya City in the summers of 2019 and 2020. The time course of the core temperature of each patient was then replicated using the integrated computational techniques through multiphysics analysis and thermoregulation under ambient condition data. According to the statistics, most elderly patients who were transported from their homes had a high core temperature. The measured core temperature in 31.4% of the patients was higher than the computed core temperature even assuming that there was no sweating. Assuming that the sweating function works well, the total amount of water loss was insufficient to have caused dehydration in a single day. These results suggest that successive heat stress during the preceding days should be considered to recreate the computed core temperature to match the measurement. These results were consistent with the previous finding that some elderly suffered from heatstroke successively over a few days. In the IoT-based monitoring system development, it would be informative for monitoring core temperature during the preceding days.
Objective: This study explored the effect of multiple-nutrient supplementation on muscle damage and liver and kidney function after vigorous exercise under heat. Methods: After an initial pilot trial comprising 89 male participants, 85 participants were recruited and assigned into three groups: a multiple-nutrient (M) group, a glucose (G) group, and a water (W) group. Multiple-nutrient supplements contain glucose, fructose, maltose, sodium, potassium, vitamin B(1), vitamin B(2), vitamin C, vitamin K, and taurine. Participants were organised to take a 3-km running test (wet-bulb globe temperature 32??C) after a short-term (7 days) supplement. Blood samples were obtained to detect biochemical parameters [glucose (GLU), aspartate aminotransferase (AST), alanine aminotransferase (ALT), blood urea nitrogen (BUN), uric acid (UA), creatinine (Cr), creatine kinase (CK), lactate dehydrogenase (LDH), and lactic acid], inflammation factors [interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α)], and oxidative stress biomarkers [superoxide dismutase (SOD) and 8-iso-prostaglandin F (2alpha) (8-iso-PGF2α)]. Results: In the pilot trial, BUN decreased significantly in the M and G groups immediately after the running test. AST, Cr, and UA were significantly reduced 24 h after the running test with single-shot multiple-nutrient supplementation. In the short-term trial, multiple nutrients further prevented the elevation of CK (p = 0.045) and LDH (p = 0.033) levels 24 h after strenuous exercise. Moreover, we found that multiple nutrients significantly reduced IL-6 (p = 0.001) and TNF-α (p = 0.015) elevation immediately after exercise. Simultaneously, SOD elevation was significantly higher in the M group immediately after exercising than in the other two groups (p = 0.033). 8-iso-PGF2α was reduced in the M group 24 h after exercise (p = 0.036). Conclusions: This study found that multiple-nutrient supplementation promoted the recovery of muscle damage and decreased liver and kidney function caused by strenuous exercise in a hot environment, probably through the inhibition of secondary damage induced by increased inflammatory reactions and oxidative stress. In this respect, the current study has important implications for the strategy of nutritional support to accelerate recovery and potentially prevent heat-related illness. This study was prospectively registered on clinicaltrials.gov on June 21, 2019 (ID: ChiCTR1900023988).
Energy efficiency in the housing sector is important for achieving carbon neutrality; to achieve this, more net-zero energy houses (ZEHs) are required. ZEHs are considered resilient to power outages. However, the type of living that can be achieved during a power outage is unclear. The purpose of this study was to examine the feasibility of staying in a ZEH with thermal comfort without a risk of heat stroke dur-ing summer power outages. We created daily schedules and conducted experiments using an actual ZEH assuming a power outage in summer. The experimental house was constructed in the suburbs of Shizuoka (about 110 km west of Tokyo), Japan, which has a humid subtropical climate. The house was equipped with a photovoltaic system of 4.62 kW and a storage battery capacity of 5.6 kWh, which can output up to 2.0 kVA. The results showed that ZEH can provide air conditioning (AC), ventilation, lighting, refrigerator, cell phone charging, televisions, and hot water supply for a 72-hour power outage. However, the use of high-load appliances and the use of bedroom AC during sleeping time caused disruption in the power supply. The use of AC on an independent circuit resulted in a predicted mean vote (PMV) of-0.5 ti 0.8, and a wet-bulb globe temperature of approximately 23 degrees C was achieved. Thus, thermal com-fort with a low risk of heat stroke was maintained. Solar shading and window openings were however not considered and further research is needed to evaluate more varied architectural design and behaviors, and to assess the potential for staying at home in a ZEH. Different weather conditions and different occu-pant assumptions (e.g., elderly) also need to be further studied.(c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
In the past, thermal comfort in naturally ventilated hospital wards was not a major issue to discuss, but now this matter needs to be revisited following the effects of climate change. A Hybrid Photovoltaic Thermal (PVT) and Heat Pump System (HPVTHPS) was proposed in this field study to enhance the thermal comfort of naturally ventilated hospital wards. The heat pump was used for heating water and producing cold air to reduce the air temperature in the ward, besides being an active cooling agent to improve the performance of the PVT system. Thus, the main purpose of this article is to evaluate an on-site performance of a HPVTHPS in providing hot water and space cooling for naturally ventilated hospital wards in tropical climates. Overall, the proposed HPVTHPS installation has reduced the room temperature of the hospital ward compared to the baseline temperature with an average temperature drop ranging from 0.5 degrees C to 3.9 degrees C. The PVT system also shows high efficiency values between 51.0% and 69.0% which include thermal and electrical energy performance. The findings in this study are very useful for hospital management in improving thermal comfort in hospital wards using efficient and low energy systems.
Power grid outdoor workers are usually exposed to hot environments and could suffer the threats to occupational health and safety like heat strain and injury. In order to predict and assess the thermophysiological responses of grid workers in the heat, the clothing thermal insulation of grid worker ensembles was measured by a thermal manikin and a multi-segment human bioheat model was employed to evaluate the thermophysiological response parameters of grid workers such as core temperature, skin temperature and sweat loss. The results show that working in a hot environment can cause a obvious increase in core temperature and skin temperature of grid workers, and the acceptable maximum working time of grid workers varies greatly in different hot environments. A reasonable work organization strategy can effectively decrease the core temperature and sweat loss, increasing the duration of acceptable maximum working time for grid workers. This study is helpful to assess heat-related risks of grid workers and support power grid companies to rationalize work organization strategies and personal protection guidelines.
Occupational heat stress is a crucial risk factor for a range of Heat-Related Illnesses (HRI). Outdoor workers in unorganized work sectors exposed to high ambient temperatures are at increased risk in developing countries. We aim to compare HRI, Productivity Loss (PL), and reduced renal health risk between workers from outdoor unorganized (N = 1053) and indoor organized (N = 1051) work sectors. Using descriptive methods and a large epidemiological cross-sectional study using mixed methods, we compared risk patterns between the two groups. We analyzed the risk of self-reported HRI symptoms, Heat Strain Indicators (HSIs), PL, and reduced kidney function using Multivariate Logistic Regression (MLR) models. Although Wet Bulb Globe Temperature (WBGT) exposures were high in both the outdoor and indoor sectors, significantly more Outdoor Unorganized Workers (OUWs) reported heat stress symptoms (45.2% vs 39.1%) among 2104 workers. OUWs had a significantly higher share of the heavy workload (86.7%) and long years of heat exposures (41.9%), the key drivers of HRIs, than the workers in indoor sectors. MLR models comparing the indoor vs outdoor workers showed significantly increased risk of HRI symptoms (Adjusted Odds Ratio) (AOR(outdoor) = 2.1; 95% C.I:1.60-2.77), HSI (AOR(outdoor) = 1.7; 95% C.I:1.00-2.93), PL (AOR(outdoor) = 11.4; 95% C.I:7.39-17.6), and reduced kidney function (Crude Odds Ratio) (CORoutdoor = 1.4; 95% C.I:1.10-1.84) for the OUWs. Among the heat-exposed workers, OUW had a higher risk of HRI, HSI, and PL even after adjusting for potential confounders. The risk of reduced kidney function was significantly higher among OUWs, particularly for those with heat exposures and heavy workload (AOR(outdoor) = 1.5; 95% C.I: 0.96-2.44, p = 0.073) compared to the indoor workers. Further, in-depth studies, protective policies, feasible interventions, adaptive strategies, and proactive mitigation efforts are urgently needed to avert health and productivity risks for a few million vulnerable workers in developing nations as climate change proceeds.
BACKGROUND: Although age and regional climate are considered to have effects on the incidence ratio of heat-related illness, quantitative estimation of age or region on the effect of occurring temperature for heat stroke is limited. METHODS: By utilizing data on the number of daily heat-related ambulance transport (HAT) in each of three age groups (7-17, 18-64, 65 years old, or older) and 47 prefectures in Japan, and daily maximum temperature (DMT) or Wet Bulb Globe Temperature (DMW) of each prefecture for the summer season, the effects of age and region on heat-related illness were studied. Two-way ANOVA was used to analyze the significance of the effect of age and 10 regions in Japan on HAT. The population-weighted average of DMT or DMW measured at weather stations in each prefecture was used as DMT or DMW for each prefecture. DMT or DMW when HAT is one in 100,000 people (T(1) and W(1), respectively) was calculated for each age category and prefecture as an indicator of heat acclimatization. The relation between T(1) or W(1) and average DMT or DMW of each age category and prefecture were also analyzed. RESULTS: HAT of each age category and prefecture was plotted nearly on the exponential function of corresponding DMT or DMW. Average R(2) of the regression function in 47 prefectures in terms of DMW was 0.86, 0.93, and 0.94 for juveniles, adults, and elderly, respectively. The largest regional difference of W(1) in 47 prefectures was 4.5 and 4.8 °C for juveniles and adults, respectively between Hokkaido and Tokyo, 3.9 °C for elderly between Hokkaido and Okinawa. Estimated W(1) and average DMT or DMW during the summer season for 47 prefectures was linearly related. Regarding age difference, the regression line showed that W(1) of the prefecture for DMW at 30 °C of WBGT was 31.1 °C, 32.4 °C, and 29.8 °C for juveniles, adults, and elderly, respectively. CONCLUSIONS: Age and regional differences affected the incidence of HAT. Thus, it is recommended that public prevention measures for heat-related disorders take into consideration age and regional variability.
The last century has seen a gradual increase in global average temperatures-a phenomenon that has come to be known as global warming. The World Meteorological Organization (WMO) has reported that 2020 was one of the three warmest years on record and that the global average temperature was ~1.2°C above preindustrial (1850-1900) levels [1]. Adverse effects on health resulting from global warming are important issues to consider, as health risks associated with such extreme heat are anticipated [2]. In fact, this warming has been shown to severely limit human activity in tropical and mid-latitude regions [3], and in particular, outdoor and manual workers who are exposed to ambient heat during working hours are susceptible to increased health risks. Thus, workers should pay attention to their own physical conditions and proactively keep out of the heat to rest when uncomfortable. Additionally, supervisors must manage worker’s physical conditions and schedule regular breaks. Therefore, in this trial a new integrated system was developed to notify individuals at risk based on their thermal physiology. This method uses biological and environmental information obtained directly via wearable sensors and the estimated body core temperature collected on-ground cannot be measured wirelessly and noninvasively [4].
Introduction: A wide variety of diseases alter the perceptions of different sensations, often evaluated in a subjective manner. Assessment of temperature perception and tolerance is a useful screening tool to evaluate the Degenerative and neuropathic changes of an individual. Therefore the current study was intended to design and develop an inexpensive device to quantify the heat threshold and tolerance in healthy participants. Materials and methods: The study was carried out in 30 apparent healthy participants for heat threshold, and tolerance was recorded on both hands’ thenar and dorsal sites on two occasions. The minimum temperature when the subject was perceived is threshold and maximum until the subject withstood tolerance. The data was collected using the electronically controlled device for these two extremes. The entire study was carried out at a controlled room temperature precisely.Results: The heat threshold was 39.84 ± 2.33 °C, and the tolerance was perceived at 46.84 ± 3.36 °C. There were no intraindividual differences (p > 0.05) in the heat threshold measured on two different periods as well as between the two hands (p > 0.05). As expected, there were significantly higher threshold values on the palm’s thenar aspect than dorsum (p < 0.05). The tolerance was significantly higher in the thenar aspect than the dorsum of both hands. (p < 0.01, p-0.03). There were no significant inter-hand differences of both surfaces of the hand. Conclusion: Our study showed that the results of threshold and tolerance using the indigenously built device were consistent and reproducible proves the robustness of the methodology. It is a cost-effective and user-friendly device that provides quantitative results of temperature extremes.
Heat stress provokes thermal discomfort to people living in semiarid and arid climates. This study evaluates thermal discomfort levels, building design concepts, and some heat mitigation strategies in low-income neighborhoods of Faisalabad, Pakistan. The outdoor and indoor weather data are collected from April to August 2016 using a weather station installed ad hoc in urban settings, and the 52 houses of the five low-income participating communities living in congested and less environment-friendly areas of Faisalabad. The discomfort index values, related to the building design concepts, including (i) house orientation to sunlight and (ii) house ventilation, are calculated from outdoor and indoor dry-bulb and wet-bulb temperatures. Our results show that although June was the hottest month of summer 2016, based on the monthly mean temperature of the Faisalabad region, the month of May produced the highest discomfort levels, which were higher in houses exposed to sunlight and without ventilation. The study also identifies some popular heat mitigation strategies adopted by the five participating low-income communities during various heat-related health complaints. The strategies are gender-biased and have medical, cultural/customary backgrounds. For example, about 52% of the males and 28% of the females drank more water during dehydration, diarrhea, and eye infection. Over 11% and 19% of the males and females, respectively, moved to cooler places during fever. About 43% of the males and 51% of the females took water showers and rested to combat flu (runny nose), headache, and nosebleed. The people did not know how to cure muscular fatigue, skin allergy (from a type of Milia), and mild temperature. Planting trees in an area and developing open parks with greenery and thick canopy trees can be beneficial for neighborhoods resembling those evaluated in this study.
The heat increase caused by climate change has worsened the urban heat environment and damaged human health, which has led to heat-related mortality. One of the most important ways to respond to heat-related damage is to develop effective forecasting tools. However, accurately predicting heatwave damage is difficult in regions in a city with different conditions. Damage due to extreme heat can be evaluated differently in each region, as climatic, demographic and socioeconomic sectors are diversely distributed across local areas. In this study, we develop a random forest-based model for estimating the occurrence of heat-related mortality in a detailed spatial unit within a city. Through hyperparameter optimization, the model yielded accuracy, F1-score and AUC values of 90.3%, 94.75%, and 86%, respectively. The estimation results of the model were interpreted from the global and local perspectives by introducing the latest SHAP method. As a result of interpretation, demographic, socioeconomic and climatic sectors were determined to contribute the most to the estimation process. This is the first study of partial scenarios through the development and interpretation of a spatial unit machine learning-based occurrence estimation model for heat-related mortality.
The frequency and intensity of compound hot extremes will be likely to increase in the context of global warming. Epidemiological studies have demonstrated the adverse effect of simple hot extreme events on mortality, but little is known about the effects of compound hot extremes on mortality. Daily meteorological, demographic, and mortality data during 2011-2017 were collected from 160 streets in Guangzhou City, China. We used distributed lag non-linear model (DLNM) to analyze the associations of different hot extremes with mortality risk in each street. Street-specific associations were then combined using a meta-analysis approach. To assess the spatial distribution of vulnerability to compound hot extremes, vulnerable characteristics at street level were selected using random forest model, and then we calculated and mapped spatial vulnerability index (SVI) at each street in Guangzhou. At street level, compared with normal day, compound hot extreme significantly increased mortality risk (relative risk(RR)=1.43, 95%CI:1.28-1.59) with higher risk for female (RR=1.54 [1.35-1.76]) and the elderly(RR for aged 65-74=1.41 [1.14-1.74]; RR for ≥75years=1.63 [1.45-1.84]) than male (RR=1.32 [1.15-1.52]) and population <65 years (RR=1.01 [0.83-1.22]). Areas with high vulnerability were in the urban center and the edge of suburban. High proportion of population over 64 years old in urban center, and high proportions of outdoor workers and population with illiteracy in suburban areas were the determinants of spatial vulnerability. We found that compound hot extreme significantly increased mortality risk at street level, which is modified by socio-economic and demographic factors. Our findings help allocate resources targeting vulnerable areas at fine-spatial scale.°.
BACKGROUND: Previous studies have reported numerous environmental factors for atopic dermatitis (AD), such as allergens and chemical stimulants. However, few studies have addressed the relationship between ambient air pollution and AD at a population level. OBJECTIVE: To evaluate the effect of air pollutants on medical care visits for AD and to identify susceptible populations. METHODS: In this time-series study conducted on 513,870 medical care visits for AD from 2012 to 2015 identified by reviewing national health insurance claim data in Incheon, Republic of Korea. Treating daily number of medical care visits for AD as a dependent variable, generalized additive models with Poisson distributions were constructed, which included air pollutant levels, ambient temperature, relative humidity, day of the week, national holiday, and season. Risks were expressed as relative risks (RR) with 95% confidence intervals (95% CIs) per interquartile range increase of each air pollutant. RESULTS: Higher levels of particulate matter of diameter ≤10 μm (PM(10)) (RR, 1.009; 95% CI, 1.007-1.012), ozone (1.028; 1.023-1.033), and sulfur dioxide (1.033; 1.030-1.037) were significantly associated with increased risk of medical care visits for AD on same days. In all age and sex groups, ozone was associated with a significantly higher risk of medical care visits, with the greatest risk among 13- to 18-year-old males (RR, 1.127; 95% CI, 1.095-1.159). CONCLUSION: This study suggests relationships of ambient PM(10), ozone, and sulfur dioxide levels with medical care visits for AD.
Several air pollution episodes occurred in Beijing before and after the 2014 Asia-Pacific Economic Cooperation (APEC) summit, during which air-pollution control measures were implemented. Within this autumn-winter transit season, domestic heating started. Such interesting period merits comprehensive chemical characterization, particularly the organic species, to look into the influence of additional heating sources and the control measures on air pollution. Therefore, this study performed daily and 6h time resolved PM2.5 sampling from the 24th October to 7th December, 2014, followed by comprehensive chemical analyses including water-soluble ions, elements and organic source-markers. Apparent alterations of chemical profiles were observed with the initiation of domestic heating. Through positive matrix factorization (PMF) source apportionment modeling, six PM2.5 sources including secondary inorganic aerosol (SIA), traffic emission, coal combustion, industry emission, biomass burning and dust were separated and identified. Coal combustion was successfully distinguished from traffic emission by hopane diagnostic ratio. The result of this study reveals a gradual shift of dominating sources for PM pollution episodes from SIA to primary sources after starting heating. BaPeq toxicity from coal combustion increased on average by several to dozens of times in the heating period, causing both long-term and short-term health risk. Air mass trajectory analysis highlights the regional influence of the industry emissions from the area south to Beijing. Control measures taken during APEC were found to be effective for reducing industry source, but less effective in reducing the overall PM2.5 level. These results provide implications for policy making regarding appropriate air pollution control measures. (c) 2021 Elsevier Ltd. All rights reserved.
The seasonal and meteorological factors in predicting infections after urological interventions have not been systematically evaluated. This study aimed to determine the seasonality and the effects of the weather on the risk and severity of infectious complications (IC) after a transrectal ultrasound-guided prostate biopsy (TRUS-Bx). Using retrospectively collected data at the tertiary care hospital in Taiwan, we investigated the seasonal and meteorological differences in IC after TRUS-Bx. The IC included urinary tract infection (UTI), sepsis, and a positive culture finding (PCF). The severity was assessed on the basis of the Common Terminology Criteria for Adverse Events grading system. The prevalences of the infectious complications (UTI, sepsis, PCF and grade ≥ 3 IC) were significantly higher in the summer than in the winter. Monthly temperature and average humidity were significant factors for IC. After adjusting the demographic factors, multivariate regression revealed that UTI, sepsis, PCF, and grade ≥ 3 IC increased by 12.1%, 16.2%, 21.3%, and 18.6% for every 1 °C increase in the monthly average temperature, respectively (UTI: p = 0.010; sepsis: p = 0.046; PCF: p = 0.037; grade ≥ 3 IC: p = 0.021). In conclusion, the development and severity of IC after TRUS-Bx had significant seasonality. These were dose-dependently associated with warmer weather. Infectious signs after TRUS-Bx should be monitored more closely and actively during warm weather.
The urban heat island (UHI) phenomenon has become a major concern for city sustainability in the wake of global warming and rapid urbanization. This has resulted in increased heat stress and worsened outdoor thermal comfort in urban microclimates. The study demonstrated that outdoor thermal stress pedestrians can be reduced in single streets by adopting mitigation strategies, that is, cool materials, vegetation, and water bodies. In this article, computational fluid dynamics (CFD) simulations using URANS modeling for four different scenarios have been performed to investigate the effectiveness of different mitigation measures in hot, humid urban climates conditions. The reduction of ambient air temperature and surface temperature characterizing the mitigation (cooling) intensity is examined at pedestrian height and diverse vertical levels. The analysis shows that on its own, water provides the largest reduction in air temperature at pedestrian height (2 degrees C), and cool materials provide a larger reduction in surface temperature (6 degrees C). When applied individually, cool materials are the more effective in the vertical direction with a UHI mitigation intensity of 1.5 degrees C, followed by vegetation, with a mitigation intensity of 1.0 degrees C. Furthermore, the impact (temperature reduction) is more significant when all three measures are combined, with a large reduction of 2 degrees C in air temperature and 9 degrees C in surface temperature observed compared to the reference case.
This study aims to develop and validate prediction models for the number of all heatstroke cases, and heatstrokes of hospital admission and death cases per city per 12 h, using multiple weather information and a population-based database for heatstroke patients in 16 Japanese cities (corresponding to around a 10,000,000 population size). In the testing dataset, mean absolute percentage error of generalized linear models with wet bulb globe temperature as the only predictor and the optimal models, respectively, are 43.0% and 14.8% for spikes in the number of all heatstroke cases, and 37.7% and 10.6% for spikes in the number of heatstrokes of hospital admission and death cases. The optimal models predict the spikes in the number of heatstrokes well by machine learning methods including non-linear multivariable predictors and/or under-sampling and bagging. Here, we develop prediction models whose predictive performances are high enough to be implemented in public health settings.
Urban heat islands (UHI) are a widely documented phenomenon that adversely increases urban overheating and, among other effects, contributes to heat-related mortalities and morbidities in urban areas. Consequently, comprehensive UHI-mitigating measures are essential for improving urban microclimate environments and contributing to salutogenic urban design practices. This study proposed urban cooling strategies involving different tree percentages and leaf area densities in a dense urban area during the summertime in Korea. The cooling effects of sixteen various combinations of proposed scenarios based on common urban tree types were studied via in-situ field measurements and numerical modeling, considering both vegetated and exposed areas. It was observed that by changing the characteristics of the leaf area density (LAD) per plant of our vegetated base area—for instance, from 4% trees to 60% trees, from a low LAD to a high LAD—the daily average and daily maximum temperatures were reduced by approximately 3 °C and 5.23 °C, respectively. The obtained results demonstrate the usefulness of urban trees to mitigate urban heating, and they are particularly useful to urban designers and policymakers in their efforts to minimize UHI effects.
A few studies on outdoor human thermal comfort (HTC) have been conducted in the tropical region in a hot and humid climate; however, there is a paucity of discussions on how exactly different spatial settings influence HTC. Thus, this paper aims to examine how land use land cover (LULC) affects HTC on the basis of the simulation of Predicted Mean Vote (PMV) and Physiologically Equivalent Temperature (PET) indices via ENVI-met and Rayman. The results reveal that people living in the urban area have a higher tendency to experience strong heat stress (25% of the areas with PMV ranging from 3.4 to 3.9 and 2% of the areas, where PMV reached 4.1), followed by the rural area (43% of the areas with PMV ranging from 2.1 to 2.4), and the suburban area (more than 50% of the areas with PMV values less than 2.4). Surprisingly, a concrete LULC in the suburb area exhibits a higher air temperature than an asphalt surface at 4 p.m., due to the large area of high albedo that increases the reflection of solar radiation, subsequently contributing to warming up the airmass. Similarly, sandy, and loamy LULC tend to emit more heat during nighttime, while the heat is absorbed slowly during daytime, and it is then slowly released during nighttime after 6 p.m. Spatial settings that promote heat stress in the urban area are mainly contributed by an LULC of asphalt, concrete, sandy, and loamy areas. Meanwhile, people in the suburban and rural areas are less likely to experience heat stress, due to agricultural plantations and lowland forest that provide shade, except for the barren lands-loamy areas. The result also indicates that tree-covered areas near the river in the suburban area afforded the best thermal experience with PMV of 2.1 and PET of 30.7. From the LULC comparison, it is pivotal to consider tree species (canopy density), surface material (albedo), sky-view factor, wind direction, and speed toward designing a more comfortable and sustainable environment.
In this study, we aimed to develop and validate a machine learning-based mortality prediction model for hospitalized heat-related illness patients. After 2393 hospitalized patients were extracted from a multicentered heat-related illness registry in Japan, subjects were divided into the training set for development (n = 1516, data from 2014, 2017-2019) and the test set (n = 877, data from 2020) for validation. Twenty-four variables including characteristics of patients, vital signs, and laboratory test data at hospital arrival were trained as predictor features for machine learning. The outcome was death during hospital stay. In validation, the developed machine learning models (logistic regression, support vector machine, random forest, XGBoost) demonstrated favorable performance for outcome prediction with significantly increased values of the area under the precision-recall curve (AUPR) of 0.415 [95% confidence interval (CI) 0.336-0.494], 0.395 [CI 0.318-0.472], 0.426 [CI 0.346-0.506], and 0.528 [CI 0.442-0.614], respectively, compared to that of the conventional acute physiology and chronic health evaluation (APACHE)-II score of 0.287 [CI 0.222-0.351] as a reference standard. The area under the receiver operating characteristic curve (AUROC) values were also high over 0.92 in all models, although there were no statistical differences compared to APACHE-II. This is the first demonstration of the potential of machine learning-based mortality prediction models for heat-related illnesses.
The changing climate has introduced new and unique challenges and threats to humans and their environment. Urban dwellers in particular have suffered from increased levels of heat stress, and the situation is predicted to continue to worsen in the future. Attention toward urban climate change adaptation has increased more than ever before, but previous studies have focused on indoor and outdoor temperature patterns separately. The objective of this research is to assess the indoor and outdoor temperature patterns of different urban settlements. Remote sensing data, together with air temperature data collected with temperature data loggers, were used to analyze land surface temperature (outdoor temperature) and air temperature (indoor temperature). A hot and cold spot analysis was performed to identify the statistically significant clusters of high and low temperature data. The results showed a distinct temperature pattern across different residential units. Districts with dense urban settlements show a warmer outdoor temperature than do more sparsely developed districts. Dense urban settlements show cooler indoor temperatures during the day and night, while newly built districts show cooler outdoor temperatures during the warm season. Understanding indoor and outdoor temperature patterns simultaneously could help to better identify districts that are vulnerable to heat stress in each city. Recognizing vulnerable districts could minimize the impact of heat stress on inhabitants.
Global climate is changing as a result of anthropogenic warming, leading to higher daily excursions of temperature in cities. Such elevated temperatures have great implications on human thermal comfort and heat stress, which should be closely monitored. Current methods for heat exposure assessments (surveys, microclimate measurements, and laboratory experiments), however, present several limitations: measurements are scattered in time and space and data gathered on outdoor thermal stress and comfort often does not include physiological and behavioral parameters. To address these shortcomings, Project Coolbit aims to introduce a human-centric approach to thermal comfort assessments. In this study, we propose and evaluate the use of wrist-mounted wearable devices to monitor environmental and physiological responses that span a wide range of spatial and temporal distributions. We introduce an integrated wearable weather station that records (a) microclimate parameters (such as air temperature and humidity), (b) physiological parameters (heart rate, skin temperature and humidity), and (c) subjective feedback. The feasibility of this methodology to assess thermal comfort and heat stress is then evaluated using two sets of experiments: controlled-environment physiological data collection, and outdoor environmental data collection. We find that using the data obtained through the wrist-mounted wearables, core temperature can be predicted non-invasively with 95 percent of target attainment within +/- 0.27 degrees C. Additionally, a direct connection between the air temperature at the wrist (T-a,T-w) and the perceived activity level (PAV) of individuals was drawn. We observe that with increased T-a,T-w, the desire for physical activity is significantly reduced, reaching ‘Transition only’ PAV level at 36 degrees C. These assessments reveal that the wearable methodology provides a comprehensive and accurate representation of human heat exposure, which can be extended in real-time to cover a large spatial distribution in a given city and quantify the impact of heat exposure on human life.
Extreme heat is a leading cause of weather-related human mortality throughout much of the world, posing a significantly heavy burden on the development of healthy and sustainable cities. To effectively reduce heat health risk, a better understanding of where and what risk factors should be targeted for intervention is necessary. However, little research has examined how different risk factors for heat-related mortality operate at varying spatial scales. Here, we present a novel application of the multiscale geographically weighted regression (GWR) approach to explore the scale of effect of each underlying risk factor using Hong Kong as a case study. We find that a hybrid of global and local processes via multiscale GWR yields a better fit of heat-related mortality risk than models using GWR and ordinary least squares (OLS) approaches. Predictor variables are categorized by the scale of effect into global variables (i.e., age and education attainment, socioeconomic status), intermediate variables (i.e., work place, birth place and language), and local variables (i.e., thermal environment, low in-come). These findings enrich our understanding of the spatial scale-dependent risk factors for heat-related mortality and shed light on the importance of hierarchical policy-making and site-specific planning processes in effective heat hazard mitigation and climate adaptation strategies.
The purpose of this study was to compare the efficacy of four cooling interventions used for reducing physiological and perceptual strain and improving exercise performance during outdoor match-play tennis in the heat. Eight competitive tennis players played four counter-balanced simulated outdoor matches in the heat (WBGT: 28.4-32.5°C) at 24- or 48-h intervals. Each match comprised 3 sets for which the “no-ad” rule was applied to limit duration variability. Players underwent the following cooling interventions: ad libitum fluid ingestion (CON), ad libitum fluid ingestion and ice vest (VEST), total ingestion of approximately 1000 g ice slurry and ice vest (Combined: BINE), or total ingestion of approximately 400 g ice slurry and ice vest (Low-combined: L-BINE). Gastrointestinal temperature was lower in the BINE and the L-BINE trials than in the CON trial at the set-break of set 1, and these differences in gastrointestinal temperature persisted throughout the remainder of the match (p < 0.05). The ratio of moderate-high intensity activity (≥10 km/h) in set 3 was significantly higher in the L-BINE trial than that in the BINE trial (p < 0.05). In the CON and BINE trials, high intensity activity was significantly lower in set 3 compared with set 1 and 2, respectively. Cooling by optimal ice slurry ingestion and ice vest may be a more effective strategy in mitigating the development of heat strain during outdoor match-play tennis in the heat.
Heat strain impairs performance across a broad spectrum of sport disciplines. The impeding effects of hyperthermia and dehydration are often ascribed to compromised cardiovascular and muscular functioning, but expert performance also depends on appropriately tuned sensory, motor and cognitive processes. Considering that hyperthermia has implications for central nervous system (CNS) function and fatigue, it is highly relevant to analyze how heat stress forecasted for the upcoming Olympics may influence athletes. This paper proposes and demonstrates the use of a framework combining expected weather conditions with a heat strain and motor-cognitive model to analyze the impact of heat and associated factors on discipline- and scenario-specific performances during the Tokyo 2021 games. We pinpoint that hyperthermia-induced central fatigue may affect prolonged performances and analyze how hyperthermia may impair complex motor-cognitive performance, especially when accompanied by either moderate dehydration or exposure to severe solar radiation. Interestingly, several short explosive performances may benefit from faster cross-bridge contraction velocities at higher muscle temperatures in sport disciplines with little or no negative heat-effect on CNS fatigue or motor-cognitive performance. In the analyses of scenarios and Olympic sport disciplines, we consider thermal impacts on “motor-cognitive factors” such as decision-making, maximal and fine motor-activation as well as the influence on central fatigue and pacing. From this platform, we also provide perspectives on how athletes and coaches can identify risks for their event and potentially mitigate negative motor-cognitive effects for and optimize performance in the environmental settings projected.
The pilgrimages of Muslims to Makkah (Hajj and Umrah) is one of the largest religious gatherings in the world which draws millions of people from around 180 countries each year. Heat stress during summer has led to health impacts including morbidity and mortality in the past, which is likely to worsen due to global warming. Here we investigate the impacts of increasing heat stress during the peak summer months over Makkah at present levels of warming as well as under Paris Agreement’s targets of 1.5 degrees C and 2 degrees C global mean temperature increase above pre-industrial levels. This is achieved by using multi member ensemble projections from the half a degree additional warming, prognosis and projected impacts project. We find a substantial increase in the exceedance probabilities of dangerous thresholds (wet-bulb temperature >24.6 degrees C) in 1.5 degrees C and 2 degrees C warmer worlds over the summer months. For the 3 hottest months, August, September and October, even thresholds of extremely dangerous (wet-bulb temperature >29.1 degrees C) health risks may be surpassed. An increase in exceedance probability of dangerous threshold is projected by two and three times in 1.5 degrees C and 2 degrees C warmer worlds respectively for May as compared to the reference climate. September shows the highest increase in the exceedance probability of extremely dangerous threshold which is increased to 4 and 13 times in 1.5 degrees C and 2 degrees C warmer worlds respectively. Based on the indicators of hazard, exposure and vulnerability, we carried out probabilistic risk analysis of life-threatening heat stroke over Makkah. A ten time increase in the heat stroke risk at higher wet-bulb temperatures for each month is projected in 2 degrees C warmer world. If warming was limited to 1.5 degrees C world, the risk would only increase by about five times, or half the risk of 2 degrees C. Our results indicate that substantial heat related risks during Hajj and Umrah happening over peak summer months, as it is the case for Hajj during this decade, will require substantial adaptation measures and would negatively affect the performance of the rite. Stringent mitigation actions to keep the global temperature to 1.5 degrees C can reduce the risks of heat related illnesses and thereby reduce the non-economic loss and damage related to one of the central pillars of a world religion.
This study aims to provide an in-depth understanding of what motivates older adults to take their adaptive behaviors during extreme heat events. Elaborating the mediating role of emotion in human behaviors, we empirically explore an interrelationship between individuals’ cognition, emotion, and heat-protective action in response to heat warning system alarms. Through face-to-face surveys and structural equation modeling, this study reveals that an increased level of cognition about climate change, heat waves, and local policy measures leads to emotional responses such as concern and worry, and consequently encourages people to comply with heat-related public guidelines. Furthermore, we also consider individuals’ pre-existing health conditions and their previous experiences of heat-related illnesses together with the emotional factors. The role of emotion in mediating between cognition and heat-protective action is much greater than in mediating between pre-existing health conditions and heat-protective action. We conclude that policy interventions to educate older adults can effectively increase the likelihood of individual compliance with the relevant preventive measures beyond their individual health and experiences.
How to maximize the cooling effect of urban parks in hot extremes has been closely linked to well-beings of citizens. Few studies have quantified urban parks’ cooling effect in hot extremes from both maximum and accumulative perspectives. Here, we explored 65 urban parks’ cooling effect based on spatially continuous cooling curves using multiple satellite images of Greater Xi’an (34 degrees 06′ similar to 34 degrees 34′ N, 108 degrees 33′ similar to 109 degrees 15′ E), one of China’s metropolises with frequent hot extremes during July and August in 2019 summer. From maximum perspective, the urban parks cool down as far as 151.4 m, and covering 63.62 ha area, circa five times their own area in hot extremes; from accumulative perspective, the average cooling intensity is 0.78 degrees C along the whole continuous cooling distance spectrum, accumulated as 153.87 degrees C.m. And the urban parks show stronger accumulative cooling effect in hot extremes than the relative moderate temperatures. The cooling range could be maximized in large parks with dense trees, also in complex-shaped parks with strong interaction with surrounding environment. Small parks such as neighborhood parks located in the densely populated area are with maximum efficiency, cooling down about nine times their own area, which could serve as highly efficient cooling networks. Enhancing vegetation growth and coupling both blue and green infrastructures are always effective to increase accumulative cooling intensity in hot extremes. Our findings provide nature-based solutions (NBS) to counteracting heat stresses from the intense and frequent hot extremes in the future, also helpful for energy saving in the continuing climate change scenario.
As the frequency, duration, and intensity of heat waves have been increasing in recent decades, the effective and efficient allocation of cooling shelters has become a significant issue in many cities. This study presents an integer programming model for allocating cooling shelters with the two conflicting objectives of maximizing coverage for the heat-vulnerable population and minimizing total operating cost of the cooling shelters. The temperature-humidity index is included in the model to reflect the weather conditions that affect heat waves. We also introduce data analysis procedures using real-time floating population data so as to track the hourly number and locations of individuals in the heat-vulnerable population. The proposed model is then validated with an application to Ulsan Metropolitan City in the Republic of Korea in which heat-vulnerable people are assigned to existing and potential cooling shelters. Given the condition of restricted budgets, we categorize and prioritize heat-vulnerable people into several groups using a clustering method and heat vulnerability index, and we suggest effective policy recommendations, so the most vulnerable people are provided cooling services first. In addition, we perform a sensitivity analysis on weather conditions, travel distance, electricity cost, and percentage of heatvulnerable population served by cooling shelters, so policy makers can be prepared to respond quickly to the various factors that can change during a heat wave and ultimately reduce heatrelated morbidity and mortality.
The rising episodes of deadly heat waves have intensified the need for a heat protection strategy. The Unani system of medicine offers ways to stay healthy in different climatic conditions. Hence, this article aims to discuss the applicability of health protection measures suggested by Unani scholars for hot weather conditions in the light of current researches. The manual literature survey of classical Unani texts was conducted to collect information on health safety measures for hot weather. A substantial search of scientific databases such as “Google Scholar” and “Medline” for proposed measures in combination with “heat-stroke”, “heat exhaustion” and “heat rash” was also conducted to identify their possible activity in heat-related illnesses. The guidelines for summer seasons in the classical Unani literature are described under the title tadābīr-i-mavsam. Unani scholars have discussed in detail the pathophysiological effects of heat and the measures to stay healthy by regulating the body system through lifestyle, diet and herbs. Most of the measures proposed by them are backed up by evidences. However, some measures have not yet been evaluated for their therapeutic or prophylactic efficacy in heat-related illnesses. On the basis of findings, the authors advocate the adoption of evidence-based measures and propose further investigation of those measures that are not well supported by the evidence or have not yet been evaluated.
Using the China Health and Retirement Longitudinal Study, this paper studies the impact of abnormal hot temperature on residents’ demand for commercial health insurance. The results show that for every 1°F rise in abnormal temperature, the probability of people buying commercial health insurance increased by 6%. Furthermore, the abnormal hot temperature has a more significant impact on the commercial health insurance demand of women, residents in the South and residents in the East. Channel analysis shows that abnormal hot temperature affects the demand for commercial health insurance through two channels: increasing residents’ concern about climate risk and affecting health. This paper provides evidence for actively promoting sustainable development and improving the construction of medical security system.
Arba’een, a Muslim pilgrimage, is one of the largest annual mass gatherings in the world, with a date fixed according to the lunar calendar. Most pilgrims start their long walking journey from Basra/Najaf toward Karbala (about 70-500 km) and are significantly affected by outdoor weather conditions during this period. Here, based on simulations performed using carefully-selected climate models, we project that heat stress during the pilgrimage is likely to reach a “dangerous” level, defined according to the US National Weather Service criteria, by the end of this century. Moreover, a significant increase in consecutive occurrence of hot days and hot nights is expected within the coming decades, which may cause a high incidence of heat-related disorders as the human body may not recover from the daytime heat loads. Our study suggests that sound adaptation measures and stringent mitigation actions must be established to ensure a safe pilgrimage in the future.
Heat-related illness (HRI) is a common occupational injury, especially in construction workers. To explore the factors related to HRI risk in construction workers under hot outdoor working conditions, we surveyed vital and environmental data of construction workers in the summer season. Sixty-one workers joined the study and the total number of days when their vital data during working hours and environmental data were recorded was 1165. Heart rate with high-risk HRI was determined using the following formula: 180 - 0.65 × age. As a result of the logistic regression analysis, age, working area, maximum skin temperature, and heart rate immediately after warming up were significantly positively related, and experience of construction was significantly negatively related to heart rate with high-risk HRI. Heart rate immediately after warming up may indicate morning fatigue due to reasons such as insufficient sleep, too much alcohol intake the night before, and sickness. Asking morning conditions may lead to the prevention of HRI. For occupational risk management, monitoring of environmental and personal conditions is required.
Heat waves are increasing in frequency and exhibit high spatial variability in their distribution over India. There are limited studies focused on thermal indices over India due to the nonavailability of high-resolution (HR) climate data. Here we develop dynamically downscaled HR (4 x 4 km) daily climate information for the months of April to June during 2001-2016 using a regional climate model called Weather Research and Forecasting (WRF) Model, which are validated with station observations. The thermal comfort, heat stress, and its spatiotemporal variability and change over India are quantified in terms of indices like excessive heat factor (EHF), the heat index (HI), humidex, apparent temperature (AT), and wet bulb globe temperature (WBGT). The results show that there is an increasing trend in annual heat waves coverage (22,240 km(2)/year), annual frequency (0.07 days/year), and average intensity (0.04 degrees C/year) during 2001-2016. The spatial distribution of indices exhibits high spatial and temporal variability. The days with the severe threshold of indices are significantly increasing over north India at the rate of EHF (15.9%), HI (14.9%), humidex (15.9%), AT (13.4%), and WBGT (13.8%). The heat waves’ most vulnerable hotspots are on the parts of Rajasthan, Uttar Pradesh, Madhya Pradesh, and the coastal regions of Andhra Pradesh and Odisha. During heat waves, prolonged exposure under the sun will lead to adverse health impacts, and it is mostly observed over severe heat wave zone. These findings stress the need for developing suitable mitigation strategies for a sustainable ecosystem with minimum impact.
Severe high-temperature leads significant risks of human health under the highly population concentration and climate change. The thermal sensitivity to high temperature is needed to be quantified associated with different population characteristics. Thermal condition was quantified by universal thermal climate index (UTCI) and thermal sensitivity was identified by thermal sensation votes (TSV), thermal comfort votes, and thermal unacceptability votes based on 667 questionnaires in Beijing, China. This study designated four indicators, i.e., neutral temperature, neutral temperature range, tolerance temperature, and tolerance temperature range to analyze the effects of individual characteristics on thermal sensitivity. A one-way ANOVA was used to identify the effects of long-term adaptation and psychological factors. Results showed that: (1) Older residents had a higher neutral temperature, narrow tolerance temperature range, and lower tolerance temperature of 1.2 degrees C UTCI than younger residents. (2) People with chronic disease had a narrow tolerance temperature range and lower tolerance temperature of 1.3 degrees C UTCI than healthy ones; (3) The proportion of people who voted strong thermal sensation (TSV >= 2) rated the highest in building areas, while the proportion decreased 31.6% in spaces with dense trees; (4) Residential history and city attractiveness had significant impacts on mean thermal sensation votes and mean thermal comfort votes, excluding the effect of thermal stress level. This study provided useful implications of specific adaption for summer extreme heat according to different population characteristics.
BACKGROUND: Occupational factors have previously been mentioned as contributing to decreased kidney function and the development of chronic kidney disease of unknown cause. Sea salt workers are one of the occupations facing high outdoor temperatures and a highly, intensive workload. OBJECTIVES: The purpose of the study was to examine whether the kidney function of sea salt workers at the beginning of the harvest season differs from kidney function at the end of the harvest season and to identify factors that can predict the change of kidney function. MATERIAL AND METHODS: Data were collected from salt workers (n=50) who were between 18–60 years of age without hypertension, diabetes, and kidney disease in Samut Sakhon province, Thailand. Urine specific gravity (USG) was used for hydration status and the estimated glomerular filter rate (eGFR) was used to measure kidney function. The mixed model was used to find differences over the harvest season and prediction of factors. RESULTS: On average, the eGFR was estimated to decrease by 15.2 ml/min/1.73 m2 over the harvest season. The decline in eGFR of sea salt workers with moderate and heavy workloads were significantly faster than their light workload counterparts after controlling for other covariates. Similarly, dehydration (USG ≥ 1.030) significantly accelerated the rate of kidney function loss. CONCLUSION: Our study confirmed exposure to heat over the harvest season leads to decreased eGFR in sea salt workers. The rate of change of eGFR could be predicted by workload and hydration status. Workers with dehydration who performed medium to heavy workloads in farms showed faster kidney function decline than those who performed light workload.
An outbreak of powerful tornadoes tore through multiple states in the central and southern United States from 10 to 11 December 2021. It is claimed the deadliest tornado outbreak that has taken place on December days. The National Oceanic and Atmospheric Administration had confirmed 66 tornadoes as of 21 December, producing at least 90 fatalities. Most tornadoes occurred at night and thus they were difficult to be visually located, which directly increases the risk for local residents. Two violent nighttime tornadoes were rated category 4 on the enhanced Fujita scale (EF4). Although a high death toll was caused during this event, the operational service actually presented an excellent performance. This tornado outbreak has aroused extensive discussion from both the public and the research community in China. This paper presents a brief discussion on the formation environment and warning services of the tornado outbreak. Recall the deadliest violent tornado in the past 45 years in China, the radar-based tornadic vortex signatures at the locations with EF4 damages show a comparable strength with those in the current cases. Some views on the tornado warning issuance and receiving and damage surveys in China are also presented.
Air temperature and humidity have a great impact on public health, leads to heat stress. The US National Weather Service uses temperature and relative humidity to build a heat index (HI) as a metric to identify the thresholds for heat stress as felt by the public. Under climate change conditions and especially in hot humid weather during summer, the number of hot days in Hanoi has increased in recent times. Subsequently, the heat index is rising in both number of occurrences and level of intensity leading to increasing temperature stress on people’s health. The daily heat index for the future was simulated using maximum daily temperature and minimum daily relative humidity based on climate change scenarios. Maximum daily temperature was provided by the climate change model, while minimum daily relative humidity was estimated from the following: maximum daily temperature, mean daily temperature and daily rainfall. Results show that in the future, the heat index will increase by 0.0777 degrees C/year in the RCP 4.5 scenario and 0.08 degrees C/year in the RCP 8.5 scenario. Number of weeks with heat at danger tends to increase to 5.5 weeks/5 year for scenario RCP 4.5, and it is 6 weeks/5 years under RCP 8.5 scenario. In particular, the number of days of heatstroke over a 30-year period (from 1991 to 2020) amounted to only 4, that is an average of 0.13 days of the year, which represents a very rare weather phenomenon in the past. In contrast, under an RCP 4.5 scenario in the future over a 30-year period, the average number of days per year will be 2, 57 days; while the average number of days per year under an RCP 8.5 scenario would be 3, 87 days. This phenomenon will be mainly concentrated in the months of June, July, and August. Projections of this type are a key tool for communities working out how they will adapt to heat stress in the context of climate change.
The frequency and intensity of high-temperature events continue to increase, resulting in a surge of pathogenicity and mortality. People with low levels of risk perception and adaptability, such as the elderly, suffer more from high temperatures. Effective intervention measures may lead to reduced levels of high temperature-related risk. The purpose of this study was to compare changes in temperature exposure, risk perception and coping behaviors under different intervention methods. Herein we conducted three different interventions including education, subsidies for electricity and uses of spray-cooling appliances as well as collected data about temperature exposure, risk perception, and coping behaviors. Before and after the experiment, we evaluated the intervention effectiveness with a number of variables related to alerting human responses under high temperatures. We conducted nonparametric tests for paired samples and generalized linear mixed effect models. Compared with subsidy support and outdoor spray-cooling methods, education is more effective as it leads to lower levels of temperature exposure, higher levels of risk perception, and more behavioral responses. The subsidy support intervention is useful in increasing risk perception and promoting home cooling practices as well. In comparison, spray cooling barely contributes to the reduction of personal temperature exposure. The encouragement of risk-related education and continued government subsidy may prevent elderly individuals from experiencing high-temperature exposure.
Rising temperatures are causing distress across the world, and for those most vulnerable, it is a silent killer. Information about indoor air temperature in residential dwellings is of interest for a range of reasons, such as health, thermal comfort and coping practices. However, there have been only few studies that measure indoor heat exposure, and contrast these to outdoor temperatures in rural-urban areas, of which none are in South Asia. We aim to close this knowledge gap with our indoor and outdoor heat measurement dataset, covering five low-income sites in South Asia. Two sites are in rural areas (Maharashtra, India), while three sites focus on urban areas (Dhaka, Delhi and Faisalabad). Data are based on 206 indoor temperature data loggers and complemented by data from five outdoor automated weather stations. The data-set can be used to examine temperature and humidity variation in low-socioeconomic status households in rural and urban areas and to better understand factors aggravating heat stress. This is important to plan and implement actions for combating heat stress.
Public health is threatened by climate change and extreme temperature events worldwide. Differences in health predispositions, access to cooling infrastructure and occupation raises an issue of heat-related health inequality in those vulnerable and disadvantaged demographic groups. To address these issues, a comprehensive understanding of the effect of elevated body temperatures on human biological systems and overall health is urgently needed. In this paper we look at the inner workings of the human innate immunity under exposure to heat stress induced through exposure to environment and physical exertion. We couple two experimentally validated computational models: the innate immune system and thermal regulation of the human body. We first study the dynamics of critical indicators of innate immunity as a function of human core temperature. Next, we identify environmental and physical activity regimes that lead to core temperature levels that can potentially compromise the performance of the human innate immunity. Finally, to take into account the response of innate immunity to various intensities of physical activities, we utilise the dynamic core temperatures generated by a thermal regulation model. We compare the dynamics of all key players of the innate immunity for a variety of stresses like running a marathon, doing construction work, and leisure walking at speed of 4 km/h, all in the setting of a hot and humid tropical climate such as present in Singapore. We find that exposure to moderate heat stress leading to core temperatures within the mild febrile range (37, 38][Formula: see text], nudges the innate immune system into activation and improves the efficiency of its response. Overheating corresponding to core temperatures beyond 38[Formula: see text], however, has detrimental effects on the performance of the innate immune system, as it further induces inflammation, which causes a series of reactions that may lead to the non-resolution of the ongoing inflammation. Among the three physical activities considered in our simulated scenarios (marathon, construction work, and walking), marathon induces the highest level of inflammation that challenges the innate immune response with its resolution. Our study advances the current state of research towards understanding the implications of heat exposure for such an essential physiological system as the innate immunity. Although we find that among considered physical activities, a marathon of 2 h and 46 min induces the highest level of inflammation, it must be noted that construction work done on a daily basis under the hot and humid tropical climate, can produce a continuous level of inflammation triggering moieties stretched at a longer timeline beating the negative effects of running a marathon. Our study demonstrates that the performance of the innate immune system can be severely compromised by the exposure to heat stress and physical exertion. This poses significant risks to health especially to those with limited access to cooling infrastructures. This is due in part to having low income, or having to work on outdoor settings, which is the case for construction workers. These risks to public health should be addressed through individual and population-level measures via behavioural adaptation and provision of the cooling infrastructure in outdoor environments.
This study investigates the varies in human physiological response, subjective sensation and acute subclinical health symptoms with increasing activity levels at different high temperatures. Thirty-two healthy subjects were recruited to walk on a treadmill in a climate chamber at a speed of 4 km/h. They experienced four temperature conditions (26 degrees C, 30 degrees C, 33 degrees C and 37 degrees C), each exposure lasting 85 min. Eardrum temperature, heart rate, skin temperature, systolic blood pressure, respiratory flow, and respiration rate changed significantly with increasing temperatures. At temperature of 37 degrees C, the SpO2 decreased significantly compared with at 33 degrees C. Subjects perceived the environment unacceptable at 37 degrees C. The perceived air quality and air freshness correlated linearly with the enthalpy of air. The intensity of headache, dizziness, fatigue and sleepiness increased with increasing temperatures, while only aggravated significantly at 37 degrees C. Additionally, compared with the results at light activity level, heart rate and other key physiological parameters increased significantly with increasing activity levels. The subjects felt “very hot” at 37 degrees C, and the change trend in symptoms reported by subjects increased significantly at 37 degrees C with the increased exposure time, while no significant change was observed in 26-33 degrees C. It indicates that exposure to 37 degrees C impairs the health and safety of heat acclimatized subjects. Using linear fitting curve to predict human physiological tolerance time suggested by ISO 9986. The result shows that eardrum temperature exceeded 38.5 degrees C for 97min continuously walk at 37 degrees C. This provides valuable information involved physiological and psychological responses when human exposed to high temperatures in daily life or industrial production.
Purpose Weather is one of the main factors affecting labour productivity. Existing weather-productivity models focussed on hot and cold climates paying less attention to the tropics. Many tropical countries are expected to be the most areas affected by accelerated climate change and global warming, which may have a severe impact on labour health and productivity. The purpose of this paper is to assess whether the existing models can be used to predict labour productivity based on weather conditions in the tropics. Design/methodology/approach Five models are identified from the literature for evaluation. Using real labour productivity data of a high-rise building project in Malaysia, the actual productivity rate was compared with predicted productivity rates generated using the five models. The predicted productivity rates were generated using weather variables collected from an adjusting weather station to the project. Findings Compared with other models evaluated in this paper, the United States Army Corps of Engineers (USACE) was found to be the best model to predict productivity based on the case study data. However, the result shows only a 57% accuracy level of the USACE model indicating the need to develop a new model for the tropics for more accurate prediction. Originality/value The result of this study is perhaps the first to apply meteorological variables to predict productivity rates and validate them using actual productivity data in the tropics. This study is the first step to developing a more accurate productivity model, which will be useful for project planning and more accurate productivity rate estimation.
Introduction: In a tropical country like India, heat-related illnesses are a common occurrence in the unforgiving summer months. Our study aimed to study the profile and outcome of patients with heat-related illnesses presenting to the emergency department (ED).Materials and Methods: This retrospective, cross-sectional study included all patients with heat-related illnesses to the ED during the months of April, May, and June of 2016. Baseline demographic characteristics, computed tomography (CT) brain findings, and hospital outcome were noted.Results: During the 3-month study period, 72 patients presented with heat-related illnesses. Two-thirds (46/72: 63.8%) suffered from heat stroke, whereas one-third (26/72: 36.2%) had heat exhaustion. Classical and exertional types were seen in 46% and 54% of heat strokes, respectively. The mean age (standard deviation) of the patients was 59.7 (13.3) years with a male preponderance (56.9%). Homemakers (37.5%) and manual laborers (20.8%) were most commonly affected. Hypotension at ED arrival was noticed in 20.8% (15/72), whereas tachycardia and tachypnea were noted in 80.5% (58/72) each. The findings on CT of the brain included acute infarcts (5/26: 19.6%) and an intra-cranial bleed (1/26: 3.8%). The mortality rate was 19.5% (14/72).Conclusion: Heat-related illnesses cause significant mortality during the relentless hot summers of a tropical country like India. Homemakers and manual labors were the most affected group. Acute changes were seen in CT brain of a quarter of patients with heat stroke.The following core competencies are addressed in this article: Patient care, Systems-based practice, Medical knowledge, Practice-based learning and improvement.
The health and economic impacts of extreme heat on humans are especially pronounced in populations without the means to adapt. We deployed a sensor network across 12 informal settlements in Makassar, Indonesia to measure the thermal environment that people experience inside and outside their homes. We calculated two metrics to assess the magnitude and frequency of heat stress conditions, wet bulb temperature and wet bulb globe temperature, and compared our in situ data to that collected by weather stations. We found that informal settlement residents experience chronic heat stress conditions, which are underestimated by weather stations. Wet bulb temperatures approached the uppermost limits of human survivability, and wet bulb globe temperatures regularly exceeded recommended physical activity thresholds, both in houses and outdoors. Under a warming climate, a growing number of people living informally will face potentially severe impacts from heat stress that have likely been previously overlooked or underestimated.
The Intergovernmental Panel on Climate Change (IPCC) projects that the frequency of heat waves (HWs) is likely to increase over most land areas in the twenty-first century. Recurrent HWs are an emerging environmental and health concern and already distress in rapidly growing and fast urbanizing South Asia. A review of original research publications of the past five decades from peer-reviewed journals and conference proceedings, covering South Asia, revealed that the region is constantly experiencing the warmest temperatures. The review attempts to comprehend HWs in different contexts, geographic locations, and on previous studies. The paper presents a compre-hensive review of existing plans/policies/guidelines in South Asia at the national/regional/city level to counter extreme heat risk. The study is extended to identify the issues and gaps in the current policies and frameworks in the larger setting of urban planning measures for adaptation and mitigation efforts. A specific set of long-term actions and vulnerability assessment concen-trated on cities must be developed and integrated into a defined heat action plan coupled with improvements in urban and regional planning. Policies and actions must address the issues of the built environment in land use/planning and address the existing institutional and implementation gaps.
Heat risk assessment is important due to serious health problems caused by heat waves. The complexity and diversity of socio-ecological characteristics in urban areas that lead to heat risk are more serious in heat-exposed areas, while risk assessments and determinant based on individuals in heat-exposed areas have been neglected in previous studies. This study pursues a new idea of combining questionnaire surveys and remote sensing analysis to identify urban heat-exposed areas and assess heat risk in heat-exposed areas of Beijing, China. Morphological spatial pattern analysis (MSPA) was used to identify large and continuous hotspot regions as urban heat-exposed areas based on summer surface temperature from 2011 to 2017. A total of 1484 valid questionnaires were completed by residents of heat-exposed areas. The majority of respondents (96.4%) indicated that they perceived heat risk. Moreover, the residents without a local “hukou” were a potentially vulnerable group (note: hukou refers to the population registration management system.). This study further analysed the diversity of community types within the heat-exposed areas. There were significant differences in heat risk among the different community types of multi-story residential districts, Hutong (a traditional architectural form) residential districts and city villages. In particular, the degree of heat risk perceived by residents living in these the community types was determined by whether they had pre-existing medical conditions; however, age only played a decisive role in city villages. This study not only enriches the current understanding of health risks affected by heat waves but also explores the determinants contributing to the severity of heat risk. The output provides important information for future development of heat mitigation and adaptation strategies.
In recent years, the phenomenon of urban warming has become increasingly serious, and with the number of urban residents increasing, the risk of heatstroke in extreme weather has become higher than ever. In order to mitigate urban warming and adapt to it, many researchers have been paying increasing attention to outdoor thermal comfort. The mean radiant temperature (MRT) is one of the most important variables affecting human thermal comfort in outdoor urban spaces. The purpose of this paper is to predict the distribution of MRT around buildings based on a commonly used multilayer neural network (MLNN) that is optimized by genetic algorithms (GA) and backpropagation (BP) algorithms. Weather data from 2014 to 2018 together with the related indexes of the grid were selected as the input parameters for neural network training, and the distribution of the MRT around buildings in 2019 was predicted. This study obtained very high prediction accuracy, which can be combined with sensitivity analysis methods to analyze the important input parameters affecting the MRT on hot summer days (the days with the highest air temperature over 30 degrees C). This has significant implications for the optimization strategies for future building and urban designers to improve the thermal conditions around buildings.
Urban heat challenges are increasingly severe, along with climate change and urbanisation. Despite significant environmental, economic, and social consequences, limited actions have been conducted to address urban heat challenges. To support the formulation of heat-health plans and guidelines at the city and community scale, this study presented results, through a questionnaire survey among 584 respondents in Shanghai, China, on heat-induced physiological and psychological impacts and analysed the variability of them with demographic characteristics. The results indicate that psychological impacts were more severe than physiological impacts in severity and susceptible people. Skin heat damage and digestive system diseases were ignored in previous studies, compared with fatal cardiovascular and respiratory diseases. Emotional irritability and difficulty in controlling temper were the two most prominent psychological symptoms. The elderly and health-vulnerable groups were more susceptible to heat-induced physiological and psychological impacts than other groups. Among different demographic groups, the most critical physiological and psychological symptoms could vary significantly. Afterwards, suggestions for heat-health plans or guidelines have been proposed. Overall, this study provides a reference for the understanding of heat-induced impacts and enhancing the capacity to cope with urban heat challenges.
This study proposes the methodology to identify heatwave hotspots in Seoul, the metropolis of Korea, using high-resolution data. Resident credit data, population mobility data, and temperature observation data are analyzed to determine vulnerable regions to heatwaves. Potentially vulnerable regions are derived in two ways: static vulnerable regions (SVRs) and dynamic vulnerable regions (DVRs), depending on their characteristics. SVRs are determined by lowincome (lower 20% income quantile) residential areas fixed on time. In contrast, DVRs vary with the time and day of the week. DVRs are defined by the place less responsive to heatwaves, where are with low population variability and low correlation with temperature. The final vulnerable regions, so-called hotspots, are determined by the high temperature predicted area where the SVRs and DVRs intersect. We examine how to remove commuting-related displacement signals, which are represented as noise when analyzing population mobility. An example of the hotspots identification result is also shown using temperature hindcast data generated by the Korean Meteorological Administration short-range forecast system. Applying the vulnerability information can improve the quality of disaster planning and decision-making by highlighting the time and area of need for resources in the implementation of short-and long-term disaster response.
Heat stress events in urban areas are increasing as a result of global warming and urban heat islands. In response to heat stress, outdoor activators naturally often move themselves to a less hot place. An understanding of human physiological responses in dynamic outdoor thermal environments is desired. This study aims to reveal the dynamic physiological adjustment and thermal perception response characteristics under varying outdoor heat stress conditions. A robust model for predicting dynamic thermal sensation outdoors has been developed. Experiments involving heat stress changes in a hot summer were conducted with 25 subjects. Three categories of data were collected including meteorological data, physiological parameters, and thermal perception. The results showed that lower-arm skin temperature (T-lowerarm) is more sensitive to changes in the outdoor thermal environment, and correlates closely with the thermal sensation vote (TSV). For a better practical application, based on the strong linear relationship between T-lowerarm and T-ty, the new dynamic outdoor thermal sensation model has been developed involving two parameters: T-lowerarm and delta T-lowerarm/delta t (the change rate of T-lowerarm). The validity of the model in transient outdoor conditions was verified. The algorithm can be integrated into a wearable armband to predict practical thermal sensation responses. This contribution will advance technologies based on the scientific findings to provide alert services to support human health and wellbeing, consequently increasing urban resilience and sustainability.
Climate change (CC) and urban heat island (UHI) are important environmental forces that have serious consequences for the existing buildings, such as increased resource consumption and environmental footprint, adverse human health effects and reduced occupant comfort. In this context, educational buildings represent a critical category amongst other building typologies, due to their high energy use, high occupant density, atypical daily/annual occupancy patterns, and their occupants’ high vulnerability to heat. Poor indoor conditions can reduce the health and productivity of students and teachers, worsen learning performance and reduce attendance. Retrofitting educational buildings is an effective solution to tackle this challenge. This study investigates the impact of CC&UHI on educational building performance and demonstrates the effectiveness of passive retrofit scenarios targeting CC&UHI mitigation and adaptation. These investigations are based on a systematic approach that consists of (i) the generation and analyses of CC&UHI-modified weather datasets, and (ii) simulation-based comparative analyses of the as-is building and various retrofit scenarios. An existing secondary school building in Ankara, Turkey is selected as a case study for evaluations of the selected performance indicators including energy use, global warming potential (GWP) and thermal comfort. Obtained results indicate that total energy consumption can be reduced up to 50% with retrofit, whereas possible reductions in indoor discomfort are even more pronounced, underlining the significance of selecting the optimal combination of passive measures for maximum impact towards the adaptation of the existing educational buildings to the changes in climatic conditions.
Elderly residents are prominent users of urban parks and comfortable open spaces in parks have been shown to improve their physical health and mental well-being. In this study, the thermal perceptions (thermal sensation, thermal comfort and thermal acceptability) of elderly visitors to an urban park in Xi’an, China was investigated using meteorological measurements, questionnaire surveys and activity records. Physiological equivalent temperature (PET) was used to determine thermal benchmarks. Spatial-temporal distributions of the elderly in open spaces were recorded and relationships among elderly residents’ thermal perceptions, their age and chronic disease were analyzed. Finally, optimal design strategies for open spaces suitable for the elderly were proposed based on meteorological characteristics, elderly residents’ attendance patterns and their thermal perceptions. Results showed that: 1) globe temperature (T(g)) and air temperature (T(a)) were the primary meteorological factors that influenced elderly residents’ thermal sensation while clothing insulation and activity intensity were negatively correlated with their thermal sensation. 2) Attendance was significantly affected by the outdoor microclimate, space functionality and facilities in spaces. The elderly mainly participated in dynamic activities and social interaction. 3) The neutral PET (NPET) was 13.2 °C, with NPET range (NPETR) of 3.1-23.2 °C. The 90% thermal acceptable PET ranged between 10.9 and 25.9 °C, and the preferred PET was 14.4 °C. Compared with the ISO7730 standard, the predicted percentage of dissatisfied (PPD) elderly park users was lower than users of indoor spaces when -1 ≤ MTSV ≤ + 1, indicating that the elderly preferred to conduct activities outside when the environment was comfortable. Additionally, NPET for the elderly with respiratory disease was higher than those with cardiovascular diseases and diabetes. 4) Optimal design strategies for open spaces were proposed for elderly residents based on their physical, physiological and psychological preferences.
Actively addressing urban heat challenges is an urgent task for numerous cities. Existing studies have primarily developed heat mitigation strategies and analyzed their cooling performance, while the adaptation strategies are far from comprehensive to protect citizens from heat-related illnesses and deaths. To address this research gap, this paper aims to enhance people’s adaptation capacity by investigating walkability within fifteen-minute cities (FMC). Taking cognizance of thermal comfort, health, and safety, this paper developed a dynamic attenuation model (DAM) of heat stress, along with heat stress aggravation, continuance, and alleviation. An indicator of remaining tolerant heat discomfort (R (t) ) was proposed with the integration of the Universal Thermal Climate Index (UTCI) to assess heat-related walkability. Following an empirical study among 128 residents in Mianyang, China, and assessing four levels of heat stress, the maximum tolerant heat discomfort was determined to be 60 min. Furthermore, the DAM was applied to an FMC with 12 neighborhoods in Fucheng, Mianyang, China. The results indicate that for each neighborhood, the street was generally walkable with an R (t) ranging between 15 and 30 min, after walking for 900 m. A population-based FMC walkability was further determined, finding that the core area of the FMC was favorable for walking with an R (t) of 45-46 min, and the perpetual areas were also walkable with an R (t) of 15-30 min. Based on these results, suggestions on the frequency of public services (frequently used, often used, and occasionally used) planning were presented. Overall, this paper provides a theoretical model for analyzing walkability and outlines meaningful implications for planning heat adaptation in resilient, safe, comfortable, and livable FMCs.
Due to direct exposure to high temperatures in summer, sanitation workers can easily experience heat-related illness and even mortality. This paper aims to determine the thresholds of the environmental parameters for sanitation workers in summer. Firstly, a field test of sanitation workers was conducted, the environmental parameters (solar radiation intensity, dry bulb temperature, wind speed and relative humidity) and mean skin temperature were measured, and the thermal comfort and work willingness were investigated via a questionnaire. Then, the mathematical programming method was adopted to obtain the safety limits and danger limits of the environmental parameters. Finally, the thresholds of the outdoor heat stress indexes, namely, the environmental stress index (ESI), discomfort index (DI), heat index (HI) and relative strain index (RSI) were obtained. The results indicate that a high solar radiation intensity, high dry bulb temperature, high wind speed and low humidity will cause more adverse effects on sanitation workers in summer. The safety limits of the solar radiation intensity, dry bulb temperature, wind speed and relative humidity are 182.42 W/m(2), 28.42 degrees C, 0.15 m/s and 71.35%, respectively, and the danger limit value are 876.86 W/m(2), 34.98 degrees C, 1.27 m/s and 36.59%, respectively. In addition, the safety limit values of the ESI, DI, HI and RSI are 27.08 degrees C, 26.23 degrees C, 31.71 degrees C and 0.13, respectively; and the danger limit values are 29.60 degrees C, 27.84 degrees C, 36.21 degrees C and 0.24, respectively. This paper can provide a study method and reference data for the work arrangement and health protection of sanitation workers in summer.
The estimation of heat-related illness cases is a key factor in proposing and implementing suitable intervention strategies and healthcare resource management. This paper proposes new frameworks to estimate the number of patients with heat-related illnesses by administrative wards in Nagoya City using 2014-2019 data. The proposed frameworks are based on the derivation of estimation formulae and machine learning. The daily residual estimation error in the 16 wards was less than one person with both the frameworks. The daily working time average ambient temperature may yield a better correlation than the daily average temperature or daily highest temperature with the number of patients transported by an ambulance from outdoor sites. The results also indicate that patients transported from indoor sites are influenced by earlier ambient conditions over approximately 50 days. In contrast, those transported from outdoor sites are influenced by a relatively short period (20 days), which may correspond to heat adaptation. The frameworks provide a better understanding of the different factors that would lead to an accurate prediction of the number of cases of heat-related patients from weather forecasts. These findings would lead to efficient ambulance allocation as well as public awareness on hot days to suppress heat-related morbidity.
With an increase in the aging population in many countries worldwide, much attention is being paid to the study of thermal comfort for the elderly. Because the elderly spend most of their time indoors, the demand for air conditioning is expected to increase, and it is important to study the thermal comfort of the elderly and appropriate operation plans for air conditioning. In this study, we conducted a field survey of thermal comfort and building energy simulation for an air-conditioned nursing home in Nagano, Japan. The field survey was conducted between June 2020 and June 2021. Over 80% of the subjects were satisfied with the indoor thermal environment. The thermal neutral temperature of the elderly was 25.9 degrees C in summer and 23.8 degrees C in winter. Future weather data was used to predict the future heating and cooling loads of the nursing home. The results showed that the total heat load may not change significantly, as the decrease in heating load compensates for the increase in cooling load. This study will serve as a useful reference for a wide range of stakeholders, including managers and designers of nursing homes.
BACKGROUND: Predictive scenarios of heatstroke over the long-term future have yet to be formulated. The purpose of the present study was to generate baseline scenarios of heat-related ambulance transportations using climate change scenario datasets in Tokyo, Japan. METHODS: Data on the number of heat-related ambulance transportations in Tokyo from 2015 to 2019 were examined, and the relationship between the risk of heat-related ambulance transportations and the daily maximum wet-bulb globe temperature (WBGT) was modeled using three simple dose-response models. To quantify the risk of heatstroke, future climatological variables were then retrieved to compute the WBGT up to the year 2100 from climate change scenarios (i.e., RCP2.6, RCP4.5, and RCP8.5) using two scenario models. The predicted risk of heat-related ambulance transportations was embedded onto the future age-specific projected population. RESULTS: The proportion of the number of days with a WBGT above 28°C is predicted to increase every five years by 0.16% for RCP2.6, 0.31% for RCP4.5, and 0.68% for RCP8.5. In 2100, compared with 2000, the number of heat-related ambulance transportations is predicted to be more than three times greater among people aged 0-64 years and six times greater among people aged 65 years or older. The variance of the heatstroke risk becomes greater as the WBGT increases. CONCLUSIONS: The increased risk of heatstroke for the long-term future was demonstrated using a simple statistical approach. Even with the RCP2.6 scenario, with the mildest impact of global warming, the risk of heatstroke is expected to increase. The future course of heatstroke predicted by our approach acts as a baseline for future studies.
The purpose of this study was to quantify the sleep disturbances caused by climate change using disability-adjusted life years (DALY). The revised sleep quality index for daily sleep (SQIDS2), a self-administered questionnaire for daily sleep quality, was developed to assess daily sleep disturbances. This questionnaire referenced and simplified the Pittsburgh Sleep Quality Index (PSQI). This study was conducted in Nagoya City in August 2011 and 2012. Sleep quality was measured using SQIDS2 and PSQI. A total of 574 participants in 2011 and 710 in 2012 responded to the survey. The sleep disturbance prevalence calculated from the SQIDS2 score was correlated with the daily minimum temperature (p = 0.0067). This score increased when the daily minimum temperature was above 24.8 degrees C. When correcting for the PSQI score, DALY loss due to heat-related sleep disturbances in Nagoya City (population: 2,266,851) was estimated to be 81.8 years in 2012. This value was comparable to the DALY loss due to heatstroke. Sleep disturbance due to climate change was quantified using the DALY based on the PSQI. Legislators must recognize the critical impact of the damage caused by sleep disturbances due to high temperatures at night. Additionally, a daily minimum temperature of 25 degrees C should be the starting point when establishing a goal or guideline for nighttime temperature.
An increase in the global surface temperature and changes in urban morphologies are associated with increased heat stress especially in urban areas. This can be one of the contributing factors underlying an increase in heat strokes. We examined the impact of summer minimum air temperatures, which often represent nighttime temperatures, as well as a maximum temperature on a heat stroke. We collected data from the records of daily ambulance transports for heat strokes and meteorological data for July and August of 2017-2019 in the Tottori Prefecture, Japan. A time-stratified case-crossover design was used to determine the association of maximum/minimum air temperatures and the incidence of heat strokes. We used a logistic regression to identify factors associated with the severity of heat strokes. A total of 1108 cases were identified with 373 (33.7%) calls originating in the home (of these, 59.8% were the age of ≥ 75). A total of 65.8% of cases under the age of 18 were related to exercise. Days with a minimum temperature ≥ 25 °C had an odds ratio (95% confidence interval) of 3.77 (2.19, 6.51) for the incidence of an exercise-related heat stroke (reference: days with a minimum temperature < 23 °C). The odds ratio for a heat stroke occurring at home or for calls for an ambulance to the home was 6.75 (4.47, 10.20). The severity of the heat stroke was associated with older age but not with air temperature. Minimum and maximum air temperatures may be associated with the incidence of heat strokes and in particular the former with non-exertional heat strokes.
BACKGROUND: An increase in extreme heat events has been reported along with global warming. Heat exposure in ambient temperature is associated with all-cause diabetes mortality and all-cause hospitalization in diabetic patients. However, the association between heat exposure and hospitalization for hyperglycemic emergencies, such as diabetic ketoacidosis (DKA), hyperosmolar hyperglycemic state (HHS), and hypoglycemia is unclear. The objective of our study is to clarify the impact of heat exposure on the hospitalization for DKA, HHS, and hypoglycemia. METHODS: Data of daily hospitalizations for hyperglycemic emergencies (i.e., DKA or HHS) and hypoglycemia was extracted from a nationwide administrative database in Japan and linked with temperature in each prefecture in Japan during 2012-2019. We applied distributed lag non-linear model to evaluate the non-linear and lagged effects of heat exposure on hospitalization for hyperglycemic emergencies. RESULTS: The pooled relative risk for hyperglycemic emergencies of heat effect (the 90th percentile of temperature with reference to the 75th percentile of temperature) and extreme heat effect (the 99th percentile of temperature with reference to the 75th percentile of temperature) over 0-3 lag days was 1.27 (95 %CI: 1.16-1.39) and 1.64 (95 %CI: 1.38-1.93), respectively. The pooled relative risk for heat effect on hospitalization for hypoglycemia and extreme heat effect over 0-3 lag days was 1.33 (95 %CI: 1.17-1.52) and 1.65 (95 %CI: 1.29-2.10), respectively. These associations were consistent by type of hyperglycemic emergencies and type of diabetes and were generally consistent by regions. DISCUSSION: Heat exposure was associated with hospitalizations for DKA, HHS and hypoglycemia. These results may be useful to guide preventive actions for the risk of fatal hyperglycemic emergencies and hypoglycemia.
Extreme heat exposure has severe negative impacts on humans, and the issue is exacerbated by climate change. Estimating spatial heat stress such as mean radiant temperature (MRT) is currently difficult to apply at city scale. This study constructed a method for estimating the MRT of street canyons using Google Street View (GSV) images and investigated its large-scale spatial patterns at street level. We used image segmentation using deep learning to calculate the view factor (VF) and project panorama into fisheye images. We calculated sun paths to estimate MRT using panorama images from Google Street View. This paper shows that regression analysis can be used to validate between estimated short-wave, long-wave radiation and the measurement data at seven field measurements in the clear-sky (0.97 and 0.77, respectively). Additionally, we compared the calculated MRT and land surface temperature (LST) from Landsat 8 on a city scale. As a result of investigating spatial patterns of MRT in Seoul, South Korea, we found that a high MRT of street canyons (>59.4 degrees C) is mainly distributed in open space areas and compact low-rise density buildings where the sky view factor is 0.6-1.0 and the building view factor (BVF) is 0.35-0.5, or west-east oriented street canyons with an SVF of 0.3-0.55. However, high-density buildings (BVF: 0.4-0.6) or high-density tree areas (Tree View Factor, TVF: 0.6-0.99) showed low MRT (<47.6). The mapped MRT results had a similar spatial distribution to the LST; however, the MRT was lower than the LST in low tree density or low-rise high-density building areas. The method proposed in this study is suitable for a complex urban environment consisting of buildings, trees, and streets. This will help decision makers understand spatial patterns of heat stress at the street level.
BACKGROUND: Although urbanization is often an important topic in climate change studies, the complex effect of urbanization on heat vulnerability in urban and rural areas has rarely been studied. We investigated the disparate effects of urbanization on heat vulnerability in urban and rural areas, using nationwide data. METHODS: We collected daily weather data for all 229 administrative districts in South Korea (2011-17). Population density was applied as an urbanization indicator. We calculated the heat-mortality risk using a distributed lag nonlinear model and analysed the relationship with population density. We also examined district characteristics that can be related to the spatial heterogeneity in heat-mortality risk. RESULTS: We found a U-shaped association between population density and heat-mortality risk, with the highest risk for rural populations; in urban areas, risk increases with increasing population density. Higher heat-mortality risk was associated with a lower number of hospital beds per person and higher percentage of people requiring recuperation. The association between hospital beds and heat-mortality risk was prominent in high-density urban areas, whereas the association between the percentage of people requiring recuperation and heat-mortality risk was pronounced in rural areas. CONCLUSIONS: Our findings indicate that the association between population density and heat-mortality risk is different in urban and rural areas, and that district characteristics related to heat-mortality risk also differ by urbanicity. These results can contribute to understanding the complex role of urbanization on heat vulnerability and can provide evidence to policy makers for prioritizing resources.
Access to urban greenspace has many benefits such as improved health and social cohesion. If access differs by population, these benefits make access to greenspace an environmental justice issue, but little is known regarding accessibility of parks among different sub-groups in Seoul, South Korea. We explored potential socioeconomic inequities for access to parks in Seoul measuring two park provision metrics: total park area per capita (TPPC), and park accessibility index determined by size and proximity of parks. We assessed correlations between a deprivation index for the 25 Gus (administrative unit equivalent to the US borough) and each park provision metric. Regression analyses were applied for the associations between eight socioeconomic indicators of the 424 Dongs (equivalent to the US neighborhood) and each park provision metric. An interquartile range (IQR) increase in percent elderly (> 65 years) (3.2%) was significantly associated with larger TPPC (1.6 m(2)/person, 95% CI: 0.8, 2.4). Park accessibility index was associated with more socioeconomic variables than was TPPC. An IQR increase in percent elderly and divorce rates (1.2/1000 population) was associated with increased park accessibility by 3571 km (95% CI: 1103, 6040) and decreased park accessibility by 1387 (95% CI: -2706, -67), respectively. An IQR increase in percentage of the population receiving social low-income support aid (2.2%) was associated with increased park accessibility (reflecting park size and proximity of parks) of residential parks near residential areas by 1568 (95% CI: 15, 3120). Results suggest higher park access for socioeconomically disadvantaged regions. Findings indicate that measures of detailed park access considering spatial proximity and park size may more accurately measure park inequity compared to more basic metrics (e.g. TPPC), which may bias estimation of park inequity by capturing only one characteristic of parks. Detailed park measures should be considered in urban planning and health studies of greenspace.
We analyzed the relationship between the temperature and traffic accidents in Seoul-Incheon, Busan, Daegu, Daejeon, and Gwangju by the time-of-day (06:00 to 22:00, divided into segments of 4 h) and age of casualties between 2012 and 2017 for the summer season (June to August). A generalized additive model and meta-analysis were employed to analyze this relationship. We found that the threshold temperatures was observed to be approximately 30 degrees C. Above this temperature, traffic accidents increased in four urban areas, except Busan, which is a popular tourist location. In total, traffic accidents increased by approximately 0.59% (95% confidence interval of 0.41-0.75) per 1 degrees C increase in the daily maximum temperature, with substantial differences between the different areas, ranging from 0.12% (CI = – 0.26-0.50) in Busan to 1.08% (CI = 0.45-1.71) in Gwangju. The morning and evening hours showed a greater increase in traffic accidents than other timeframes. The increase in traffic accidents for young casualties was statistically significant at all times, and that for elderly casualties was observed at 10:00-14:00 and 18:00-22:00. The results of this study could provide information for developing customized traffic accident reduction policies considering time-of-day, age of casualties, and type of city.
Many countries are operating a heatwave warning system (HWWS) to mitigate the impact of heatwaves on human health. The level of heatwave warning is normally determined by using the threshold temperature of heat-related morbidity or mortality. However, morbidity and mortality threshold temperatures have not been used together to account for the severity of health impacts. In this study, we developed a heatwave warning system with two different warning levels: Level-1 and Level-2, by analyzing the severity and likelihood of heat-related morbidity and mortality using the generalized additive model. The study particularly focuses on the cases in Seoul, South Korea, between 2011 and 2018. The study found that the threshold temperature for heat-related morbidity and mortality are 30 °C and 33 °C, respectively. Approximately 73.1% of heat-related patients visited hospitals when temperature was between 30 °C and 33 °C. We validated the developed HWWS by using both the threshold temperatures of morbidity and mortality. The area under curves (AUCs) of the proposed model were 0.74 and 0.86 at Level-1 and Level-2, respectively. On the other hand, the AUCs of the model using only the mortality threshold were 0.60 and 0.86 at Level-1 and Level-2, respectively. The AUCs of the model using only the morbidity threshold were 0.73 and 0.78 at Level-1 and Level-2, respectively. The results suggest that the updated HWWS can help to reduce the impact of heatwaves, particularly on vulnerable groups, by providing the customized information. This also indicates that the HWWS could effectively mitigate the risk of morbidity and mortality.
BACKGROUND: Due to climate change, days with high temperatures are becoming more frequent. Although the effect of high temperature on the kidneys has been reported in research from Central and South America, Oceania, North America and Europe, evidence from Asia is still lacking. This study aimed to examine the association between short-term exposure to high temperatures and acute kidney injury (AKI) in a nationwide study in South Korea. METHODS: We used representative sampling data from the 2002-2015 National Health Insurance Service-National Sample Cohort in South Korea to link the daily mean temperatures and AKI cases that occurred in the summer. We used a bidirectional case-crossover study design with 0-7 lag days before the emergency room visit for AKI. In addition, we stratified the data into six income levels to identify the susceptible population. RESULTS: A total of 1706 participants were included in this study. The odds ratio (OR) per 1°C increase at 0 lag days was 1.051, and the ORs per 1°C increase at a lag of 2 days were both 1.076. The association between exposure to high temperatures and AKI was slightly greater in the low-income group (OR = 1.088; 95% CI: 1.049-1.128) than in the high-income group (OR = 1.065; 95% CI: 1.026-1.105). CONCLUSIONS: In our study, a relationship between exposure to high temperatures and AKI was observed. Precautions should be taken at elevated temperatures to minimize the risk of negative health effects.
Many studies have shown that heat waves can cause both death and disease. Considering the adverse health effects of heat waves on vulnerable groups, this study highlights their impact on workers. The present study thus investigated the association between heat exposure and the likelihood of hospitalization and death, and further identified the risk of heat-related diseases or death according to types of heat and dose-response modeling with heat threshold. Workers were selected from the Korean National Health Insurance Service-National Sample Cohort 2002-2015, and regional data measured by the Korea Meteorological Administration were used for weather information. The relationship between hospitalization attributable to disease and weather variables was analyzed by applying a generalized additional model. Using the Akaike information criterion, we selected a model that presented the optimal threshold. Maximum daily temperature (MaxT) was associated with an increased risk of death and outdoor mortality. The association between death outdoors and MaxT had a threshold of 31.2 °C with a day zero lag effect. History of medical facility visits due to the health effects of heat waves was evident in certain infectious and parasitic diseases (A and B), cardio and cerebrovascular diseases (I20-25 and I60-69), injury, poisoning, and other consequences of external causes (S, T). The study demonstrated that heat exposure is a risk factor for death and infectious, cardio-cerebrovascular, and genitourinary diseases, as well as injuries or accidents among workers. The finding that heat exposure affects workers’ health has future implications for decision makers and researchers.
OBJECTIVE: This study aimed to determine the association between maximum daily temperature and work-related injuries according to employment status in South Korea. METHODS: Data on workers’ compensation claims and daily maximum temperature between May 20 and September 10, 2017-2018, were collected and analyzed. The absolute temperature risk effect (ATR) was evaluated by comparing the risk effect at 2 temperatures (30°C vs 33°C) across all communities using 2-stage time-series analysis. RESULTS: The association between high temperatures and work-related injuries was statistically significant in the construction sector (ATR, 1.129; 95% confidence interval [CI], 1.010-1.261). In addition, the findings of this study also demonstrated a higher risk effect among nonpermanent workers (ATR, 1.109; 95% CI, 1.013-1.214) at 33°C versus 30°C when compared with permanent workers (ATR, 0.963; 95% CI, 0.891-1.041). CONCLUSIONS: This study found a significant association between high temperatures and work-related injuries among nonpermanent workers in South Korea.
BACKGROUND: Environmental factors have been associated with adverse health effects in epidemiological studies. The main exposure variable is usually determined via prior knowledge or statistical methods. It may be challenging when evidence is scarce to support prior knowledge, or to address collinearity issues using statistical methods. This study aimed to investigate the importance level of environmental variables for the under-five mortality in Malaysia via random forest approach. METHOD: We applied a conditional permutation importance via a random forest (CPI-RF) approach to evaluate the relative importance of the weather- and air pollution-related environmental factors on daily under-five mortality in Malaysia. This study spanned from January 1, 2014 to December 31, 2016. In data preparation, deviation mortality counts were derived through a generalized additive model, adjusting for long-term trend and seasonality. Analyses were conducted considering mortality causes (all-cause, natural-cause, or external-cause) and data structures (continuous, categorical, or all types [i.e., include all variables of continuous type and all variables of categorical type]). The main analysis comprised of two stages. In Stage 1, Boruta selection was applied for preliminary screening to remove highly unimportant variables. In Stage 2, the retained variables from Boruta were used in the CPI-RF analysis. The final importance value was obtained as an average value from a 10-fold cross-validation. RESULT: Some heat-related variables (maximum temperature, heat wave), temperature variability, and haze-related variables (PM10, PM10-derived haze index, PM10- and fire-derived haze index, fire hotspot) were among the prominent variables associated with under-five mortality in Malaysia. The important variables were consistent for all- and natural-cause mortality and sensitivity analyses. However, different most important variables were observed between natural- and external-cause under-five mortality. CONCLUSION: Heat-related variables, temperature variability, and haze-related variables were consistently prominent for all- and natural-cause under-five mortalities, but not for external-cause.
The impacts of climate change and degradation are increasingly felt in Malaysia. While everyone is vulnerable to these impacts, the health and wellbeing of children are disproportionately affected. We carried out a study composed of two major components. The first component is an environmental epidemiology study comprised of three sub-studies: (i) a global climate model (GCM) simulating specific health-sector climate indices; (ii) a time-series study to estimate the risk of childhood respiratory disease attributable to ambient air pollution; and (iii) a case-crossover study to identify the association between haze and under-five mortality in Malaysia. The GCM found that Malaysia has been experiencing increasing rainfall intensity over the years, leading to increased incidences of other weather-related events. The time-series study revealed that air quality has worsened, while air pollution and haze have been linked to an increased risk of hospitalization for respiratory diseases among children. Although no clear association between haze and under-five mortality was found in the case-crossover study, the lag patterns suggested that health effects could be more acute if haze occurred over a longer duration and at a higher intensity. The second component consists of three community surveys on marginalized children conducted (i) among the island community of Pulau Gaya, Sabah; (ii) among the indigenous Temiar tribe in Pos Kuala Mu, Perak; and (iii) among an urban poor community (B40) in PPR Sg. Bonus, Kuala Lumpur. The community surveys are cross-sectional studies employing a socio-ecological approach using a standardized questionnaire. The community surveys revealed how children adapt to climate change and environmental degradation. An integrated model was established that consolidates our overall research processes and demonstrates the crucial interconnections between environmental challenges exacerbated by climate change. It is recommended that Malaysian schools adopt a climate-smart approach to education to instill awareness of the impending climate change and its cascading impact on children’s health from early school age.
It is recognized that as humans age, their ability to withstand high or low temperatures reduces. Temperature extremes can also worsen chronic conditions, including cardiovascular, respiratory and other health issues. This study analyses 40 apartments in a single building in Auckland, New Zealand to determine whether the newly designed and constructed apartment, specifically for retirees, is delivering a suitable thermal interior environment during the warmest months of the year. Despite holding this green certification and meeting specific requirements to achieve cooling points that are meant to reduce the likelihood of overheating, the building exhibits significant signs of overheating in the two warmest months of the year (January and February) with two-thirds of apartments failing the CIBSE TM59 overheating criteria. The summertime performance of this green-rated building crucial insights for design professionals policymakers and developers of green building rating tools.
Heat waves are unusually high temperature events over consecutive days and may cause adverse impacts such as morbidity and mortality. The interaction between heat waves and urban heat island (UHI) effects has remained a subject of debate, as some studies prove heat wave-UHI synergy while others do not. Furthermore, heat waves affect tropical cities more severely than mid-latitude cities, but there is a disproportionate lack of heat wave studies focusing on tropical cities. We attempt to narrow this gap by studying the heat wave in Singapore in April 2016 using ground observations and the Weather Research and Forecasting (WRF) model. Compared to non-heat wave days, the ground observations show that daytime temperatures can be 3 degrees C higher during the heat wave. Despite the temperature spike, the UHI intensity is not amplified during the heat wave, maintaining its peak near 2.5 degrees C during both heat wave and non-heat wave periods. WRF simulation results also agree well with measurements and predict UHI peaks near 2.5 degrees C during both periods, showing no heat wave-UHI synergy. The spatially averaged UHI intensity also shows no such synergy. There is no significant change of wind speed, soil moisture availability or heat storage flux during the heat wave. Therefore, the lack of heat wave-UHI synergy in our study is consistent with current understanding of factors contributing to UHI. This study shows that the heat wave-UHI interaction in a tropical city can be different from that in cities in the temperate climate zone and more studies should be conducted in tropical cities, which are projected to suffer larger impacts of increasing heat stress.
BACKGROUND: Excessive heat exposure and dehydration among agricultural workers have been reported to reduce kidney function and lead to chronic kidney disease of unknown etiology (CKDu). OBJECTIVE: This cross-sectional study aimed to assess heat exposure, factors related to dehydration and the relationship between dehydration and biomarkers of kidney function among sea salt workers in Thailand. MATERIAL AND METHODS: Wet bulb globe temperature (WBGT) was used at the time workers started work outdoors on salt farms. Urine-specific gravity, urine osmolarity, and serum creatinine were collected from 50 workers after work. RESULTS: The results showed that more than 50% of the participants were dehydrated after work. The maximum hours spent working per day was 10. The average water intake was 1.51 L. Urine specific gravity was highly significant correlated with urine osmolality (rs = 0.400, p<0.01), and urine osmolality was significantly correlated with the estimated glomerular filtration rate (eGFR) (rs = 0.349, p<0.05). In bivariate analysis adjusted for age, sex, and current alcohol consumption, we found that a WBGTTWA ≥ 30°C (OR = 0.08, 95% CI = 0.01-0.44, p = 0.003) and hours spent working (OR=2.22, 95% CI = 1.42-3.47, p <0.001) were independently associated with dehydration. This suggests that workers should increase their time spent on breaks and increase water consumption. CONCLUSIONS: Educational program on heat exposure and heat-related illness prevention strategies should be provided.
Increased heat stress affects well-being, comfort, and economic activities across the world. It also causes a significant decrease in work performance, as well as heat-related mortality. This study aims to investigate the impacts of the projected climate change scenario under RCP8.5 on heat stress and associated work performance in Thailand during the years 2020-2029. The model evaluation shows exceptional performance in the present-day simulation (1990-1999) of temperature and relative humidity, with R-2 values ranging from 0.79 to 0.87; however, the modeled temperature and relative humidity are all underestimated when compared to observation data by -0.9 degrees C and -27%, respectively. The model results show that the temperature change will tend to increase by 0.62 degrees C per decade in the future. This could lead to an increase in the heat index by 2.57 degrees C if the temperature increases by up to 1.5 degrees C in Thailand. The effect of climate change is predicted to increase heat stress by 0.1 degrees C to 4 degrees C and to reduce work performance in the range of 4% to >10% across Thailand during the years 2020 and 2029.
No abstract available.
BACKGROUND: Exposure to non-optimum ambient temperature has been linked to increased risk of total cardiovascular disease (CVD) mortality; however, the adverse effects on mortality from specific types of CVD remain less understood. OBJECTIVES: To comprehensively investigate the association of ambient temperature with cause-specific CVD mortality, and to estimate and compare the corresponding mortality burden. METHODS: We conducted a time-stratified case-crossover study of 1000,014 CVD deaths in Jiangsu province, China during 2015-2019 using data from the China National Mortality Surveillance System. Residential daily 24-hour average temperature for each subject was extracted from a validated grid data at a spatial resolution of 0.0625° × 0.0625°. We fitted distributed lag non-linear models (DLNM) based on conditional logistic regression to quantitatively investigate the association of ambient temperature with total and cause-specific CVD mortality, which was used to further estimate mortality burden attributable to non-optimum ambient temperatures. RESULTS: With adjustment for relative humidity, we observed reverse J-shaped exposure-response associations of ambient temperature with total and cause-specific CVD mortality, with minimum mortality temperatures ranging from 19.5 °C to 23.0 °C. An estimated 20.3% of the total CVD deaths were attributable to non-optimum temperatures, while the attributable fraction (AF) of mortality from chronic rheumatic heart diseases, hypertensive diseases, ischemic heart diseases (IHD), pulmonary heart disease, stroke, and sequelae of stroke was 22.4%, 23.2%, 23.3%, 20.9%, 17.6% and 21.3%, respectively. For total and cause-specific CVDs, most deaths were attributable to moderate cold temperature. We observed significantly higher mortality burden from total and certain cause-specific CVDs in adults 80 years or older and those who were widowed. CONCLUSION: Exposure to ambient temperature was significantly associated with increased risk of cause-specific CVD mortality. The burden of CVD mortality attributable to non-optimum temperature was substantial especially in older and widowed adults, and significantly varied across specific types of CVD.
BACKGROUND: The effect of ambient temperature on allergic rhinitis (AR) remains unclear. Accordingly, this study aimed to explore the relationship between ambient temperature and the risk of AR outpatients in Xinxiang, China. METHOD: Daily data of outpatients for AR, meteorological conditions, and ambient air pollution in Xinxiang, China were collected from 2015 to 2018. The lag-exposure-response relationship between daily mean temperature and the number of hospital outpatient visits for AR was analyzed by distributed lag non-linear model (DLNM). Humidity, long-time trends, day of the week, public holidays, and air pollutants including sulfur dioxide (SO(2)), and nitrogen dioxide (NO(2)) were controlled as covariates simultaneously. RESULTS: A total of 14,965 AR outpatient records were collected. The relationship between ambient temperature and AR outpatients was generally M-shaped. There was a higher risk of AR outpatient when the temperature was 1.6-9.3 °C, at a lag of 0-7 days. Additionally, the positive association became significant when the temperature rose to 23.5-28.5 °C, at lag 0-3 days. The effects were strongest at the 25th (7 °C) percentile, at lag of 0-7 days (RR: 1.32, 95% confidence intervals (CI): 1.05-1.67), and at the 75th (25 °C) percentile at a lag of 0-3 days (RR: 1.15, 95% CI: 1.02-1.29), respectively. Furthermore, men were more sensitive to temperature changes than women, and the younger groups appeared to be more influenced. CONCLUSIONS: Both mild cold and mild hot temperatures may significantly increase the risk of AR outpatients in Xinxiang, China. These findings could have important public health implications for the occurrence and prevention of AR.
Under the background of global warming, it has been confirmed that heat exposure has a huge impact on human health. The current study aimed to evaluate the effects of daily mean ambient temperature on hospital admissions for obstructive nephropathy (ON) at the population level. A total of 19,494 hospitalization cases for ON in Wuhan, China from January 1, 2015 to December 31, 2018 were extracted from a nationwide inpatient database in tertiary hospitals according to the International Classification of Diseases (ICD)- 10 codes. Daily ambient meteorological and pollution data during the same period were also collected. A quasi-Poisson Generalized Linear Model (GLM) combined with a distributed lag non-linear model (DLNM) was applied to analyze the lag-exposure-response relationship between daily mean temperature and daily hospital admissions for ON. Results showed that there were significantly positive associations between the daily mean temperature and ON hospital admissions. Relative to the minimum-risk temperature (-3.4 ℃), the risk of hospital admissions for ON at moderate hot temperature (25 ℃, 75th percentile) occurred from lag day 4 and stayed to lag day 12 (cumulative relative risk [RR] was 1.846, 95 % confidence interval [CI]: 1.135-3.005, over lag 0-12 days). Moreover, the risk of extreme hot temperature (32 ℃, 99th percentile) appeared immediately and lasted for 8 days (RR = 2.019, 95 % CI: 1.308-3.118, over lag 0-8 days). Subgroup analyses indicated that the middle-aged and elderly (≥45 years) patients might be more susceptible to the negative effects of high temperature, especially at moderate hot conditions. Our findings suggest that temperature may have a significant impact on the acute progression and onset of ON. Higher temperature is associated with increased risks of hospital admissions for ON, which indicates that early interventions should be taken in geographical settings with relatively high temperatures, particularly for the middle-aged and elderly.
OBJECTIVE: The relationship between outdoor temperature and blood pressure (BP) has been inconclusive. We analyzed data from a prospective cohort study in northwestern China to investigate the effect of outdoor temperature on BP and effect modification by season. METHODS: A total of 32,710 individuals who participated in both the baseline survey and the first follow-up in 2011-2015 were included in the study. A linear mixed-effect model and generalized additive mixed model (GAMM) were applied to estimate the association between outdoor temperature and BP after adjusting for confounding variables. RESULTS: The mean differences in systolic blood pressure (SBP) and diastolic blood pressure (DBP) between summer and winter were 3.5 mmHg and 2.75 mmHg, respectively. After adjusting for individual characteristics, meteorological factors and air pollutants, a significant increase in SBP and DBP was observed for lag 06 day and lag 04 day, a 0.28 mmHg (95% CI: 0.27-0.30) per 1 °C decrease in average temperature for SBP and a 0.16 mmHg (95% CI: 0.15-0.17) per 1 °C decrease in average temperature for DBP, respectively. The effects of the average temperature on both SBP and DBP were stronger in summer than in other seasons. The effects of the average temperature on BP were also greater if individuals were older, male, overweight or obese, a smoker or drinker, or had cardiovascular diseases (CVDs), hypertension, and diabetes. CONCLUSIONS: This study demonstrated a significant negative association between outdoor temperature and BP in a high-altitude environment of northwest China. Moreover, BP showed a significant seasonal variation. The association between BP and temperature differed by season and individuals’ demographic characteristics (age, gender, BMI), unhealthy behaviors (smoking and alcohol consumption), and chronic disease status (CVDs, hypertension, and diabetes).
BACKGROUND: Composite temperature-related indices have been utilized to comprehensively reflect the impact of multiple meteorological factors on health. We aimed to evaluate the predictive ability of temperature-related indices, choose the best predictor of stroke morbidity, and explore the association between them. METHODS: We built distributed lag nonlinear models to estimate the associations between temperature-related indices and stroke morbidity and then applied two types of cross-validation (CV) methods to choose the best predictor. The effects of this index on overall stroke, intracerebral hemorrhage (ICH), and ischemic stroke (IS) morbidity were explored and we explained how this index worked using heatmaps. Stratified analyses were conducted to identify vulnerable populations. RESULTS: Among 12 temperature-related indices, the alternative temperature-humidity index (THIa) had the best overall performance in terms of root mean square error when combining the results from two CVs. With the median value of THIa (25.70 °C) as the reference, the relative risks (RRs) of low THIa (10th percentile) reached a maximum at lag 0-10, with RRs of 1.20 (95%CI:1.10-1.31), 1.49 (95%CI:1.29-1.73) and 1.12 (95%CI:1.03-1.23) for total stroke, ICH and IS, respectively. According to the THIa formula, we matched the effects of THIa on stroke under various combinations of temperature and relative humidity. We found that, although the low temperature (<20 °C) had the greatest adverse effect, the modification effect of humidity on it was not evident. In contrast, lower humidity could reverse the protective effect of temperature into a harmful effect at the moderate-high temperature (24 °C-27 °C). Stratification analyses showed that the female was more vulnerable to low THIa in IS. CONCLUSIONS: THIa is the best temperature-related predictor of stroke morbidity. In addition to the most dangerous cold weather, the government should pay more attention to days with moderate-high temperature and low humidity, which have been overlooked in the past.
This paper investigates the relationship between temperature and hospitalization in China. Using inpatient visit claims of two major public insurance schemes covering 47 cities in 28 provinces for three years, we see a 7.3% increase in hospital admissions on days on which the average temperature is above 27 degrees C, and a 2% increase in 31-day cumulative hospital admissions relative to a benchmark-temperature day in the subsequent weeks. Such an effect is much larger than evidence from developed economies. Using detailed information on medical bills, we calculate that an additional hot day nationwide is associated with approximately 2 billion yuan (roughly equivalent to 0.3 billion US dollars) increase in medical expenses that are related to inpatient services, 1.9 billion yuan (roughly equivalent to 0.29 billion US dollars) of which is borne by the public insurance system, and 0.2 billion yuan (roughly equivalent to 0.01 billion US dollars) of which is borne by the insured.
Association between acute myocardial infarction (AMI) morbidity and ambient temperature has been examined with generalized linear model (GLM) or generalized additive model (GAM). However, the effect size by these two methods might be biased due to the autocorrelation of time series data and arbitrary selection of degree of freedom of natural cubic splines. The present study analyzed how the climatic factors affected AMI morbidity for older adults in Shanghai with Mixed generalized additive model (MGAM) that addressed these shortcomings mentioned. Autoregressive random effect was used to model the relationship between AMI and temperature, PM10, week days and time. The degree of freedom of time was chosen based on the seasonal pattern of temperature. The performance of MGAM was compared with GAM on autocorrelation function (ACF), partial autocorrelation function (PACF) and goodness of fit. One-year predictions of AMI counts in 2011 were conducted using MGAM with the moving average. Between 2007 and 2011, MGAM adjusted the autocorrelation of AMI time series and captured the seasonal pattern after choosing the degree of freedom of time at 5. Using MGAM, results were well fitted with data in terms of both internal (R2 = 0.86) and external validity (correlation coefficient = 0.85). The risk of AMI was relatively high in low temperature (Risk ratio = 0.988 (95% CI 0.984, 0.993) for under 12°C) and decreased as temperature increased and speeded up within the temperature zone from 12°C to 26°C (Risk ratio = 0.975 (95% CI 0.971, 0.979), but it become increasing again when it is 26°C although not significantly (Risk ratio = 0.999 (95% CI 0.986, 1.012). MGAM is more appropriate than GAM in the scenario of response variable with autocorrelation and predictors with seasonal variation. The risk of AMI was comparatively higher when temperature was lower than 12°C in Shanghai as a typical representative location of subtropical climate.
BACKGROUND: Extreme ambient temperature has an adverse effect on pregnancy outcomes, but the conclusions have been inconsistent. The influence of ambient temperature and diurnal temperature variation on the premature rupture of membranes (PROM) needs further study. METHODS AND FINDINGS: The daily data of PROMs, daily meteorological and air pollutant were obtained. After controlling for potential confounding factors, the quasi-Poisson generalized additive model (GAM) combined with the distributed lag nonlinear model (DLNM) was used to analyze the association between temperature or diurnal temperature variation and PROM, including preterm premature rupture of membranes (PPROM) and term premature rupture of membranes (term PROM). Compared with the median temperature(18.7 °C), the mean temperature of 5-7 days lagging beyond 31.5 °C and below -1.5 °C was positively correlated with PROM; the mean temperature had more sensitive effect on the term PROM. Exposure to extremely high temperatures (97.5th percentile, 32 °C) had a 6-day lagging relative risk (RR) (95% CI: 1.005-1.160) of 1.08 for PROM and a 6-day lagging RR of 1.079 (95% CI: 1.005-1.159) for term PROM; Exposure to a high diurnal temperature variation (diurnal temperature variation greater than 16 °C) was positively correlated with the term PROM. Compared with the 2.5th percentile diurnal temperature variation (2 °C), exposure to the 95th percentile diurnal temperature variation (17 °C) significantly increased the risk of term PROM (RR: 1.229, 95% CI: 1.029-1.467). CONCLUSIONS: Exposure to a high-temperature and a high diurnal temperature variation environment will increase the relative risks of PROM. For pregnant women in the 3rd trimester, it is important to reduce exposure to extremely high-temperatures and greater diurnal temperature changes.
BACKGROUND: The burden of cardiovascular disease (CVD) on the current aging society in China is substantial. Climate change, including extreme temperatures and humidity, has a detrimental influence on health. However, epidemiological studies have been unable to fully identify the association between climate change and CVD among older adults. Therefore, we investigated the associations between temperature and relative humidity and CVD among older adults in China. METHODS: We used cohort data from the China Longitudinal Health and Longevity Survey (CLHLS) conducted in 2002, 2005, 2008, 2011, 2014, and 2018. A total of 39,278 Chinese adults 65 years and older participated in the analyses. The average annual temperatures and relative humidity during 2001 and 2017 (before the survey year) at the city level in China were used as the exposure measures. We selected patients with hypertension, heart disease, and stroke to create a sample of CVD patients. The associations between temperature and relative humidity and CVD were analyzed using the generalized estimation equation (GEE) model. Covariates included sociodemographic factors, health status, lifestyle, and cognitive function. RESULTS: The average annual temperature was negatively correlated with the prevalence of CVD. Every 1°C increase in the average annual temperature reduced the rates of hypertension by 3% [odds ratio (OR): 0.97; 95% confidence interval (CI): 0.96-0.97], heart disease by 6% (OR: 0.94; 95% CI: 0.92-0.95), and stroke by 5% (OR: 0.95; 95% CI: 0.94-0.97). The results of the analyses stratified by sex, urban/rural residence, and educational level were robust. The average annual relative humidity was inversely associated with the likelihood of CVD among older adults. Every 1% increase in the average annual relative humidity reduced the rates of hypertension by 0.4% (OR: 0.996; 95% CI: 0.99-1.00), heart disease by 0.6% (OR: 0.994; 95% CI: 0.99-1.00), and stroke by 0.08% (OR: 0.992; 95% CI: 0.98-1.00). However, the effects were more obvious with higher humidity levels (>70). CONCLUSION: Our findings suggest that higher temperatures and relative humidity may reduce the risk of CVD among older adults.
Existing studies suggested that ambient temperature may affect the attack of acute appendicitis. However, the identification of the quantitative effect and vulnerable populations are still unknown. The purposes of this study were to quantify the impact of daily mean temperature on the hospitalization of acute appendicitis and clarify vulnerable groups, further guide targeted prevention of acute appendicitis in Tongling. Daily data of cases and meteorological factors were collected in Tongling, China, during 2015-2019. Time stratified case-crossover design and conditional logistic regression model were used to evaluate the odds ratio (OR) of ambient temperature on hospitalizations for acute appendicitis. Stratified analyses were performed by sex, age, and marital status. The odds ratio (OR) of hospitalizations for acute appendicitis increased by 1.6% for per 1 ℃ rise in mean temperature at lag3[OR = 1.016, 95% confidence interval (CI): 1.004-1.028]. In addition, our results suggest it is in the women that increased ambient temperature is more likely to contribute to acute appendicitis hospitalizations; we also found that the married are more susceptible to acute appendicitis hospitalizations due to increased ambient temperature than the unmarried; people in the 21-40 years old are more sensitive to ambient temperature than other age groups. The significant results of the differences between the subgroups indicate that the differences between the groups are all statistically significant. The elevated ambient temperatures increased the risk of hospitalizations for acute appendicitis. The females, married people, and patients aged 21-40 years old were more susceptible to ambient temperature. These findings suggest that more attention should be paid to the impact of high ambient temperature on acute appendicitis in the future.
BACKGROUND: Evidence is limited regarding the association between temperatures and health costs. OBJECTIVES: We tried to investigate the association between temperatures and emergency department visits (EDVs) costs in China. METHODS: Daily data on EDVs costs, weather, air pollution were collected from 17 sites in China during 2014-2018. A quasi-Poisson generalized additive regression with distributed lag nonlinear model was applied to assess the temperature-EDVs cost association. Random-effect meta-analysis was used to pool the estimates from each site. Attributable fractions and national attributable EDVs costs due to heat and cold were calculated. RESULTS: Relative risk (RR) due to extreme heat over 0-7 lag days was 1.14 [95% confidence intervals (CI): 1.08-1.19] and 1.11 (95% CI: 1.07-1.16) for EDVs examination (including treatment) and medicine cost, respectively. People aged 18-44 and those with genitourinary diseases were at higher risk from heat. 0.72% of examination cost and 0.57% of medicine cost were attributed to extreme heat, costing 274 million Chinese Yuan annually. Moderate heat had lower RR but higher attributable fraction of EDVs costs. Exposure to extreme cold over 0-21 lag days increased the risk of medicine cost for people aged 18-44 [RR: 1.30 (95% CI: 1.10-1.55)] and those with respiratory diseases [RR: 1.56 (95% CI: 1.14-2.14)], but had non-statistically significant attributable fraction of the total EDVs cost. CONCLUSIONS: Exposure to heat and cold resulted in remarkable health costs. More resources and preparedness are needed to tackle such a challenge as our climate is rapidly changing.
BACKGROUND: For the reason that many studies have been inconclusive on the effect of humidity on respiratory disease, we examined the association between absolute humidity and respiratory disease mortality and quantified the mortality burden due to non-optimal absolute humidity in Guangzhou, China. METHODS: Daily respiratory disease mortality including total 42,440 deaths from 1 February 2013 to 31 December 2018 and meteorological data of the same period in Guangzhou City were collected. The distributed lag non-linear model was used to determine the optimal absolute humidity of death and discuss their non-linear lagged effects. Attributable fraction and population attributable mortality were calculated based on the optimal absolute humidity, defined as the minimum mortality absolute humidity. RESULTS: The association between absolute humidity and total respiratory disease mortality showed an M-shaped non-linear curve. In total, 21.57% (95% CI 14.20 ~ 27.75%) of respiratory disease mortality (9154 deaths) was attributable to non-optimum absolute humidity. The attributable fractions due to high absolute humidity were 13.49% (95% CI 9.56 ~ 16.98%), while mortality burden of low absolute humidity were 8.08% (95% CI 0.89 ~ 13.93%), respectively. Extreme dry and moist absolute humidity accounted for total respiratory disease mortality fraction of 0.87% (95% CI – 0.09 ~ 1.58%) and 0.91% (95% CI 0.25 ~ 1.39%), respectively. There was no significant gender and age difference in the burden of attributable risk due to absolute humidity. CONCLUSIONS: Our study showed that both high and low absolute humidity are responsible for considerable respiratory disease mortality burden, the component attributed to the high absolute humidity effect is greater. Our results may have important implications for the development of public health measures to reduce respiratory disease mortality.
Climate-related disasters are increasing across the globe, but their adverse health impacts are unevenly distributed. The people most severely affected tend to be from socio-economically disadvantaged, vulnerable populations, who have high exposure to risk conditions and insufficient adaptive capacity. Despite the increasing health impacts of climate change and disaster risks felt in Asian countries such as China, Indonesia and Vietnam, there are few attempts to access and translate literature and evidence on climate-related disasters and adaptation activities from non-English speaking countries. Conducted by a multi-country project team, this review aims to better understand the current literature and to study gaps in these three countries through an extensive search of literature, in English, Chinese, Indonesian and Vietnamese. Through a systematic review process a total of 298 studies out of 10,139 were included in this study. Key findings confirm that all three countries have experienced increasing climate-related disasters with their associated health impacts, and that adaptation strategies are urgently needed to reduce the risk and vulnerability of the most affected populations. Future studies should consider conducting vulnerability assessments to inform translational research on developing effective adaptation strategies. Authors commented that a common challenge they found was the shortterm nature of disaster response mechanisms, and the lack of long-term investment and policy support for capacity building and multisectoral collaborative research that address the needs of populations vulnerable to climate-related disasters. Thus, to better prepare for future disasters, it is vital that governments and international agencies prioritize funding policies to fill this gap.
Climate change causing an increase of frequency and magnitude of heat waves has a huge impact on the urban population worldwide. In Indonesia, the Southeast Asian country in the tropical climate zone, the increasing heat wave duration due to climate change will be also magnified by projected rapid urbanization. Therefore, not only climate change mitigation measures but also adaptation solutions to more frequent extreme weather events are necessary. Adaptation is essential at local levels. The projected increase of the heat wave duration will trigger greater health-related risks. It will also drive higher energy demands, particularly in urban areas, for cooling. New smart solutions for growing urbanization for reducing urban heat island phenomenon are critical, but in order to identify them, analyzing the changing magnitude and spatial distribution of urban heat is essential. We projected the current and future spatial variability of heat stress index in three cities in Indonesia, namely, Medan, Surabaya, and Denpasar, under climate change and land-cover change scenarios, and quantified it with the Universal Thermal Climate Index (UTCI) for two periods, baseline (1981-2005) and future (2018-2042). Our results demonstrated that currently the higher level of the UTCI was identified in the urban centers of all three cities, indicating the contribution of urban heat island phenomenon to the higher UTCI. Under climate change scenarios, all three cities will experience increase of the heat, whereas applying the land-cover scenario demonstrated that in only Medan and Denpasar, the UTCI is likely to experience a higher increase by 3.1 degrees C; however, in Surabaya, the UTCI will experience 0.84 degrees C decrease in the period 2018-2042 due to urban greening. This study advanced the UTCI methodology by demonstrating its applicability for urban heat warning systems and for monitoring of the urban green cooling effect, as well as it provides a base for adaptation measures’ planning.
As a highly important meteorological hazard, heat waves notably impact human health and socioeconomics, and accurate heat wave risk identification and assessment are effective ways to address this issue. The current spatial scale of heat wave risk assessment is relatively coarse, hardly meeting fine-scale heat wave risk assessment requirements. Therefore, based on multi-source fine-scale remote sensing data and socioeconomic data, this paper evaluates the heat wave risk along the Jakarta-Bandung high-speed railway, obtains the spatial distribution of heat wave risk in 2005, 2014 and 2019, and analyzes spatiotemporal risk variations over the past 15 years. The results show that most high-risk areas were affected by high-temperature hazards. Over time, the hazard, exposure, vulnerability and risk levels increased by 25.82%, 3.31%, 14.82% and 6.97%, respectively, from 2005-2019. Spatially, the higher risk in the northwest is mainly distributed in Jakarta. Additionally, a comparative analysis was conducted on the risk results, and the results showed that the 100-m scale showed more spatial differences than the kilometer scale. The research results in this paper can provide scientific advice on heat wave risk prevention considering the Jakarta-Bandung high-speed railway construction and regional economic and social development.
BACKGROUND: Previous studies focusing on urban, industrialised regions have found that excess heat exposure can increase all-cause mortality, heat-related illnesses, and occupational injuries. However, little research has examined how deforestation and climate change can adversely affect work conditions and population health in low latitude, industrialising countries. METHODS: For this modelling study we used data at 1 km^(2) resolution to compare forest cover and temperature conditions in the Berau regency, Indonesia, between 2002 and 2018. We used spatially explicit satellite, climate model, and population data to estimate the effects of global warming, between 2002 and 2018 and after applying 1·0°C, 1·5°C, and 2·0°C of global warming to 2018 temperatures, on all-cause mortality and unsafe work conditions in the Berau regency, Indonesia. FINDINGS: Between 2002 and 2018, 4375 km(2) of forested land in Berau was cleared, corresponding to approximately 17% of the entire regency. Deforestation increased mean daily maximum temperatures by 0·95°C (95% CI 0·97–0·92; p<0·0001). Mean daily temperatures increased by a population-weighted 0·86°C, accounting for an estimated 7·3–8·5% of all-cause mortality (or 101-118 additional deaths per year) in 2018. Unsafe work time increased by 0·31 h per day (95% CI 0·30–0·32; p<0·0001) in deforested areas compared to 0·03 h per day (0·03–0·04; p<0·0001) in areas that maintained forest cover. With 2·0°C of additional future global warming, relative to 2018, deforested areas could experience an estimated 17-20% increase in all-cause mortality (corresponding to an additional 236-282 deaths per year) and up to 5 h of unsafe work per day. INTERPRETATION: Heat exposure from deforestation and climate change has already started affecting populations in low latitude, industrialising countries, and future global warming indicates substantial health impacts in these regions. Further research should examine how deforestation is currently affecting the health and wellbeing of local communities. FUNDING: University of Washington Population Health Initiative. TRANSLATION: For the Bahasa translation of the abstract see Supplementary Materials section.
BACKGROUND: Climate change, as a defining issue of the current time, is causing severe heat-related illness in the context of extremely hot weather conditions. In Japan, the remarkable temperature increase in summer caused by an urban heat island and climate change has become a threat to public health in recent years. METHODS: This study aimed to determine the potential risk factors for heatstroke by analysing data extracted from the records of emergency transport to the hospital due to heatstroke in Fukuoka City, Japan. In this regard, a negative binomial regression model was used to account for overdispersion in the data. Age-structure analyses of heatstroke patients were also embodied to identify the sub-population of Fukuoka City with the highest susceptibility. RESULTS: The daily maximum temperature and wet-bulb globe temperature (WBGT), along with differences in both the mean temperature and time-weighted temperature from those of the consecutive past days were detected as significant risk factors for heatstroke. Results indicated that there was a positive association between the resulting risk factors and the probability of heatstroke occurrence. The elderly of Fukuoka City aged 70 years or older were found to be the most vulnerable to heatstroke. Most of the aforementioned risk factors also encountered significant and positive associations with the risk of heatstroke occurrence for the group with highest susceptibility. CONCLUSION: These results can provide insights for health professionals and stakeholders in designing their strategies to reduce heatstroke patients and to secure the emergency transport systems in summer.
BACKGROUND: The complex role of urbanisation in heat-mortality risk has not been fully studied. Japan has experienced a rapid population increase and densification in metropolitan areas since the 2000s; we investigated the effects of population concentration in metropolitan areas on heat-mortality risk using nationwide data. METHODS: We collected time-series data for mortality and weather variables for all 47 prefectures in Japan (1980-2015). The prefectures were classified into three sub-areas based on population size: lowest (<1 500 000), intermediate (1 500 000 to 3 000 000), and highest (>3 000 000; i.e. metropolitan areas). Regional indicators associated with the population concentration of metropolitan areas were obtained. RESULTS: Since the 2000s, the population concentration intensified in the metropolitan areas, with the highest heat-mortality risk in prefectures with the highest population. Higher population density and apartment % as well as lower forest area and medical services were associated with higher heat-mortality risk; these associations have generally become stronger since the 2000s. CONCLUSIONS: Population concentration in metropolitan areas intensified interregional disparities in demography, living environments, and medical services in Japan; these disparities were associated with higher heat-mortality risk. Our results can contribute to policies to reduce vulnerability to high temperatures.
This study assesses heatstroke risk in the near future (2031-2050) under RCP8.5 scenario. The developed model is based on a generalized linear model with the number of ambulance transport due to heatstroke (hereafter the patients with heatstroke) as the explained variable and the daily maximum temperature or wet bulb globe temperature (WBGT) as the explanatory variable. With the model based on the daily maximum temperature, we performed the projection of the patients with heatstroke in case of considering only climate change (Case 1); climate change and population dynamics (Case 2); and climate change, population dynamics, and long-term heat acclimatization (Case 3). In Case 2, the number of patients with heatstroke in the near future will be 2.3 times higher than that in the baseline period (1981 – 2000) on average nationwide. The number of future patients with heatstroke in Case 2 is about 10 % larger than that in Case 1 on average nationwide despite population decline. This is due to the increase in the number of elderly people from the baseline period to the near future. However, in 20 prefectures, the number of patients in Case 2 is smaller compared to Case 1. Comparing the results from Cases 1 and 3 reveals that the number of patients with heatstroke could be reduced by about 60 % nationwide by acquiring heat tolerance and changing lifestyles. Notably, given the lifestyle changes represented by the widespread use of air conditioners, the number of patients with heatstroke in the near future will be lower than that of the baseline period in some areas. In other words, lifestyle changes can be an important adaptation to the risk of heatstroke emergency. All of the above results were also confirmed in the prediction model with WBGT as the explanatory variable.
In the context of climate change, most of the global regions are facing the threat of high temperature. Influenced by tropical cyclones in the western North Pacific Ocean, high temperatures are more likely to occur in central China, and the economic losses caused by heat are in urgent need of quantification to form the basis for health decisions. In order to study the economic burden of high temperature on the health of Wuhan residents between 2013 and 2019, we employed meta-analysis and the value of statistical life (VSL) approach to calculate the relative risk of high temperature health endpoints, the number of premature deaths, and the corresponding economic losses in Wuhan City, China. The results suggested that the pooled estimates of relative risk of death from high temperature health endpoints was 1.26 [95% confidence interval (CI): 1.15, 1.39]. The average number of premature deaths caused by high temperature was estimated to be 77,369 (95% CI: 48,906-105,198) during 2013-2019, and the induced economic losses were 156.1 billion RMB (95% CI: 92.28-211.40 billion RMB), accounting for 1.81% (95% CI: 1.14-2.45%) of Wuhan’s annual GDP in the seven-year period. It can be seen that high temperature drives an increase in the premature deaths, and the influence of high temperature on human health results in an economic burden on the health system and population in Wuhan City. It is necessary for the decision-makers to take measures to reduce the risk of premature death and the proportion of economic loss of residents under the impacts of climate change.
BACKGROUND: As climate change, compound hot extremes (CHEs), daytime and nighttime persistent hot extremes, are projected to become much more frequent and intense, which may pose a serious threat to human health. However, evidence on the impact of CHEs on injury is rare. METHODS: We collected injury death data and daily meteorological data from six Chinese provinces during 2013-2018. A time-stratified case-crossover design with two-stage analytic approach was applied to assess the associations of CHEs with injury mortality by intention, mechanism, age and gender. Using the projected daily temperatures of five General Circulation Models (GCMs), we projected the frequency of CHEs and CHEs-attributable mortality burden of injury under three Representative Concentration Pathway (RCP) scenarios. RESULTS: CHEs were significantly associated with increased injury mortality risk (RR = 1.14, 95%CI: 1.09-1.19), with strong effects on unintentional injuries (RR = 1.16, 95%CI:1.11,1.22) and intentional injuries (RR = 1.11, 95%CI:0.99,1.25). Female (RR = 1.21,95%CI: 1.13-1.29) and the elderly (RR = 1.30, 95%CI: 1.22-1.39) were more susceptible to CHEs. Both the frequency and injury mortality burden of CHEs showed a steep rising trend under RCP8.5 scenario, with a 7.37-fold and 8.22-fold increase respectively, by the end of the century, especially in southern, eastern, central and northwestern China. CONCLUSION: CHEs were associated with increased injury mortality risk, and the CHEs-attributable injury mortality burden was projected to aggravate substantially in the future as global warming. It is urgent to develop targeted adaptation policies to alleviate the health burden of CHEs.
BACKGROUND: Many studies have shown that heatwaves are associated with an increased prevalence of urinary diseases. However, few national studies have been undertaken in China, and none have considered the associated economic losses. Such information would be useful for health authorities and medical service providers to improve their policy-making and medical resource allocation decisions. OBJECTIVES: To explore the association between heatwaves and hospital admissions for urinary diseases and assess the related medical costs and indirect economic losses in China from 2014 to 2019. METHODS: Daily meteorological and hospital admission data from 2014 to 2019 were collected from 23 study sites with different climatic characteristics in China. We assessed the heatwave-hospitalization associations and evaluated the location-specific attributable fractions (AFs) of urinary-related hospital admissions due to heatwaves by using a time-stratified case-crossover method with a distributed lag nonlinear model. We then pooled the AFs in a meta-analysis and estimated the national excess disease burden and associated economic losses. We also performed stratified analyses by sex, age, climate zone, and urinary disease subtype. RESULTS: A significant association between heatwaves and urinary-related hospital admissions was found with a relative risk of 1.090 (95 % confidence interval (CI): 1.050, 1.132). The pooled AF was 8.27 % (95%CI: 4.77 %, 11.63 %), indicating that heatwaves during the warm season (May to September) caused 248,364 urinary-related hospital admissions per year, with 2.42 (95%CI: 1.35, 3.45) billion CNY in economic losses, including 2.23 (95%CI: 1.29, 3.14) billion in direct losses and 0.19 (95%CI, 0.06, 0.31) billion in indirect losses, males, people aged 15-64 years, residents of temperate continental climate zones, and patients with urolithiasis were at higher risk. CONCLUSION: Tailored community health campaigns should be developed and implemented to reduce the adverse health effects and economic losses of heatwave-related urinary diseases, especially in the context of climate change.
Heatwaves with unprecedented conditions have devastating health impacts. The summer of 2017 saw unusual heat in China and other regions on earth. Although epidemiologic evidence is clear for elevated mortality risks of heatwaves, the economic impacts due to heatwave-associated mortality remain poorly characterized. Hence, this study systematically assessed the mortality and economic impacts of the 2017 exceptional heatwaves in China. We first used the generalized linear mixed-effect model with Poisson distribution to examine the mortality risks of the 2017 heatwaves in 91 Chinese counties. Further, we calculated the excess deaths attributable to heatwaves in 2852 counties. Finally, we evaluated the city- and province-level death-related economic burden of the 2017 heatwaves based on the value of statistical life (VSL). We found that the 2017 exceptional heatwaves had a statistically significant association (relative risk was 1.23, 95% confidence interval 1.14-1.32) with all-cause mortality across 91 Chinese counties. Nationwide, a total of 16,299 all-cause deaths that occurred in 2017 were attributable to the exceptional heatwaves, resulting in an overall death-related economic loss of 61,304 million RMB as valued by VSL. Given that extraordinary heatwaves are projected to be more frequent under global climate change, our findings could enhance the current understanding of heatwaves’ health and economic impacts and add valuable insights in projection studies of estimating the future health burden of heatwaves.
Objectives: To assess the relationship between regional climatic factors and child drowning in China. Methods: Provincial age-specific drowning rate, climatic and income data were collected. We conducted a geographically weighted regression to evaluate the association between drowning and climatic factors. A generalized additive model was used to comprise a bivariate term with which to investigate the interaction of environmental risk factors and whether such interactions influence drowning mortality. Results: In southern China, an abundance of water systems and increased precipitation, as well as hotter and longer summers, lead to significantly higher drowning compared with that in northern China. Long summers and low economic performance in parts of Xinjiang were key factors for its high drowning mortality rate. Linear and nonlinear joint effects were observed between the risk factors of drowning. Conclusion: Different regions should use adaptive measures to reduce drowning risks, for example, communication campaigns during the summer period or when the weather changes.
BACKGROUND: Antibiotic resistance leads to longer hospital stays, higher medical costs, and increased mortality. However, research into the relationship between climate change and antibiotic resistance remains inconclusive. This study aims to address the gap in the literature by exploring the association of antibiotic resistance with regional ambient temperature and its changes over time. METHODS: Data were obtained from the China Antimicrobial Surveillance Network (CHINET), monitoring the prevalence of carbapenem-resistant Acinetobacter baumannii (CRAB), Klebsiella pneumoniae (CRKP) and Pseudomonas aeruginosa (CRPA) in 28 provinces/regions over the period from 2005 to 2019. Log-linear regression models were established to determine the association between ambient temperature and antibiotic resistance after adjustment for variations in socioeconomic, health service, and environmental factors. FINDINGS: A 1 °C increase in average ambient temperature was associated with 1.14-fold increase (95%-CI [1.07-1.23]) in CRKP prevalence and 1.06-fold increase (95%-CI [1.03-1.08]) in CRPA prevalence. There was an accumulative effect of year-by-year changes in ambient temperature, with the four-year sum showing the greatest effect on antibiotic resistance. Higher prevalence of antibiotic resistance was also associated with higher antibiotic consumption, lower density of health facilities, higher density of hospital beds and higher level of corruption. INTERPRETATION: Higher prevalence of antibiotic resistance is associated with increased regional ambient temperature. The development of antibiotic resistance under rising ambient temperature differs across various strains of bacteria. FUNDING: The National Key R&D Program of China (grant number: 2018YFA0606200), National Natural Science Foundation of China (grant number: 72074234), Fundamental Scientific Research Funds for Central Universities, P.R. China (grant number: 22qntd4201), China Medical Board (grant number: CMB-OC-19-337).
Urolithiasis was a global disease and it was more common in southern China. This study looked into the association between daily temperature and urolithiasis hospital admissions in Ganzhou, a large prefecture-level city in southern China. In Ganzhou City from 2016 to 2019, a total of 60,881 hospitalized cases for urolithiasis from 69 hospitals and meteorological data were gathered. The effect of high ambient temperature on urolithiasis hospital admissions was estimated using a distributed lag nonlinear model. Stratified analysis was done to examine sex differences. The study found that in Ganzhou of China, the exposure-response curves approximated a “J” shape which across genders were basically similar. The maximum lag effect occurred on the second day after high temperatures for males but on the third day for females. Compared to the 10 °C reference temperature and considering the cumulative lag effect of 10 days, the relative risks of the daily mean temperature at the 95th percentile on the total, male, and female hospital admissions for urolithiasis were 2.026 (95% CI: 1.628, 2.521), 2.041 (95% CI: 1.603, 2.598), and 2.030 (95% CI: 1.552, 2.655), respectively, but the relative risks between sex were not statistically significant (p = 0.977). Urolithiasis morbidity risk in China could be exacerbated by high temperatures. The effect of high temperature on urolithiasis was similar across genders.
Ambient high temperature is a worldwide trigger for hypertension events. However, the effects of heat exposure on hypertension and years of life lost (YLL) due to heat remain largely unknown. We conducted a multicenter study in 13 cities in Jiangsu Province, China, to investigate 9727 individuals who died from hypertension during the summer months (May to September) between 2016 and 2017. Meteorological observation data (temperature and rainfall) and air pollutants (fine particulate matter and ozone) were obtained for each decedent by geocoding the residential addresses. A time-stratified case-crossover design was used to quantify the association between heat and different types of hypertension and further explore the modification effect of individual and hospital characteristics. Meanwhile, the YLL associated with heat exposure was estimated. Our results show that summer heat exposure shortens the YLL of hypertensive patients by a total of 14,74 years per month. Of these, 77.9% of YLL was mainly due to hypertensive heart disease. YLL due to heat was pronounced for essential hypertension (5.1 years (95% empirical confidence intervals (eCI): 4.1-5.8)), hypertensive heart and renal disease with heart failure (4.4 years (95% eCI: 0.9-5.9)), and hypertensive heart and renal disease (unspecified, 3.5 years (95% eCI: 1.8-4.5)). Moderate heat was associated with a larger YLL than extreme heat. The distance between hospitals and patients and the number of local first-class hospitals can significantly mitigate the adverse effect of heat exposure on longevity. Besides, unmarried people and those under 65 years of age were potentially susceptible groups, with average reduced YLL of 3.5 and 3.9 years, respectively. Our study reveals that heat exposure increases the mortality risk from many types of hypertension and YLL. In the context of climate change, if effective measures are not taken, hot weather may bring a greater burden of disease to hypertension due to premature death.
The aim of this study was to evaluate the short-term effect of temperature on the risk of acute pancreatitis (AP) in southern China. We performed a time-series study of 2822 patients admitted with a first episode of AP in Nanchang between May 2014 and June 2017. A generalized additive model combined with a distributed lag non-linear model was applied to assess the association of temperature and AP. In subgroup analysis, according to different etiologies of pancreatitis, significant associations were found between daily average temperature and non-biliary pancreatitis hospitalization at lags of 0-7 days, but not for biliary pancreatitis or total AP. Higher daily average temperature tended to increase the occurrence of non-biliary pancreatitis at lags of 0-7 days. These findings suggest that high temperature is associated with higher non-biliary pancreatitis risk in Nanchang, China. In the context of global warming, the morbidity of non-biliary pancreatitis may increase.
BACKGROUND: Many studies have shown that various kinds of diseases were associated with the variation of ambient temperature. However, there’s only a scrap of evidence paying attention to the link between temperature and skin diseases, and no relevant national research was performed in China. OBJECTIVE: This study aimed to quantify the effect of heat on skin diseases and identify the vulnerable populations and areas in China. METHODS: Daily meteorological data, air pollutant data and outpatient data were collected from in 18 sites of China during 2014-2018. A time-series study with distributed lag nonlinear model and multivariate meta-analysis was applied to analyze the site-specific and pooled associations between daily mean temperature and daily outpatient visits of skin diseases by using the data of warm season (from June to September). Stratified analysis by age, sex and climate zones and subtypes of skin diseases were also conducted. RESULTS: We found a positive linear relationship between the ambient temperature and risk of skin diseases, with a 1.25% (95%CI: 0.34%, 2.16%) increase of risk of outpatient visits for each 1 °C increase in daily mean temperature during the warm season. In general, groups aged 18-44 years, males and people living in temperate climate regions were more susceptible to high temperature. Immune dysfunction including dermatitis and eczema were heat-sensitive skin diseases. CONCLUSIONS: Our findings suggested that people should take notice of heat-related skin diseases and also provided some references about related health burden for strategy-makers. Targeted measures for vulnerable populations need to be taken to reduce disease burden, including monitoring and early warning systems, and sun-protection measures.
As one of the most common complications of early pregnancy, spontaneous abortion is associated with environmental factors, but reports estimating the effect of ambient temperature on spontaneous abortion are still inconclusive. Herein, a case-control study (1002 cases and 2004 controls) in Nanjing, China, from 2017 to 2021 was conducted to evaluate the association between temperature exposure and the risk of spontaneous abortion by using distributed lag nonlinear model (DLNM). As a result, daily mean temperature exposure and early spontaneous abortion showed a nonlinear relationship in 14-day lag periods. Moreover, taking the median temperature (17 °C) as a reference, gradually increased positive effects of high temperature on spontaneous abortion could be found during the 4 days prior to hospitalization, and the highest odds ratio (OR) of 2.07 (95% confidence interval (CI): 1.36, 3.16) at extremely hot temperature (33 °C) was observed at 1 lag day. The results suggested that high-temperature exposure in short times during early pregnancy might increase the risk of SAB. Thus, our findings highlight the potential risk of short-term high-temperature exposure during early pregnancy, and more evidence was given for the effects of climate change on maternal health.
BACKGROUND: The health impact of short-term heat exposure is well documented. However, limited studies explored the association between life-time summer heat exposure and lung function. OBJECTIVE: To examine the association between life-time summer heat exposure and lung function among young adults. METHODS: We conducted a retrospective cohort study among 1928 college students in Shandong, China from September 4, 2020 to November 15, 2020. Life-time summer heat exposure for participants were estimated based on the nearest station meteorological data after the participant’s birth date and divided by their learning phases. Lung function indicators included forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). A multiple linear regression model was conducted to examine the associations between summer heat exposure and lung function. Stratificationanalysis by cooling facilities and respiratory diseases history were also conducted. RESULTS: The study subjects had a slight majority of women (58.8%), age 19.2 ± 0.6 years. Each 1 °C increase in life-time summer mean temperature was associated with 1.07% [95% confidence interval (CI): -1.95-0.18%] decrease in FVC and 0.88% (95 %CI: -1.71, -0.05%) decrease in FEV1. Participants with respiratory diseases and non-cooling facility users were more susceptible to summer heat exposure. The usage of fan and air condition could effectively reduce the deleterious heat effects on lung function. CONCLUSION: Life-time summer heat exposure is significantly associated with the reduction of lung function in young adults. Cooling facilities are necessary for pre-school children to reduce heat effects. Fan and air-condition are effective cooling facilities, especially for people with respiratory diseases.
A heat danger day is defined as an extreme when the heat stress index (a combined temperature and humidity measure) exceeding 41 degrees C, warranting public heat alerts. This study assesses future heat risk (i.e. heat danger days times the population at risk) based on the latest Coupled Model Intercomparison Project phase 6 projections. In recent decades (1995-2014) China’s urban agglomerations (Beijing-Tianjin-Hebei, Yangtze River Delta, Middle Yangtze River, Chongqing-Chengdu, and Pearl River Delta (PRD)) experienced no more than three heat danger days per year, but this number is projected to increase to 3-13 days during the population explosion period (2041-2060) under the high-emission shared socioeconomic pathways (SSP3-7.0 and SSP5-8.5). This increase will result in approximately 260 million people in these agglomerations facing more than three heat danger days annually, accounting for 19% of the total population of China, and will double the current level of overall heat risk. During the period 2081-2100, there will be 8-67 heat danger days per year, 60%-90% of the urban agglomerations will exceed the current baseline number, and nearly 310 million people (39% of the total China population) will be exposed to the danger, with the overall heat risk exceeding 18 times the present level. The greatest risk is projected in the PRD region with 67 heat danger days to occur annually under SSP5-8.5. With 65 million people (68% of the total population) experiencing increased heat danger days, the overall heat risk in the region will swell by a factor of 50. Conversely, under the low-emission pathways (SSP1-2.6 and SSP2-4.5), the annual heat danger days will remain similar to the present level or increase slightly. The result indicates the need to develop strategic plans to avoid the increased heat risk of urban agglomerations under high emission-population pathways.
As a combination of temperature and humidity, wet-bulb temperature (WBT) is useful for assessing heat stress and its societal and economic impacts. However, spatial and temporal behaviors of summer WBT in China remain poorly understood. In this study, we investigate the dominant spatiotemporal modes of summer (June-July-August) WBT in the mainland of China during 1960-2017 by using empirical orthogonal function (EOF) analysis and reveal their corresponding underlying mechanisms. The leading mode (EOF1) of summer WBT in China shows a nationwide increasing WBT with a stronger magnitude in northern and western than southeastern China. The second mode (EOF2) displays a zonal pattern with anomalously increased WBT in the west and decreased WBT in the east. The third mode (EOF3) shows a meridional feature with the largest WBT trends appearing in the Yangtze River valley. Further examinations suggest that EOF1 exhibits remarkable interdecadal/long-term variations and is likely connected with global warming and the Atlantic Multidecadal Oscillation (AMO), which induce an anomalous anticyclone centering over northern China and covering nearly the whole country. This anticyclone not only plays a key role in the nationwide WBT increases, but also dominates the spatial pattern of EOF1 by modulating relative humidity. EOF2 and EOF3 reflect interannual variations and show significant correlations with the El Nino-Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO), respectively. A zonal wavelike pattern with troughs over Balkhash and northeastern China, and Mongolia high substantially modulates the water vapor transport in China, thus playing a key role in EOF2. In the case of EOF3, an anomalous anticyclone in the middle-upper troposphere and a shallow intensified cyclone in the lower troposphere collectively format the spatial pattern of EOF3 by inducing significant increases in temperature in central-eastern China and transporting a large amount of water vapor to northeastern China, respectively. These findings are critical to improve our understanding of summer WBT in China and to mitigate the negative effects of heat stress.
With the acceleration of urbanization throughout the world, climate problems related to climate change including urban heat islands and global warming have become challenges to urban human settlements. Numerous studies have shown that greenways are beneficial to urban climate improvement and can provide leisure places for people. Taking the coastal greenway in Qingdao as the research object, mobile measurements of the microclimate of the greenway were conducted in order to put forward an evaluation method for the research of outdoor thermal comfort. The results showed that different vegetation coverage affected the PET (physiologically equivalent temperature), UTCI (Universal Thermal Climate Index) as well as thermal comfort voting. We found no significant correlation between activities, age, gender, and thermal comfort voting. Air temperature sensation and solar radiation sensation were the primary factors affecting the thermal comfort voting of all sections. Otherwise, within some sections, wind sensation and humidity sensation were correlated with thermal sensation voting and thermal comfort voting, respectively. Both PET and UTCI were found to have a negative correlation with the vegetation coverage on both sides of the greenway. However, the vegetation coverage had positive correlation (R = 0.072) for thermal sensation and significant positive correlation (R = 0.077*) for thermal comfort. The paved area cover was found to have a positive correlation with PET and UTCI, while having a negative correlation with thermal sensation (R = -0.049) and thermal comfort (R = -0.041). This study can provide scientific recommendations for the planning and design of greenway landscapes to improve thermal comfort.
With the effects of climate change, people are increasingly facing human-perceived heat stress (HPHS), which describes the combined effects of high temperature, high humidity, and low surface wind speed. HPHS has a significant impact on industrial and agricultural production, people’s lifestyles, and public health. However, the characteristics of HPHS with respect to changes and influencing factors have not been fully investigated using dynamic classification of urban, suburban, and rural stations based on absolute and relative thresholds of seven HPHS indices in Southwest China. The results of this study revealed that, first, during the period 1961-2019, the normal annual and seasonal HPHS values and extreme HPHS days increased significantly, while the extreme HPHS values for the seven HPHS indices decreased. Second, based on the absolute and relative thresholds, the frequency and intensity of the impact of urbanization differed in four regions, and in Yunnan and Guizhou in particular. Different HPHS indices and different dynamic station classification methods result in different esti -mations of the effects of urbanization on annual and seasonal changes in the regional climate. Therefore, choosing an appropriate dynamic station classification method and considering the applicability of different indices in different seasons in different regions is very important. Third, the Granger causality test shows that the percentage of stations with Granger causality between landscape composition indices and seven extreme HPHS is the highest among all influencing factors. At the same time, boosted regression tree detection also showed that the landscape composition indices had the highest contribution percentage to the seven extreme HPHS. There-fore, rational planning of land-use patterns, especially in relation to urban forest land, grassland, wetland, and water bodies (including vertical landscape composition, configuration planning, and building density and layout) has implications for the realization of the United Nations Sustainable Development Goals (SDGs), in particular SDG 11, Sustainable Cities and Communities.
Cardiovascular disease (CVD) has become a severe public health and social issue in China. However, in northwest China, evidence on the association between ambient temperature and CVD hospitalisations in suburban farmers is somewhat limited. We collected CVD hospitalisations and meteorological data (2012-2015) in Zhangye suburbs and assessed the temperature-related risk and burden of admission by fitting a distributed lag nonlinear model to probe the relationship between ambient temperature and CVD hospitalisations among farmers in suburban northwest China. The results show that 23,921 cases of CVD admissions were recorded from 2012 to 2015. There was a “U-shaped” association between temperature and hospitalisations. Compared with the minimum admissions temperature (MAT) at 15.3 °C, the cumulative relative risk (RR) over lag 0-21 days was 1.369 (95% CI 0.980-1.911) for extreme cold temperature (1st percentile, -15 °C), 1.353 (95% CI 1.063-1.720) for moderate cold (5th percentile, -11 °C), 1.415 (95% CI 1.117-1.792) for extreme heat (99th percentile, 26 °C), and 1.241 (95% CI 1.053-1.464) for moderate heat (95th percentile, 24 °C). Female farmers were more susceptible to low and high temperatures than male farmers. Farmers aged ≥ 65 years old were more sensitive to low temperatures, while farmers aged < 65 years old were more sensitive to high temperatures. A total of 13.4% (3,208 cases) of the hospitalisation burden for CVD were attributed to temperature exposure, with the moderate range of temperatures accounting for the most significant proportion (12.2%). Ambient temperature, primarily moderate temperatures, might be an essential factor for cardiovascular-related hospitalisations among farmers in suburban northwest China.
What is already known about this topic? Previous studies have mainly focused on the relationship between temperature and mortality from stroke, but analysis on the effects on years of life lost (YLL) is limited. What is added by this report? YLLs were used as the health outcome, and cold and hot weather were found to be significantly associated with an increase in YLLs from stroke and for different groups, with a stronger effect found to be associated with low temperature. What are the implications for public health practice? These findings could help identify vulnerable regions and populations that have a more serious temperature-related burden and to guide the practical and effective measures for stroke control from a YLL perspective.
BACKGROUND: Whether ambient temperature exposure contributes to death from asthma remains unknown to date. We therefore conducted a case-crossover study in China to quantitatively evaluate the association and burden of ambient temperature exposure on asthma mortality. METHODS: Using data from the National Mortality Surveillance System in China, we conducted a time-stratified case-crossover study of 15 888 individuals who lived in Hubei and Jiangsu province, China and died from asthma as the underlying cause in 2015-2019. Individual-level exposures to air temperature and apparent temperature on the date of death and 21 days prior were assessed based on each subject’s residential address. Distributed lag nonlinear models based on conditional logistic regression were used to quantify exposure-response associations and calculate fraction and number of deaths attributable to non-optimum ambient temperatures. RESULTS: We observed a reverse J-shaped association between air temperature and risk of asthma mortality, with a minimum mortality temperature of 21.3 °C. Non-optimum ambient temperature is responsible for substantial excess mortality from asthma. In total, 26.3% of asthma mortality were attributable to non-optimum temperatures, with moderate cold, moderate hot, extreme cold and extreme hot responsible for 21.7%, 2.4%, 2.1% and 0.9% of asthma mortality, respectively. The total attributable fraction and number was significantly higher among adults aged less than 80 years in hot temperature. CONCLUSIONS: Exposure to non-optimum ambient temperature, especially moderate cold temperature, was responsible for substantial excess mortality from asthma. These findings have important implications for planning of public-health interventions to minimize the adverse respiratory damage from non-optimum ambient temperature.
Climate change has been referred to as one of the greatest threats to human health, with reports citing likely increases in extreme meteorological events. In this study, we estimated the relationships between temperature and outpatients at a major hospital in Qingdao, China, during 2015-2017, and assessed the morbidity burden. The results showed that both low and high temperatures were associated with an increased risk of outpatient visits. High temperatures were responsible for more morbidity than low temperatures, with an attributed fraction (AF) of 16.86%. Most temperature-related burdens were attributed to moderate cold and hot temperatures, with AFs of 5.99% and 14.44%, respectively, with the young (0-17) and male showing greater susceptibility. The results suggest that governments should implement intervention measures to reduce the adverse effects of non-optimal temperatures on public health-especially in vulnerable groups.
Previous studies demonstrate a significant correlation between the vertical elevation of urban morphology and UHI, however, topological parameters are barely considered.
Urban heat island (UHI), referring to higher temperatures in urban extents than its surrounding rural regions, is widely reported in terms of negative effects to both the ecological environment and human health. To propose effective mitigation measurements, spatiotemporal variations and control machines of surface UHI (SUHI) have been widely investigated, in particular based on the indicator of SUHI intensity (SUHII). However, studies on SUHI frequency (SUHIF), an important temporal indicator, are challenged by a large number of missing data in daily land surface temperature (LST). Whether there is any city with strong SUHII and low SUHIF remains unclear. Thanks to the publication of daily seamless all-weather LST, this paper is proposed to investigate spatiotemporal variations of SUHIF, to compare SUHII and SUHIF, to conduct a pattern classification, and to further explore their driving factors across 305 Chinese cities. Four main findings are summarized below: (1) SUHIF is found to be higher in the south during the day, while it is higher in the north at night. Cities within the latitude from 20 degrees N and 40 degrees N indicate strong intensity and high frequency at day. Climate zone-based variations of SUHII and SUHIF are different, in particular at nighttime. (2) SUHIF are observed in great diurnal and seasonal variations. Summer daytime with 3.01 K of SUHII and 80 of SUHIF, possibly coupling with heat waves, increases the risk of heat-related diseases. (3) K-means clustering is employed to conduct pattern classification of the selected cities. SUHIF is found possibly to be consistent to its SUHII in the same city, while they provide quantitative and temporal characters respectively. (4) Controls for SUHIF and SUHII are found in significant variations among temporal scales and different patterns. This paper first conducts a comparison between SUHII and SUHIF, and provides pattern classification for further research and practice on mitigation measurements.
Due to global warming and human activities, heat stress (HS) has become a frequent extreme weather event around the world, especially in megacities. This study aims to quantify the responses of urban HS (UHS) to anthropogenic heat (AH) emission and its antrophogenic sensible heat (ASH)/anthropogenic latent heat (ALH) components and increase in the size of cities in the south and north China for the 2019 summer based on observations and numerical simulations. AH release could aggravate UHS drastically, producing maximal increment in moist entropy (an effective HS metric) above 1 and 2 K over the south and north high-density urban regions mainly through ALH. In contrast, future urban expansion leads to an increase in HS coverage, and it has a larger impact on UHS intensity change (6 and 2 K in south and north China) relative to AH. The city radius of 60 km is a possible threshold to plan to city sprawl. Above that city size, the HS intensity change due to urban expansion tends to slow down in the north and inhibit in the south, and about one-third of the urban regions might be hit by extreme heat stress (EHS), reaching maximal hit ratio. Furthermore, changes in warmest EHS events are more associated with high humidity change responses, irrespective of cities being in the north or south of China, which support the idea that humidity change is the primary driving factor of EHS occurrence. The results of this study serve for effective urban planning and future decision making.
Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 degrees C and 2.6 degrees C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.
Internal migration from rural to urban areas is prevalent in China. Past studies demonstrated that thermal adaptation differed among people from various climate regions. However, the outdoor thermal comfort of exercising people with a diverse climatic background remains largely unexplored. This study examines the relationship between short-term physiological and psychological thermal adaptation and outdoor thermal comfort of exercising people from different climate zones in China. We recruited first-year students (n = 145) who engaged in outdoor training between 3 and September 14, 2018 in Guangzhou, China. Physiological parameters include heart rate (HR) from fitness trackers and skin temperature (Tskin) from iButtons. These students were surveyed regarding their thermal comfort and psychological state over the study period (n = 968). Physiological Equivalent Temperature (PET) was calculated from weather station data at the training sites. T-tests reveal differences in HR and thermal perception between local and non-local students, but not Tskin. Under similar PET conditions, non-local students reported a higher thermal sensation and greater thermal discomfort than local students during the first week of training. Logistic regression indicates that HR and metabolic rate predict the thermal sensation of non-local students, but not local students. Wind sensation, pleasantness level, fatigue, and perceived suitability for outdoor activities are significant predictors of local and non-local students’ thermal comfort. Our research highlights both physiological and psychological factors (including emotion and fatigue) are necessary to understand acclimatized and non-acclimatized people’s thermal perception. Addressing thermal discomfort at an early stage can prevent more severe heat-related illnesses.
BACKGROUND: Evidence of the effectiveness of intervention against extreme heat remains unclear, especially among children, one of the vulnerable populations. This study aimed to evaluate the effectiveness of a primary school-based intervention program against heatwave and climate change in China to provide evidence for development of policies for adaptation to climate change. METHODS: Two primary schools in Dongtai City, Jiangsu Province, China, were randomly selected as intervention and control schools (CTR registration number: ChiCTR2200056005). Health education was conducted at the intervention school to raise students’ awareness and capability to respond to extreme heat during May to September in 2017. Knowledge, attitude, and practice (KAP) of students and their parents at both schools were investigated by questionnaire surveys before and after intervention. The changes in KAP scores after intervention were evaluated using multivariable difference-in-difference (DID) analysis, controlling for age, sex, etc. Results: The scores of knowledge, attitude, and practice of students and their parents increased by 19.9% (95%CI: 16.3%, 23.6%) and 22.5% (95%CI: 17.8%, 27.1%); 9.60% (95%CI: 5.35%, 13.9%) and 7.22% (95%CI: 0.96%, 13.5%); and 9.94% (95%CI: 8.26%, 18.3%) and 5.22% (95%CI: 0.73%, 9.71%), respectively, after intervention. The KAP score changes of boys were slightly higher than those of girls. Older students had higher score changes than younger students. For parents, the higher the education level, the greater the score change, and change in scores was greater in females than in males. All the health education activities in the program were significantly correlated with the changes in KAP scores of primary school students after intervention, especially those curricula with interesting activities and experiential learning approaches. CONCLUSIONS: Heat and health education program in primary school was an effective approach to improve cognition and behavior for both students and their parents to better adapt to heatwaves and climate change. The successful experience can be generalized to respond to the increasing extreme weather/climate events in the context of climate change, such as heatwaves, and other emergent occasions or public health education, such as the control and prevention of COVID-19.
Heatwaves can produce catastrophic effects on public health and natural systems, especially under global warming. There are two methods to measure heatwaves, computed by relative and absolute thresholds, namely relative and absolute heatwaves (RHWs and AHWs). Generally, AHWs mostly occur in hot areas because of fixed thresholds, while RHWs represent anomalous events for the local climate, making them possible everywhere in the warm season. Based on observations and CMIP6 outputs, this study compared AHWs and RHWs in Eastern China (EC) with five sub-regions [Northeast China (NEC), North China (NC), Lower Yangtze River (LYR), Middle Yangtze River (MYR) and South China (SC)]. Similarities among RHWs and AHWs were found in present-day trends (1995-2014) and spatial distributions. The heatwave intensity/days for RHWs and AHWs both displayed highest future increases in northern/southern EC, and the increases for 2081-2100 would be 1.5 times as high as 2041-2060. All these similarities illustrate that applying either relative or absolute thresholds in EC, historical temporal variations, changing future spatial patterns, and increasing ratio from 2081-2100 to 2041-2060, would show reliable results. As far as differences are concerned, RHWs were observed across the entire EC, while AHWs did not show up in parts of NC and NEC. Considering model performance, RHWs would perform better than AHWs in most areas of EC. The annual heatwave intensity/days were higher for RHWs than for AHWs during present-day and future periods, which might overestimate heat-related risks. Overall, this study recommended RHWs for heatwave analyses, particularly for future projections, but for risk assessment, the choice of thresholds is crucial. The results reinforced the necessity to further improve model performance to address various needs.
Background: The morbidity and mortality rates from heat illness have increased due to a higher number of heatwaves. Effective urgent care of heat illness is crucial for optimizing patient outcomes. However, few studies have examined the emergency preparedness measures required for treating such patients. Methods: From December 23, 2019, to January 23, 2020, a content-validated instrument containing the Perceived Emergency Preparedness Scale for heat illness (heatPEPS) was administered to emergency nurses in China through WeChat. Some of these nurses were retested two weeks later. SPSS 26, IRTPRO 4.2, and NVivo 12 Plus were used for data analysis. Results: In total, 46.4% (200/431) of the participants returned valid responses. With dichotomous scoring, a high score for heatPEPS (mean 7.29; SD 1.667) was elicited. The reduced 9-item heatPEPS had a perfect fit with the 2PL model (M-2 = 27.24, p > 0.05; RMSEA = 0.01) and acceptable internal (alpha = 0.68) and test-rest reliability (intraclass correlation = 0.56). Many participants (74%) were dissatisfied with their heat illness-related knowledge and skills, suggesting an area that could be improved for better emergency preparedness. Conclusion: Emergency departments appear to be well-prepared; however, this is subject to social desirability bias. The 9-item heatPEPS is a reliable and valid tool to measure emergency preparedness for heat illness.
Extreme heatwaves are among the most important climate-related disasters affecting public health. Assessing heatwave-related population exposures under different warming scenarios is critical for climate change adaptation. Here, the Coupled Model Intercomparison Project phase 6 (CMIP6) multi-model ensemble output results are applied over several warming periods in the Intergovernmental Panel on Climate Change AR6 report, to estimate China’s future heatwave population exposure under 1.5 degrees C and 2.0 degrees C warming scenarios. Our results show a significant increase in projected future annual heatwave days (HD) under both scenarios. With an additional temperature increase of 0.5 degrees C to 2.0 degrees C of warming, by mid-century an additional 20.15 percent increase in annual HD would occur, over 1.5 degrees C warming. If the climate warmed from 1.5 degrees C to 2.0 degrees C by mid-century, population exposure would increase by an additional 40.6 percent. Among the three influencing elements that cause the changes in population exposure related to heatwaves in China-climate, population, and interaction (e.g., as urbanization affects population redistribution)-climate plays the dominant role in different warming scenarios (relative contribution exceeds 70 percent). Therefore, considering the future heat risks, humanity benefits from a 0.5 degrees C reduction in warming, particularly in eastern China. This conclusion may provide helpful insights for developing mitigation strategies for climate change.
Heatwaves have afflicted human health, ecosystem, and socioeconomy and are expected to intensify under warming climate. However, few efforts have been directed to moist heat stress (MHS) considering relative humidity and wind speed, and moist heat stress risk (MHSR) considering exposure and vulnerability. Here we showed MHS and MHSR variations across China during 1998-2100 using China Meteorological Administration Land Data Assimilation System datasets, the 6th Coupled Model Intercomparison Project (CMIP6) merged datasets, Gross Domestic Product, population and leaf area index. We detected increased MHS across China under different Shared Socioeconomic Pathways (SSPs). Specifically, the historical MHS occurred mostly during mid-July to mid-August. We found increasing trends of 0.08%/year, 0.249%/year, and 0.669%/year in the MHS-affected areas under SSP126, SSP245, and SSP585, respectively. Furthermore, we observed the highest increasing rate of MHSR in Northwest and Southwest China, while the MHSR across Northeast and North China under SSP126 shifted from increasing to decreasing trends. Noteworthy is that the increasing trend of MHSR under SSP585 is 1.5-2.6 times larger than that under SSP245, especially in North and South China. This study highlights spatiotemporal evolutions of MHS and MHSR and mitigation to moisture heat stress in a warming climate.
Understanding the spatiotemporal trends of temperature in the context of global warming is significant for public health. Although many studies have examined changes in temperature and the impacts on human health over the past few decades in many regions, they have often been carried out in data-rich regions and have rarely considered acclimatization explicitly. The most frequent temperature (MFT) indicator provides us with the ability to solve this problem. MFT is defined as the longest period of temperature throughout the year to which a human is exposed and therefore acclimates. In this study, we propose a new method to estimate the number of heat exposure days from the perspective of temperature distribution and MFT, based on the daily mean temperature readings of 2142 weather stations in eight major climate zones in China over the past 20 years. This method can be used to calculate the number of heat exposure days in terms of heat-related mortality risk without the need for mortality data. We estimated the distribution and changes of annual mean temperature (AMT), minimum mortality temperature (MMT), and the number of heat exposure days in different climate zones in China. The AMT, MMT, and number of heat exposure days vary considerably across China. They all tend to decrease gradually from low to high latitudes. Heat exposure days are closely related to the risk of heat-related mortality. In addition, we utilized multiple linear regression (MLR) to analyze the association between the risk of heat-related mortality and the city and its climatic characteristics. Results showed that the number of heat exposure days, GDP per capita, urban population ratio, proportion of elderly population, and climate zone were found to modify the estimate on heat effect, with an R-2 of 0.71. These findings will be helpful for the creation of public policies protecting against high-temperature-induced mortalities.
Climate change leads to heat-related changes in labor productivity, which have additional economic impacts. Based on a framework that considers the impacts evolving from climate change to labor productivity to economic impact, we estimate the changes in labor productivity for indoor and outdoor activities and different work intensities at the grid level in China under a wide range of climatic and socioeconomic conditions and then evaluate the economic impacts in seven regions and eight sectors. The results show that (a) the negative impacts of labor productivity are concentrated in outdoor sectors, and the labor productivity of indoor sectors will decrease slightly or even increase due to high air-conditioning device penetration rates under relatively optimistic scenarios. (b) The national results show that total economic impacts increase by 0.28%-0.61% of the GDP for each 1 degrees C rise in the temperature, and the total economic impacts of labor productivity reductions in the most pessimistic scenario reach 1.15%-2.67% of the GDP in 2100. (c) The regional results indicate that the regions with lower labor productivity impacts (Northwest and Northeast China) still suffer large economic impacts, highlighting the importance of economic impact assessments across the regions. (b) The sectors in the seven regions of China that are most sensitive to climate change are agriculture and construction. The economic impacts in the manufacturing and service sectors, which contribute 22%-35% and 11%-15% of regional GDP losses, respectively, cannot be ignored, and should receive more attention in climate mitigation policies. Plain Language Summary Climate change will increase the heat stress in working environment, which limits the labor productivity of workers. Reductions in labor productivity will also lead to economic impacts. The consequences of this impact chain within China have been evaluated for the first time. Outdoor workers will be seriously affected by heat stress, while indoor workers’ productivity may benefit from the popularity of air-conditioning devices. However, all regions of China will face the negative economic impacts of increased heat stress under climate change. Even if the heat-related labor productivity of a region is not severely affected, the economic impacts cannot be ignored due to the economic links between regions and sectors. The agriculture and construction suffer from the most serious economic impact. Although labor productivity in the indoor sectors will benefit from the popularity of air-conditioning devices, the economic impact of the manufacturing and service sectors cannot be underestimated.
With the continued global warming, quantifying the risks of human and social-economic exposure to extremely high temperatures is very essential. The simulated extreme high-temperature days (EHTDs) with a maximum temperature higher than 35 degrees C (38 degrees C, 40 degrees C) in Southern China during 1980-1999 and 2080-2099 are analyzed using the NEX-GDDP dataset. By comparing the climatology of the two scenario periods, the multi-model ensemble mean patterns show that EHTDs will greatly increase at the end of the 21st century, and its center at 35 degrees C is projected to shift to Guangxi from Jiangxi. Model diversities are fairly small, and the spread increases with T-level rises. EOF analysis shows that the 100-years warming will impact the southern part greater than the northern part. Trend patterns exhibit comparable results to models, but with a relatively large spread. The population and economy exposure to extremely high temperatures are calculated, showing that they both will experience a large increase in future projected decades. In historical decades, the growth of population and Gross Domestic Product have dominated the increasing exposure risks, but these effects weaken with the T-level increases. In future decades, climate change plays a leading role in affecting the exposure, and its effect strengthens with the T-level increases. For historical to future changes, the dominant contributor to population exposure changes is the climate factor (74%), while substantially 90% contribution to economy exposure changes is dominated by the combined effects of climate and economy growth.
Exposure to extreme heat is a significant public health problem and the primary cause of weather-related mortality, which can be anticipated by accurately predicting outdoor thermal sensation. Empirical models have shown better accuracy in predicting thermal sensation than the most frequently used theoretical thermal indices, which have ignored adaptability to local climate and resulted in underestimating or overestimating the neutral levels of residents. This study proposes a scheme to build an empirical model by considering the multiple linear regression of thermal sensation and microclimatic parameters during summer in Chongqing, China. Thermal environment parameters (air temperature, relative humidity, wind speed, and surface temperature) were recorded and analyzed, together with 375 questionnaire survey responses referring to different underlying surfaces. The results found that the proposed model predicted neutral sensations as warm and 19.4% of warm sensations as hot, indicating that local residents adapted to warm or even hot sensations. In addition, the empirical model could provide references for local pedestrians’ daytime path choices. Residents might feel more comfortable staying beside a pond from 8:00 to 11:00 or sheltering under trees from 08:00 to 14:00 and 17:00 to 19:00. Masonry offered a comfortable microclimate between 10:15 and 11:00, and residents on the lawns were comfortable from 17:30 to 19:00. However, asphalt should be equipped with cooling infrastructures in order to cool thermal sensation.
Cardiovascular disease (CVD) is a leading threat to global public health. Although associations between temperature and CVD hospitalization have been suggested for developed countries, limited evidence is available for developing countries or rural residents. Moreover, the effect of apparent temperature (AT) on the spectrum of cause-specific CVDs remains unknown. Based on 2,024,147 CVD hospitalizations for rural residents from eight regions in Fujian Province, China, during 2010-2016, a quasi-Poisson regression with distributed lag non-linear model was fitted to estimate the AT effect on daily CVD hospitalization for each region, and then pooled in a meta-regression that included regional indicators related to rural residents. Stratified analyses were performed according to the cause of hospitalization, sex and age groups. Finally, we calculated the fraction of CVD hospitalizations attributable to AT, as a reflection of the burden associated with AT. The heat effect appeared at lag 0-1 days, with 19% (95% CI, 11-26%) increased risk of CVD hospitalization, which was worse for ischemic heart disease, heart failure, arrhythmias and ischemic stroke. The decreased AT was associated with increase of hemorrhagic stroke at lag 0-28 days. People aged 65 and above suffered more from the heat effect on cardiovascular and cerebrovascular diseases. Regions with a lower gross value of agricultural production, rural residents’ per capita net income, number of air conditioners and water heaters were more susceptible. A large number of hospitalizations were attributable to heat for most subcategories. High AT level increased CVD hospitalization, and the subcategories had different susceptibilities. The effects were modified by individual and regional characteristics. These findings have important implications for the development of targeted interventions and for hospital service planning.
The purpose of this work was to assess population vulnerability to heat-related health risks and its relationship with urbanization levels to provide essential information for the future development and policy-making for climate change adaptation. We constructed a heat vulnerability index (HVI), quantified the population heat vulnerability in each county across China by a principal component analysis (PCA) of multiple factors, and assessed urbanization levels in each county using multisource data. Then, the HVI was validated using the heat-attributable fraction (heat-AF) of nonaccidental mortality based on death monitoring data and meteorological data from 95 counties across China. The results showed that our HVI was significantly positively associated with the heat AF of nonaccidental mortality. A negative correlation was observed between the urbanization level and the HVI. The HVI was generally higher in less urbanized western China and lower in the more urbanized eastern regions. The baseline mortality occupies the top position in the importance ranking of the heat-vulnerability indicators at all three urbanization levels, but the other indicators, including the aging rate, agricultural population rate, education, ethnic structure, economic status, air conditioner ownership rate, and number of hospitals, ranked differently among different urbanization levels. This finding indicates that to reduce population heat vulnerability, the most important approach is to improve the health status of the whole population and reduce baseline mortality; additionally, regional-specific measures and emphasis should be adjusted reasonably along with the process of urbanization according to the characteristics and key factors of local heat vulnerability.
Global warming, high temperatures, and heatwave weather are some of the factors affecting human settlement environment health. In high-temperature weather, human production and life are seriously threatened, as long-term exposure to high temperatures causes a variety of diseases, and children and elderly, who have poor tolerance, require strengthened protection. From a human perspective, this study calculated the thermal duration distribution of high temperatures based on maximum temperature data in a central urban area of Beijing combined with the results of the sixth population census of Beijing, investigated the population distribution of individuals under 15 years old and over 65 years old, and analyzed the spatial distribution of a thermal exposure space in a central urban area of Beijing with the help of the ArcGIS platform. Based on 130 district districts, streets with high-risk heat exposure spaces in the central urban area of Beijing were reddened to determine the distribution of high-risk grades. Using the semantic segmentation method and a street view map, the high-risk thermal exposure space environment from the humanistic perspective was restored, and the typical characteristics were summarized and analyzed. Finally, the environmental characteristics of the high-risk thermal exposure space were analyzed from the humanistic perspective, and an improvement strategy for thermal exposure spaces was proposed based on the perspective of emotional relief.
The surface urban heat island (SUHI) effect poses a significant threat to the urban environment and public health. This paper utilized the Local Climate Zone (LCZ) classification and land surface temperature (LST) data to analyze the seasonal dynamics of SUHI in Wuhan based on the Google Earth Engine platform. In addition, the SUHI intensity derived from the traditional urban-rural dichotomy was also calculated for comparison. Seasonal SUHI analysis showed that (1) both LCZ classification and the urban-rural dichotomy confirmed that Wuhan’s SHUI effect was the strongest in summer, followed by spring, autumn and winter; (2) the maximum SUHI intensity derived from LCZ classification reached 6.53 °C, which indicated that the SUHI effect was very significant in Wuhan; (3) LCZ 8 (i.e., large low-rise) had the maximum LST value and LCZ G (i.e., water) had the minimum LST value in all seasons; (4) the LST values of compact high-rise/midrise/low-rise (i.e., LCZ 1-3) were higher than those of open high-rise/midrise/low-rise (i.e., LCZ 4-6) in all seasons, which indicated that building density had a positive correlation with LST; (5) the LST values of dense trees (i.e., LCZ A) were less than those of scattered trees (i.e., LCZ B) in all seasons, which indicated that vegetation density had a negative correlation with LST. This paper provides some useful information for urban planning and contributes to the healthy and sustainable development of Wuhan.
BACKGROUND: Although the existing studies have suggested a significant association between high temperatures and urolithiasis, no nationwide studies have quantified the burden attributable to environmental heat stress and explored how the urolithiasis burden would vary in a warming climate. METHODS: We collected data on urolithiasis attacks from 137 hospitals in 59 main cities from 20 provincial regions of China from 2000 to 2020. An individual-level case-crossover analysis was conducted to estimate the effect of daily wet-bulb globe temperature (WBGT), a heat stress index combining temperature and humidity, on urolithiasis attacks. Stratified analyses were performed by region, age, and sex. We further quantified the future WBGT-related burden of urolithiasis from the Coupled Model Intercomparison Project Phase 6 under three Shared Socioeconomic Pathway (SSP) scenarios. RESULTS: In total, 118,180 urolithiasis patients were evaluated. The exposure-response curve for the association between WBGT and urolithiasis attacks was J-shaped, with a significantly increased risk for WBGT higher than 14.8 °C. The middle-aged and elderly group (≥45 years old) had a higher risk of WBGT-related urolithiasis attacks than in the younger group, while no significant sex difference was observed. The attributable fraction (AF) due to high WBGT would increase from 10.1% in the 2010s to 16.1% in the 2090s under the SSP585 scenario. Warm regions were projected to experience disproportionately higher AFs and larger increments in the future. CONCLUSIONS: This nationwide investigation provides novel evidence on the acute effect of high WBGT on urolithiasis attacks and demonstrates the increasing disease burden in a warming climate.
The peak summer (July-August; JA) muggy hot weather over Northeast China (NEC) negatively impacts local socioeconomic development and human health. This study investigates the physical connection between sea surface temperature (SST) and year-to-year variations in the number of peak summer muggy hot days (MHDs) in NEC (PSMHDNEC) for the period 1979-2018. We found that on the interannual timescale, SST anomalies (SSTAs) over the tropical North Australia (TNA) sector have a stable and significant negative correlation with PSMHDNEC since the early summer of June; however, the strongest negative correlation occurs in the JA. Our further analyses indicate that the SST cooling over the TNA sector could form a large-scale atmospheric teleconnection emanating northwest of the TNA through the profound in situ diabatic cooling anomalies tied to the SST cooling, which propagates poleward from the northeastern Pacific Ocean. This teleconnection might remotely strengthen the local-scale anticyclonic anomaly centered near NEC, a critical system responsible for a higher PSMHDNEC. Under such circumstances, the NEC region is dominated by high-pressure anomalies, facilitating the establishment of localized MHD-favorable environmental conditions (e.g., increased surface air temperature and enhanced downward solar radiation flux with suppressed convection activities). During years of negative SSTAs over TNA, local SSTAs can persist from early summer until JA via the wind-evaporation-SST feedback. Therefore, it appears that SSTAs over the TNA sector may be a significant remote tropical forcing factor for the interannual variability of PSMHDNEC, and the corresponding June SST cooling may act as a potential predictability source physically contributing to a higher PSMHDNEC.
During the COVID-19 pandemic, wearing protective facemasks (PFMs) can effectively reduce infection risk, but the use of PFMs can amplify heat-related health risks. We studied the amplified PFM-induced human thermal stress via both field measurements and model simulations over a typical subtropical mountainous city, Hong Kong. First, a hot and humid PFM microenvironment has been observed with high temperature (34-35 °C) and high humidity (80-95%), resulting in an aggravated facial thermal stress with a maximal PFM-covered facial heat flux of 500 W/m(2) under high-intensity activities. Second, to predict the overall PFM-inclusive human thermal stress, we developed a new facial thermal load model, S (PFM) and a new human-environment adaptive thermal stress (HEATS) model by coupling S (PFM) with an enhanced thermal comfort model to resolve modified human-environment interactions with the intervention of PFM under realistic climatic and topographical conditions. The model was then applied to predict spatiotemporal variations of PFM-inclusive physiological subjective temperature (PST) and corresponding heat stress levels during a typical heat wave event. It was found wearing PFM can significantly aggravate human thermal stress over Hong Kong with a spatially averaged PST increment of 5.0 °C and an additional spatial area of 158.4% exposed to the severest heat risks. Besides, PFM-inclusive PST was found to increase nonlinearly with terrain slopes at a rate of 1.3-3.9 °C/10°(slope), owing to elevated metabolic heat production. Furthermore, urban residents were found to have higher PFM-aggravated heat risks than rural residents, especially at night due to synergistic urban heat and moisture island effects.
Extreme heat events are gaining ever more policy and societal attention under a warming climate. Although a breadth of expertises are required to understand drivers of vulnerability to hazards such as extreme heat, it is also acknowledged that expert assessments in group settings may be subject to biases and uneven power relations. In this Technical Note, we outline a structured deliberative process for supporting experts to work collaboratively to assess social vulnerability to a climate-related hazard, in this case extreme heat in Taiwanese cities. We argue that adapting elicitation approaches such as Q-Methodology for use in collaborative settings can help to organise expert discussion and enable dialogue and mutual learning, in a way that supports consensus-building on vulnerability assessment. Outcomes from our collaborative assessments suggest elderly people living alone, elderly people over 75, pre-existing circulatory diseases and level of participation in community decision-making may all be notable drivers of heat vulnerability in the Taiwanese context. Methodologically, we argue that collaborative sorting exercises offer a way to embed local and experiential knowledges into assessments of available evidence, but that strong facilitation and additional checks are necessary to ensure an inclusive process that reflects the diversity of perspectives involved. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11069-022-05280-4.
BACKGROUND: Despite emerging recognition of the benefits of green and blue spaces on human health, evidence for their effect modifications on heat-mortality associations is limited. We aimed to investigate the effect modifications of green and blue spaces on heat-mortality associations among different age and sex groups and at different heat levels. METHODS: Daily mortality and meteorological data from 2008 to 2017 in Hong Kong, China were collected. The Normalized Difference Vegetation Index and distance to coast were used as proxies for green and blue space exposure, respectively. Time-series analyses was performed using fitting generalized linear mixed models with an interaction term between heat and levels of exposure to either green or blue space. Age-, sex-, and heat level-stratified analyses were also conducted. RESULTS: With a 1 °C increase in temperature above the 90th percentile (29.61 °C), mortality increased by 5.7% (95% confidence interval [CI]: 1.6, 10.1%), 5.4% (1.4, 9.5%), and 4.6% (0.8, 8.9%) for low, medium and high levels of green space exposure, respectively, and by 7.5% (3.9, 11.2%) and 3.5% (0.3, 6.8%) for low and high levels of blue space exposure, respectively. Significant effect modifications of green and blue spaces were not observed for the whole population or any specific age and sex group, either at a moderate heat level or a heat level (Ps > 0.05). CONCLUSIONS: No significant effect modifications of green and blue spaces on heat-related mortality risk were observed in Hong Kong. These findings challenge the existing evidence on the prominent protective role of green and blue spaces in mitigating heat-related mortality risks.
Due to climate change, the heatwave has become a more serious public health threat with aging as an aggravating factor in recent years. There is a pressing need to detect the most effective prevention and response measures. However, the specific health effects of interventions have not been characterized on an individual scale. In this study, an intervention experiment was designed to explore the health effects of heat exposure at the individual level and assess the effects of different interventions based on a comprehensive health sensitivity index (CHSI) in Xinyi, China. Forty-one subjects were recruited randomly, and divided into one control group and three intervention groups. Interventions included education (Educate by lecturing, offering relative materials, and communication), subsidy support (offer subsidy to offset the cost of running air conditioning), and cooling-spray (install a piece of cooling-spray equipment in the yard). Results showed that systolic blood pressure (SBP) and deep sleep duration (DSD) were significantly affected by short-term heat exposure, and the effects could be alleviated by three types of interventions. The estimated CHSI indicated that the effective days of the education group were longer than other groups, while the lower CHSI of the subsidy group showed lower sensitivity than the control group. These findings provide feasible implementation strategies to optimize Heat-health action plans and evaluate the intervention performance. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary material is available in the online version of this article at 10.1007/s11783-022-1545-4 and is accessible for authorized users.
Few studies have examined individual socioeconomic status (SES) as a potential modifier of ambient temperature-health associations, especially for temperature-related hospitalizations. We fit penalized distributed lag non-linear models within generalized additive models to study the short-term associations (0-3 days) between temperature and hospital admissions stratified by common causes, age, and individual SES, as determined by whether patients received public assistance (PA) to cover their medical fee at the time of hospitalizations, during the hot season (May 15 to October 15) in Hong Kong for the years 2010-2019. We calculated the ratio of relative risk (RRR) and corresponding 95% confidence interval (CI) to statistically test the difference of the associations between PA groups. For 75 + patients, the PA group had significantly increased risks of hospitalizations at higher temperature for most causes, with relative risks (RR, 99th %ile vs. 25%ile) and 95% CIs of 1.138 (1.099, 1.179), 1.057 (1.008, 1.109), and 1.163 (1.094, 1.236) estimated for all non-cancer non-external, circulatory, and respiratory admissions, respectively. There were slight decreases of RRs with higher temperature for 75 + patients without PA. The strengths of temperature-hospitalization associations were strongly and significantly different between PA groups for all examined causes for 75 + patients, with the most considerable discrepancy found for ischemic heart disease (RRR = 1.266; 95% CI, 1.137, 1.410). Hospitalizations for patients aged 15-74 were less affected by heat, and the difference of the associations between groups was small. Individual SES is a significant modifier of high temperature-hospitalization associations in Hong Kong among the elderly. Public health interventions are needed to better protect this subpopulation from adverse health impacts of high temperature.
Anthropogenic modification of the natural environment has caused significant impacts on the local atmosphere and far-reaching changes to the global climate. Taking Hong Kong as a case study, high-resolution (250 m) mesoscale simulations are conducted using Meso-NH coupled with the multi-layer Town Energy Balance to investigate the effects of past (early 1960s), present (2018), and future (late 2040s) urban developments on the city’s surface energy balance, heat island, boundary layer structure, and heat stress during a prolonged heatwave event. Overall, horizontal and vertical urban expansion has caused the urban areas to become warmer, drier, less ventilated, and more susceptible to hot nights. The dense built-up urban core in the Kowloon peninsula is also found to deepen the urban boundary layer and enhance the coastal urban heat island circulation. Reclaimed land exhibits the largest differences in 2-m air temperature relative to a no urban scenario due to the drastic change in surface thermal properties. Areas downwind of the planned artificial islands in East Lantau are expected to experience warmer and calmer conditions due to the altered wind field. Study findings raise awareness regarding the increasingly long durations of strong heat stress in urban areas and the need for heat stress mitigation.
Thermal comfort analogs can be used to quantify the similarity of thermal comfort between current and future climates and are critical for raising awareness of future climate change. However, the similarity of thermal comfort analogs in consecutive future periods and under different emission scenarios remains unclear. This knowledge gap has significantly limited our understanding of future climate change and its effects on the living environment, especially from a human perception perspective. In this study, we identified the universal thermal climate index (UTCI) analogs of 352 cities in China under four specific emission scenarios for future periods (2021-2080). The results show that the UTCI analogs show significant spatial differentiation between cities. The analogs of northern cities primarily shift to cities with a neighboring latitude (-5 degrees to 5 degrees), whereas most central and southern cities mainly shift their analogs to lower-latitude cities. The shift to lower-latitude cities with latitude differences exceeding 5 degrees is enhanced with time and increased anthropogenic emissions. In addition, compared with the temperature analogs, the shift of UTCI analogs is more intense and the shift direction is more complex. The results of this study provide insights into future climate change and heat-related health risks.
With the increases in hot weather frequency and intensity induced by observed and predicted climate change, heat exposure is an evolving challenge. We estimated a fixed effect econometric model to data on 5,404 individuals drawn from the China Health and Retirement Longitudinal Study database. These observations were used to examine the effect of heat stress on cognitive performance for those above 40 years of age who are often household decision-makers. We found today’s heat stress decreases performance on verbal and math test scores, and that cumulative heat exposure over the last 3 days adversely affects verbal test scores. We also found that middle-aged women and people in rural areas exhibit substantial heat stress-induced reductions on cognitive test scores. This finding implies that continuing climate change may well diminish decision-making capacity and effectiveness.
Extreme thermal environment harms the health of outdoor workers and poses a potential threat to workplace safety. A field survey, including thermal parameter measurements, was conducted at construction sites in South China during the summer of 2019. The relationship between health risk and thermal parameters was obtained. The thermal sensation and satisfaction rate of the workers at different outdoor environmental conditions were analyzed, and recommendations were made based on the comparison of thermal indices. The thermal stress categories of the thermal indices were also investigated. The results suggest that the intensity of working conditions should be reduced when the air temperature is higher than 34 degrees C; the satisfaction rate of workers was found to be relatively high when the outdoor temperature is lower than 34 degrees C and the wind speed is greater than 1.3 m/s. Thermal indicators used to evaluate the comfort level of outdoor workers need to be modified according to the local climate and working environment to avoid excessive exposure to high-temperature work environments.
Long-lasting heatwaves have seriously threatened human health. Exploring the distribution of heat vulnerability is important for urban risk management. A model of heat vulnerability coupled with physical and social conditions based on exposure, sensitivity, and adaptation was established in Chongqing, a mountainous megacity in China, and 11 indicators were adopted to assess heat vulnerability. Heat perception evaluated by social media data is used to validate heat vulnerability. Four primary outcomes emerged. First, integration of high physical and low social heat vulnerabilities was found in central areas, while low physical and high social heat vulnerabilities were concentrated in suburban areas. Second, the spatial distribution of heat vulnerability is consistent with that of heat perception. Third, high social exposure, high physical and social sensitivity, and low physical adaptation led to high heat vulnerability in central areas, while high heat vulnerability in suburban areas was primarily caused by high physical exposure and low social adaptation. Finally, due to the barriers of mountains and rivers, both physical and social heat vulnerabilities form unique decentralized patterns following urbanization. According to the finding of heat vulnerability, mitigative and adaptive strategies (e.g. hierarchical layouts, green measures, and vulnerable health databases) are proposed to improve climate resilience.
This study investigates public participation in heat impact reduction by analysing adaptive behaviours, familiarity with urban heat island (UHI) and cooling strategies, the perceived urgency of heat impact actions and citizen’s willingness to pay through a questionnaire survey in Chongqing, China. The results indicate that airconditioning systems are the dominant cooling facility in both work and living environments. Respondents had a moderately familiar understanding of several cooling strategies such as urban vegetation, shading devices, water-based artificial facilities, urban design for shading and ventilation and water bodies. Familiarity with innovative materials and techniques for pavements, roofs and facades was less than moderate. Urban planning and design for heat resilient cities was thought to be the most urgent intervention, followed by the establishment of temporary cooling facilities. Most respondents indicated that cost-sharing mechanisms for urban heat prevention and control systems should at least include the government, whilst 50% of the respondents preferred collaborative payment among government, developers, and owners. Only 41.6% of the interviewees expressed their willingness to pay, with a share varying between 20 and 80 RMB. A conservative estimate indicated that there could be an average payment of 45.95 RMB and 19.10 RMB among the 234 respondents who were willing to pay and all 562 respondents regardless of willingness, respectively. Respondents’ heat-related responses and actions towards urban heat challenges were dependent on a wide range of factors like gender, age, education, economic status, health, exposure, habit formation and behavior change, social acceptance, etc. Moreover, such factors could interact with each other affecting public behavior with different weights. Overall, this study increases our understanding of people’s perceptions and proactiveness in reducing urban heat and provides guidance for decision-makers towards a novel user-aware approach to the implementation of urban heat prevention, adaptation, and mitigation strategies.
High temperatures pose great threats to the health of urban populations. The use of air conditioners (AC) is an important adaptive means to reduce the morbidity and mortality of heat-related diseases. However, it remains unclear how exposure and sensitivity factors affect residents’ AC use. This study aimed to answer this question through a case study in 78 residential areas in Beijing, China. We conducted over 7,000 structured interviews during June 20-August 5, 2017 to learn respondents’ AC use, health conditions and socioeconomic status. We also used remote sensing data to obtain land surface temperature (LST) and proportion of greenspace in residential areas. We applied a multilevel logistic regression to assess the influences of these factors on probability of frequent AC use. The results showed mixed impacts from sensitivity factors on AC use. While respondents with chronic diseases were 14.7% more likely to use AC every day, probability of AC use decreased by 29.2% with the increase of age groups. Instead of economic cost, the main reason preventing respondents from using AC was “feeling uncomfortable” or consider it as “unhealthy”. At the scale of residential area, results did not find significant impact of LST on AC use, while proportion of greenspace posed a negative impact on probability of using AC every day even when LST was considered.
More than half of the total population in China are living in cities. Especially, the people in highly developed and spatially integrated city clusters, i.e., urban agglomerations (UAs), are facing increasing human-perceived heat stress that describes the combined effects of hot temperature, high humidity, and lowered surface wind speed. By analyzing multiple indicators over 20 major UAs across China, we demonstrate that summer heat stress has been significantly intensifying in nearly all UAs during 1971–2014. This intensification is more profound in northern than southern regions and is especially stronger in more urbanized and densely populated areas (e.g., Beijing-Tianjin-Hebei and the Yangtze River Delta). Based on a dynamic classification of weather stations using time-varying land use/land cover maps, we find that urban core areas exhibit distinctly stronger increasing heat stress trends than their surrounding rural areas. On average, urbanization contributes to approximately one-quarter of the total increase in mean heat stress over urban core areas of UAs and nearly half of the total increase in extreme heat stress events. The urbanization effect is also dependent on the geographical region within China. Urbanization tends to have stronger intensifying effects on heat stress in UAs with higher population density in low-altitude areas, while it has a relatively weaker intensifying and even weakening effect in some arid and high-altitude regions. Moreover, as various heat stress metrics may yield different estimations of long-term trend and urbanization contribution, the particular choice of heat stress indicator is of critical importance for investigations on this subject matter.
Due to the progress in global warming, the frequency, duration and intensity of climate extremes are increasing. As one of these extremes, heat waves influence the well-being of human beings and increase societies’ energy consumption. The Water-Cooling Island (WCI) effect of urban water bodies (UWBs) is important in urban heat wave mitigation. In this paper, the impact of WCI, especially the landscape pattern of the surrounding area, was explored. The results indicate that water bodies with a larger total area and simpler shape have a longer cooling effect. In the areas surrounding UWBs, a lower percentage or discrete distribution of impervious surfaces or green land provide a longer cooling effect. The amplitude of WCI is mainly decided by the impervious surface in the surrounding areas. A lower percentage or discrete distribution of impervious surfaces or green land leads to a smaller-amplitude WCI. The gradient is impacted by the shape of the UWB and surrounding green land. A complex shape and discrete distribution of green land lead to a higher gradient of WCI. The linear regress model was significant in terms of WCI range and gradient, while the model of WCI amplitude was not significant. This indicates that WCI is directly decided by impact factors through gradient and range. The conclusions provide a methodology for WCI prediction and optimization, which is important when mitigating summer heat waves.
Urban heatwaves increase residential health risks. Identifying urban residential sensitivity to heatwave risks is an important prerequisite for mitigating the risks through urban planning practices. This research proposes a new paradigm for urban residential sensitivity to heatwave risks based on social media Big Data, and describes empirical research in five megacities in China, namely, Beijing, Nanjing, Wuhan, Xi’an and Guangzhou, which explores the application of this paradigm to real-world environments. Specifically, a method to identify urban residential sensitive to heatwave risks was developed by using natural language processing (NLP) technology. Then, based on remote sensing images and Weibo data, from the perspective of the relationship between people (group perception) and the ground (meteorological temperature), the relationship between high temperature and crowd sensitivity in geographic space was studied. Spatial patterns of the residential sensitivity to heatwaves over the study area were characterized at fine scales, using the information extracted from remote sensing information, spatial analysis, and time series analysis. The results showed that the observed residential sensitivity to urban heatwave events (HWEs), extracted from Weibo data (Chinese Twitter), best matched the temporal trends of HWEs in geographic space. At the same time, the spatial distribution of observed residential sensitivity to HWEs in the cities had similar characteristics, with low sensitivity in the urban center but higher sensitivity in the countryside. This research illustrates the benefits of applying multi-source Big Data and intelligent analysis technologies to the understand of impacts of heatwave events on residential life, and provide decision-making data for urban planning and management.
High-density cities are faced with growing extreme hot weather driven by climate change and local urbanization, but localized heat risk detection is still at an early stage for most cities (Watts et al., 2019). This study developed a spatiotemporal hazard-exposure-vulnerability assessment of the extreme heat risk in Hong Kong for 2006, 2011, and 2016 integrating cumulative very hot day hours and hot night hours in summer, population density and a principal component analysis (PCA) of demo-socioeconomic characteristics. The risk was found spatially variant, and high-risk spots were identified at the community scale for both daytime and nighttime with underlying determinants behind. In both the daytime and the nighttime, high risk mainly occurred in the core urban areas. Nearly 10 more hot-spots were found in the nighttime than those in the daytime. Several old communities in Kowloon stayed at high risk from 2006 to 2016. Some new towns in the New Territories turned to be at higher risk in 2016 compared to 2006 and 2011, and this result showed signs to be emerging hot-spots in the near future. This study would be a useful reference for community-scale heat risk assessment and mitigation for the development of healthy and sustainable high-density cities.
Large-scale modifications to urban underlying surfaces owing to rapid urbanization have led to stronger urban heat island (UHI) effects and more frequent urban heat wave (HW) events. Based on observations of automatic weather stations in Beijing during the summers of 2014–2020, we studied the interaction between HW events and the UHI effect. Results showed that the UHI intensity (UHII) was significantly aggravated (by 0.55°C) during HW periods compared to non-heat wave (NHW) periods. Considering the strong impact of unfavorable weather conditions and altered land use on the urban thermal environment, we evaluated the modulation of HW events and the UHI effect by wind speed and local climatic zones (LCZs). Wind speeds in urban areas were weakened due to the obstruction of dense high-rise buildings, which favored the occurrence of HW events. In detail, 35 HW events occurred over the LCZ1 of a dense high-rise building area under low wind speed conditions, which was much higher than that in other LCZ types and under high wind speed conditions (< 30 HW events). The latent heat flux in rural areas has increased more due to the presence of sufficient water availability and more vegetation, while the increase in heat flux in urban areas is mainly in the form of sensible heat flux, resulting in stronger UHI effect during HW periods. Compared to NHW periods, lower boundary layer and wind speed in the HW events weakened the convective mixing of air, further expanding the temperature gap between urban and rural areas. Note that LCZP type with its high-density vegetation and water bodies in the urban park area generally exhibited, was found to have a mitigating effect on the UHI, whilst at the same time increasing the frequency and duration of HW events during HW periods. Synergies between HWs and the UHI amplify both the spatial and temporal coverage of high-temperature events, which in turn exposes urban residents to additional heat stress and seriously threatens their health. The findings have important implications for HWs and UHII forecasts, as well as for scientific guidance on decision-making to improve the thermal environment and to adjust the energy structure.
Nighttime heat waves have greater impacts on human society than daytime because nighttime heat waves deprive humans to recover from daytime heat and increase energy consumption for cooling. In this study, we found increased occurrence and severity of nighttime heat waves across China during 1980-2017 based on measurements from more than 2,000 meteorological stations. The nighttime heat waves have been longer lasting and occurred more often in spring and fall. Compared to rural areas, urban areas have shown enhanced frequency, intensity, and duration of nighttime heat waves. Urbanization accounted for nearly 50% of the extended duration and nearly 40% of the enhanced intensity and frequency of nighttime heat waves in urban areas relative to rural areas. Urban expansion, causing reduced evapotranspiration and weakened wind speed that normally cools the lower atmosphere by turbulent heat loss and cooled air advection, led to nighttime urban heat island, thus magnifying nighttime heat extremes. Plain Language Summary Extreme temperature events will likely increase and cause severe damage to human society and natural ecosystem under climate change and urbanization. Compared to daytime, nighttime heat waves reduce people’s ability to cool off and prevent the human body recovering from daytime heat exposure, and therefore increase the risks of heat illnesses and deaths. Here, we show that nighttime heat waves have been more frequent, longer lasting, and severer, and occurred increasingly in spring and fall in China. These changes have been more intensive in urban areas than their surrounding rural areas. Urbanization accounted for nearly 50% of the extended duration, and nearly 40% of the enhanced intensity and frequency of nighttime heat waves in urban areas relative to rural areas. Nighttime urban heat island due to rapid urban expansion magnified nighttime heat extremes.
Global climate change results in an increased risk of high urban temperatures, making it crucial to conduct a comprehensive assessment of the high-temperature risk of urban areas. Based on the data of 194 meteorological stations in China from 1986 to 2015 and statistical yearbooks and statistical bulletins from 2015, we used GIS technology and mathematical statistics to evaluate high-temperature spatial and temporal characteristics, high-temperature risk, and high-temperature vulnerability of 31 cities across China. Over the past 30 years, most Chinese cities experienced 5-8 significant oscillation cycles of high-temperature days. A 15-year interval analysis of high-temperature characteristics found that 87% of the cities had an average of 5.44 more high-temperature days in the 15-year period from 2001 to 2015 compared to the period from 1986 to 2000. We developed five high-temperature risk levels and six vulnerability levels. Against the background of a warming climate, we discuss risk mitigation strategies and the importance of early warning systems.
In the context of climate change, the outdoor thermal environment is essential for urban health, particularly in hot and humid climate zones. In most cities in southern China, traditional shophouse neighbourhoods are regarded as a reference for climate-responsive urban morphology because multiple shading strategies are integrated, including deep canyons, semi-open arcades, and vegetation. In total, four shading strategies, namely, the height-to-width ratio of canyons and arcades, tree coverage area, and orientation, are employed in this study to compare their cooling efficiency in street canyons during summer daytime. The ENVI-met is employed for the microclimatic simulations and validated by site measurement data. The impact of varying sky view factor on the physiologically equivalent temperature was quantified to assess the cooling efficiency of each shading strategy. Our results demonstrate that the cooling efficiency of orientations varies significantly with sky view factor and is negatively associated with pedestrian thermal comfort in alleys, but positive in street canyons with arcades and trees. Varying the height-to-width ratio of canyons in arcade streets presents the best cooling efficiency, except in the east-west orientation. Shading by arcades shows a slightly higher cooling efficiency than tree coverage.
OBJECTIVES: Heat injuries have become a considerable health risk for sport and exercise participants in Australia. This study seeks to update the Australian sports case numbers by considering data from hospital admission and emergency department (ED) presentations (collectively referred to as total hospitalisations). Specifically, this study aimed to report epidemiological features (incidence and case characteristics) for sport related heat injury (SRHI) cases treated in hospital, over an 11-year period in Victoria, Australia. DESIGN: Analysis of administrative health data. METHODS: Data were extracted from the Victorian Injury Surveillance Unit for hospital admissions and ED presentations separately using diagnosis and activity codes (focused on subgroups of T67 – effects of heat and light and U5000-U7100). Descriptive data were reported by age, sex, financial year and activity, and population trends reported for SRHI incidence rate. RESULTS: A total of 323 SRHI cases (ED=142, 44%; admissions=181, 56%) were identified, representing 10.2% of all heat injury cases (non-sport cases=2834). The highest number of SRHI cases were in golf (n=43, 13.3%) and lawn bowls (n=38, 11.8%). The age groups >65 and 15-34years reported a total of 114 cases (35.3%) and 106 cases (32.8%), respectively. CONCLUSIONS: Findings were consistent with previous Australian studies with SRHI comprising 10% of all heat injury cases. Strategies for SRHI awareness can be aimed at the age and sport groups with greater representation in the cases identified. We had expected several-times more ED presentations than admissions, suggesting fewer of the mild-moderate cases of SRHI attend for emergency care and that alternative data are needed to capture these.
Extreme high-temperature events pose a threat to human beings on Earth. In coastal cities, the sea breeze is widely known as a prevailing wind that can cool the near-surface air. However, the cumulative cooling effect and its attenuation process during the sea breeze penetration have not been well investigated. In this study, we analyze sea breeze cooling capacity (SBCC) and propose a new method in estimating the penetration distance of sea breeze cooling in metropolitan Adelaide during summer using data from the Adelaide urban heat island monitoring network. The results show that during a sea breeze day, wind direction rapidly changes from southeast to southwest in the morning, and it gradually returns to southeast in the afternoon. It takes 67 min on average for the sea breeze cooling fronts to penetrate inside metropolitan Adelaide. The SBCC value is 21.3 degrees C h per event averaged spatially in Adelaide summer. During the penetration process, the SBCC values decrease at a rate of 0.7 and 0.9 degrees C h per kilometer from coast to inland on an average sea breeze day and a hot sea breeze day, respectively. Correspondingly, the mean cooling penetration distances are 42 and 29 km along the prevailing wind path. A multiple linear regression analysis indicates that the distance from the coast and elevation at the onshore point together explain 88% of the spatial variability of the temporally average SBCC in the study area. The spatial pattern and penetration distance of the cumulative sea breeze cooling effect contribute to a better understanding of this common cooling source for heat mitigation in coastal cities where a large number of people reside.
The warming trend over recent decades has already contributed to the increased prevalence of heat-vulnerable chronic diseases in many regions of the world. However, understanding the relationship between heat-vulnerable chronic diseases and heatwaves remains incomplete due to the complexity of such a relationship mingling with human society, urban and natural environments. Our study extends the Social Ecological Theory by constructing a tri-environmental conceptual framework (i.e., across social, built, and natural environments) and contributes to the first nationwide study of the relationship between heat-vulnerable chronic diseases and heatwaves in Australia. We utilize the random forest regression model to explore the importance of heatwaves and 48 tri-environmental variables that contribute to the prevalence of six types of heat-vulnerable diseases. We further apply the local interpretable model-agnostic explanations and the accumulated local effects analysis to interpret how the heat-disease nexus is mediated through tri-environments and varied across urban and rural space. The overall effect of heatwaves on diseases varies across disease types and geographical contexts (latitudes; inland versus coast). The local heat-disease nexus follows a J-shape function-becoming sharply positive after a certain threshold of heatwaves-reflecting that people with the onset of different diseases have various sensitivity and tolerance to heatwaves. However, such effects are relatively marginal compared to tri-environmental variables. We propose a number of policy implications on reducing urban-rural disparity in Healthcare and service distribution, delineating areas, and identifying the variations of sensitivity to heatwaves across urban/rural space and disease types. Our conceptual framework can be further applied to examine the relationship between other environmental problems and health outcomes.
BACKGROUND: Exposure to high ambient temperatures has been shown to increase the risk of spontaneous preterm birth. Determining which maternal factors increase or decrease this risk will inform climate adaptation strategies. OBJECTIVES: This study aims to assess the risk of spontaneous preterm birth associated with exposure to ambient temperature and differences in this relationship between mothers with different health and demographic characteristics. METHODS: We used quasi-Poisson distributed lag non-linear models to estimate the effect of high temperature-measured as the 95th percentile of daily minimum, mean and maximum compared with the median-on risk of spontaneous preterm birth (23-36 weeks of gestation) in pregnant women in New South Wales, Australia. We estimated the cumulative lagged effects of daily temperature and analyses on population subgroups to assess increased or decreased vulnerability to this effect. RESULTS: Pregnant women (n = 916,678) exposed at the 95th percentile of daily mean temperatures (25°C) had an increased risk of preterm birth (relative risk 1.14, 95% confidence interval 1.07, 1.21) compared with the median daily mean temperature (17°C). Similar effect sizes were seen for the 95th percentile of minimum and maximum daily temperatures compared with the median. This risk was slightly higher among women with diabetes, hypertension, chronic illness and women who smoked during pregnancy. CONCLUSIONS: Higher temperatures increase the risk of preterm birth and women with pre-existing health conditions and who smoke during pregnancy are potentially more vulnerable to these effects.
BACKGROUND: Heat exposure is a risk factor for urologic diseases. However, there are limited existing studies that have examined the relationship between high temperatures and urologic disease. The aim of this study was to examine the associations between heat exposure and hospitalizations for urologic diseases in Queensland, Australia, during the hot seasons of 1995-2016 and to quantify the attributable risks. METHODS: We obtained 238 427 hospitalized cases with urologic diseases from Queensland Health between 1 December 1995 and 31 December 2016. Meteorological data were collected from the Scientific Information for Land Owners-a publicly accessible database of Australian climate data that provides daily data sets for a range of climate variables. A time-stratified, case-crossover design fitted with the conditional quasi-Poisson regression model was used to estimate the associations between temperature and hospitalizations for urologic diseases at the postcode level during each hot season (December-March). Attributable rates of hospitalizations for urologic disease due to heat exposure were calculated. Stratified analyses were performed by age, sex, climate zone, socio-economic factors and cause-specific urologic diseases. RESULTS: We found that a 1°C increase in temperature was associated with a 3.3% [95% confidence interval (CI): 2.9%, 3.7%] increase in hospitalization for the selected urologic diseases during the hot season. Hospitalizations for renal failure showed the strongest increase 5.88% (95% CI: 5.25%, 6.51%) among the specific causes of hospital admissions considered. Males and the elderly (≥60 years old) showed stronger associations with heat exposure than females and younger groups. The sex- and age-specific associations with heat exposure were similar across specific causes of urologic diseases. Overall, nearly one-fifth of hospitalizations for urologic diseases were attributable to heat exposure in Queensland. CONCLUSIONS: Heat exposure is associated with increased hospitalizations for urologic disease in Queensland during the hot season. This finding reinforces the pressing need for dedicated public health-promotion campaigns that target susceptible populations, especially for those more predisposed to renal failure. Given that short-term climate projections identify an increase in the frequency, duration and intensity of heatwaves, this public health advisory will be of increasing urgency in coming years.
Heatwaves are associated with increased mortality and are exacerbated by the urban heat island (UHI) effect. Thus, to inform climate change mitigation and adaptation, we quantified the mortality burden of historical heatwave days in Sydney, Australia, assessed the contribution of the UHI effect and used climate change projection data to estimate future health impacts. We also assessed the potential for tree cover to mitigate against the UHI effect. Mortality (2006-2018) records were linked with census population data, weather observations (1997-2016) and climate change projections to 2100. Heatwave-attributable excess deaths were calculated based on risk estimates from a published heatwave study of Sydney. High resolution satellite observations of UHI air temperature excesses and green cover were used to determine associated effects on heat-related mortality. These data show that >90% of heatwave days would not breach heatwave thresholds in Sydney if there were no UHI effect and that numbers of heatwave days could increase fourfold under the most extreme climate change scenario. We found that tree canopy reduces urban heat, and that widespread tree planting could offset the increases in heat-attributable deaths as climate warming progresses.
Heatwaves are an accustomed extreme event of the Australian climate, which can cause catastrophic impacts on human health, agriculture, and urban and natural systems. We have analyzed the trends in Australia-wide heatwave metrics (frequency, duration, intensity, number, cumulative magnitude, timing, and season duration) across 69 extended summer seasons (i.e., from November-1951 to March-2020). Our findings not only emphasize that heatwaves are becoming hotter, longer, and more frequent, but also signify that they are occurring with excess heat, commencing much earlier, and expanding their season over many parts of Australia in recent decades. The Australian heatwave trends have strengthened since last observed Australian study was conducted. We also investigated the heatwave and severe heatwave trends at a local city-scale using three different observational products (AWAP and SILO gridded datasets and ACORN_SATV2 station data) over selected time periods (1911-2019, 1911-1964, and 1965-2019). Results suggest that heatwave trends are noticeably different amongst the three datasets. However, the results highlight that the severe heatwave cumulative magnitude and their season duration have been increasing significantly in recent decades over Australia’s southern coastal cities (like Melbourne and Adelaide). The climatological mean of the most heatwave and severe heatwave metrics is substantially higher in recent decades compared to earlier periods across all the cities considered. The findings of our study have significant implications for the development of advanced heatwave planning and adaptation strategies.
Most studies evaluating future changes in climate extremes over Australia have examined events that occur once or more each year. However, it is extremes that occur less frequently than this that generally have the largest impacts on sectors such as infrastructure, health and finance. Here we use an ensemble of high resolution (similar to 10 km) climate projections from the NSW and ACT Regional Climate Modelling (NARCliM) project to provide insight into how such rare events may change over southeast Australia in the future. We examine changes in the frequency of extremes of heat, rainfall, bushfire weather, meteorological drought and thunderstorm energy by the late 21st century, focusing on events that currently occur once every 20 years (those with a 5% Annual Exceedance Probability). Overall the ensemble suggests increases in the frequency of all five extremes. Heat extremes exhibit the largest change in frequency and the greatest ensemble agreement, with current 1-in-20 year events projected to occur every year in central Australia and at least every 5 years across most of southeast Australia, by the late 21st century. The five capital cities included in our model domain are projected to experience multiple climate extremes more than twice as frequently in the late 21st century, with some cities projected to experience 1-in-20 year events more than six times as frequently. Although individual simulations show decreases in some extremes in some locations, there is no strong ensemble agreement for a decrease in any of the climate extremes over any part of southeast Australia. These results can support adaptation planning and should motivate further research into how extremely rare events will change over Australia in the future.
BACKGROUND: Climate change is causing an increase in the frequency and severity of heatwave events, with a corresponding negative impact on human health. Health service utilisation during a heatwave is increased, with a greater risk of poor health outcomes identified for specific population groups. In this study, we examined the impact of heatwave events on ambulance dispatches in Tasmania, Australia from 2008 to 2019 to explore health service utilisation and identify the most vulnerable populations at a local level. METHODS: We used a time-stratified case-crossover analysis with conditional logistic regression to examine the association between ambulance dispatches and three levels of heatwave events (extreme, severe, and low-intensity). We examined the relationship for the whole study population, and by age, gender, socio-economic advantage and clinical diagnostic group. RESULTS: We found that ambulance dispatches increase by 34% (OR 1.34, 95% CI 1.18-1.52) during extreme heatwaves, by 10% (OR 1.10, 95% CI 1.05-1.15) during severe heatwaves and by 4% (OR 1.04, 95% CI 1.02-1.06) during low-intensity heatwaves. We found significant associations for the elderly (over 65), the young (5 and under) and for regions with the greatest socio-economic disadvantage. CONCLUSION: Heatwaves were associated with increased demands on ambulance services in Tasmania. In subgroups of people aged over 65 or under 5 years of age, and those from areas of higher disadvantage, we generally observed greater effect sizes than for the population as a whole.
Historically, heatwaves are Australia’s most destructive natural hazard in terms of loss of life. This study analyses statistics of fatalities associated with heatwaves in Australia from 2001 to 2018 as noted by a Coroner. At least 473 heat-related deaths were reported to a Coroner during the period of research, of which 354 occurred during heatwave conditions and, of these, 244 within buildings. Most indoor heatwave fatalities occurred in older housing stock. There was no overall trend in the number or rate of fatalities but, rather, a record of generally low numbers with periodic excursions into very high numbers. Almost two-thirds (63%) of heatwave fatalities occurred during two severe heatwave years: 2009 and 2014. The record was dominated by male fatalities. The risk of dying in a heatwave increased with age, socio-economic disadvantage, social isolation, geographical remoteness, the presence of disabilities (physical or mental) and some prescribed medications and the absence or non-use of air conditioning or other building heat protection. Other risk factors and behaviours were examined and recommendations to decrease future heatwave deaths suggested.
OBJECTIVE: To determine if global warming has changed the balance of summer and winter deaths in Australia. METHODS: Counts of summer and winter cause-specific deaths of subjects aged 55 and over for the years 1968-2018 were entered into a Poisson time-series regression. Analysis was stratified by states and territories of Australia, by sex, age and cause of death (respiratory, cardiovascular, and renal diseases). The warmest and coldest subsets of seasons were compared. RESULTS: Warming over 51 years was associated with a long-term increase in the ratio of summer to winter mortality from 0.73 in the summer of 1969 to 0.83 in the summer of 2018. The increase occurred faster in years that were warmer than average. CONCLUSIONS: Mortality in the warmest and coldest times of the year is converging as annual average temperatures rise. Implications for public health: If climate change continues, deaths in the hottest months will come to dominate the burden of mortality in Australia.
Heat kills more Australians than any other natural disaster. Previous Australian research has identified increases in Emergency Department presentations in capital cities; however, little research has examined the effects of heat in rural/regional locations. This retrospective cohort study aimed to determine if Emergency Department (ED) presentations across the south-west region of Victoria, Australia, increased on high-heat days (1 February 2017 to 31 January 2020) using the Rural Acute Hospital Data Register (RAHDaR). The study also explored differences in presentations between farming towns and non-farming towns. High-heat days were defined as days over the 95th temperature percentile. International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) codes associated with heat-related illness were identified from previous studies. As the region has a large agricultural sector, a framework was developed to identify towns estimated to have 70% or more of the population involved in farming. Overall, there were 61,631 presentations from individuals residing in the nine Local Government Areas. Of these presentations, 3064 (5.0%) were on days of high-heat, and 58,567 (95.0%) were of days of non-high-heat. Unlike previous metropolitan studies, ED presentations in rural south-west Victoria decrease on high-heat days. This decrease was more prominent in the farming cohort; a potential explanation for this may be behavioural adaption.
OBJECTIVE: To examine the cost benefits of a heat health warning system (HHWS) in South Australia. METHODS: Information from key agencies was used to estimate the costs associated with the South Australian HHWS, including for three targeted public health interventions. Health cost savings were estimated based on previously reported HHWS-attributable reductions in hospital and emergency department (ED) admissions and ambulance callouts. RESULTS: The estimated cost for a one-week activation of the HHWS was AU$593,000. Activation costs compare favourably with the potential costs averted through HHWS-attributable reductions in hospital admissions and ambulance callouts with an estimated benefit-cost ratio of 2.0-3.3. CONCLUSIONS: On the basis of estimated cost benefit, the South Australian HHWS is a no-regret public health response to heatwaves. IMPLICATIONS FOR PUBLIC HEALTH: As global temperatures rise there are likely to be significant health impacts from more frequent and intense heatwaves. This study indicates that HHWSs incorporating targeted supports for vulnerable groups are likely to be cost-effective public health interventions.
Increasing temperature and its impact on population health is an emerging significant public health issue in the context of climate change in Australia. While previous studies have primarily focused on risk assessment, very few studies have evaluated heat-attributable emergency department (ED) visits and associated healthcare costs, or projected future health and economic burdens. This study used a distributed lag non-linear model to estimate heat attributable ED visits and associated healthcare costs from 13 hospitals in Perth, Western Australia, and to project the future healthcare costs in 2030s and 2050s under three climate change scenarios-Representative Concentration Pathways (RCPs)2.6, RCP4.5 and RCP8.5. There were 3697 ED visits attributable to heat (temperatures above 20.5 degrees C) over the study period 2012-2019, accounting for 4.6% of the total ED visits. This resulted in AU$ 2.9 million in heat-attributable healthcare costs. The number of ED visits projected to occur in the 2030s and 2050s ranges from 5707 to 9421 under different climate change scenarios, which would equate to AU$ 4.6-7.6 million in heat associated healthcare costs. The heat attributable fraction for ED visits and associated healthcare costs would increase from 4.6% and 4.1% in 2010s to 5.0%-6.3% and 4.4%-5.6% in 2030s and 2050s, respectively. Future heat attributable ED visits and associated costs will increase in Perth due to climate change. Excess heat will generate a substantial population health challenge and economic burdens on the healthcare system if there is insufficient heat adaptation. It is vital to reduce greenhouse gas emissions, develop heat-related health interventions and optimize healthcare resources to mitigate the negative impact on the healthcare system and population health in the face of climate change.
Extreme heat events are a leading natural hazard risk to human health. Under all future climate change models, extreme heat events will continue to increase in frequency, duration, and intensity. Evidence from previous extreme heat events across the globe demonstrates that adverse cardiovascular events are the leading cause of morbidity and mortality, particularly amongst the elderly and those with pre-existing cardiovascular disease. However, less is understood about the adverse effects of extreme heat amongst specific cardiovascular diseases (i.e., heart failure, dysrhythmias) and demographics (sex, ethnicity, age) within Australia and New Zealand. Furthermore, although Australia has implemented regional and state heat warning systems, most personal heat-health protective advice available in public health policy documents is either insufficient, not grounded in scientific evidence, and/or does not consider clinical factors such as age or co-morbidities. Dissemination of evidence-based recommendations and enhancing community resilience to extreme heat disasters within Australia and New Zealand should be an area of critical focus to reduce the burden and negative health effects associated with extreme heat. This narrative review will focus on five key areas in relation to extreme heat events within Australia and New Zealand: 1) the potential physiological mechanisms that cause adverse cardiovascular outcomes during extreme heat events; 2) how big is the problem within Australia and New Zealand?; 3) what the heat-health response plans are; 4) research knowledge and translation; and, 5) knowledge gaps and areas for future research.
Information on the spatiotemporal characteristics of Beijing’s urban-rural near-surface air temperature difference, known as the canopy layer urban heat island (UHI), is important for future urban climate management strategies. This paper investigates the variation of near-surface air temperatures within Beijing at a neighbourhood-scale resolution (similar to 100 m) during winter 2016 and summer 2017. We perform simulations using the urban climate component of the ADMS-Urban model with land surface parameters derived from both local climate zone classifications and OpenStreetMap land use information. Through sensitivity simulations, the relative impacts of surface properties and anthropogenic heat emissions on the temporal variation of Beijing’s UHI are quantified. Measured UHI intensities between central Beijing (Institute of Atmospheric Physics) and a rural site (Pinggu) during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) campaigns, peak during the evening at similar to 4.5 degrees C in both seasons. In winter, the nocturnal UHI is dominated by anthropogenic heat emissions but is underestimated by the model. Higher-resolution anthropogenic heat emissions may capture the effects of local sources (e.g. residential buildings and adjacent major roads). In summer, evening UHI intensities are underestimated, especially during heatwaves. The inability to fully replicate the prolonged release of heat stored in the urban fabric may explain this. Observed negative daytime UHI intensities in summer are more successfully captured when surface moisture levels in central Beijing are increased. However, the spatial correlation between simulated air temperatures and satellite-derived land surface temperatures is stronger with a lower urban moisture scenario. This result suggests that near-surface air temperatures at the urban meteorological site are likely influenced by fine-scale green spaces that are unresolved by the available land cover data and demonstrates the expected differences between surface and air temperatures related to canopy layer advection. This study lays the foundations for future studies of heat-related health risks and UHI mitigation strategies across Beijing and other megacities.
The urbanization process leads to the enhancement of the urban heat island (UHI) effect, and the high temperature brought by it exacerbates the risk of heat exposure and seriously endangers human health. Analyzing the spatiotemporal characteristics and levels of heat exposure risk is important for formulating heat risk prevention and control measures. Therefore, this study analyzes the spatiotemporal characteristics of heat exposure risk based on the UHI footprint (FP) and explores the relationship between it and urbanization factors in the Beijing-Tianjin-Hebei (BTH) region from 2000 to 2020, and obtains the following conclusions: (1) The BTH region suffers from severe UHI problems, with FP ranging from 6.05 km (Chengde) to 32.51 km (Beijing), and the majority of cities show significant trends of FP increase. (2) With the increase in FP, massive populations are exposed within the heat risk areas, with the average annual population at risk across cities ranging from 269,826 (Chengde) to 166,020,390 (Beijing), with a predominance of people exposed to high risk (more than 65% of the total) and generally showing increasing trends. (3) The population at risk of heat exposure is significantly correlated with urbanization factors, indicating that urbanization is an important reason for the increase in the risk population and the enhancement of the risk level. These results suggest that with the continuous urbanization process, the heat exposure risk problem faced by cities in the BTH region will persist and gradually worsen, which must be paid attention to and effective mitigation measures must be taken.
Both extreme heat and heavy air pollution can cause adverse health impacts on urban inhabitants. To understand heat stress and its relationship with boundary layer structure and air pollution in Beijing, this study analyzed surface meteorological observations, radiosonde measurements, and ground-level PM2.5 and O3 concentrations in summer from 2015 to 2019, in conjunction with simulated air quality and MERRA-2 data. We measured the heat stress using a heat index that combines temperature and humidity to quantify the sensible temperature as perceived by humans, and found that high heat risk in Beijing was often associated with a low boundary layer height and poor air quality. To reveal the underlying physical mechanism involved, we objectively classified the synoptic conditions in North China. The typical synoptic pattern associated with the coupling of heat and pollution in Beijing was found to feature a southeast-to-north pressure gradient at the 700-hPa level, leading to westward warm advection above planetary boundary layer (PBL) and southward movement of warm, humid, and polluted air masses within the PBL towards Beijing. The elevated warm advection can enhance the capping of thermal inversion over the PBL and suppress the PBL’s development and the vertical dispersion of pollutants. With mountains to the north and west, pollutants and heat can be trapped in a limited volume in Beijing, increasing the health risk from heat and pollution. These findings on the meteorological mechanisms of the coupling between heat and pollution in Beijing may have important implications for limiting the current health risk and preparing for any projected changes in it in the future.
The growing elderly population living in high density cities undergoing mass urbanization raises concerns over age-friendliness of neighborhood open space, an essential component for healthy aging-in-place as elderly tend to spend most of their time at home and immediate home environment. This study discusses factors that influence age-friendly open space design pertaining to outdoor thermal environment and physical design element for highdensity high-rise housing in hot weather, using the case of public housing developments in Hong Kong. Field measurements, observations and linear regression data analyses are used to understand dynamic thermal condition, adaptive elderly user behavior and response to planned open space. It is demonstrated that four influential factors are important to correlate with elderly residents’ use of open space: 1) mean radiant temperature (MRT); 2) air temperature; 3) greenery; and 4) outdoor seating. Moreover, it is found that MRT, specifically longwave MRT, is the most influential and impacts the effectiveness of greenery and outdoor seating. In addition, the study proposes guide points to reflect the effect of each factor and shed more insight into improving age-friendly neighborhood open space design against climate-change induced heat-related health issues.
Against the background of global climate change, the increasing heat health risk from the combined effect of changes in high temperature, exposure, vulnerability, and other factors has become a growing concern. Yet the low number of temperature observation stations is insufficient to represent the complex changes in urban heatwaves, and subdistrict-scale (town, township, neighborhood committee, and equivalent) heat health risk and adaptability assessments are still limited. In this study, we built daytime and nighttime high-temperature interpolation models supported by data from 225 meteorological stations in Beijing. The models performed well at interpolating the cumulative hours of high temperature and the interpolation quality at night was better than that during the day. We further established a methodological framework for heat health risk and adaptability assessments based on heat hazard, population exposure, social vulnerability, and adaptability at the subdistrict scale in Beijing. Our results show that the heat health risk hotspots were mainly located in the central urban area, with 81 hotspots during the day and 76 at night. The average value of the heat health risk index of urban areas was 5.60 times higher than that of suburban areas in the daytime, and 6.70 times higher than that of suburban areas in the night. Greater population density and higher intensity of heat hazards were the main reasons for the high risk in most heat health risk hotspots. Combined with a heat-adaptive-capacity evaluation for hotspot areas, this study suggests that 11 high-risk and low-adaptation subdistricts are priority areas for government action to reduce heat health risk in policy formulation and urban development.
Heatstroke is defined as severe symptoms of heat-related illness, which could lead to death. Sugarcane farmers are at high risk of heatstroke under extremely hot outdoor working conditions. We explored the prevalence of heat-related illness symptoms and risk factors related to heat-related illness among sugarcane farmers working in the summer. We conducted a cross-sectional study using questionnaire interviews among 200 sugarcane farmers in Kamphaeng Phet Province, Thailand. The questionnaire addressed demographics, heat-related symptoms experienced during summer at work, and occupational factors. Bioelectrical impedance analysis was used to assess body mass index and body fat percentage. Watson formula equations were used to estimate total body water. The prevalence of heat-related illness symptoms was 48%; symptoms included heavy sweating, weakness/fatigue, dizziness, muscle cramps, headache, and vertigo. Factors associated with heat-related illness included women and clothing. Sugarcane farmers wearing two-layer shirts had a higher risk of heat-related illness. Farmers with fluid intake 3.1-5.0 liters per day had a 79% lower risk of heat-related illness. Our findings demonstrated that sugarcane farmers are at risk of heat-related illness. We confirmed that working conditions, including wearing proper clothing and water-drinking habits, can reduce this risk.C
Extreme urban heat alongside higher ambient temperatures in urban areas causes serious energy, comfort, health and environmental problems. The implementation of urban heat mitigation techniques can significantly reduce urban temperatures and counterbalance the impact of extreme urban heat. This study assesses the potential cooling ability of modified urban albedo strategies through the implementation of reflective and super reflective materials, as well as the global climatic impacts on a subtropical desert urban environment in Dubai, UAE. Three scenarios using low, average and high albedo modifications are designed and evaluated in parallel to a reference scenario. A physically-based mesoscale urban modeling system is used to assess the thermal and meteorological impacts of the albedo modifications during both the summer and winter seasons at a city scale. The reduction of ambient temperature during the peak of a summer day (14:00 LT) is shown to be 0.6 degrees C, 1.4 degrees C and 2.6 degrees C when urban albedo is increased by 0.20, 0.45 and 0.60 respectively. The winter cooling penalty ranges between 0.6 degrees C and 1.1 degrees C for the different albedo scenarios. The increase of the urban albedo also significantly reduces the planetary boundary layer (PBL) depth due to the loss of sensible heat and decreases the intensity of the convective mixing and advection flows from the desert to the city, improving the mitigation potential of the reflective materials; however this increases the risk of a higher pollutants concentration. A much higher mitigation potential is observed for the high-density parts of the city when compared to that of the low-density parts of the city. Irrespective of linear function in the drop of ambient temperature and changing fraction of global albedo, our results reported that the cooling potential of reflective materials is highly influenced by the climate, landscape, and urban characteristics of the cities.
Mapping the elderly population exposure to heat hazard in urban areas is important to inform adaptation strategies for increasingly-deadly urban heat under climate change. However, fine-scale mapping is lacking, because global climate change projections have not previously been integrated with urban heat island effects especially with urban three-dimensional characteristics for within-city heat risk analyses. This study compared the spatial patterns of deadly heat exposure for elderly populations in two East Asian megacities, Seoul and Tokyo, using current climate (2006-2015) and two future periods (2040s and 2090s). We integrated global warming projections (the Shared Socioeconomic Pathway 5 based on Representative Concentration Pathway 8.5) with local urban characteristics and demographics. We found that, for the historical period, the overall hotspots of elderly population exposure to urban heat was larger in Tokyo because of relatively higher maximum air temperatures and lack of green spaces, whereas in the future periods, Seoul will have larger hotspots because the elderly population density will have increased. About 20% of the area in Seoul and 0.3-1% of Tokyo will be hotpots in the 2040s, and the size of these hotspots increases to 25-26% and 2-3%, respectively, in the 2090s. The spatial patterns of hotspots identify different types of priority areas and suggest that alternative adaptation strategies for two cities are appropriate. The approach introduced here will be useful for identifying sustainable thermal environments in other cities with high density elderly population and severe heat hazard. (c) 2021 Elsevier B.V. All rights reserved.
Urban heat islands (UHI) exacerbates the heat-related risk associated with global warming, increasing morbidity and mortality of urban residents. While the impacts of the spatial pattern of urban greenspace (UG) and its change on urban heat have been widely examined, there is less understanding of the aggregate effect of the change of UG-considering the loss and gain of UG simultaneously -on urban temperature. This study aims to fill this gap by using Beijing, China as a case study. Using a newly developed index -dynamic index of UG (UGDI) that simultaneously measures the loss and gain of UG in a certain unit of analysis, we investigated how changes in UG affect the daytime and nighttime land surface temperature (LST). We found: (1) A substantial proportion (49.90%) of grids with increased UG cover had increased LST during the daytime, with a magnitude ranging from 0.02 to 1.82 ?, indicating that the increase in UG does not always result in reduction of LST. (2) UGDI had a significantly positive correlation with LST change, suggesting that increase in UG does not necessarily result in decrease of LST, which can be affected by the degree of dynamics of UG. (3) The evapotranspiration (ET) rate of vegetation for lost greenspace was higher than that of new greenspace, indicating that adding the same amount of UG might not able to provide the same amount of cooling effects provided by lost ones. Results can enhance our understanding on how (landscape) process affects ecological effect. Future research and practical manage-ment strategies shall move beyond net increase of UG and focus more on its change process. This finding provides new evidence for explaining the effect of the change of UG on LST, and offers new insights for planning and managing urban natural resource to enhance resilience of cities to climate warming.
Rapid urbanization has led to altered thermal circulations in major cities that are responsible for the increasing occurrence of urban heat islands (UHIs) and events such as tropical nights and heat waves. To effectively mitigate such events, low-impact development (LID) and green infrastructure strategies have been developed. In Korea, LID techniques focus mainly on road pavement materials; however, issues regarding the reliability of measurements due to differences in the measurement equipment and studied specimens persist. This study presents the design of a green infrastructure surface temperature measurement (GSTM) instrument and a reliable methodology developed to evaluate the performance of pavement materials under controlled climate conditions. The developed GSTM instrument and methodology were tested by monitoring the surface temperature of materials based on LID practices and dense-graded asphalt and evaluating their ability to mitigate UHI and tropical night phenomena. The experiments were conducted under controlled climate conditions, using summer climate conditions of Seoul’s typical meteorological year data. The UHI and tropical night phenomena mitigation performance of the pavement materials was evaluated by analyzing the correlation between the pavement materials’ albedo and surface temperature using porous block specimens of different colors and LID-based pavement materials. The greening block recorded the most significant reduction in surface temperature, showing a difference of 22.6 °C, 185 min to the dense-graded asphalt. The white and yellow porous blocks showed surface temperature differences of 10.2 °C and 8.2 °C respectively compared to the dense-graded asphalt. The results revealed that pavement materials with higher albedo, more evaporation, and lower heat capacity have superior performance in mitigating UHI and tropical night events.
Urban areas generally have higher near-surface air temperature and lower air humidity than rural areas. Little is known about how heat stress, the combined effect of high air temperature and high humidity on human physiology, will be affected by future urban land expansion. Here we use a mesoscale numerical weather prediction model to examine the effects of urban land expansion from 2000 to 2050 on heat stress (measured as wet-bulb globe temperature, WBGT) in the urban areas of China, India, and Nigeria, which are projected to account for one-third of global urban population growth through 2050. Our results show that urban expansion slightly reduces heat stress during the day (similar to 0.2 degrees C) but substantially intensifies it at night, by similar to 1 degrees C on average and by up to 2-3 degrees C in five mega-urban regions (MURs). These effects exist with or without climate change induced by rising concentrations of greenhouse gases (GHGs). Installing cool roofs-an urban heat island mitigation measures-can reduce the daytime WBGT by 0.5-1 degrees C, partially offsetting the heat stress conditions caused by GHG-induced climate change. However, even with cool roofs, the nighttime WBGTs are higher by 0.3-0.9 degrees C over the whole countries studied, and by 1-2 degrees C in the MURs under the urban expansion scenario, compared to the situation in which urban areas remain unchanged. These results show that future urban expansion and heat island mitigation can result in potential daytime benefits but also persistent nighttime risks.
The intensification of heat stress reduces the labor capacity and hence poses a threat to socio-economic development. The reliable projection of the changing climate and the development of sound adaptation strategies are thus desired for adapting to the decreasing labor productivity under climate change. In this study, an optimization modeling approach coupled with dynamical downscaling is proposed to design the optimal adaptation strategies for improving labor productivity under heat stress in China. The future changes in heat stress represented by the wet-bulb globe temperature (WBGT) are projected with a spatial resolution of 25 × 25 km by a regional climate model (RCM) through the dynamical downscaling of its driving global climate model (GCM). Uncertain information such as system costs, environmental costs, and subsidies are also incorporated into the optimization process to provide reliable decision alternatives for improving labor productivity. Results indicate that the intensification of WBGT is overestimated by the GCM compared to the RCM. Such an overestimation can lead to more losses in working hours derived from the GCM than those from the RCM regardless of climate scenarios. Nevertheless, the overestimated heat stress does not alter the regional measures taken to adapt to decreasing labor productivity. Compared to inland regions, the monsoon-affected regions tend to improve labor productivity by applying air conditioning rather than working overtime due to the cost differences. Consequently, decision-makers need to optimally make a balance between working overtime and air conditioning measures to meet sustainable development goals.
The intensification of heat stress in a changing climate poses great threats to both human health and labor productivity. It is of great practical importance to assess the impacts of climate-induced heat stress on labor productivity and to develop effective adaptation strategies. In this paper, an integrated optimization-based productivity restoration modeling framework is proposed for the first time to develop the optimal policies for adaptation to climate change. To address underlying uncertainties associated with climate and labor management systems, we take into account ensemble projections from five global climate models (GCMs) under two Representative Concentration Pathways (RCP2.6 and RCP8.5) and inexact system costs. The system costs, including direct and indirect costs such as management costs, energy costs, and labor costs, are presented as interval numbers due to inherent uncertainty caused by population growth, technology development, and other social-economic factors. Uncertain information can be effectively communicated into the optimization processes in this study to generate optimal and reliable decision alternatives. We find that the increased Wet-Bulb Globe Temperature (WBGT) will lead to a large reduction in labor capacities over China except for the Tibetan Plateau under both RCPs by the end of the 21st century. The less developed regions tend to achieve the minimum system cost by having labor productivity recovered through working overtime due to the relatively low cost of overtime. This could result in more heat-related work injuries in the less developed regions. Since the less developed regions are not heat-prone areas in China, the changing climate would be a more dangerous threat and cause more damages to these regions where the residents are less acclimatized to heat stress. Moreover, we obtain a range of minimum system costs from 1.86 to 8.97 billion dollars under RCP2.6 and from 9.42 to 32.31 billion dollars under RCP8.5 (about 0.2% of China’s GDP in 2019, 0.01% of China’s GDP projected in 2100 under a sustainable socio-economic development scenario) for the restoration of labor productivity in a warming climate. We argue that urgent actions are needed to mitigate global warming impacts on labor productivity.
Several heat records have been broken in recent years and decades. Extreme high temperature not only damages human health, but also increases the risk of wildfires. As a common urban infrastructure, urban green space has been proved to have a cooling effect. In this study, the physical indicators and temperature data of 36 green spaces in Xi’an were collected, and the influence of different physical indicators of green spaces on their thermal environment was explored through correlation analysis. The results suggest that the area of green space should be between 0.6-0.7 square kilometers or the perimeter should range from 4000 to 4500 m in order to obtain the lowest internal temperature. When the area of water body in the green space is between 0.3-0.4 square kilometers or the perimeter is about 5000 m, its internal temperature is the lowest. Indicators of green space in the conclusion can be directly understood and referred by urban planners and policy makers. Results of this study thus have implications for improving urban thermal comfort by controlling the physical indicators of green space.
Global endeavors to respond to the problems caused by climate change and are leading to higher temperatures inside homes, which can cause skin conditions (such as eczema), lethargy, and poor concentration; disturbed sleep and fatigue are also rising. The energy performance of buildings is influenced by interactions and associations of numerous different variables, such as the envelope specifications as well as the design, technologies, apparatuses, and occupant behaviours. This paper introduces simple and sustainable strategies that are not dependent on expensive or sophisticated technologies, as they rely only on the actions practiced by the building’s occupants (movable window shading, and nighttime natural ventilation) instead of completely relying on high-cost mechanical cooling systems in buildings located in the main Eastern Mediterranean climates represented in the country of Jordan. These low-energy solutions could be applied to low-income houses in hot areas to avoid health problems, such as dermatological diseases, and save a significant amount of energy. The final results indicate that window shading has significant potential in reducing the cooling load in different climate zones. Natural ventilation exhibits high energy-saving abilities in climates that have cool nights, whereas its abilities in hot climates where nights are moderate is limited.
Average global temperatures and frequencies of heat waves are increasing with detrimental effects on health and wellbeing. This study presents a case study from two cities in the Northern Territory with the aim of exploring if and how people make deliberate adaptations to cope with increasing heat. Results show that 37% of all respondents made adjustments, with the most common being increased use of air-conditioning (65% of those responding to heat), followed by staying inside more often (22%) and passive cooling through modifications of house and garden (17%). Young people increasingly refrain from outside activities as temperatures increase. We also found that adaptive capacity was a function of education, long-term residency, home ownership and people’s self-rated wellbeing. Homeowners were more likely to adjust their living environment to the heat and renters less so. Being a property owner was commonly associated with the installation of solar panels to pay for high energy bills needed to run air-conditioning. Those who had solar panels at home were about ten times more likely to use air-conditioning more frequently in response to increasing heat. Our results confirm a growing dependence on artificially controlled environments to cope with heat in cities.
BACKGROUND: Previous studies have reported that high ambient temperature is associated with increased risk of suicide; however, the association has not been extensively investigated with drug overdose which is the most common method of unsuccessful suicidal behavior in Japan. Therefore, this study aims to examine the short-term association between daily mean temperature and the incidence of self-harm attempts by drug overdose in Tokyo, Japan. METHODS: We collected the emergency ambulance dispatch data and daily meteorological data in Tokyo from 2010 to 2014. A quasi-Poisson regression model incorporating a distributed lag non-linear function was applied to estimate the non-linear and delayed association between temperature and drug overdose, adjusting for relative humidity, seasonal and long-term trends, and days of the week. Sex, age and location-specific associations of ambient temperature with drug overdose was also estimated. RESULTS: 12,937 drug overdose cases were recorded during the study period, 73.9% of which were female. We observed a non-linear association between temperature and drug overdose, with the highest risk observed at 21 °C. The highest relative risk (RR) was 1.30 (95% Confidence Interval (CI): 1.10-1.67) compared with the risk at the first percentile of daily mean temperature (2.9 °C) over 0-4 days lag period. In subgroup analyses, the RR of a drug overdose at 21 °C was 1.36 (95% CI: 1.02-1.81) for females and 1.07 (95% CI: 0.66-1.75) for males. Also, we observed that the risk was highest among those aged ≥65 years (RR = 2.54; 95% CI: 0.94-6.90), followed by those aged 15-34 years (RR = 1.25; 95% CI: 0.89-1.77) and those aged 35-64 years (RR = 1.15; 95% CI: 0.78-1.68). There was no evidence for the difference in RRs between urban (23 special wards) and sub-urban areas in Tokyo. CONCLUSIONS: An increase in daily mean temperature was associated with increased drug overdose risk. This study indicated the positive non-linear association between temperature and incomplete attempts by drug overdose. The findings of this study may add further evidence of the association of temperature on suicidal behavior and suggests increasing more research and investigation of other modifying factors.
BACKGROUND: Epidemiological studies based on mortality and crime data have indicated that short-term exposure to higher temperature increases the risk of suicide and violent crimes. However, there are few studies on non-fatal intentional injury, especially on non-fatal self-harm which is much more common than suicide. OBJECTIVES: We aimed to clarify how short-term exposure to temperature is associated with emergency ambulance transport caused by intentional injuries including acts of self-harm and assault. METHOD: We applied a time-stratified case-crossover design using a conditional quasi-Poisson regression model for each of the 46 prefectures. All temperatures were converted to percentile value for each prefecture, to account for the varied climate across Japan. A Distributed Lag Non-Linear Model was used to explore the temperature percentile and lag pattern. The prefecture-specific results were combined using a meta-analysis with the random effects model. RESULT: Between 2012 and 2015, the number of acts of self-harm and assault across all 46 prefectures totaled 151,801 and 95,861, respectively. We found that as the temperature increased, the relative risk (RRs) for both self-harm and assault behaviors increased in a nearly linear manner. The pooled relative risk at the 99th percentile temperature for self-harm behavior was 1.11 (95% CI: 1.07, 1.15) compared with the risk at the 1st percentile temperature, and that for assault was 1.12 (95% CI: 1.08, 1.16) at lag 0. The RRs were highest at lag0 and less than 1 at lag7-20. CONCLUSION: The present study found that short-term exposure to higher temperature promotes the risk of emergency ambulance transport due to acts of self-harm and assault. The lag pattern indicates a possible “displacement” effect. These results suggest that exposure to high temperatures may potentially function as a trigger for intentional injuries.
Vietnam is highly vulnerable to climate change-related extreme weather events such as heatwaves. This study assesses the association between heatwaves and hospitalizations due to mental and behavioral disorders (MBDs) in Ho Chi Minh City (HCMC). We collected daily MBD hospital admissions data at the HCMC Mental Health Hospital from 2017 to 2019. Heatwaves effects were characterized into the main effect (i.e., the intensity of temperature during heatwaves) and the added effect (i.e., the duration of heatwaves). Time series Poisson regression coupled with a distributed lag linear model (DLM) was used to quantify the 14-day lags effect of heatwaves. Confounders including long-term trend, seasonality, days of the week, holidays, and relative humidity were included in the model. Heatwaves increased all-cause MBD hospitalization by 62% (95%Cl, 36-93%) for the main effect and by 8% (95% Cl, - 3% to 19%) for the added effect. Noticeably, the group aged 18-60 years old was affected by the main effect of the heatwave, while the group aged 61 years and older was affected by the added effect of the heatwave. The effects of heatwaves differed among groups of MBD hospitalizations. The mental and behavioral disorder group due to psychoactive substance use was significantly affected by the main effect of heatwaves (RR:2.21; 95%Cl:1.55-3.15). The group of schizophrenia, schizotypal and delusional disorders were highly vulnerable towards both the main and the added effect of heatwaves with RR = 1.50 (95%CI, 1.20-1.86) and RR = 1.14 (95%CI, 1.01-1.30), respectively.
The effect of thermal discomfort on human well-being and performance was studied in the field office, and an attempt was made to elucidate its psychological mechanism. Thirty participants were recruited to perform subjective evaluations and performance tests under 5 different conditions (25 degrees C, 27 degrees C, 29 degrees C, 31 degrees C, 33 degrees C). During the experiment, the air temperature was considered as an independent variable and other parameters were kept at the same level. The results show that thermal discomfort can lead to poor comfort and reduced performance, and people report that many sick building syndrome symptoms are intensified, showing more negative emotions and reducing their motivation. When people’s thermal sensation vote is -0.13, the best performance can be obtained. But the changes in human performance are not only caused by objective environmental factors, but also by psychological factors such as emotion and motivation. When people’s negative emotions decrease or their motivations increase, performance will also increase.
The combined effect of global warming and the heat island effect keeps the temperature of cities rising in the summer, seriously threatening the physical and mental health of urban residents. Taking the area within the Sixth Ring Road of Beijing as an example, based on Landsat remote sensing images, meteorological stations, and questionnaires, this study established a relational model between temperature and hostility and then analyzed the changes in the emotional health risk (hostility) in the study area and the mechanism of how outdoor activity duration influences hostility. Results show that: (1) the area within the Sixth Ring Road of Beijing had a higher and higher temperature from 1991 to 2020. Low-temperature areas gradually shrank, and medium- and high-temperature areas extended outwards from the center. (2) The threat of high temperature to residents’ hostility gradually intensified-the sphere of influence expanded, low-risk areas quickly turned into medium-high-risk areas, and the level of hostility risk increased. Level 1 risk areas of hostility had the most obvious reduction-a 74.33% reduction in area proportion; meanwhile, Level 3 risk areas had the most significant growth-a 50.41% increase in area proportion. (3) In the first 120 min of outdoor activities under high temperature, residents’ hostility was negatively correlated with outdoor activity duration; after more than 120 min, hostility became positively correlated with duration. Therefore, figuring out how temperature changes influence human emotions is of great significance to improving the living environment and health level of residents. This study attempts to (1) explore the impact of temperature changes and outdoor activity duration on hostility, (2) evaluate residents’ emotional health risk levels affected by high temperature, and (3) provide a theoretical basis for the early warning mechanism of emotional health risk and the planning of healthy cities.
The emotional health of urban residents has been seriously threatened by frequent and normalized heat waves. This study constructed the VI-level assessment standard for emotional health risk using data from satellite images, meteorological sites, questionnaire surveys, and statistical yearbooks to assess the effect of high temperatures on negative emotions in Hangzhou. The results showed that the morphological changes of urban high-temperature areas were aggregated from a cross-shape to a large patch shape, then dispersed into cracked patch shapes. Additionally, the health risk of daytime negative emotions peaked at the VI-level from 1984 to 2020, and the influence level of the typical period risk increased by 1-2 levels compared with the daytime. Additionally, driven by urban spatial structure policies, the risk pattern of emotional health expanded outward from a single center into multiple centers. The emotional health risk level rose and then descended in urban centers, and the innovation industries drove the variation tendency of hot spots. Furthermore, high educational background, employment, and couples living together were critical variables that could alleviate the emotional health risk to the middle-aged and elderly population. This study aimed to optimize the urban spatial structure and alleviate residents’ emotional health hazards for healthy urban planning.
OBJECTIVES: In the context of frequent global extreme weather events, there are few studies on the effects of sequential extreme precipitation (EP) and heatwaves (HW) events on schizophrenia. We aimed to quantify the effects of the events on hospitalizations for schizophrenia and compare them with EP and HW alone to explore the amplification effect of successive extremes on health loss. METHODS: A time-series Poisson regression model combined with a distributed lag non-linear model was applied to estimate the association between sequential EP and HW events (EP-HW) and schizophrenia hospitalizations. The effects of EP-HW with different intervals and intensities on the admission of schizophrenia were compared. In addition, we calculated the mean attributable fraction (AF) and attributable numbers (AN) per exposure of extreme events to reflect the amplification effect of sequential extreme events on health hazards compared with individual extreme events. RESULTS: EP-HW increased the risk of hospitalization for schizophrenia, with significant effects lasting from lag0 (RR and 95% CI: 1.150 (1.041-1.271)) to lag11 (1.046 (1.000-1.094)). Significant associations were found in the subgroups of male, female, married people, and those aged≥ 40 years old. Shorter-interval (0-3days) or higher-intensity EP-HW (both precipitation ≥ P97.5 and mean temperature ≥ P97.5) had a longer lag effect compared to EP-HW with longer intervals or lower intensity. We found that the mean AF and AN caused by each exposure to EP-HW (AF: 0.074% (0.015%-0.123%); AN: 4.284 (0.862-7.118)) were higher than those induced by each exposure to HW occurring alone (AF:0.032% (0.004%-0.058%); AN:1.845 (0.220-3.329)). CONCLUSIONS: Sequential extreme precipitation-heatwaves events significantly increase the risk of hospitalizations for schizophrenia, with greater impact and disease burden than independently occurring extremes. The impact of consecutive extremes is supposed to be considered in local sector early warning systems for comprehensive public health decision-making.
The association between heat and diseases has been extensively reported. However, its associated healthcare costs and attributable fraction due to heat were scarcely explored. The aim of this study was to estimate hospitalisation costs attributable to heat in Sydney, and to project future costs under climate change scenarios. Using a distributed lag nonlinear model, this study estimated heat-attributable hospitalisation costs in Sydney; and using 2010-2016 data as baseline, future costs for 2030s and 2050s were estimated under three climate change scenarios depending on greenhouse gas emissions – Representative Concentration Pathway (RCP)2.6, RCP4.5, and RCP8.5. Higher temperatures were found to be associated with increased hospitalisation costs. About 8-9% of the total hospitalisation costs were attributable to heat. The total costs attributable to heat over the baseline period 2010-2016 were estimated to be AU$252 million, with mental health hospitalisation making the largest contribution. Hospitalisation costs are estimated to increase substantially to AU$387-399 million in the 2030s, and AU$506-570 million by midcentury under different climate change scenarios. Urgent action is required to reduce heatattributable illness in our communities, particularly for mental health conditions. Relevant preparations including healthcare workforce capacity building and resource allocation are needed to deal with these challenges in the context of climate change.
OBJECTIVES: To describe the number and case characteristics of sport and recreation-related exertional heat deaths in Australia and summarise recommendations derived from case narratives. DESIGN: Descriptive, population-based, retrospective cohort study. METHODS: Cases were identified using the National Coronial Information System (NCIS) through multiple search strategies comprising queries, keywords and cause of death codes. Cases were included where there was evidence that the deceased was actively engaged in sport or recreation and exertional heat illness was causal or contributory to the death. Data extraction were performed independently, in duplicate, to ensure accuracy. Descriptive statistics are used to report deceased’s socio-demographic characteristics, incident characteristics, type of sport/recreational activity and time sequence of events. Content analysis is used to summarise recommendations. RESULTS: Thirty-eight deaths (males n = 29, 74%; median age = 40 years, range 8-77) were identified during the study period (2001 to 2018), with 22 recommendations for five cases. Two cases occurred during organised sport and 36 during active recreation, of which 27 were in hiking. Eleven (29%) individuals were international visitors. There were 22 recommendations across 5 cases presented, with a focus on education and training. CONCLUSIONS: Exertional heat deaths in outdoor recreation in Australia were far more prevalent than cases in organised sport. The largest proportion of deaths occurred in hiking with two populations featuring: males aged 15-45 years and international visitors. Considering the incident characteristics and time sequence of events, measures such as early recognition of symptoms, provision of first aid and timely access to emergency medical care are important to prevent fatalities.
Background: The negative impacts of environmental factors on allergic respiratory diseases (ARD) in children have gotten a lot of attention recently. However, the influence of climatic conditions, especially extreme temperatures, on childhood ARD induced by house dust mites (HDM-ARD) is uncertain. Objective: We aimed to quantify the associations between outpatient visits for HDM-ARD and extreme temperatures in Shanghai, China. Methods: A distributed lag nonlinear model combined with Quasi-Poisson generalized linear model was used to analyze data. Results: Daily mean temperature was significantly associated with outpatient visits for childhood ARD and HDM-ARD. Exposure to extreme temperatures increased the cumulative relative risks of outpatient visits for ARD and HDM-ARD in children (RRlag0-28 for the 5th percentile of Tmean: 2.97, 95% confidence interval (CI): 1.25, 7.06; RRlag0-28 for the 95th percentile of Tmean: 2.85, 95% CI: 1.03, 7.86). Boys were vulnerable to extreme lower temperature, while girls were more sensitive to extreme higher temperature in both ARD and HDM-ARD. The effect seemed to be most pronounced among 6-11 years of age school children. Conclusion: Our study presents quantitative evidence that extreme temperatures prompted outpatient visits for children with ARD, especially HDM-ARD, in Shanghai, China. These findings might have significant consequences for developing appropriate preventive measures for vulnerable populations.
BACKGROUND: Ambient temperature change is a risk factor for urolithiasis that cannot be ignored. The association between temperature and urolithiasis varies from region to region. Our study aimed to analyze the impact of extremely high and low temperatures on the number of inpatients for urolithiasis and their lag effect in Ganzhou City, China. METHODS: We collected the daily number of inpatients with urolithiasis in Ganzhou from 2018 to 2019 and the meteorological data for the same period. The exposure-response relationship between the daily mean temperature and the number of inpatients with urolithiasis was studied by the distributed lag non-linear model (DLNM). The effect of extreme temperatures was also analyzed. A stratification analysis was performed for different gender and age groups. RESULTS: There were 38,184 hospitalizations for urolithiasis from 2018 to 2019 in Ganzhou. The exposure-response curve between the daily mean temperature and the number of inpatients with urolithiasis in Ganzhou was non-linear and had an observed lag effect. The warm effects (30.4°C) were presented at lag 2 and lag 5-lag 9 days, and the cold effects (2.9°C) were presented at lag 8 and lag 3-lag 4 days. The maximum cumulative warm effects were at lag 0-10 days (cumulative relative risk, CRR = 2.379, 95% CI: 1.771, 3.196), and the maximum cumulative cold effects were at lag 0-5 (CRR = 1.182, 95% CI: 1.054, 1.326). Men and people between the ages of 21 and 40 were more susceptible to the extreme temperatures that cause urolithiasis. CONCLUSION: Extreme temperature was correlated with a high risk of urolithiasis hospitalizations, and the warm effects had a longer duration than the cold effects. Preventing urolithiasis and protecting vulnerable people is critical in extreme temperature environments.
Epidemiological studies have proven that extreme temperatures have a significant threat to public health. This study aimed to investigate the association between extreme temperatures and circulatory mortality from January 1, 2014, to December 31, 2016, in Harbin, a city with a cold climate in Northeast China. We set a maximum lag of 27 days to evaluate the hysteresis effects of different temperatures on circulatory mortality using a distributed lag nonlinear model (DLNM). Results indicated that daily mean temperature and circulatory mortality presented approximately an L-shaped, and the cumulative relative risks (RRs) decreased continuously as the temperature increased in both low and high temperatures. Extremely low temperature showed a hysteresis and durability on circulatory mortality, with the largest RR of 1.023 (95%CI: 1.001-1.046) at lag 26, and RR of the cumulative cold effect of 0-27 days was 1.302 (95%CI: 1.160-1.462). The effect of extremely high temperatures presented more acute and intense, with the largest RR of 1.033 (95%CI: 1.004-1.063) at lag 0. RR of the cumulative hot effect of 0-3 days was 1.056 (1.008-1.106). In addition, females were more susceptible to extremely low temperatures, while males were more vulnerable to extremely high temperatures. This study demonstrated that extremely low temperatures have a stronger effect on circulatory mortality than extremely high temperatures in Harbin.
With the rapid increase in global warming, the impact of extreme temperatures on morbidity and mortality related to respiratory diseases has attracted considerable attention. In the current study, we quantified the relative risks (RRs) of mortality for respiratory diseases in three capital cities in Northeast China. We used a distributed lag nonlinear model (DLNM) based on a generalized additive model (GAM) to estimate the impact of extreme temperatures on respiratory mortality in Shenyang, Changchun, and Harbin from 2014 to 2016. The results revealed that the maximum cumulative RRs and 95% confidence intervals (CIs) were 1.52 (1.28-1.80), 1.42 (1.07-1.89), and 1.38 (1.21-1.58) in Shenyang, Changchun, and Harbin respectively when the median temperature was used as reference. The effect of extremely high temperature (99th percentile relative to 90th percentile) on respiratory mortality was found to be strongest in Shenyang (at the lowest latitude), while the effect of extreme low temperature (1st percentile relative to 10th percentile) on respiratory mortality was strongest in Harbin (at the highest latitude). In Shenyang and Changchun, the effects of high temperatures were much more intense and pronounced in females. Furthermore, the effect of high temperatures was more acute, whereas the effect of low temperatures was longer lasting.
Global climate change increased air temperature variability and enhanced the frequency and intensity of extreme weather events, such as heat waves and cold spells with adverse impacts on public health. In this study, we examined the relationships of the daily air temperature with mortality in Shanghai in 2003, a record hot year. We found V-shaped associations between causespecific mortality and daily air temperature. The temperature-mortality relationship well manifests in three temperature measures, but with varied temperature thresholds for different age groups and mortality categories. Two heat waves and one cold spell were identified in 2003 and brought out excess mortality. The first heat wave lasting for 19 days had a significant impact on total non-accidental, cardiovascular and respiratory deaths compared to the corresponding reference period. The second heat wave lasting for 14 days have resulted in excess mortality in three categories of mortality but without statistical significance. The cold spell lasting for 7 days only had a significant impact on total non-accidental and cardiovascular mortality. We also found the elderly are more sensitive to temperature variation. Our results suggest that air temperature is a significant factor influencing human mortality, particularly for the elderly.
Out-of-hospital cardiac arrest (OHCA) is a notable public health issue with negative outcomes, such as high mortality and aftereffects. Additionally, the adverse effects of extreme temperatures on health have become more important under climate change; however, few studies have investigated the relationship between temperature and OHCA. In this study, we examined the association between temperature and OHCA and its underlying risk factors. We conducted a two-stage time-series analysis using a Poisson regression model with a distributed lag non-linear model (DLNM) and meta-analysis, based on a nationwide dataset from South Korea (2008-2018). We found that 17.4% of excess OHCA was attributed to cold, while 0.9% was attributed to heat. Based on central estimates, excess OHCA attributed to cold were more prominent in the population with hypertension comorbidity (31.0%) than the populations with diabetes (24.3%) and heart disease (17.4%). Excess OHCA attributed to heat were larger in the populations with diabetes (2.7%) and heart disease comorbidity (2.7%) than the population with hypertension (1.2%) based on central estimates. Furthermore, the time-varying excess OHCA attributed to cold have decreased over time, and although those of heat did not show a certain pattern during the study period, there was a weak increasing tendency since 2011. In conclusion, we found that OHCAs were associated with temperature, and cold temperatures showed a greater impact than that of hot temperatures. The effects of cold and hot temperatures on OHCA were more evident in the populations with hypertension, diabetes, and heart diseases, compared to the general population. In addition, the impacts of heat on OHCA increased in recent years, while those of cold temperatures decreased. Our results provide scientific evidence for policymakers to mitigate the OHCA burden attributed to temperature.
Understanding extreme temperature variations is important for countries to manage risks associated with climate change. Yet, the characteristics of temperature extremes and possible climate change impacts have not been adequately investigated in Singapore. In this study, we attempted to do so by defining 14 extreme temperature indices (ETIs) for the period of 1982-2018 in Singapore, and investigating the trends of those ETIs using a pre-whitening Man-Kendall test coupled with the Sen’s slope estimator method. The linear and nonlinear relationships between ETIs and El Nino Southern Oscillation (ENSO) were also examined using correlation, composite and wavelet analysis. Our results indicate that trends of temperature extremes varied according to station locations, ETIs and time scales. In all stations, ETIs such as the monthly mean value of the diurnal range between maximum and minimum temperatures (DTR), cool nights (TN10p) and cool days (TX10p) presented decreasing trends, while the rest of them exhibited increasing trends. The composite values varied for different ETIs-meaning that while eight no-threshold ETIs reflected smaller values, other ETIs reflected relatively larger composite values, indicating that ENSO may have affected those ETIs more. The ETIs were mainly statistically and significantly coherent with ENSO at a 2-8 year cycle. We hope that our findings would be beneficial for climate action planning and temperature-related disaster prevention in Singapore.
BACKGROUND: Previous studies have found that exposed to low and high outdoor temperature was associated with cardiovascular diseases morbidity and mortality. The risk factors for cardiovascular disease include high blood lipid, high uric acid (UA) and high fasting plasma glucose (FPG). However, few studies have explored the effects of low and high temperature on these metabolic indicators. OBJECTIVE: To explore the effect of low and high temperature on metabolic indicators in adults from northwest of China. METHODS: Based on a prospective cohort study, a total of 30,759 individuals who participated in both baseline and first follow-up from 2011 to 2015 were selected in this study. The meteorological observation data and environmental monitoring data were collected in the same period. Associations between cold and hot temperature and blood lipid (total cholesterol (TC), triglycerides (TG), low density lipoprotein-cholesterol (LDL-C), and high density lipoprotein-cholesterol (HDL-C)), UA and FPG were conducted with mixed effect models after adjusting for confounding factors. RESULTS: A nonlinear relationship between outdoor temperature and metabolic indicators was found. For the cold effects, each 5 °C decrease of mean temperature was associated with an increase of 5.07% (95% CI: 3.52%, 6.63%) in TG and 2.85% (95% CI: 2.18%, 3.53%) in UA, While a decrease of 3.38% (95% CI: 2.67%, 4.09%) in HDL-C and 1.26% (95% CI: 0.48%, 2.04%) in LDL-C. For the heat effects, each 5 °C increase in mean temperature was associated with 1.82% (95% CI: 0.89%, 2.76%), 0.56% (95% CI: 0.11%, 1.00%), 5.82% (95% CI: 4.58%, 7.06%), 9.02% (95% CI: 7.17%, 10.87%), 0.20% (95% CI: 0.01%, 0.40%), and 1.22% (95% CI: 0.19%, 2.24%) decrease in TC, TG, HDL-C, LDL-C, UA and FPG. Age, smoking, drinking, high-oil diet and hyperlipidemia might modify the association between mean temperature and metabolic indicators. CONCLUSION: There was a significant effect of cold and hot temperature on metabolic indicators in a high altitude area of northwestern China. These results provide a basis for understanding the underlying mechanism of the influence of temperature on metabolic diseases.
BACKGROUND: The influences of air pollution exposure and temperature on respiratory diseases have become major global health concerns. This study investigated the relationship between ambient air pollutant concentrations and temperature in cold industrial cities that have the risk of hospitalization for respiratory diseases. METHODS: A time-series study was conducted in Changchun, China, from 2015 to 2019 to analyse the number of daily admissions for respiratory diseases, air pollutant concentrations, and meteorological factors. Time-series decomposition was applied to analyse the trend and characteristics of the number of admissions. Generalized additive models and distributed lag nonlinear models were constructed to explore the effects of air pollutant concentrations and temperature on the number of admissions. RESULTS: The number of daily admissions showed an increasing trend, and the seasonal fluctuation was obvious, with more daily admissions in winter and spring than in summer and autumn. There were positive and gradually decreasing lag effects of PM10, PM2.5, NO(2), and CO concentrations on the number of admissions, whereas O(3) showed a J-shaped trend. The results showed that within the 7-day lag period, 0.5°C was the temperature associated with the lowest relative risk of admission due to respiratory disease, and extremely low and high temperatures (<-18°C, >27°C, respectively) increased the risk of hospitalization for respiratory diseases by 8.3% and 12.1%, respectively. CONCLUSIONS: From 2015 to 2019, respiratory diseases in Changchun showed an increasing trend with obvious seasonality. The increased concentrations of SO(2), NO(2), CO, PM2.5, O(3) and PM10 lead to an increased risk of hospitalization for respiratory diseases, with a significant lag effect. Both extreme heat and cold could lead to increases in the risk of admission due to respiratory disease.
Extreme temperature could affect traffic crashes by influencing road safety, vehicle performance, and drivers’ behavior and abilities. Studies evaluating the impacts of extreme temperatures on the risk of traffic crashes have mainly overlooked the potential role of vehicle air conditioners. The aim of this study, therefore, was to evaluate the effect of exposure to extreme cold and hot temperatures on seeking medical attention due to motorcycle crashes. The study was conducted in Iran by using medical attendance for motorcycle crashes from March 2011 to June 2017. Data on daily minimum, mean and maximum temperature (°C), relative humidity (%), wind velocity (km/h), and precipitation (mm/day) were collected. We developed semi-parametric generalized additive models following a quasi-Poisson distribution with the distributed nonlinear lag model to estimate the immediate and lagged associations (reported as relative risk [RR], and 95% confidence interval [CI]). Between March 2011 and June 2017, 36,079 medical attendances due to motorcycle road traffic crashes were recorded (15.8 ± 5.92 victims per day). In this time period, the recorded temperature ranged from -11.2 to 45.4 °C (average: 25.5 ± 11.0 °C). We found an increased risk of medical attendance for motorcycle crashes (based on maximum daily temperature) at both extremely cold (1st percentile) and hot (99th percentile) temperatures and also hot (75th percentile) temperatures, mainly during lags 0 to 3 days (e.g., RR: 1.12 [95% CI: 1.05: 1.20]; RR: 1.08 [95% CI: 1.01: 1.16]; RR: 1.20 [95% CI: 1.09: 1.32] at lag0 for extremely cold, hot, and extremely hot conditions, respectively). The risk estimates for extremely hot temperatures were larger than hot and extremely cold temperatures. We estimated that 11.01% (95% CI: 7.77:14.06) of the medical attendance for motorcycle crashes is estimated to be attributable to non-optimal temperature (using mean temperature as exposure variable). Our findings have important public health messaging, given the considerable burden associated with road traffic injury, particularly in low- and middle-income countries.
BACKGROUND: Out-of-hospital-cardiac arrest (OHCA) is frequently linked to environmental exposures. Climate change and global warming phenomenon have been found related to cardiovascular morbidity, however there is no agreement on their impact on OHCA occurrence. In this nationwide analysis, we aimed to assess the incidence of the OHCA events attended by emergency medical services (EMS), in relation to meteorological conditions: temperature, humidity, heat index and solar radiation. METHODS: We analyzed all adult cases of OHCA in Israel attended by EMS during 2016-2017. In the case-crossover design, we compared ambient exposure within 72 h prior to the OHCA event with exposure prior to the four control times using conditional logistic regression in a lag-distributed non-linear model. RESULTS: There were 12,401 OHCA cases (68.3% were pronounced dead-on-scene). The patients were on average 75.5 ± 16.2 years old and 55.8% of them were males. Exposure to 90th and 10th percentile of temperature adjusted to humidity were positively associated with the OHCA with borderline significance (Odds Ratio (OR) =1.20, 95%CI 0.97; 1.49 and OR 1.16, 95%CI 0.95; 1.41, respectively). Relative humidity below the 10th percentile was a risk factor for OHCA, independent of temperature, with borderline significance (OR = 1.16, 95%CI 0.96; 1.38). Analysis stratified by seasons revealed an adverse effect of exposure to 90th percentile of temperature when estimated in summer (OR = 3.34, 95%CI 1.90; 3.5.86) and exposure to temperatures below 10th percentile in winter (OR = 1.75, 95%CI 1.23; 2.49). Low temperatures during a warm season and high temperatures during a cold season had a protective effect on OHCA. The heat index followed a similar pattern, where an adverse effect was demonstrated for extreme levels of exposure. CONCLUSIONS: Evolving climate conditions characterized by excessive heat and low humidity represent risk factors for OHCA. As these conditions are easily avoided, by air conditioning and behavioral restrictions, necessary prevention measures are warranted.
Epidemiological studies have reported the association between extreme temperatures and adverse reproductive effects. However, the susceptible period of exposure during pregnancy remains unclear. This study aimed to assess the impact of extreme temperature on the stillbirth rate. We performed a time-series analysis to explore the associations between temperature and stillbirth with a distributed lag nonlinear model. A total of 22,769 stillbirths in Taiwan between 2009 and 2018 were enrolled. The mean stillbirth rate was 11.3 ± 1.4 per 1000 births. The relative risk of stillbirth due to exposure to extreme heat temperature (> 29 °C) was 1.18 (95% CI 1.11, 1.25). Pregnant women in the third trimester were most susceptible to the effects of extreme cold and heat temperatures. At lag of 0-3 months, the cumulative relative risk (CRR) of stillbirth for exposure to extreme heat temperature (29.8 °C, 97.5th percentile of temperature) relative to the optimal temperature (21 °C) was 2.49 (95% CI: 1.24, 5.03), and the CRR of stillbirth for exposure to extreme low temperature (16.5 °C, 1st percentile) was 1.29 (95% CI: 0.93, 1.80). The stillbirth rate in Taiwan is on the rise. Our findings inform public health interventions to manage the health impacts of climate change.
BACKGROUND: This study aimed to explore the effects of heatwaves and cold spells on blood pressure, thrombus formation, and systemic inflammation at admission in patients with ischemic stroke. METHODS: Data of patients with ischemic stroke who were admitted to the Second Hospital of Tianjin Medical University between May 2014 and March 2019 were reviewed, along with meteorological data from the same time period. A total of 806 clinically confirmed patients with ischemic stroke (34-97 years old) were included in the final analysis. Heatwaves and cold spells were defined as ≥2 consecutive days with average temperature >95(th) percentile (May-August) and <5(th) percentile (November-March), respectively. Coagulation parameters, inflammation indices, blood pressure, and neurological impairment were evaluated within 24 hours of admission. General linear and logistic regression models were created to investigate the relationships of heatwaves and cold spells with the examination results of patients with ischemic stroke at admission. RESULTS: After adjustment for potential environmental confounders, heatwaves were positively associated with high systolic blood pressure (SBP) (β=8.693, P=0.019), diastolic blood pressure (DBP) (β=3.665, P=0.040), reduced thrombin time (TT) (β=-0.642, P=0.027), and activated partial thromboplastin time (APTT) (β=-1.572, P=0.027) in ischemic stroke patients at admission. Cold spells were positively associated with high SBP (β=5.277, P=0.028), DBP (β=4.672, P=0.012), fibrinogen (β=0.315, P=0.011), globulin (β=1.523, P=0.011), and reduced TT (β=-0.784, P<0.001) and APTT (β=-1.062, P=0.024). Cold spells were also associated with a higher risk of respiratory infection [odds ratio (OR) =2.677, P=0.001]. CONCLUSIONS: Exposure to heatwaves or cold spells was associated with blood pressure and coagulation at admission in patients with ischemic stroke. Cold spells also resulted in higher levels of inflammation. These findings suggest that changes in coagulation, blood pressure, and inflammation may be the potential biological mechanisms underlying the cerebrovascular effects of exposure to extreme temperatures.
Day-to-day change in ambient temperature is associated with acute myocardial infarction (AMI) attacks, but evidence is scarce about the effects of extreme temperatures on the risk of AMI within hours of exposure. This study investigated the hour-level associations between extreme temperatures and AMI occurrence. State-wide data on AMI patients and temperature during winter and summer of 2013-2015 were obtained for Queensland state of Australia. We employed a fixed time-stratified case-crossover analysis to quantify the risk of AMI associated with temperature within 24 h after exposure. Subgroups analyses by age, gender and disease history were also conducted. We observed a very acute effect of cold on men (occurred 9-10 h after exposure), women (19-22 h after exposure), and the elderly (4-20 h after exposure). Cold was associated with elevated AMI risk for men within 9 h (OR = 2.1, 95 % CI: 1.2-3.6), women within 19 h (OR = 2.5, 95 % CI: 1.0-6.0), and the elderly within 4 h (OR: 2.0, 95 % CI: 1.0-4.0). However, elevated risk of AMI associated with heat occurred 15 h later for men (OR: 3.9; 95 % CI: 1.1-13.9) and 23 h later for adults (OR: 4.1, 95 % CI: 1.1-15.4). People never suffered AMI and the elderly with diabetes or hyperlipidaemia were particularly vulnerable to cold. Those that were particularly vulnerable to heat were men never experienced AMI or having hypertension or having hyperlipidaemia as well as women ever suffered AMI. Effects of temperature on AMI risk at sub-daily timescales should be considered to prevent cardiac events.
BACKGROUND: A growing number of studies have investigated the effect of increasing temperatures on morbidity and health service use. However, there is a lack of studies investigating the temperature-attributable cost burden. OBJECTIVES: This study examines the relationship of daily mean temperature with hospital admissions, length of hospital stay (LoS), and costs; and estimates the baseline temperature-attributable hospital admissions, and costs and in relation to warmer climate scenarios in Adelaide, South Australia. METHOD: A daily time series analysis using distributed lag non-linear models (DLNM) was used to explore exposure-response relationships and to estimate the aggregated burden of hospital admissions for conditions associated with temperatures (i.e. renal diseases, mental health, diabetes, ischaemic heart diseases and heat-related illnesses) as well as the associated LoS and costs, for the baseline period (2010-2015) and different future climate scenarios in Adelaide, South Australia. RESULTS: During the six-year baseline period, the overall temperature-attributable hospital admissions, LoS, and associated costs were estimated to be 3915 cases (95% empirical confidence interval (eCI): 235, 7295), 99,766 days (95% eCI: 14,484, 168,457), and AU$159 million (95% eCI: 18.8, 269.0), respectively. A climate scenario consistent with RCP8.5 emissions, and including projected demographic change, is estimated to lead to increases in heat-attributable hospital admissions, LoS, and costs of 2.2% (95% eCI: 0.5, 3.9), 8.4% (95% eCI: 1.1, 14.3), and 7.7% (95% eCI: 0.3, 13.3), respectively by mid-century. CONCLUSIONS: There is already a substantial temperature-attributable impact on hospital admissions, LoS, and costs which are estimated to increase due to climate change and an increasing aged population. Unless effective climate and public health interventions are put into action, the costs of treating temperature-related admissions will be high.
Urban heat island can exacerbate the harmful influence on human health and urban environment in historical and cultural block within Beijing Old City, China. To improve urban resilience and human well-being, protect historical and cultural heritage, nature-based solutions for urban heat mitigation are being the hotspot of research. However, only few studies focused on the comprehensive thermal environment of historical and cultural block from the social, ecological and technical aspects. Thus, we set-up scenarios combining with the three domains, to explore the cooling effect and thermal comfort improvement of Dashilar Block through ENVI-met. The results showed that 1) The areas with highest air temperature (Ta) and physiological equivalent temperature (PET) were mainly distributed in Peizhi Hutong and Zongshu Toutiao. 2) Five mitigation scenarios adapting to historical protection requirements and public preferences were vertical greening, traditional greening, quality improvement greening, high-albedo paving, and comprehensive. 3) The comprehensive and vertical greening scenarios could reduce the mean Ta of whole block by 1.01 degrees C or 0.38 degrees C, decrease the percentage of Ta hotter zone by 13.87% or 19.63%, and reduce the local Ta inside the block by 0.65 degrees C-1.80 degrees C or 0.33 degrees C-1.05 degrees C, respectively, which turned out the cooling effect and thermal comfort improvement of abovementioned two scenarios could significantly alleviate the heat stress. The comprehensive and vertical greening can act as the preferred nature-based solution for heat mitigation in Dashilar Block. We believed that this study would provide novel insights into the balance between urban heat mitigation and heritage protection during the renewal of Beijing Old City.
Extreme heat events caused by climate change have serious adverse effects on residents’ health in many coastal metropolises in southeast China. Adaptive capacity (AC) is crucial to reduce heat vulnerability in the human-environment system. However, it is unclear whether changes in individual characteristics and socioeconomic conditions likely amplify or attenuate the impacts of residents’ heat adaptive capacity (HAC) changes. Moreover, which public policies can be implemented by the authorities to improve the HAC of vulnerable groups remains unknown. We conducted a questionnaire survey of 630 residents of Xiamen, a typical coastal metropolis, in 2018. The effects of individual and household characteristics, and government actions on the residents’ HAC were examined by using ordinal logistic regression analysis. Results show that the majority (48.10%) of Xiamen residents had a “medium” HAC level, followed by a “high” level (37.14%). On Xiamen Island, residents who settled locally for one-three years and spent less than one hour outdoors might report weaker HAC, and their HAC would not improve with increased air conditioning units in household. In other areas of Xiamen, residents with more rooms in their households, no educational experience, and building areas <50 m(2) might report better HAC. Further, vulnerable groups, such as local residents and outdoor workers on Xiamen Island, people lacking educational experience and renters in other areas of Xiamen, showed better AC to hot weather than those in previous studies. Low-income groups should be given more attention by local governments and community groups as monthly household income played a positive role in improving Xiamen residents' HAC. Rational green spaces planning and cooling services, such as street sprinkling operations, provided by municipal departments can effectively bring benefits to Xiamen residents. Identification of basic conditions of AC has significant implications for practical promoting targeted measures or policies to reduce health damages and livelihood losses of urban residents during extreme heat events.
BACKGROUND: Workplace heat exposure can cause a series of heat-related illnesses and injuries. Protecting workers especially those undertake work outdoors from the risk of heat strain is a great challenge for many workplaces in China under the context of climate change. The aim of this study is to investigate the perceptions and adaptation behaviors of heat exposure among construction workers and to provide evidence for the development of targeted heat adaptation strategies nationally and internationally. METHODS: In 2020, we conducted a cross-sectional online questionnaire survey via WeChat Survey Star in China, using a purposive snowball sampling approach. A total of 326 construction workers submitted completed questionnaires. The perceptions of workplace heat exposure were measured using seven indicators: concerns over high temperature, perception of high temperature injury, attitudes towards both heat-related training and regulations, adjustment of working habits during heat, heat prevention measures in the workplace, and reduction of work efficiency. Bivariate and multivariate regression analyses were used to identify the factors significantly associated with workers’ heat perceptions and behavioral responses. RESULTS: 33.3% of the respondents were moderately or very concerned about heat exposure in the workplace. Less than half of the workers (43.8%) were worried about heat-related injuries. Workers who have either experienced work-related injuries (OR=1.30, 95% CI 1.03-1.62) or witnessed injuries to others during high temperatures (OR=1.12, 95% CI 1.02-1.27) were more concerned about heat exposure compared to other workers. Most respondents (63.5%) stated that their work efficiency declined during extremely hot weather. The factors significantly associated with a reduction of work efficiency included undertaking physically demanding jobs (OR=1.28, 95% CI 1.07-1.54) and witnessing other workers’ injuries during high temperatures (OR=1.26, 95% CI 1.11-1.43). More than half of the workers were willing to adjust their work habits to adapt to the impact of high temperatures (81.6%). The internet was the most common method to obtain heat prevention information (44.7%), and the most frequently used heat prevention measure was the provision of cool drinking water (64.8%). CONCLUSIONS: Chinese construction workers lack heat risk awareness and are not well prepared for the likely increasing heat exposure in the workplace due to global warming. Therefore, there is a need to improve their awareness of heat-related injuries, strengthen high temperature related education and training, and update the current heat prevention policies to ensure compliance and implementation.
Older people are more vulnerable to climate change and with its increasing elderly population, inadequate research on the health impacts of climate change has focused on this particular population in China. This study evaluates climate change and health-related knowledge, attitudes and practices (KAP) of elderly residents in three cities Suzhou, Hefei and Xiamen. This cross-sectional study included 3466 participants. Data analysis was undertaken using descriptive methods (Chi-square test). Results showed that the elderly were most concerned about heatwaves, flooding and drought and the main perceived health risks included heatstroke and respiratory diseases. Finally, over half of the participants from Suzhou city reported that they did not receive enough government assistance in extreme events (56%). Findings from this work provide important insights for new adaptation strategies targeting the elderly population. It is recommended that the government should focus on creating awareness of the necessary adaptations the elderly will need to take to alleviate the impact of climate change on their physical health.
Background: Short-term heat exposure might induce stroke morbidity and mortality, and there were several studies explored the possible vulnerable populations. At present, the research on the modification effect of intra-urban landscape characteristics on the association between heat and stroke morbidity is limited, especially in China. Methods: We collected data on 22,424 first-ever strokes between 2010 and 2016 in Shenzhen, from June to August of each year. We adopted the case-only study combined with logistic regression models to examine the modification effects of 5 urban landscape characteristics. We studied the characteristics of relevant vulnerable populations through stratification analyses. Results: High values (refer to the median values) of nighttime land surface temperature (LST) and the proportion of impervious surface may aggravate the harmful effects of heat on stroke morbidity, with the OR values (95% CI) of 1.205 (1.053, 1.357) and 1.115 (1.010, 1.220); while, high values of NDVI and the proportion of water bodies may alleviate the harmful effects of heat, with the OR values (95% CI) of 0.772 (0.699, 0.845) and 0.821 (0.741, 0.901). The OR value of daytime LST was 1.004 (0.861, 1.147). Statistically significant modification effects were located in the population without Shenzhen’s household registration; as for nighttime LST, statistically significant modification effects were located in females and the elderly. Conclusions: High values of nighttime LST and the proportion of impervious surface might aggravate the harmful effects of heat on stroke morbidity, while high green space and water cover might alleviate its effects. Immigrants were the related vulnerable populations. The government should take measures to cope with climate warming and pay attention to the health effects of heat on immigrants. (c) 2021 Published by Elsevier B.V.
Introduction: Cardiovascular disease is one of the leading causes of mortality worldwide. Acute myocardial infarction (AMI) is associated with weather change. The study aimed to investigate if weather change was among the risk factors of coronary artery disease to influence AMI occurrence in Taiwan and to generate a model to predict the probabilities of AMI in specific weather and clinical conditions. Method: This observational study utilized the National Health Insurance Research Database and daily weather reports from Taiwan Central Weather Bureau to evaluate the discharge records of patients diagnosed with AMI from various hospitals in Taiwan between January 1, 2008 and December 31, 2011. Generalized additive models (GAMs) were used to estimate the effective parameters on the trend of the AMI incidence rate with respect to the weather and health factors in the time-series data and to build a model for predicting AMI probabilities. Results: A total of 40,328 discharges were listed. The minimum temperature, maximum wind speed, and antiplatelet therapy were negatively related to the daily AMI incidence; however, a drop of 1° when the air temperature was below 15°C was associated with an increase of 1.6% of AMI incidence. By using the meaningful parameters including medical and weather factors, an estimated GAM was built. The model showed an adequate correlation in both internal and external validation. Conclusion: An increase in AMI occurrence in colder weather has been evidenced in the study, but the influence of wind speed remains uncertain. Our analysis demonstrated that the novel GAM model can predict daily onset rates of AMI in specific weather conditions.
Little evidence about the effects of cold spells on serum lipid levels is available. The aim of this study was to explore the association between cold spells and serum lipid levels among the elders in Jinan, China. Data of old adults from health check-up program in Shandong Provincial Qianfoshan Hospital was collected for this study. Linear mixed models combined with distributed lag nonlinear models were used to examine the relationship between cold spells and serum lipid levels, considering the confounding effects of age, sex, blood pressure, body mass index, and other meteorological factors. Subgroup analysis by gender and analysis based on different definitions of cold spells were also conducted. Increased TG levels in lag 0-lag 2 days and decreased TG levels in lag 5-lag 8 days after cold spells were observed among the elders. The largest increase was 0.363 mmol/L (95% CI: 0.184 ~ 0.543) in lag 0 day, while the largest decreased TG levels was 0.083 mmol/L (95% CI: 0.147 ~ 0.019) in lag 6 day. Similar results were obtained in the analysis of different sex and based on different definitions of cold spells. However, no significant association was found between cold spells with TC, LDL-C, and HDL-C. This study indicates that cold spells were significantly associated with serum TG levels in the elders. Effective preventive measures should be implemented around the cold spells to reduce the volatility of serum lipid levels and the occurrence of subsequent cardiovascular diseases.
Background The association between ambient temperature and cardiovascular diseases has been well established, but evidence of temporal changes in the risk of acute aortic dissection (AAD) onset is lacking. Methods and Results We conducted an 8-year time-series study based on data from 2120 patients diagnosed with AAD at Tongji Hospital (Wuhan, China). Daily meteorological parameters were measured in the study area. Spearman’s rank correlation analysis was applied to measure the associations between daily meteorological data and air pollution indicators. A distributed lag nonlinear model following quasi-Poisson regression was used to express the nonlinear exposure-response relationships and lag effects of daily mean temperature and temperature variability on the occurrence of AAD. Considering a 25-day lag effect, lower or higher temperatures with reference to 25°C did not alter the onset risk of AAD. The lag effect of daily mean temperature on the incidence of AAD is statistically significant within 2 days, and the impact of daily mean temperature on the risk is most influential on the day. The exposure-response curve between daily mean temperature and onset risks of AAD at lag 0 showed that the extremely cold temperature (2.5th percentile, 0.5°C) significantly increased the AAD risk for the total (relative risk, 1.733; 95% CI, 1.130-2.658) and type A dissection (relative risk, 3.951; 95% CI, 1.657-9.418). Temperature variability within 1 week did not affect the onset risks of AAD for the total. Conclusions We confirmed that extremely cold temperatures significantly increased the AAD risk, which could contribute to early prevention and timely diagnosis of the disease.
Playgrounds in urban parks are important for children’s physical and mental health, but global warming has led to a worsening outdoor environment and children’s outdoor activities have been affected. Improving the outdoor thermal comfort (OTC) of playgrounds can encourage children to engage in more and safer outdoor activities. However, there are a limited number of studies focusing on preschoolers’ outdoor thermal comfort (OTC) and most of them have substituted children’s thermal comfort with caregivers’ evaluations. To investigate the differences between children’s and caregivers’ evaluations of thermal sensation, thermal benchmarks and thermal adaptive behavior for children, we conducted meteorological measurements on representative playgrounds in three parks in Wuhan, China, and administered thermal perception questionnaires to preschool children and their caregivers. In addition, the Physiological Equivalent Temperature (PET) was used to establish evaluation criteria for children’s OTC and to make recommendations for the improvement of the playground environment. We draw five conclusions by analyzing 719 valid questionnaires: (1) Children were less sensitive to changes in meteorological factors than caregivers and had better tolerance of cold environments. (2) The NPET for preschoolers was evaluated by children and by caregivers, respectively, as 22.9 degrees C and 22.3 degrees C in summer and 10.6 degrees C and 11.2 degrees C in winter. (3) Playgrounds in Wuhan’s parks are uncomfortable for a long time in summer and a short time in winter. (4) Both children and caregivers want to improve summer comfort by lowering the temperature and winter comfort by increasing solar radiation. At the same time, children and caregivers show different preferences in adaptive behavior choices. (5) Adding deciduous trees and water play facilities can improve the site thermal environment. Furthermore, the OTC of humans can be improved by adding more service facilities on playgrounds.
Due to limits to standard methods for surveying outdoor thermal comfort (OTC), it is difficult to compare thermal benchmarks and thermal index calibrations among studies and climatic regions. Using uniform standard meteorological measurements and questionnaire surveys, our study conducted an OTC study in urban parks in Beijing, Xi’an and Hami; representative of cities in China’s cold regions. The Universal Thermal Climate Index (UTCI) was used as the thermal comfort index, and differences in residents’ thermal perceptions and outdoor thermal benchmarks among these cities were compared. Results showed that: 1) air temperature (T(a)) and globe temperature (T(g)) were two primary factors affecting residents’ thermal sensations in the three cities during winter. Residents’ thermal sensation in Beijing and Hami was negatively correlated with wind speed (V(a)). Residents in Xi’an and Hami preferred a higher relative humidity (RH). Residents in Beijing and Hami preferred a lower V(a) to improve OTC related to local climatic characteristics. 2) Xi’an residents had the highest neutral UTCI (NUTCI) (17.3 °C), followed by Beijing (17.0 °C) and Hami (6.4 °C). Xi’an residents had slightly wider neutral UTCI range (NUTCIR) (7.9-26.7 °C) compared to Beijing (8.7-25.4 °C), while Hami residents had the narrowest NUTCIR (1.5-11.3 °C). The “no thermal stress” range in the three cities was 6.1-26.0 °C in Beijing, 6.7-25.5 °C in Xi’an, and -2.2-12.2 °C in Hami. 3) Calibrated thermal indices, based on the ASHRAE 7-point scale, were gained to judge the thermal qualities of an environment for all three cities.
BACKGROUND: The existing evidence suggests that pre-existing diabetes may modify the association between heat and hospitalizations for acute myocardial infarction (AMI). METHODS: This study included patients who were hospitalized for AMI from 1 January 2005 to 31 December 2013 in Brisbane, Australia, and also included those who died within 2 months after discharge. A time-stratified case-crossover design with conditional logistic regression was used to quantify the associations of heat and cold with hospitalizations and post-discharge deaths due to AMI in patients with and without pre-existing diabetes. Stratified analyses were conducted to explore whether age, sex and suburb-level green space and suburb-level socio-economic status modified the temperature-AMI relationship. Heat and cold were defined as the temperature above/below which the odds of hospitalizations/deaths due to AMI started to increase significantly. RESULTS: There were 14 991 hospitalizations for AMI and 1811 died from AMI within 2 months after discharge during the study period. Significant association between heat and hospitalizations for AMI was observed only in those with pre-existing diabetes (odds ratio: 1.19, 95% confidence interval: 1.00-1.41) [heat (26.3°C) vs minimum morbidity temperature (22.2°C)]. Cold was associated with increased odds of hospitalizations for AMI in both diabetes and non-diabetes groups. Significant association between cold and post-discharge deaths from AMI was observed in both diabetes and non-diabetes groups. CONCLUSIONS: Individuals with diabetes are more susceptible to hospitalizations due to AMI caused by heat and cold.
Climate may significantly affect human society. Few studies have focused on the temperature impact on residents’ health, especially mental health status. This paper uses 98 423 observations in China to study the relationship between temperature and health, based on the China Family Panel Studies survey during 2010-16. We analyze the health effects of extreme hot and cold weather and compare the effects under different social demographic factors including gender, age, and income. We find that temperature and health status exhibit a nonlinear relationship. Women and low-income households are more likely to be impacted by extreme cold, whereas men, the elderly, and high-income households are more sensitive to extreme heat. Our results highlight the potential effects of extreme temperatures on physical and mental health and provide implications for future policy decisions to protect human health under a changing climate.
OBJECTIVE: We aimed to examine the temporal trends of the association between extreme temperature and schizophrenia (SCZ) hospitalisations in Hefei, China. METHODS: We collected time-series data on SCZ hospitalisations for 10 years (2005-2014), with a total of 36 607 cases registered. We used quasi-Poisson regression and distributed lag non-linear model (DLNM) to assess the association between extreme temperature (cold and heat) and SCZ hospitalisations. A time-varying DLNM was then used to explore the temporal trends of the association between extreme temperature and SCZ hospitalisations in different periods. Subgroup analyses were conducted by age (0-39 and 40+ years) and gender, respectively. RESULTS: We found that extreme cold and heat significantly increased the risk of SCZ hospitalisations (cold: 1st percentile of temperature 1.19 (95% CI 1.04 to 1.37) and 2.5th percentile of temperature 1.16 (95% CI 1.03 to 1.31); heat: 97.5th percentile of temperature 1.37 (95% CI 1.13 to 1.66) and 99th percentile of temperature 1.38 (95% CI 1.13 to 1.69)). We found a slightly decreasing trend in heat-related SCZ hospitalisations and a sharp increasing trend in cold effects from 2005 to 2014. However, the risk of heat-related hospitalisation has been rising since 2008. Stratified analyses showed that age and gender had different modification effects on temporal trends. CONCLUSIONS: The findings highlight that as temperatures rise the body’s adaptability to high temperatures may be accompanied by more threats from extreme cold. The burden of cold-related SCZ hospitalisations may increase in the future.
To examine the associations between ambient temperature and hospitalizations for acute kidney injury (AKI) in Queensland, Australia, 1995-2016. Data were collected on a total of 34 379 hospitalizations for AKI from Queensland between 1 January 1995 and 31 December 2016. Meteorological data were downloaded from the Queensland Government’s Department of Environment and Science. We assessed the temperature-AKI relationship using a time-stratified case-crossover design fitted with conditional quasi-Poisson regression model and time-varying distributed lag non-linear model. Stratified analyses were performed by age, sex, climate zone and socioeconomic group. Both cold and hot temperatures were associated with hospitalizations for AKI. There were stronger temperature-AKI associations among women than men. Cold effects were only positive in the > 70 years age group. Hot effects were stronger in the <= 59 years age group than in the >60 years age group. In different climate zone areas, cold effects decreased with increasing local mean temperatures, while hot effects increased. In different socio-economic status groups, hot effects were stronger in the poor areas than the affluent areas. From 1995 to 2016, the magnitude of associations between cold temperature and hospitalizations for AKI decreased, while the hot effect increased. The associations between hot temperature and hospitalizations for AKI become stronger, while the magnitude of cold effect decreased from 1995 to 2016. This trend may accelerate over the coming decades, which warrants further research. More attention is needed toward susceptible population including women, people > 70 years, and the people living in hot climate zones and in low socioeconomic status areas.
This study aimed to estimate respiratory disease hospitalization costs attributable to ambient temperatures and to estimate the future hospitalization costs in Australia. The associations between daily hospitalization costs for respiratory diseases and temperatures in Sydney and Perth over the study period of 2010-2016 were analyzed using distributed non-linear lag models. Future hospitalization costs were estimated based on three predicted climate change scenarios-RCP2.6, RCP4.5 and RCP8.5. The estimated respiratory disease hospitalization costs attributable to ambient temperatures increased from 493.2 million Australian dollars (AUD) in the 2010s to more than AUD 700 million in 2050s in Sydney and from AUD 98.0 million to about AUD 150 million in Perth. The current cold attributable fraction in Sydney (23.7%) and Perth (11.2%) is estimated to decline by the middle of this century to (18.1-20.1%) and (5.1-6.6%), respectively, while the heat-attributable fraction for respiratory disease is expected to gradually increase from 2.6% up to 5.5% in Perth. Limitations of this study should be noted, such as lacking information on individual-level exposures, local air pollution levels, and other behavioral risks, which is common in such ecological studies. Nonetheless, this study found both cold and hot temperatures increased the overall hospitalization costs for respiratory diseases, although the attributable fractions varied. The largest contributor was cold temperatures. While respiratory disease hospitalization costs will increase in the future, climate change may result in a decrease in the cold attributable fraction and an increase in the heat attributable fraction, depending on the location.
BACKGROUND: Extreme temperatures are associated with the risk of preterm birth (PTB), but evidence on the effects of different clinical subtypes and across different regions is limited. We aimed to evaluate the effects of maternal exposure to extreme temperature on PTB and its clinical subtypes in China, and to identify effect modification of regional factors in dimensions of population, economy, medical resources and environmental factors. METHODS: This was a prospective population-based cohort of 210,798 singleton live births from 16 counties in eight provinces across China during 2014-2018. We used an extended Cox regression with time-varying variables to evaluate the effects of extreme heat and cold on PTB and its subtypes in the entire pregnancy, each trimester, the last gestational month and week. Meta-analysis and meta-regression were conducted to estimate the pooled effects of each city and effect modification by regional characteristics. FINDINGS: Exposure to heat and cold during the entire pregnancy significantly increased the risk of PTB. The effects varied with subtypes, for medically indicated and spontaneous PTB, hazard ratios were 1·84 (95% CI: 1·29, 2·61) and 1·50 (95% CI: 1·11, 2·02) for heat, 2·18 (95% CI: 1·83, 2·60) and 2·15 (95% CI: 1·92, 2·41) for cold. The associations were stronger for PTB less than 35 weeks than those during weeks 35-36. The effects varied across locations, and GDP per capita (β=-0·16) and hospital beds per 1000 persons (β=-0·25) were protective factors for the effects. INTERPRETATION: Extreme temperature can increase the risk of medically indicated and spontaneous PTB, and higher regional socio-economic status may moderate such effects. In the context of climate change, such findings may have important implications for protecting the health of vulnerable groups, especially newborns. FUNDING: National Key R&D Program of China (2018YFA0606200), National Natural Science Foundation of China (42175183), Strategic Priority Research Program of the Chinese Academy of Sciences (XDA20030302), National Natural Science Foundation of China (42071377).
Extreme temperatures were considered natural hazards because they could increase morbidity and mortality. Understanding the extreme temperature changes at different warming levels is crucial to climate change mitigation and adoption for human health. This study projected climate change effects on the intensity, occurrence, and duration of extreme temperatures in Taiwan with 2 and 4 degrees C global warming scenarios using the Weather Research and Forecasting model. The future climate simulations were conducted with the pseudo-global warming approach, and the future climate changes were obtained from the ensemble mean of simulations in the Coupled Model Intercomparison Project 5. The simulated daily mean temperature increased by 1.40 and 3.09 degrees C under 2 and 4 degrees C global warmings. In a warming world, the daily maximum temperature was projected to increase by 1.35-3.00 degrees C, whereas the daily minimum temperature was even higher, leading to weaker diurnal temperature variation in most regions. The simulation results show that intensified heatwaves with frequent and prolonged durations become par for the course, whereas extremely cold days disappear gradually. The occurrence of heatwaves in the future is projected to be five times that in the current climate. Comparing the global warming impacts over different land-use types, the heatwave occurrence over urban areas rose more quickly than over other land-use types; forests are less vulnerable to global warming. On the contrary, the changes in extremely cold days over urban areas were weaker than over other land-use types. Overall, the effects of global warming on temperature revealed that extreme events were more severe with increased temperature than with the mean state of air temperature. Nonlinear behaviours indicated that global warming should be limited to 2 degrees C, and the additional 2 degrees C warming (from 2 to 4 degrees C) should be addressed carefully.
Although numerous studies have investigated premature deaths attributable to temperature, effects of temperature on years of life lost (YLL) remain unclear. We estimated the relationship between temperatures and YLL, and quantified the YLL per death caused by temperature in China. We collected daily meteorological and mortality data, and calculated the daily YLL values for 364 locations (2013-2017 in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces, and 2006-2011 in other locations) in China. A time-series design with a distributed lag nonlinear model was first employed to estimate the location-specific associations between temperature and YLL rates (YLL/100,000 population), and a multivariate meta-analysis model was used to pool location-specific associations. Then, YLL per death caused by temperatures was calculated. The temperature and YLL rates consistently showed U-shaped associations. A mean of 1.02 (95% confidence interval: 0.67, 1.37) YLL per death was attributable to temperature. Cold temperature caused 0.98 YLL per death with most from moderate cold (0.84). The mean YLL per death was higher in those with cardiovascular diseases (1.14), males (1.15), younger age categories (1.31 in people aged 65-74 years), and in central China (1.34) than in those with respiratory diseases (0.47), females (0.87), older people (0.85 in people ≥75 years old), and northern China (0.64) or southern China (1.19). The mortality burden was modified by annual temperature and temperature variability, relative humidity, latitude, longitude, altitude, education attainment, and central heating use. Temperatures caused substantial YLL per death in China, which was modified by demographic and regional characteristics.
People in urban agglomerations (UAs) are increasingly exposed to elevated extreme temperature events under global warming and local human activities such as urbanization. While the urbanization effects on local temperature changes have been well studied, possibly different effects on human perceived temperature (HPT), which measures the compound influences of multiple indicators (e.g., temperature, humidity, and wind), remain much less understood. Here, we examine the long-term changes in mean and extreme HPT in 20 major UAs across the mainland of China since the 1970s, and evaluate the effect of urbanization based on a dynamic classification of urban and rural stations using time-varying land use/land cover maps. The results show that mean HPT and actual near-surface air temperature (T) in both summer and winter seasons display significant trends in most portions of China, while the frequency of extreme HPT and T events in summer (winter) exhibits increasing (decreasing) tendency. These trends are particularly stronger in more populated and urbanized UAs. It is estimated that urbanization averagely accounts for around 1/6 of the total increasing trend in mean HPT and T in the urban core areas of 20 UAs. In both seasons, the effects of urbanization on mean HPT are more profound than T. Moreover, urbanization significantly increases the occurrence frequency of summertime hot extremes and decreases the occurrence of wintertime cold events. Regionally, northern UAs in general exhibit more remarkable trends than the south. The urbanization process exerts more prominent effects in HPT than T in nearly three-quarters of all UAs, except several regions with a complex topography and lower urbanization level. These findings reported here can provide suggestions and support for urban planning of decision-maker and human perceived thermal comfort choices of humans living in UAs.
BACKGROUND: Non-optimal temperatures are associated with mortality risk, yet the heterogeneity of temperature-attributable mortality burden across subnational regions in a country was rarely investigated. We estimated the mortality burden related to non-optimal temperatures across all provinces in China in 2019. METHODS: The global daily temperature data were obtained from the ERA5 reanalysis dataset. The daily mortality data and exposure-response curves between daily temperature and mortality for 176 individual causes of death were obtained from the Global Burden of Disease Study 2019 (GBD 2019). We estimated the population attributable fraction (PAF) based on the exposure-response curves, daily gridded temperature, and population. We calculated the cause- and province-specific mortality burden based on PAF and disease burden data from the GBD 2019. FINDINGS: We estimated that 593·9 (95% UI:498·8, 704·6) thousand deaths were attributable to non-optimal temperatures in China in 2019 (PAF=5·58% [4·93%, 6·28%]), with 580·8 (485·7, 690·1) thousand cold-related deaths and 13·9 (7·7, 23·2) thousand heat-related deaths. The majority of temperature-related deaths were from cardiovascular diseases (399·7 [322·8, 490·4] thousand) and chronic respiratory diseases (177·4 [141·4, 222·3] thousand). The mortality burdens were observed significantly spatial heterogeneity for both high and low temperatures. For instance, the age-standardized death rates (per 100 000) attributable to low temperature were higher in Western China, with the highest in Tibet (113·7 [82·0, 155·5]), while for high temperature, they were greater in Xinjiang (1·8 [0·7, 3·3]) and Central-Southern China such as Hainan (2·5 [0·9, 5·4]). We also observed considerable geographical variation in the temperature-related mortality burden by causes of death at provincial level. INTERPRETATION: A substantial mortality burden was attributable to non-optimal temperatures across China, and cold effects dominated the total mortality burden in all provinces. Both cold- and heat-related mortality burden showed significantly spatial variations across China. FUNDING: National Key Research and Development Program.
Little is known about the association between air temperature and causes-specific respiratory diseases (RD), especially in northwest China. A time-stratified case crossover design with a distributed lag nonlinear model (DLNM) was conducted to assess the nonlinear and delayed ef-fects of temperature on total and cause-specific outpatient visits, with analyses stratified by gender and age. The cumulative effects of temperature were irregular M-shaped curves for total and upper respiratory tract infection (URTI), with inverted U-shaped curve for pneumonia, bronchitis and chronic obstructive pulmonary disease (COPD). Positive cold and heat effects were observed for URTI, pneumonia, bronchitis and COPD, bronchitis was most vulnerable to cold but pneumonia was more affected to heat. Heat effects were immediate whereas cold effects were delayed and lasted longer. The magnitude of temperature effects varies greatly by age, gender, and disease. Notably, the cold effect was greater for children aged 0-14 than that of other age groups. This study suggested that both cold and hot temperatures exposure could increase all-cause and cause-specific respiratory outpatient visits in Lanzhou, China. The harmful effect and duration of cold were greater than that of heat, and children aged 0-14 were more sensitive to cold. Protection against extreme temperatures should be strengthened.
BACKGROUND: Evidence is scant on the relative and attributable contributions of ambient temperature on stroke subtypes mortality. Few studies have examined modification effects of multiple greenness indicators on such contributions, especially in China. We quantified the associations between ambient temperature and overall, ischemic, and hemorrhagic stroke mortality; further examined whether the associations were modified by greenness. METHODS: We conducted a multicenter time-series analysis from January 1, 2013 to December 31, 2019. we adopted a distributed lag non-linear model to evaluate county-specific temperature-stroke mortality associations. We then applied a random-effects meta-analysis to pool county-specific effects. Attributable mortality was calculated for cold and heat, defined as temperatures below and above the minimum mortality temperature (MMT). Finally, We conducted a multivariate meta-regression to determine associations between greenness and stroke mortality risks for cold and heat, using normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), and enhanced vegetation index (EVI) as quantitative indicators of greenness exposure. RESULTS: In the study period, 138,749 deaths from total stroke were reported: 86,873 ischemic and 51,876 hemorrhagic stroke. We observed significant W-shaped relationships between temperature and stroke mortality, with substantial differences among counties and regions. With MMT as the temperature threshold, 17.16 % (95 % empirical CI, 13.38 %-19.75 %) of overall, 20.05 % (95 % eCI, 16.46 %-22.70 %) of ischemic, and 12.55 % (95 % eCI, 5.59 %-16.24 %) of hemorrhagic stroke mortality were attributable to non-optimum temperature (combining cold and heat), more mortality was caused by cold (14.94 %; 95 % eCI, 11.57 %-17.34 %) than by heat (2.22 %; 95 % eCI, 1.54 %-2.72 %). Higher levels of NDVI, SAVI and EVI were related to mitigated effects of non-optimum temperatures-especially heat. CONCLUSIONS: Exposure to non-optimum temperatures aggravated stroke mortality risks; increasing greenness could alleviate that risks. This evidence has important implications for local communities in developing adaptive strategies to minimize the health consequences of adverse temperatures.
Limited evidence is available on apparent temperature (AT) and hospital admissions for acute cardiac events. We examined the associations of AT with admissions for acute cardiac events and acute coronary syndrome (ACS), and explored the effect difference between ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction ACS (NSTE-ACS). Poisson regression with distributed lag non-linear model was applied to examine the temperature-lag-admission associations. Stratified analyses were performed by gender and age-groups for acute cardiac events. A total of 11,657 acute cardiac events admissions were collected from hospital-based chest pain centers in Beijing, during 2017-2019. The single day effect of low AT (-11 degrees C, 2.5th percentile) appeared on the 2nd day and persisted until the 11th day, with estimated relative risk (RR) ranging from 1.44 (95% CI: 1.159, 1.790) to 1.084 (95% CI: 1.022, 1.150) for acute cardiac events and from 1.034 (95% CI: 1.010, 1.059) to 1.006 (95% CI: 1.000, 1.011) for ACS. The single day effect of high AT (34 degrees C, 97.5th percentile) was only observed on the current day. The cold effect on acute cardiac events was more pronounced among female and older patients. The cumulative effect of high AT on STEMI admissions and low AT on NSTE-ACS reached a peak RR peak of 2.545 (95% CI: 1.016, 6.375) and 3.71 (95% CI: 1.315, 10.469) on lag 0-6 days, respectively. Both high and low ATs were associated with increased risk of acute cardiac events and ACS admissions. STEMI admissions may be more sensitive to high AT while NSTE-ACS to low AT.
BACKGROUND: Most studies have focused on the relationship between ambient temperature and stroke mortality, but studies on the relationship between ambient temperature and stroke occurrence are still limited and inconsistent. OBJECTIVE: This study aimed to analyze the effect of ambient temperature and other environmental factors on emergency stroke visits in Beijing. METHODS: Our study utilized stroke visit data from the Beijing Red Cross Emergency Medical Center during 2017-2018, and applied a generalized additive model (GAM) as well as a distributed lag non-linear model (DLNM), respectively, regarding the direct, lagged, and cumulative effects of ambient temperature alone and with correction for other environmental factors on stroke occurrence. RESULTS: With a total of 26,984 emergency stroke patients in 2017-2018, both cold and hot effects were observed and weakened after correction for other environmental factors. Compared to the reference temperature, in the multi-factor model, extreme cold (-10°C) reached a maximum relative risk (RR) of 1.20 [95% Confidence Interval (CI): 1.09, 1.32] at lag 14 days, and extreme hot (30°C) had a maximum RR of 1.07 (95% CI: 1.04, 1.11) at lag 6 days. The cumulative effect of extreme cold reached a maximum of 2.02 (95% CI: 1.11, 3.67) at lag 0-14 days, whereas the cumulative effect of extreme hot temperature is greatest at lag 0-10 days, but no statistically significant effect was found. In addition, ischemic stroke patients, the elderly, and males were more susceptible to the effects of cold temperature. CONCLUSIONS: There is a non-linear relationship between ambient temperature and stroke occurrence, with cold temperature having a greater and longer-lasting impact than hot temperature.
By using 64,270 daily observations from a large hospital in Guangzhou between 2017 and 2019, we analyzed the impact of extreme temperature on the health of newborns via OLS regression with time fixed effect. Given that the short-term temperature change can be regarded as exogenous and random, solving the potential endogenous problem is critical. We find that extreme temperature negatively affects the health of newborns. The Apgar score, an index for evaluating neonatal health, decreases by 0.008 (0.029%) when the duration of extreme temperature events increases by a day. A series of robustness checks verify the reliability of this negative effect. Extreme temperature also has a particularly serious effect on the health of newborns whose mothers have poor education. By gradually extending the observation period, we find that the effect of extreme temperature on neonatal health is mainly concentrated 1-6 weeks before delivery, whereas the effect of extreme temperature on hospitalization cost is mainly concentrated 4-8 weeks before delivery. This paper provides a valuable reference for evaluating the health and social costs of extreme weather, and our findings are conducive to the construction of climate resilient health systems, especially in Guangzhou.
BACKGROUND: Previous studies have shown negative relationships between ambient temperature and blood pressure (BP). However, few studies estimated temperature-adjusted hypertension prevalence and control rate in different population. OBJECTIVE: To estimate the effects of temperature on BP, and further calculate temperature-adjusted hypertension prevalence and control rate. METHODS: Meteorological and BP data in Guangdong Province from 2004 to 2015 were collected. There were 31 351 participants aged 18 years and over. Based on 2018 European society Arterial Hypertension Guidelines, participants were divided into normotensive patients (n = 23 046), known hypertensive patients (n = 2807), and newly detected hypertensive patients (n = 5498). We first used generalized additive model to establish the nonlinear relationship between daily mean temperature and BP, and then calculated the linear effects of temperature on BP among populations with different hypertension status. Finally, we calculated the temperature-adjusted hypertension prevalence and control rate. RESULTS: Generally, there is an inverse relationship between temperature and BP. For a 1 °C increase in temperature, the decreased SBPs for normotensive patients, newly detected hypertensive patients, and known hypertensive patients were 0.37 [95% confidence interval (CI): -0.40, -0.33] mmHg, 0.21 (95% CI: -0.32, -0.10) mmHg and 0.81 (95% CI: -1.02, -0.59) mmHg, while reduced DBPs were 0.19 (95% CI: -0.21, -0.16) mmHg, 0.01 (95% CI: -0.06,0.08) mmHg, and 0.44 (95% CI: -0.56, -0.32) mmHg, respectively. At 5, 10, 15, 20, and 25 °C, the hypertension prevalence rates were 32.5, 29.7, 27.7, 26.0, and 25.0%, respectively, and the control rates were 12.0, 17.5, 23.5, 30.1, and 37.1%, respectively. CONCLUSION: Low temperature increased BP for all populations, especially for known hypertensive patients, which makes hypertension prevalence increase and control rate decrease if temperature reduce. Our findings suggest that temperature should be considered in hypertension clinic management and epidemiological survey.
BACKGROUND: Few studies have explored the role of ambient temperature in asthma exacerbation. OBJECTIVE: We aimed to explore the association of temperature with diurnal peak expiratory flow (PEF) variation and asthma exacerbation. METHOD: We developed a longitudinal study among asthmatic adults in 18 Chinese cities. Subjects recorded PEF in dynamic pulmonary function monitoring from 2017 to 2020. Linear mixed-effect model and generalized additive model with distributed non-linear models were used to assess the effect of temperature and temperature change between neighboring days (TCN) on diurnal PEF variation and the risk of asthma exacerbation. RESULT: We evaluated a total of 79,217 daily PEF monitoring records from 4467 adult asthmatic patients. There were significant increase of diurnal PEF variation and higher risk of asthma exacerbation with cold and sudden temperature drop. Compared with the referent temperature (99th percentile, 32 °C), exposure to moderate cold (25th percentile, 3 °C) and extreme cold (2.5th percentile, -7 °C) was associated with elevations of 1.28% and 1.16% in diurnal PEF variation over lag 0-2 days, respectively. The odds ratios of asthma exacerbation (determined by diurnal PEF variation >20%) at the two temperature cutoffs were 1.68 and 1.73. A sudden temperature drop (2.5th percentile of TCN, -5 °C) was associated with 1.13% elevation in diurnal PEF variation, and with increased risk of asthma exacerbation (odd ratio = 1.50) over lag 0-4 days. CONCLUSION: This large multicenter study provided the first-hand empirical evidence that cold temperature and a temperature drop may increase the risk of asthma exacerbation.
A high premium has been put on researching the effects of cold spells because of their adverse influence on people’s daily lives and health. The study aimed to find the most appropriate definition of the cold spell in Shenzhen and quantify the impact of cold spells on mortality. Based on the daily mortality data in Shenzhen from 2013 to 2017 and the meteorological and pollutant data from the same period, we quantified the effect of cold spells using eight different definitions in the framework of a distributed lag non-linear model with a quasi-Poisson distribution. In Shenzhen, low temperatures increase the risk of death more significantly than high temperatures (using the optimal temperature as the cut-off value). Comparing the quasi-Akaike information criterion value, attribution fraction (b-AF), and attribution number (b-AN) for all causes of deaths and non-accidental deaths, the optimal definition of the cold spell was defined as the threshold was 3rd percentile of the daily average temperature and duration for 3 or more consecutive days (all causes: b-AF = 2.31% [1.01-3.50%], b-AN = 650; non-accidental: b-AF = 1.92% [0.57-3.17%], b-AN = 471). For cardiovascular deaths, the best definition was the temperature threshold as the 3rd percentile of the daily average temperature with a duration of 4 consecutive days (cardiovascular: b-AF = 1.37% [0.05-2.51%], b-AN = 142). Based on the best definition in the model, mortality risk increased in cold spells, with a statistically significant lag effect occurring as early as the 4th day and the effect of a single day lasting for 6 days. The maximum cumulative effect occurred on the 14th day (all-cause: RR = 1.54 [95% CI, 1.20-1.98]; non-accidental: RR = 1.43 [95% CI, 1.11-1.84]; cardiovascular: RR = 1.58 [95% CI, 1.00-2.48]). The elderly and females were more susceptible to cold spells. Cold spells and their definitions were associated with an increased risk of death. The findings of this research provide information for establishing an early warning system, developing preventive measures, and protecting susceptible populations.
Buildings made of snow and ice in severely cold areas can provide people with tourist experiences. Utilizing natural resources in an appropriate manner such as constructing energy efficient residential buildings that are suited to local climate conditions is important for maintaining indoor thermal comfort, creating ecologically living spaces, and reducing energy consumption. In this study, an igloo was built in the traditional manner at Harbin Institute of Technology to detect the heat transfer mechanism of ice and snow, and indoor thermal comfort in an extremely cold region of China. The thermal benefits of the igloo were investigated based on field measurements. Periodic heat transfer theory was applied to study the heat transfer mechanism in the igloo wall and human thermal comfort was analyzed in the chamber and under ambient conditions. The results showed the following. (1) The air temperature and relative humidity were higher and more stable in the chamber without any heating measures. (2) The air temperature was about 4 degrees C higher in the chamber than the ambient temperature. (3) The maximum snow depth where the ambient temperature affected the chamber temperature was 200 mm. (4) The igloo provided a more comfortable thermal environment compared with the outdoor conditions. These findings may provide the basis for understanding the thermal benefit of igloos based on the utilization of natural resources. Theoretically and practically, our results may provide an experimental basis for studying the heat transfer mechanism to facilitate the establishment of design and construction standards for snow and ice buildings.
OBJECTIVES: We aimed to investigate the acute effect of extreme cold weather on circulatory disease mortality of older adults in Jinan, with individual and regional-scale characteristics as subgroup analyses to further identify vulnerable populations. METHODS: This study contained the death data of Jinan from 2011 to 2020 (Nov-Mar). A time-stratified case-crossover method was used to estimate the effects of extreme cold weather and lags 0-8 days, controlling for holiday and relative humidity. To evaluate the impact of different durations and thresholds of extreme cold weather, we considered 4 cold day and 12 cold wave definitions RESULTS: Our results showed an increase in circulatory disease deaths under several definitions. The number of older adults died of circulatory diseases totaled 92,119 during the study period. In the definitions of cold day, the maximum significant effect ranging from 1.08 (95% CI: 1.03,1.14) to 1.13 (95% CI: 1.04,1.24) and appeared on Lag5 or Lag6. In the definitions of cold wave, the maximum significant effect ranging from 1.07 (95% CI: 1.02, 1.12) to 1.14 (95% CI: 1.03, 1.25). The cold effect is mainly attributable to cold day rather than an added effect related to the duration. Our research confirmed that extreme cold weather had a stronger impact on women [maximum effects with an OR of 1.21 (95% CI: 1.08, 1.36) in P1, 1.19 (95% CI: 1.05, 1.36) in M12)], and the effect gradient increased with age. CONCLUSIONS: Our findings support the evidence on the impact of extreme cold weather on circulatory disease mortality and provide a basis for policymakers to select target groups to develop policies and reduce the public health burden.
Background: Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in China. Although numerous studies have been conducted to determine the risk factors for COPD mortality such as ambient air pollution, the results are not fully consistent. Methods: This study included mortality analysis and a case-control design by using the data extracted from the Mortality Registration System in Jiading District, Shanghai. Traditional logistic regression, geographically weighted logistic regression (GWLR), and spatial scan statistical analysis were performed to explore the geographic variation of COPD mortality and the possible influencing factors. Results: Traditional logistic regression showed that extreme lower temperature in the month prior to death, shorter distance to highway, lower GDP level were associated with increased COPD mortality. GWRL model further demonstrated obvious geographical discrepancies for the above associations. We additionally identified a significant cluster of low COPD mortality (OR = 0.36, P = 0.002) in the southwest region of Jiading District with a radius of 3.55 km by using the Bernoulli model. The geographical variation in age-standardized mortality rate for COPD in Jiading District was explained to a certain degree by these factors. Conclusion: The risk of COPD mortality in Jiading District showed obvious geographical variation, which were partially explained by the geographical variations in effects of the extreme low temperature in the month prior to death, residential proximity to highway, and GDP level.
Previous studies have reported that daily average temperature is connected with respiratory diseases (RD), but proof is limited for the influence of the extreme low temperature on RD in Lanzhou, a northwestern China of temperate area. Generalized additive model (GAM) was built in this work to describe the relationship between daily mean temperature and RD in Lanzhou, China from 2012 to 2017. The results indicated that the exposure-response curve was inverse J-shaped, showing the lower the temperature, the larger the relative risk (RR). The RR of daily emergency room (ER) admissions in P5 extreme low temperature (the temperature below the fifth percentile, etc.) was larger than that in P10. The P5 extreme low temperature has the strongest effect at lag 0, and the RRs were 1.043 (95% CI: 1.030, 1.055) for the total, 1.031 (95% CI: 1.015, 1.046) for males and 1.058 (95% CI: 1.039, 1.077) for females. For different age groups, the largest RRs were 1.026 (95% CI: 1.013, 1.039) for the children (age < 16 years) at lag 5, 1.057 (95% CI: 1.030, 1.085) for the young adults (aged 16-45 years), 1.060 (95% CI: 1.023, 1.099) for the middle-aged (aged 46-60 years) and 1.121 (95% CI: 1.077, 1.166) for the elderly group of age > 60 years. Meanwhile, females and the elderly were more vulnerable to extreme temperature. The results could strengthen the scientific evidence of effects of extreme low temperature on RD in temperate areas.
Ambient cold is associated with substantial population attributable fraction of mortality in China, and respiratory health is vulnerable to cold exposure. This study aimed to examine the effect of cold spells on risk of deaths from chronic obstructive pulmonary disease (COPD). We collected daily data on deaths from COPD and climatic factors from 1 January 2016 to 31 December 2019 in 13 cities of Jiangsu Province, China. We used a quasi-Poisson generalized linear model coupled with a distributed lag non-linear model to quantify the association between risk of COPD deaths and exposure to cold spells (defined as 2 or more consecutive days with mean temperature ≤ 5(th) percentile of daily mean temperature distribution in cold months). Stratification analyses by age, sex, education, and occupation were undertaken to identify vulnerable subgroups. The results suggested that exposure to cold spells was associated with a higher risk of COPD deaths in Lianyungang (relative risk (RR): 1.70; 95% confidence interval (CI): 1.31, 2.21), Nanjing (RR: 1.54; 95% CI: 1.16, 2.04), Nantong (RR: 1.97; 95% CI: 1.68, 2.31), Suzhou (RR: 1.97; 95% CI: 1.55, 2.50), Suqian (RR: 1.68; 95% CI: 1.23, 2.29), Taizhou (RR: 1.70; 95% CI: 1.32, 2.19), Wuxi (RR: 1.99; 95% CI: 1.53, 2.60), Xuzhou (RR: 1.71; 95% CI: 1.01, 2.90), Yancheng (RR: 1.78; 95% CI: 1.53, 2.06), Yangzhou (RR: 2.78; 95% CI: 2.06, 3.76), and Zhenjiang (RR: 1.79; 95% CI: 1.26, 2.55). All subgroups seemed to be vulnerable to the effect of cold spells. The recommendation of this study is that individuals with pre-existing COPD, regardless of age, sex, education, or occupation, should be made aware of the health risk posed by cold spells and should be encouraged to take cold adaptation actions before cold season arrives. The main limitation of this study is that it is subject to ecological fallacy.
BACKGROUND: Pulmonary embolism (PE) is an important cause of death and its seasonality has long been observed. Very few epidemiological studies have explored the potential role of ambient temperature in PE symptom onset, especially at the hourly level. METHODS: We conducted a time-stratified case-crossover study among 17,903 PE patients with hourly onset of symptom from 1590 hospitals across China between January 2015 and September 2020. Conditional logistic regression model combined with distributed lag non-linear models were used to explore the associations between hourly ambient temperature and PE symptom onset. The attributable fractions due to non-optimum temperature were calculated. RESULTS: The exposure-response relationship curve was inverse and almost linear. Lower temperature was significantly associated with higher risk of PE symptom onset when temperature was below 18 °C. This risk occurred immediately at the same hour, attenuated thereafter, and became nonsignificant at approximately 72 h after exposure. Compared with the referent temperature (P(99), 34.1 °C), the odds ratio of PE symptom onset associated with extremely low temperature (P(1), -16.1 °C) over lag 0-72 h was 1.63 (95%CI: 1.23, 2.16). Low temperature may account for 16.19 % of the symptom onset nationally with higher proportion in the south of China. The effects were stronger in older adults, males, and cold seasons. CONCLUSIONS: We provided the first-hand robust evidence that transient exposure (at the hourly level) to low temperature might trigger the symptom onset of PE and constitute a considerable burden for PE patients. Targeted protections and health education are needed for susceptible populations.
BACKGROUND: Many studies have investigated the devastating health effects of heat waves, but less is known about health risks related to cold spells, despite evidence that extreme cold may contribute to a larger proportion of deaths. OBJECTIVES: We aimed to systematically investigate the association between cold spells and mortality in Japan. METHODS: Daily data for weather conditions and 12 common causes of death during the 1972-2015 cold seasons (November-March) were obtained from 47 Japanese prefectures. Cold spells were defined as ≥ 2 consecutive days with daily mean temperatures ≤ 5th percentile for the cold season in each prefecture. Quasi-Poisson regression was combined with a distributed lag model to estimate prefecture-specific associations, and pooled associations at the national level were obtained through random-effects meta-analysis. The potential influence of cold spell characteristics (intensity, duration, and timing in season) on associations between cold spells and mortality was examined using a similar two-stage approach. Temporal trends were investigated using a meta-regression model. RESULTS: A total of 18,139,498 deaths were recorded during study period. Mortality was significantly higher during cold spell days vs. other days for all selected causes of death. Mortality due to age-related physical debilitation was more strongly associated with cold spells than with other causes of death. Associations between cold spells and mortality from all causes and several more specific outcomes were stronger for longer and more intense cold spells and for cold spells earlier in the cold season. However, although all outcomes were positively associated with cold spell duration, findings for cold spell intensity and seasonal timing were heterogeneous across the outcomes. Associations between cold spells and mortality due to cerebrovascular disease, cerebral infarction, and age-related physical debility decreased in magnitude over time, whereas temporal trends were relatively flat for all-cause mortality and other outcomes. DISCUSSION: Our findings may have implications for establishing tailored public health strategies to prevent avoidable cold spell-related health consequences. https://doi.org/10.1289/EHP7109.
Deleterious effect of cold on overall mortality is well-established. We studied associations between the air temperature and the number f ambulance calls for asthma in Nur-Sultan, Kazakhstan – the second coldest capital in the world. Daily counts of ambulance calls for asthma in Nur-Sultan for the cold seasons (October-March) 2006-2010 were obtained from the Municipal Ambulance Station. Associations between the number of calls and mean and minimum apparent temperatures (average for lags 0-15) were studied using first-order Poisson auto-regression models controlling for wind speed and effects of month, year, weekends and holidays. Altogether, there were 7373 ambulance calls for asthma during the study period. An inverse association between minimum apparent temperature and the number of calls was observed for the age-group 60 years and older. A decrease of the minimum apparent temperature by 1 °C was associated with an increase in the number of calls by 1.7% (95% CI: 0.1%-3.3%) across the whole temperature spectrum. No associations in other age groups were found. Our results suggest an inverse association between the average 15-day lag minimum apparent temperature and the number of ambulance calls during the cold season in Nur-Sultan, but this is limited to the oldest age-group.
BACKGROUND: Emerging evidence supports an association between heat exposure and acute kidney injury (AKI). However, there is a paucity of studies on the association between cold exposure and AKI. OBJECTIVE: We aimed to investigate the associations of cold exposure with hospital admission and mortality due to AKI and to explore whether these associations were influenced by age and sex. METHODS: Information on daily counts of hospital admission and mortality due to AKI in 16 regions of Korea during the cold seasons (2010-2019) was obtained from the National Health Insurance Service (a single national insurer providing universal health coverage) and Statistics Korea. Daily mean temperature and relative humidity were calculated from hourly data obtained from 94 monitoring systems operated by the Korean Meteorological Administration. Associations of low temperatures (<10th percentile of daily mean temperature) and cold spells (≥2 consecutive days with <5th percentile of daily mean temperature) up to 21 days with AKI were estimated using quasi-Poisson regression models adjusted for potential confounders (e.g., relative humidity and air pollutants) with distributed lag models and univariate meta-regression models. RESULTS: Low temperatures were associated with hospital admission due to AKI [relative risk (RR) = 1.12, 95 % confidence interval (CI): 1.09, 1.16]. Cold spells were associated with hospital admission (RR = 1.87, 95 % CI: 1.46, 2.39) and mortality due to AKI (RR = 4.84, 95 % CI: 1.30, 17.98). These associations were stronger among individuals aged ≥65 years than among those aged <65 years. CONCLUSION: Our results underscore the need for the general population, particularly the elderly, physicians, and other healthcare providers to be more vigilant to cold exposure, given the risk of AKI. Government agencies need to develop specific strategies for the prevention and early detection of cold exposure-related AKI.
BACKGROUND: Climate change is predicted to increase the frequency, intensity, and duration of extreme cold events in the mid-latitudes. However, although diabetes is one of the most critical metabolic diseases due to its high and increasing prevalence worldwide, few studies have investigated the short-term association between cold exposure and diabetes-related outcomes. OBJECTIVE: The aim of this study was to investigate the associations between cold spells and their characteristics (intensity, duration, and seasonal timing) and hospital admission and mortality due to diabetes. METHODS: This study used claims data from the National Health Insurance Service and cause-specific mortality data from Statistics Korea (2010-2019). Cold spells were defined as ≥2 consecutive days with a daily mean temperature lower than the region-specific 5th percentile during the cold season (November-March). Quasi-Poisson regressions combined with distributed lag models were used to assess the associations between exposures and outcomes in 16 regions across the Republic of Korea. Meta-analyses were conducted to pool the region-specific estimates. RESULTS: Exposure to cold spells was associated with an increased risk of hospital admission [relative risk (RR) = 1.45, 95% confidence interval (CI): 1.26, 1.66] and mortality (RR = 2.02, 95% CI: 1.37, 2.99) due to diabetes. The association between cold spells and hospital admission due to diabetes was stronger for cold spells that were more intense, longer, and occurred later during the cold season. The association between cold spells and diabetes-related mortality was stronger for more intense and longer cold spells. CONCLUSION: This study emphasizes the importance of developing effective interventions against cold spells, including education on the dangers of cold spells and early alarm systems. Further studies are needed to create real-world interventions and evaluate their effectiveness in improving diabetes-related outcomes.
Extremely cold events have occurred frequently around the world in the past few years, and people will inevitably be exposed to extremely cold environments during certain activities in modern society. Cold stress seriously threatens human health and safety. The purpose of this study was to study the physiological responses and thermal sensation of humans exposed to extreme cold. Twelve healthy males were exposed to a cold (-20 degrees C) environment in a climate chamber for 30 min after a preconditioning phase. This cold exposure was followed by 40 min of recovery at 24 degrees C. Thermal sensation and physiological parameters, including core temperature, local skin temperature, blood pressure, and heart rate, were recorded throughout the entire process. The results show that the ear is the most sensitive to ambient temperature changes. Blood pressure increased 17.6% within a minute of cold exposure. The average heart rate continued to drop in each period. Establishing a transition space can relieve the pressure stimulus of a large temperature difference. There are functional correlations between the local skin temperature and thermal perception, and the ear exhibits the best correlation. The asymmetry of thermal sensation in extremely cold environments is eliminated when the temperature difference exceeds a certain threshold between 40 degrees C and 44 degrees C. The results of this study are of great significance for extreme cold protection.
As the global climate continues to warm, there is an increased focus on heat, but the role of low temperatures on health has been overlooked, especially for developing countries. Methods We collected the admission data of childhood asthma in 2013-2016 from Anhui Provincial Children’s Hospital, as well as meteorological data from the Meteorological Bureau for the study period and collected data of pollutants from 10 monitoring stations around Hefei city. Poisson’s generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM) was used to estimate the short-term effects of cold spell on childhood asthma in cold seasons (November to March). 16 definitions of cold spells were clearly compared, which combining 4 temperature indexes (daily minimum and mean temperature; daily minimum and mean apparent temperature), 2 temperature thresholds (2.5th and 5th) and 3 durations of at least 2-4 days. We then have an analysis of the modifying effect of characteristics of cold spells and individuals(gender and age), with a view to discovering the susceptible population to cold spell. Results There was significant association between cold spells and admission risk for childhood asthma. And the definition, in which daily minimum apparent temperature falls below 5th percentile for at least 3 consecutive days, produced the optimum model fit performance. Based on this optimal fit we found that, for the total population, the effect of cold spell lasted approximately five days (lag1-lag5), with the largest effect occurring in lag 3 (RR = 1.110; 95% CI: 1.052-1.170). In subgroup analysis, the cumulative effect of lag0-7 was higher in males and school-age children than in females and other age groups, respectively. In addition, we found that the effect of is higher as the duration increases. Conclusion This study suggests an association between cold spell and childhood asthma, and minimum AT may be a better indicator to define the cold spells. Boys and school-age children are more vulnerable to cold spell. And one of our very interesting findings is that if a cold spell lasts for several days, the impact of the cold spell on those later days is likely to be greater than that of the previous days. In conclusion, we should pay more attention to the protection of boys and school-aged children in our future public health protection and give more attention to those cold spells that last longer. Therefore, we recommend that schools and health authorities need to take targeted measures to reduce the risk of asthma in children during the cold spell.
Ambient temperature is an important contributor to mortality burden worldwide, most of which is from cold exposure. However, little is known about the cold impact on life expectancy loss. This paper aimed to estimate cold-related life expectancy loss from cause-, age-, and gender-specific cardiovascular and respiratory diseases. Daily deaths from cardiovascular and respiratory diseases and weather records were acquired for Hong Kong, China during 2000-2016. Years of life lost (YLL) that considers life expectancy at the time of death was calculated by matching each death by age and sex to annual life tables. Using a generalized additive model that fits temperature-YLL association, we estimated loss of years in life expectancy from cold. Cold was estimated to cause life expectancy loss of 0.9 years in total cardiovascular disease, with more years of loss in males than in females and in people aged 65 years and older than in people aged up to 64 years. Cold-related life expectancy loss in total respiratory diseases was 1.2 years, with more years of loss in females than in males and comparable years of loss in people aged up to 64 years and in people aged 65 years and older. Among cause-specific diseases, we observed the greatest life expectancy loss in pneumonia (1.5 years), followed by ischaemic heart disease (1.2 years), COPD (1.1 years), and stroke (0.3 years). Between two periods of 2000-2007 and 2008-2016, cold-related life expectancy loss due to cardiovascular disease did not decrease and cold-related life expectancy loss due to respiratory disease even increased by five times. Our findings suggest an urgent need to develop prevention measures against adverse cold effects on cardiorespiratory disease in Hong Kong.
BACKGROUND: Previous studies have demonstrated the seasonal variations of non-variceal upper gastrointestinal bleeding (UGIB), but there is scanty data on lower gastrointestinal bleeding (LGIB) and the association with other meteorological parameters. METHODS: We included all patients hospitalized for UGIB and LGIB between 2009 and 2018 in Hong Kong. The monthly age-standardized and sex-standardized GIB incidences were fitted to meteorological data including average temperature (AT), maximum temperature (MaxT), minimum temperature (MinT), temperature range (TR), average precipitation, average atmospheric pressure (AtomP), and average relative humidity after adjusting for prescriptions of aspirin, proton pump inhibitors, and Helicobacter pylori eradication therapy using the autoregressive integrated moving average model. RESULTS: Despite a gradual decline in UGIB incidences, the incidences of UGIB were still higher in winter months. The incidence and fluctuation of both UGIB and LGIB were higher in the older age groups, especially those ≥80 years. The seasonality was only identified in those ≥60 years for UGIB, and only in those ≥80 years for LGIB. UGIB incidence was inversely associated with AT, MaxT, and MinT, but positively associated with TR and AtomP. LGIB was also significantly associated with AT, MaxT, MinT, and AtomP. CONCLUSION: Despite the changes in GIB incidences, the seasonal patterns of GIB were still marked in the elderly. With the aging population, the impacts of seasonal variations on GIB incidences could be considerable.
BACKGROUND: Previous studies have revealed the relationship between cold spells and morbidity and mortality due to respiratory diseases, while the detrimental effects of cold spells on the length of hospital stay and hospitalization expenses remain largely unknown. METHODS: We collected hospitalization data for respiratory diseases in 11 cities of Shanxi, China during 2017-2019. In each case, exposure to meteorological variables and air pollution was estimated by the bilinear interpolation approach and inverse distance weighting method, respectively, and then averaged at the city level. Cold spells were defined as the daily mean temperature below the 10(th), 7.5(th), or 5(th) percentiles for at least 2 to 5 consecutive days. We applied distributed lag non-linear models combined with generalized additive models to assess cumulative effects and harvesting effects. RESULTS: There were significant associations between cold spells and hospital admissions, length of hospital stay, and hospital expenses for respiratory diseases. Compared with the non-cold spell period, the overall (lag 0-21) cumulative risk of hospitalization for total respiratory diseases was 1.232 (95 % CI: 1.090, 1.394) on cold spell days, and the increased length of hospital stay and hospitalization expenses were 112.793 (95 % CI: 10.755, 214.830) days and 127.568 (95 % CI: 40.513, 214.624) thousand Chinese yuan. The overall cumulative risks of cold spells on total respiratory diseases and pneumonia were statistically significant. We further observed harvesting effects in the associations between cold spells and hospital admission, length of hospital stay, and hospitalization expenses for respiratory diseases. CONCLUSIONS: Cumulative cold-spell exposure for up to three weeks is associated with hospitalization, length of hospital stay, and hospital expenses for respiratory diseases. The observed harmful effects of cold spells on respiratory diseases can be partly attributable to harvesting effects.
AIMS: The incidence of acute aortic dissection (AAD) has been shown to have seasonal variation, but whether this variation can be explained by non-optimum ambient temperature and temperature change between neighbouring days (TCN) is not clear. METHODS AND RESULTS: We performed a time-stratified case-crossover study in the Registry of Aortic Dissection in China covering 14 tertiary hospitals in 11 cities from 2009 to 2019. A total of 8182 cases of AAD were included. Weather data at residential address were matched from nearby monitoring stations. Conditional logistic regression model and distributed lag nonlinear model were used to estimate the associations of daily temperature and TCN with AAD, adjusting for possible confounders. We observed an increase of AAD risk with lower temperature cumulated over lag 0-1 day and this association became statistically significant when daily mean temperature was below 24°C. Relative to the referent temperature (28°C), the odds ratios (ORs) of AAD onset at extremely low (-10°C) and low (1°C) temperature cumulated over lag 0-1 day were 2.84 [95% confidence interval (CI): 1.69, 4.75] and 2.36 (95% CI: 1.61, 3.47), respectively. A negative TCN was associated with increased risk of AAD. The OR of AAD cumulated over lag 0-6 days was 2.66 (95% CI: 1.76, 4.02) comparing the extremely negative TCN (-7°C) to no temperature change. In contrast, a positive TCN was associated with reduced AAD risk. CONCLUSION: This study provides novel and robust evidence that low ambient temperature and temperature drop between neighbouring days were associated with increased risk of AAD onset. KEY QUESTION: Incidence of acute aortic dissection (AAD) was reported to have seasonal trends, but it remains unclear whether non-optimum ambient temperature and temperature change between neighbouring days (TCN) is associated with AAD onset. KEY FINDING: Daily mean temperature lower than 24°C was significantly associated with increased risk of AAD at lag 0-1 day. A negative TCN (temperature drop) was associated with increased risk of AAD, whereas a positive TCN was associated with decreased risk. TAKE HOME MESSAGE: This multi-centre, case-crossover study provides novel and robust evidence that low ambient temperature and temperature drop between neighbouring days were associated with increased AAD risk.
BACKGROUND: The cold season seems to be a trigger for atrial fibrillation (AF). Some reports are controversial and demonstrate variability according to the climatic characteristics in different regions. OBJECTIVES: To analyze whether meteorological factors contribute to seasonal variation of exacerbation of AF diagnosed in patients referred to the emergency department (ED) of our hospital. METHODS: We retrospectively reviewed medical data of consecutive patients admitted to the ED with symptomatic acute onset AF from 1 January 2016 to 31 December 2018. We recorded the mean monthly outdoor temperature, barometric pressure, and relative humidity during the study period. RESULTS: During the study period, 1492 episodes of AF were recorded. New onset AF were 639 (42.8%) and paroxysmal atrial fibrillation (PAF) were 853 (57.2%) (P = 0.03). The number of overall admission of AF episodes was not distributed uniformly through the year. Incidence of AF episodes peaked during December and was lowest in June (P = 0.049). Of 696 episodes (46.6 %) the patients were hospitalized and for 796 (53.4%) the patients were discharged (0.01). The number of hospitalizations was not distributed uniformly through the year (P = 0.049). The highest number of hospitalizations happened in December and the lowest in May. Outdoor temperature and barometric pressure (but not relative humidity) may mediate a monthly fluctuation in AF episodes with highest number of ED visits in December and the lowest in June. CONCLUSIONS: Meteorological conditions influence exacerbation of AF episodes and hospitalization. Outdoor temperature and barometric pressure may mediate a monthly fluctuation in AF.
INTRODUCTION: The SARS-CoV-2 (COVID-19) pandemic has caused unprecedented social and economic disruption, accompanied by the enactment of a multitude of public health measures to restrain disease transmission. These public health and social measures have had a considerable impact on lifestyle and mental wellbeing, which has been well studied with metropolitan populations. However, limited literature concerning such effects on a selectively rural population is presently available. Additionally, the use of a standardised scoring system for lifestyle may be valuable for an overall assessment of lifestyle that may be incorporated into clinical practice. METHODS: This study examined the associations between psychological distress and changes in SNAPS health behaviours (smoking, nutrition, alcohol, physical activity, sleep) since the onset of COVID-19 in Australia. A cross-sectional anonymous survey was distributed online to adults in the Western New South Wales Primary Health Network in August 2020 and included measures of psychological distress, income, disposition and lifestyle factors during the pandemic as well as changes to lifestyle due to COVID-19. A novel Global Lifestyle Score (GLS) was generated as a holistic assessment of lifestyle across multiple domains. RESULTS: The survey was completed by 304 individuals (modal age group 45-54 years, 86.8% female). High distress on the Kessler-5 scale was present in over one-third of participants (n=95, 33.7%). Detrimental change was reported for sleep (22.7%), nutrition (14.5%), alcohol (16.7%), physical exercise (34.0%) and smoking (24.7%) since the onset of the pandemic. Changes in sleep, nutrition, physical activity and smoking were associated with distress. Participants with a poor lifestyle (GLS) during the pandemic were significantly more distressed. Perceived COVID-19 impact was associated with high distress, drought impact and loss of income. Participants who reported negative impact from both COVID-19 and drought were significantly more distressed than those reporting a negative impact from drought alone or neither event. CONCLUSION: High rates of distress among rural Australians during the COVID-19 pandemic was linked to low GLS, worsening lifestyles and loss of income. Healthy lifestyle strategies should be considered by health professionals for the management of crisis-related distress. Further research may explore the impact of COVID-19 on a larger study population with a greater proportion of male participants and to examine the effect of modifying lifestyle factors in reducing distress in the context of a stressor such as this pandemic.
OBJECTIVE: To identify the modifiable psychological and behavioural coping strategies associated with low levels of psychological distress, independent of more stable personality and demographic factors, in a sample of farmers who reported being exposed to a recent stressful event during an extended drought. DESIGN/SETTING/PARTICIPANTS: Three hundred and nine South Australian, drought-affected grain, sheep and/or cattle farmers completed printed or online questionnaires. Only those who reported experiencing a stressful event in the past month that they rated ≥7 on a scale ranging from 1 (not stressful at all) to 10 (extremely stressful) were included in the analyses (n = 175, 65.06%). Participants ranged in age from 24 to 85 years and 40% were female. MAIN OUTCOME MEASURES: Psychological distress was measured using the Kessler Psychological Distress Scale, and coping strategies were measured using a situational version of the COPE inventory. Five personality factors (extraversion, neuroticism, openness, conscientiousness and agreeableness) were assessed using the Quickscales-R. RESULTS: In the final multivariable model, distress was elevated among individuals reporting higher neuroticism and behavioural disengagement, and lower in individuals reporting greater use of acceptance. These 3 variables explained 44% of the variance in distress. CONCLUSION: Farmers recently exposed to a significant stressor, who used acceptance as a coping strategy, did not engage in behavioural disengagement and scored low on neuroticism, were least likely to experience distress. Given the stability of personality factors, interventions that foster farmers’ use of acceptance and prevent behavioural disengagement as coping strategies might assist them with the management of future stressors, particularly in times of drought.
Farming women have rarely been the focus of scholarly work on drought and/or distress. This article focuses on farming women’s lived experience of drought and distress, drawing on a participatory filmmaking project created by a small group of farming women from Southern Australia. Feminist materialism and Barad’s (2003) concept of ‘intra-action’ provides a useful lens to examine both the film as an artefact as well as the discussions among the women during its creation. Intra-action enables an exploration of how farming women’s bodies come into being as distressed in moments of time through and with drought as a complex constellation of multiple ‘matter’. The film and narratives show distressed bodies emerging with dust, wind, objects and the suffering of non-human animals. For these women, distress emerges from hearing, sensing, seeing and feeling the irritation of dirt splattered against window panes, the emotional pain and economic consequences of topsoil blowing across paddocks and as feed becomes hard to source, the recognition of the suffering of sheep. The power of these animate and inanimate ‘things’-windmills, windows, troughs, work boots, animals and soil-were sensorily entangled with women’s bodies. For farming women, distress materialises within their bodies through processes of intra-action in their more-than-human worlds.
Drought is thought to impact upon the mental health of agricultural communities, but studies of this relationship have reported inconsistent results. A source of inconsistency could be the aggregation of data by a single spatiotemporal unit of analysis, which induces the modifiable areal and temporal unit problems. To investigate this, mental health-related emergency department (MHED) presentations among residents of the Wheat Belt region of Western Australia, between 2002 and 2017, were examined. Average daily rainfall was used as a measure of drought. Associations between MHED presentations and rainfall were estimated based on various spatial aggregations of underlying data, at multiple temporal windows. Wide variation amongst results was observed. Despite this, two key features were found: Associations between MHED presentations and rainfall were generally positive when rainfall was measured in summer months (rate ratios up to 1.05 per 0.5 mm of daily rainfall) and generally negative when rainfall was measured in winter months (rate ratios as low as 0.96 per 0.5 mm of daily rainfall). These results demonstrate that the association between drought and mental health is quantifiable; however, the effect size is small and varies depending on the spatial and temporal arrangement of the underlying data. To improve understanding of this association, more studies should be undertaken with longer time spans and examining specific mental health outcomes, using a wide variety of spatiotemporal units.
Long-lasting drought can have a serious impact on human society and even lead to regime change and the demise of civilizations. Case studies will help to understand the evolution and mechanism of drought under different spatiotemporal scales and social contexts, providing references for dealing with the risk brought by extreme drought. In the late 1920s, northern China witnessed an extreme drought, however, the government had done little to deal with it, causing large losses at the time. This extreme drought event can be served as a case study of the social impact of drought. We collected newspaper records during the drought period, processed qualitative records with textual analysis, and explored the impact path of drought on the human system with network analysis. This research draws the following conclusions: (1) The great drought in northern China caused 19 kinds of recorded events to the human system. (2) The transmission process of drought impact on the human system had two characteristics: hierarchical propagation and cascading effects. The former was reflected in the transmission process of drought impacts among natural, supporting and humanity systems, and the latter was reflected in the transmission process of drought impact within the humanity system. (3) The core event of the natural system is “meteorological drought”; the core event of the supporting system is “food production damage”; the core events of the humanity system are “physical health decline” and “eating alternative foods” (population subsystem), “rising of food prices” (economic subsystem) and “bandits” (social subsystem). These events constitute the main network of how drought affected society. (4) The most special event among all events is “food production damage”, which receives most of the effects of meteorological drought, transmits the effects to other systems and controls the transition of drought effects from nature to human society. Strengthening the resilience of food production systems is an important measure to control the escalation of drought effects.
The upstream construction of hydropower dams may drastically intensify climate change impacts due to changing the natural river flood-drought cycle and reducing the amount of water that flows into the lower Mekong Delta river, leading to hydrological and environmental health impacts. However, until now the influence of drought on residents’ health in the lower MDR, where river drought is highly sensitive to recently built hydropower plants, has not been examined. The objectives of this study are, for the first time, to detect the health impacts of river drought on residents and to evaluate the contribution of hydropower dams to the impacts of drought on health in the lower Mekong Delta Region (MDR). We applied the multi-step approaches of a Detection and Attribution study. First, we detected the effects of the river drought on the risk of hospitalization using a Multivariable Fractional Polynomials algorithm (MFP). Second, we linked the long-term changes of the river water level (RWL) to the operation of the first hydropower dam in the upper MDR using the interrupted time-series model (ITS). Finally, we quantified the hospitalizations and related economic loss attributed to the river drought. The results show that the percentage changes in risk of all-cause, respiratory, and renal hospitalizations attributed to the river drought were 2%, 2%, and 7%. There were significant reductions in average level and trend of the RWL during the post-1995 period, when the first hydropower dam began operation in the upper MDR, even though the cumulative rainfall in the MDR had not changed. The all-cause hospitalizations attributed to the river drought were 1134 cases during the period 1995-2014, which resulted in total additional cost at two provincial hospitals of US $360,385. This current study demonstrates the link between hydropower dams, river drought, and health impacts. As the MDR is highly vulnerable to climate change, these findings about the devastating impacts of hydropower dams and environmental change have important implications for the lives of downstream residents.
Loss and Damage studies have tended to focus on rapid-onset events with lesser attention to slow-onset events such as drought. Even when discussed, narratives around droughts emphasize implications on rural populations and there remain empirical and conceptual gaps on drought impacts in urban areas. We focus on losses and damages associated with urban drought and water insecurity through a review of interventions and policies in seven Asian countries. We find evidence of urban droughts leading to tangible losses (e.g. groundwater over-extraction, economic impacts) and intangible losses (e.g. conflict, increased drudgery). We highlight examples of Asian cities minimizing urban drought-related losses and damages through nature-based, institutional, technological, and behavioral adaptation interventions. We argue that water management policies that take into account current and projected L&D of urban droughts as well as beyond-urban dynamics of water availability and sharing are essential for effective climate adaptation.
Background: In this study, we investigated the associations Lake Urmia’s drought to the prevalence of thyroid nodules (TNs) and metabolic syndrome (MetS) among local inhabitants of the lake. Methods: In this cross-sectional study which was started in 2014, we collected data on 992 adults who participated in the Azar cohort study, in Shabestar county, Iran. The sociodemographic status, smoking, and medical history of the subjects living in the areas adjacent to (n = 163) and far from (n = 829) Lake Urmia were collected through questionnaires. After obtaining written consent, anthropometric factors and blood pressure (BP) were measured. The lipid profile and fasting blood glucose (FBG) of the respondents were measured using colorimetric methods, and all underwent thyroid examination and sonography. Furthermore, the size and characteristics of nodules were determined with a fine-needle aspiration biopsy (FNAB) method. Results: We did not find any significant difference in the prevalence of TNs between the two groups (P=0.44), whereas the prevalence of MetS were significantly higher among the subjects from the regions that were far from the Lake (P=0.04). After adjustment for confounding factors (age and gender) in both groups, low risk of TNs (OR=1.20, 95% CI:0.89-1.62) and high risk of TNs (OR=1.19, 95% CI:0.65-2.19) were not significantly associated to MetS (P>0.05). Conclusion: In this study, Lake Urmia’s drought was identified to be with no contribution to the prevalence of TNs and MetS. Therefore, long term perspective studies are suggested to reach precise results.
Hemorrhagic fever with renal syndrome (HFRS) continued to affect human health across Eurasia, which complicated by climate change has posed a challenge for the disease prevention measures. Nation-wide surveillance data of HFRS cases were collected during 2008-2020.The seasonality and epidemiological features were presented by combining the HFRS incidence and the endemic types data. Factors potentially involved in affecting incidence and shaping disease seasonality were investigated by generalized additive mixed model, distributed lag nonlinear model and multivariate meta-analysis. A total of 76 cities that reported totally 111,054 cases were analyzed. Three endemic types were determined, among them the Type I cities (Hantaan virus-dominant) were related to higher incidence level, showing one spike every year in Autumn-Winter season; Type II (Seoul virus-dominant) cities were related to lower incidence, showing one spike in Spring, while Type III (Hantaan/Seoul-mixed type) showed dual peaks with incidence lying between. Persistently heavy rainfall had significantly negative influence on HFRS incidence in Hantaan virus-dominant endemic area, while a significantly opposite effect was identified when continuously heavy rainfall induced floods, where temperature and relative humidity affected HFRS incidence via an approximately parabolic or linear manner, however few or no such effects was shown in Seoul virus-dominant endemic areas, which was more vulnerable to temperature variation. Dual seasonal pattern of HFRS was depended on the dominant genotypes of hantavirus, and impact of climate on HFRS was greater in Hantaan virus-dominant endemic areas, than in Seoul virus-dominant areas.
Drought and flood are two of the most destructive natural disasters with the most significant impact and greatest losses in the Dadu River basin (DRB). However, their impacts on people’s life have not attracted enough attention from scholars. In this study, the Standardized Precipitation Index (SPI) describing the drought/flood situation and the Composite Index of Human Well-being (CIHW) are calculated, and a framework is further constructed to assess the impacts of drought and flood disasters on human well-being in the DRB. The results show that the annual and seasonal SPI in the DRB generally exhibit an increasing trend in fluctuations during 2000-2009, indicating a wetting climate in this basin. Overall, the upper reaches of the DRB have experienced an evolution of flood-drought-flood state transition, where the variation amplitude of the SPI in the western sub-basin is greater than that in the eastern sub-basin. In addition, the lower reaches of the DRB have suffered more dramatic and periodic changes from the drought/flood disasters in terms of the SPI. For human well-being during 2000-2019, Maerkang City in the upper reaches, Kangding City in the middle reaches, and Shimian County in the lower reaches of the DRB are at a relatively higher level, with the CIHW decreasing from administrative centers to the around. Moreover, the CIHW over the whole basin increases gradually from 2000 to 2019. The SPI has significantly negative effects on different capitals, following a descending order of financial, social, physical, human and natural capitals. The counties of the basin are divided into four groups, namely the group with high disaster risks and high human well-being, the group with high disaster risks and low human well-being, the group with low disaster risks and high human well-being, and the group with low disaster risks and low human well-being. The panel regression results suggest that the construction of water conservancy facilities, the financial inputs in agriculture and meteorology, and the educational level have positive impacts on human well-being, but the impacts differ from different groups. The construction of water conservancy facilities has highly significant impacts on human well-being in all groups; the education level has no significant impact on the group with high disaster risk and high human well-being, which has not passed the significance test; while the financial inputs in agriculture and meteorology have relatively higher impacts on the whole basin and on the group with low disaster risk and low human well-being compared with other groups. Therefore, it is suggested that the negative impacts of drought and flood disasters can be mitigated through strengthening infrastructure construction, responding appropriately to climate change, avoiding disasters at the source of major projects and improving the disaster prevention and mitigation systems.
Climate change may contribute to the spatio-temporal occurrence of disasters. Long-term studies of either homogeneous or heterogeneous responses of historical disasters to climate change are, however, limited by the quality and quantity of the available proxy data. Here we reconstruct spatio-temporal patterns of five types of disasters in China during the period AD 1368-1911. Our analyses of these time series reveal that warmer temperatures decreased the occurrence of disasters in the monsoon-affected parts of central-east China, but it increased the frequency and intensity of disasters along the boundary of arid and humid conditions in parts of southwest and northeast China, probably driven by the interplay among monsoon, westerlies, polar vortex and variation of temperature. Moreover, we show that drought and flood events had cascading effects on the occurrences of locust outbreaks, famine and human epidemics. Our findings suggest that climate can contribute to the spatio-temporal occurrence of disasters, and therefore may contribute to an improvement of China’s regional to national risk management of future climate and environmental change.
Objective: This study aimed to 1) investigate the psychometric properties of the Climate Change Anxiety Scale or CCAS (Clayton & Karazsia, 2020) and 2) examine the mediating role of climate change anxiety on the link between experience of climate change and behavioural engagement in climate mitigation in Filipino youth. Method: A total of 452 Filipino adolescents responded to the survey (Mean Age = 19.18, SD = .99). Results: A modified two-factor model of the CCAS displayed superior fit relative to the other three models tested. Confirmatory factor analysis in Phase 1 yielded a stable two-factor structure with strong factor loadings and good internal consistency. In Phase 2, cognitive-emotional, but not the functional impairment component of climate anxiety, showed a mediating effect on the relationship between experience of climate change and behavioural engagement in climate mitigation. Conclusions: This study is the first to demonstrate that CCAS subscales have distinct mediating roles in linking Filipino adolescents’ experience of climate change and mitigation behaviours. Further validation of the CCAS is recommended, as well as further research on the factors that can promote environment-friendly behaviours in Filipino youth.
Vanuatu, a Pacific Small Island Developing State, has high exposure to climate extremes, such as tropical cyclones and interannual rainfall variability, which can have devastating short- and long-term impacts on food and nutrition security (FNS). This paper presents local experiences of the effects of climate extremes on FNS in Vanuatu through a case study of two recent events: Tropical Cyclone Pam (2015) and an El Nino-induced drought (2015-2017). A qualitative research approach, using a range of data collection methods, was used to document people’s lived experiences in two villages in Vanuatu. This study found that climate extremes affected the FNS of people in the two study villages directly, with effects on gardens and food production, and indirectly, by exacerbating the nutrition transition, a shift away from traditional diets energy-dense imported food that is already progressing in Vanuatu. These effects undermine long-term FNS and health. Climate extremes also eroded food-related cultural practices and traditions and constrained local agency to make food choices. The magnitude and extent of these impacts, however, are influenced by structural vulnerabilities and local resiliencies. The adaptive capacity and resilience of communities needs to be strengthened in a way that allows people to exercise agency in their responses to climate extremes and to promote FNS, including cultural acceptability and food preferences, and long-term health.
BACKGROUND: Cold significantly increases the risk of mortality. However, the health risks associated with cold spells, persistent and extreme cold temperature events, have yet to be investigated in detail. METHODS: Meteorological and mortality data was collated from 280 counties in China from 2013 through 2019. GLM (Generalized Linear Models) was used to calculate county-level exposure-response relationships for nine different cold spell definitions. Next, we estimated the exposure-response associations between cold spells and mortality in national, Southern, and Northern China. Based on exposure-response relationships, along with the population and mortality data, we then calculated the number of excess deaths due to the cold spell of 2839 counties across China in 2018. Then, we calculated the loss of VSL (value of a statistical life) in each province. RESULTS: We identified that P5day7 was the cold spell definition that was associated with the highest health in China. Compared with non-cold spell days, the risk of non-accidental mortality, circulatory mortality, and respiratory mortality, on cold spell days increased by 17.4% (95% confidence interval [CI]: 15.8%, 19.0%), 20.8% (95%CI: 18.8%, 23.0%), and 22.7% (95%CI: 19.5%, 25.9%) respectively at lag 7 day in the South. In the North, the risk increased by 13.0% (95% CI: 11.0%, 15.0%), 13.8% (95% CI: 11.4%, 16.2%), and 21.0% (95% CI: 16.6%, 25.6%), respectively. The number of related deaths in China were 57,783, 29,827, and 10,922. The corresponding VSLs were 229,195, 118,322, and 43,315 million CNY (Chinese Yuan), thus accounting for 0.25%, 0.13%, and 0.05% of national GDP (Gross Domestic Product). CONCLUSION: Cold spells have caused a severe epidemiological and economic burden in China. South China should pay more attention to the health risks associated with cold spells.
The association between temperature and mortality has been widely investigated, however, studies on the effects of central heating on mortality risk are sparse. We applied a variant of difference-in-differences (DID) approach to assess the effects of central heating on winter mortality in China, and further analyzed the modification effect of central heating on the temperature-mortality association. Central heating was negatively associated with winter mortality (OR: 0.42, 95% CI: 0.39, 0.46) with higher effects on females and the elderly. Compared with cardiovascular or cerebrovascular diseases, central heating had a much greater effect on respiratory diseases. Every week less in central heating duration was associated with a 3.32% (95% CI: 3.03%, 3.61%) increased risk in total mortality. We found the temperature effect was much more pronounced among the locations without central heating (ER: 5.01%, 95% CI: 4.68%, 5.34%) than those with central heating (ER: 0.01%, 95% CI: -0.74%, 0.75%). The analysis suggests that central heating significantly decreases winter mortality in northern China, which may partly be achieved by attenuating the mortality caused by temperature. Therefore, central heating should be developed in some regions of southern China to reduce the mortality risk of low temperature in winter.
Low-temperature weather accompanied by strong chill wind is considered as a great risk factor for human health in winter, especially in some extreme weather conditions. Based on the observation data and the NCEP/NCAR reanalysis data of air temperature and wind velocity in 1961–2019, the warming pause of wind chill temperature (WCT) in the 21st century in China is first revealed in this paper. A significant increasing trend of WCT is found during 1961–1999 (P1), and a slight decreasing trend in 1999–2019 (P2) is detected by a 21 year running trend analysis. The extreme cold WCT day (WCD) with the WCT index below the 10th percentile also shows a decreasing trend in P1 but a slight increasing trend in P2. Both the WCT and the extreme WCD consistently display the warming pause in seven climatic regions in China. That means the slowdown or even decrease of human bioclimatic temperature in recent two decades may lead to an increasing risk of frostbite and other cold-related diseases in the country. Both the decreasing trend of mean temperature and the increasing trend of the wind speed contribute to the slowdown of the human-perceived warming in the 21st century, and this conjoint contribution could be linked to the East Asian winter monsoon circulations over Siberia, i.e. the Siberian high. The variation of averaged sea level pressure over the central region of the Siberian high shows high consistency with both the WCT and the extreme WCD in the whole study period, by a decreasing rate of −1.28 hPa per decade in P1 and an increasing rate of 1.26 hPa per decade in P2.
BACKGROUND: Few multicity studies have evaluated the association between cold spells and mortality risk and burden. OBJECTIVES: We aimed to estimate the association between cold spells and cause-specific mortality and to evaluate the mortality burden in China. METHODS: We conducted a time-series analysis with a nationally representative Disease Surveillance Points System database during the cool seasons spanning from 2013 to 2015 in 272 Chinese cities. We used 12 cold-spell definitions and overdispersed generalized additive models with distributed lag models to estimate the city-specific cumulative association of cold spells over lags of 0-28 d. We controlled for the nonlinear and lagged effects of cold temperature over 0-28 d to evaluate the added effect estimates of cold spell. We also quantified the nationwide mortality burden and pooled the estimated association at national and different climatic levels with meta-regression models. RESULTS: For the cold-spell definition of daily mean temperatures of ≤ 5th percentile of city-specific daily mean temperature and duration of ≥ 4 consecutive d, the relative risks (i.e., risk ratios) associated with cold spells were 1.39 [95% confidence interval (CI): 1.15, 1.69] for non-accidental mortality, 1.66 (95% CI: 1.20, 2.31) for coronary heart disease mortality, 1.49 (95% CI: 1.12, 1.97) for stroke mortality, and 1.26 (95% CI: 0.85, 1.87) for chronic obstructive pulmonary disease mortality. Cold spells showed a maximal lagged association of 28 d with the risks peaked at 10-15 d. A statistically significant attributable fraction (AF) of non-accidental mortality [2.10% (95% CI: 0.94%, 3.04%)] was estimated. The risks were higher in the temperate continental and the temperate monsoon zones than in the subtropical monsoon zone. The elderly population was especially vulnerable to cold spells. DISCUSSION: Our study provides evidence for the significant relative risks of non-accidental, cardiovascular, and respiratory mortality associated with cold spells. The findings on vulnerable populations and differential risks in different climatic zones may help establish region-specific forecasting systems against the hazardous impact of cold spells. https://doi.org/10.1289/EHP9284.
BACKGROUND: There is a paucity of studies investigating extreme cold events and asthma exacerbations. This study examined whether an association exists between cold spells and daily hospital admissions for asthma in Beijing, China from 2012 to 2016. METHODS: Daily hospital admissions for asthma, meteorological variables and air quality data were collected during 2012-2016 in Beijing. A cold spell was defined as a period of at least two consecutive days with the daily mean temperature below or at the 5th percentile (-7 °C) in cold seasons (November to March) during the study period. We applied a time-series design using quasi-Poisson regression combined with a distributed lag model to estimate the risk of asthma hospital admissions associated with cold spells. Stratified analyses by gender and age groups were conducted to identify the potential susceptible subpopulations to cold spells. We also explored the effect modification by air quality by dividing the daily air quality index (AQI) into two levels (high and low) based on the median value. RESULTS: Cold spells increased the risk of asthma hospital admissions, with the maximum cumulative relative risk (CRR) over three weeks (Lag0-21) in the total population. The highest single-day relative risk (RR) was found on the days of cold spells (Lag0) with the RR = 1.059 (95% CI: 1.008-1.113), and the CRR at Lag0-21 was 1.333 (95% CI: 1.049-1.693). Across different gender and age groups, younger people (<65 years) were more sensitive to cold spells. No significant effect modification by AQI was detected. CONCLUSION: Short-term exposure to cold spells is associated with an increased risk of hospital admissions for asthma in Beijing. During the cold spells, younger people aged <65 years were at particular risk for asthma exacerbations. Our results suggest that extreme cold events have a significant impact on asthma.
WHAT IS ALREADY KNOWN ABOUT THIS TOPIC? In recent years, climate change may lead to an increase in cold spells in the middle latitudes, and there is a positive correlation between cold spells and population mortality. WHAT IS ADDED BY THIS REPORT? The acute response period and the vulnerable population were identified under the optimal definition of cold spells, and the mortality burden caused by cold spells was estimated. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE? This research would provide evidence on the acute mortality effects of cold spells in southern China. Therefore, vulnerable populations, especially the elderly, should take timely measures to reduce the health damage caused by cold spells, especially in the first week after cold waves.
Cold spells have been associated with specific diseases. However, there is insufficient scientific evidence on the effects of cold spells on out-of-hospital cardiac arrest (OHCA). Data on OHCA cases and on meteorological factors and air pollutants were collected between 2013 and 2020. We adopted a quasi-Poisson generalized additive model with a distributed lag nonlinear model (DLNM) to estimate the effect of cold spells on daily OHCA incidence. Backward attributable risk within the DLNM framework was calculated to quantify the disease burden. We compared the effects and OHCA burden of cold spells using nine definitions. The risks of different cold spells on OHCA increased at higher intensities and longer durations. Based on Akaike’s information criterion for the quasi-Poisson regression model and the attributable risk, the optimal cold spell was defined as a period in the cold month when the daily mean temperature was below the 10th percentile of the temperature distribution in the study period for at least 2 days. The single-day effect of the optimal cold spell on OHCA occurred immediately and lasted for approximately 1 week. The maximum single-day effect was 1.052 (95% CI: 1.018-1.087) at lag0, while the maximum cumulative effect was 1.433 (95% CI:1.148-1.788) after a 14-day lag. Men were more susceptible to cold spells. Young and middle-aged people were affected by cold spells similar to the elderly. Cold spells can increase the risk of OHCA with an approximately 1-week lag effect. Health regulators should take more targeted measures to protect susceptible populations during cold weather.
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Under-five years old acute watery diarrhea (U5AWD) accounts for most diarrheal diseases’ burden, but little is known about the adjusted effect of meteorological and socioeconomic determinants. A dataset containing the seasonal numbers of U5AWD cases at the district level of Iran is collected through MOHME. Accordingly, the district-level standardized incidence ratio and Moran’s I values are calculated to detect the significant clusters of U5AWD over sixteen seasons from 2014 to 2018. Additionally, the author tested twelve Bayesian hierarchical models in order to determine which one was the most accurate at forecasting seasonal number of incidents. Iran features a number of U5AWD hotspots, particularly in the southeast. An extended spatiotemporal model with seasonally varying coefficients and space-time interaction outperformed other models, and so became the paper’s proposal in modeling U5AWD. Temperature demonstrated a global positive connection with seasonal U5AWD in districts (IRR: 1.0497; 95% CrI: 1.0254-1.0748), owing to its varying effects during the winter ((IRR: 1.0877; 95% CrI: 1.0408-1.1375) and fall (IRR: 1.0866; 95% CrI: 1.0405-1.1357) seasons. Also, elevation (IRR: 0.9997; 95% CrI: 0.9996-0.9998), piped drinking water (IRR: 0.9948; 95% CrI: 0.9933-0.9964), public sewerage network (IRR: 0.9965; 95% CrI: 0.9938-0.9992), years of schooling (IRR: 0.9649; 95% CrI: 0.944-0.9862), infrastructure-to-household size ratio (IRR: 0.9903; 95% CrI: 0.986-0.9946), wealth index (IRR: 0.9502; 95% CrI: 0.9231-0.9781), and urbanization (IRR: 0.9919; 95% CrI: 0.9893-0.9944) of districts were negatively associated with seasonal U5AWD incidence. Strategically, developing geoinformation alarm systems based on meteorological data might help predict U5AWD high-risk areas. The study also anticipates increased rates of U5AWD in districts with poor sanitation and socioeconomic level. Therefore, governments should take appropriate preventative actions in these sectors.
Understanding the geographical distribution in the association of temperature with childhood diarrhea can assist in formulating effective localized diarrhea prevention practices. This study aimed to identify the geographical variation in terms of temperature thresholds, lag effects, and attributable fraction (AF) in the effects of ambient temperature on Class C Other Infectious Diarrhea (OID) among children <5 years in Jiangsu Province, China. Daily data of OID cases and meteorological variables from 2015 to 2019 were collected. City-specific minimum morbidity temperature (MMT), increasing risk temperature (IRT), maximum risk temperature (MRT), maximum risk lag day (MRD), and lag day duration (LDD) were identified as risk indicators for the temperature-OID relationship using distributed lag non-linear models. The AF of OID incidence due to temperature was evaluated. Multivariable regression was also applied to explore the underlying modifiers of the AF. The geographical distributions of MMT, IRT, and MRT generally decreased with the latitude increment varying between 22.3-34.7 °C, -2.9-18.1 °C, and -6.8-23.2 °C. Considerable variation was shown in the AF ranging from 0.2 to 8.5%, and the AF significantly increased with latitude (95% confidence interval (CI): -3.458, -0.987) and economic status decrement (95% CI: -0.161, -0.019). Our study demonstrated between-city variations in the association of temperature with OID, which should be considered in the localized clinical and public health practices to decrease the incidence of childhood diarrhea.
Nowadays the World is facing a scarcity of safe drinking water and the water sector encounters great challenges. The impact of a growing population and the change of climate on water availability and quality; public health and environmental issues related to emerging pollutants are the major challenges that need to be addressed. In drinking water, there may be a chance of having water-related diseases and health issues due to the occurrence of some pathogens. In the present study, we synthesized nanosilica from rice husk and it was encapsulated with sodium alginate beads and tested its efficiency for removal of bacteria from drinking water. These beads are novel since it is fully bio-origin, biodegradable and cost-effective. The isolated nanosilica were characterized spectroscopically and morphologically (FT-IR, XRD, FESEM, and HRTEM). The synthesized beads were characterized by FT-IR, FESEM, and EDX and antibacterial analysis. Using the Petrifilm method and column disinfection experiment, different filler loadings were optimized and found that higher content (1.25 g) of nanosilica reduced bacterial contamination of drinking water. The alginate-nanosilica beads are cost-effective compared to alginate beads incorporated with other nanomaterials. The antibacterial evaluation verified superior antibacterial efficacy against E.coli. The prepared alginate-nanosilica beads can be used in the wastewater treatment industry, as an effective antibacterial agent.
This study explored the environmental determinants of different months on snail density measured in April at different types of snail habitats (marshlands, inner embankments, and hills) by considering spatial effects. Data were gathered from surveys on snails that were conducted in Hunan Province in April 2016, and information was collected on environmental variables. To investigate the environmental factors influencing snail density in various types of snail habitats, the ordinary least square model, spatial lag model, and spatial error model were all used. The environmental determinants for snail density showed different effects in the three types of snail habitats. In marshlands, snail density measured in April was associated positively with the normalized difference vegetation index (NDVI) and was associated negatively with flooding duration and annual hours of sunshine. Extreme temperatures correlated strongly to snail density measured in April (P < 0.05). In areas inside embankments, snail density measured in April increased with a decreased distance between snail habitat and the nearest river (P < 0.05). In hills, extreme heat, annual hours of sunshine, NDVI in September, and annual average land surface temperature (LST) were associated negatively with snail density measured in April, whereas index of moisture (IM) was associated positively with snail density measured in April (P < 0.05). The effects of LST and hours of sunshine on snail density measured in April varied with months of the year in the three different types of snail habitats (P < 0.05). Our study might provide a theoretical foundation for preventing snail transmission and subsequent spread of schistosomiasis.
BACKGROUND: Dengue is an endemic vector-borne disease influenced by environmental factors such as landscape and climate. Previous studies separately assessed the effects of landscape and climate factors on mosquito occurrence and dengue incidence. However, both factors concurrently coexist in time and space and can interact, affecting mosquito development and dengue disease transmission. For example, eggs laid in a suitable environment can hatch after being submerged in rain water. It has been difficult for conventional statistical modeling approaches to demonstrate these combined influences due to mathematical constraints. OBJECTIVES: To investigate the combined influences of landscape and climate factors on mosquito occurrence and dengue incidence. METHODS: Entomological, epidemiological, and landscape data from the rainy season (July-December) were obtained from respective government agencies in Metropolitan Manila, Philippines, from 2012 to 2014. Temperature, precipitation and vegetation data were obtained through remote sensing. A random forest algorithm was used to select the landscape and climate variables. Afterward, using the identified key variables, a model-based (MOB) recursive partitioning was implemented to test the combined influences of landscape and climate factors on ovitrap index (vector mosquito occurrence) and dengue incidence. RESULTS: The MOB recursive partitioning for ovitrap index indicated a high sensitivity of vector mosquito occurrence on environmental conditions generated by a combination of high residential density areas with low precipitation. Moreover, the MOB recursive partitioning indicated high sensitivity of dengue incidence to the effects of precipitation in areas with high proportions of residential density and commercial areas. CONCLUSIONS: Dengue dynamics are not solely influenced by individual effects of either climate or landscape, but rather by their synergistic or combined effects. The presented findings have the potential to target vector surveillance in areas identified as suitable for mosquito occurrence under specific climatic conditions and may be relevant as part of urban planning strategies to control dengue.
Dengue is a mosquito-borne viral infection, found in tropical and sub-tropical climates worldwide, mostly in urban and semi-urban areas. Countries like Pakistan receive heavy rains annually resulting in floods in urban cities due to poor drainage systems. Currently, different cities of Pakistan are at high risk of dengue outbreaks, as multiple dengue cases have been reported due to poor flood control and drainage systems. After heavy rain in urban areas, mosquitoes are provided with a favorable environment for their breeding and transmission through stagnant water due to poor maintenance of the drainage system. The history of the dengue virus in Pakistan shows that there is a closed relationship between dengue outbreaks and a rainfall. There is no specific treatment for dengue; however, the outbreak can be controlled through internet of medical things (IoMT). In this paper, we propose a novel privacy-preserved IoMT model to control dengue virus outbreaks by tracking dengue virus-infected patients based on bedding location extracted using call data record analysis (CDRA). Once the bedding location of the patient is identified, then the actual infected spot can be easily located by using geographic information system mapping. Once the targeted spots are identified, then it is very easy to eliminate the dengue by spraying the affected areas with the help of unmanned aerial vehicles (UAVs). The proposed model identifies the targeted spots up to 100%, based on the bedding location of the patient using CDRA.
Melioidosis is endemic in the remote Katherine region of northern Australia. In a population with high rates of chronic disease, social inequities, and extreme remoteness, the impact of melioidosis is exacerbated by severe weather events and disproportionately affects First Nations Australians. All culture-confirmed melioidosis cases in the Katherine region of the Australian Top End between 1989-2021 were included in the study, and the clinical features and epidemiology were described. The diversity of Burkholderia pseudomallei strains in the region was investigated using genomic sequencing. From 1989-2021 there were 128 patients with melioidosis in the Katherine region. 96/128 (75%) patients were First Nations Australians, 72/128 (56%) were from a very remote region, 68/128 (53%) had diabetes, 57/128 (44%) had a history of hazardous alcohol consumption, and 11/128 (9%) died from melioidosis. There were 9 melioidosis cases attributable to the flooding of the Katherine River in January 1998; 7/9 flood-associated cases had cutaneous melioidosis, five of whom recalled an inoculating event injury sustained wading through flood waters or cleaning up after the flood. The 126 first-episode clinical B. pseudomallei isolates that underwent genomic sequencing belonged to 107 different sequence types and were highly diverse, reflecting the vast geographic area of the study region. In conclusion, melioidosis in the Katherine region disproportionately affects First Nations Australians with risk factors and is exacerbated by severe weather events. Diabetes management, public health intervention for hazardous alcohol consumption, provision of housing to address homelessness, and patient education on melioidosis prevention in First Nations languages should be prioritised.
BACKGROUND: Although studies have provided the estimates of floods-diarrhoea associations, little is known about the lag effect, effect modification, and attributable risk. Based on Sichuan, China, an uneven socio-economic development province with plateau, basin, and mountain terrains spanning different climatic zones, we aimed to systematically examine the impacts of floods on diarrheal morbidity. METHODS: We retrieved information on daily diarrheal cases, floods, meteorological variables, and annual socio-economic characteristics for 21 cities in Sichuan from January 1, 2017 to December 31, 2019. We fitted time-series Poisson models to estimate the city-specific floods-diarrhoea relation over the lags of 0-14 days, and then pooled them using meta-analysis for cumulative and lag effects. We further employed meta-regression to explore potential effect modifiers and identify effect modification. We calculated the attributable diarrheal cases and fraction of attributable morbidity within the framework of the distributed lag model. RESULTS: Floods had a significant cumulative association with diarrhoea at the provincial level, but varied by regions and cities. The effects of the floods appeared on the second day after the floods and lasted for 5 days. Floods-diarrhoea relations were modified by three effect modifiers, with stronger flood effects on diarrhoea found in areas with higher air pressure, lower diurnal temperature range, or warmer temperature. Floods were responsible for advancing a fraction of diarrhoea, corresponding to 0.25% within the study period and 0.48% within the flood season. CONCLUSIONS: The impacts imposed by floods were mainly distributed within the first week. The floods-diarrhoea relations varied by geographic and climatic conditions. The diarrheal burden attributable to floods is currently low in Sichuan, but this figure could increase with the exposure more intensive and the effect modifiers more detrimental in the future. Our findings are expected to provide evidence for the formulation of temporal- and spatial-specific strategies to reduce potential risks of flood-related diarrhoea.
BACKGROUND: Schistosomiasis is a highly recurrent parasitic disease that affects a wide range of areas and a large number of people worldwide. In China, schistosomiasis has seriously affected the life and safety of the people and restricted the economic development. Schistosomiasis is mainly distributed along the Yangtze River and in southern China. Anhui Province is located in the Yangtze River Basin of China, with dense water system, frequent floods and widespread distribution of Oncomelania hupensis that is the only intermediate host of schistosomiasis, a large number of cattle, sheep and other livestock, which makes it difficult to control schistosomiasis. It is of great significance to monitor and analyze spatiotemporal risk of schistosomiasis in Anhui Province, China. We compared and analyzed the optimal spatiotemporal interpolation model based on the data of schistosomiasis in Anhui Province, China and the spatiotemporal pattern of schistosomiasis risk was analyzed. METHODS: In this study, the root-mean-square-error (RMSE) and absolute residual (AR) indicators were used to compare the accuracy of Bayesian maximum entropy (BME), spatiotemporal Kriging (STKriging) and geographical and temporal weighted regression (GTWR) models for predicting the spatiotemporal risk of schistosomiasis in Anhui Province, China. RESULTS: The results showed that (1) daytime land surface temperature, mean minimum temperature, normalized difference vegetation index, soil moisture, soil bulk density and urbanization were significant factors affecting the risk of schistosomiasis; (2) the spatiotemporal distribution trends of schistosomiasis predicted by the three methods were basically consistent with the actual trends, but the prediction accuracy of BME was higher than that of STKriging and GTWR, indicating that BME predicted the prevalence of schistosomiasis more accurately; and (3) schistosomiasis in Anhui Province had a spatial autocorrelation within 20 km and a temporal correlation within 10 years when applying the optimal model BME. CONCLUSIONS: This study suggests that BME exhibited the highest interpolation accuracy among the three spatiotemporal interpolation methods, which could enhance the risk prediction model of infectious diseases thereby providing scientific support for government decision making.
In Jambi province, Sumatra, Indonesia, flooding is a recurrent rainy season phenomenon. Historically considered manageable, recent political economic developments have changed this situation. Today, flooding is an environmental hazard and a threat to people’s livelihoods and health. Based on qualitative research and literature that has developed relational approaches to risk and water, we investigate past and present hydrosocial relations in Jambi province and reconstruct the changing meaning of flooding. We suggest that flooding as a hazard in Jambi was produced through the introduction of the plantation industry to the area and its prioritization of dry land for agm-industrial development. This development altered the materiality of water flows, reconfigured power relations and changed the socio-cultural dimensions of flooding. Together, these changes have led to a separation of flooding from its original social and geographic realm, producing new risks and vulnerabilities. This paper provides insights into the material and symbolic dimensions that influence how environmental processes come to be imagined, controlled and contested. It shows how tracing the socionatural production of hazards may help explain the increasingly systemic nature of risks and provide insights into the wider social meaning of environmental risks.
The epidemic of leptospirosis in humans occurs annually in Thailand. In this study, we have developed mathematical models to investigate transmission dynamics between humans, animals, and a contaminated environment. We compared different leptospire transmission models involving flooding and weather conditions, shedding and multiplication rate in a contaminated environment. We found that the model in which the transmission rate depends on both flooding and temperature, best-fits the reported human data on leptospirosis in Thailand. Our results indicate that flooding strongly contributes to disease transmission, where a high degree of flooding leads to a higher number of infected individuals. Sensitivity analysis showed that the transmission rate of leptospires from a contaminated environment was the most important parameter for the total number of human cases. Our results suggest that public education should target people who work in contaminated environments to prevent Leptospira infections.
Bacterial pathogens in surface waters threaten human health. The health risk is especially high in developing countries where sanitation systems are often lacking or deficient. Considering twelve flash-flood events sampled from 2011 to 2015 at the outlet of a 60-ha tropical montane headwater catchment in Northern Lao PDR, and using Escherichia coli as a fecal indicator bacteria, our objective was to quantify the contributions of both surface runoff and sub-surface flow to the in-stream concentration of E. coli during flood events, by (1) investigating E. coli dynamics during flood events and among flood events and (2) designing and comparing simple statistical and mixing models to predict E. coli concentration in stream flow during flood events. We found that in-stream E. coli concentration is high regardless of the contributions of both surface runoff and sub-surface flow to the flood event. However, we measured the highest concentration of E. coli during the flood events that are predominantly driven by surface runoff. This indicates that surface runoff, and causatively soil surface erosion, are the primary drivers of in-stream E. coli contamination. This was further confirmed by the step-wise regression applied to instantaneous E. coli concentration measured in individual water samples collected during the flood events, and by the three models applied to each flood event (linear model, partial least square model, and mixing model). The three models showed that the percentage of surface runoff in stream flow was the best predictor of the flood event mean E. coli concentration. The mixing model yielded a Nash-Sutcliffe efficiency of 0.65 and showed that on average, 89% of the in-stream concentration of E. coli resulted from surface runoff, while the overall contribution of surface runoff to the stream flow was 41%. We also showed that stream flow turbidity and E. coli concentration were positively correlated, but that turbidity was not a strong predictor of E. coli concentration during flood events. These findings will help building adequate catchment-scale models to predict E. coli fate and transport, and mapping the related risk of fecal contamination in a global changing context.
In this study, the adsorption-elution method was modified to concentrate viral particles in water samples and investigate the contamination of groundwater with norovirus genogroup II (NoV GII), rotavirus A (RVA), and Pepper mild mottle virus (PMMoV). The mean recovery rate of a murine norovirus strain, which was inoculated into groundwater samples collected from a deep well, was the highest (39%) when the viral RNA was directly extracted from the membrane instead of eluting the adsorbed viral particles. This adsorption-direct extraction method was applied to groundwater samples (20 liters) collected from deep wells used for the public drinking water supply (n = 22) and private wells (n = 9). RVA (85 copies/liter) and NoV GII (35 copies/liter) were detected in water samples from a deep well and a private well, respectively. PMMoV was detected in 95% and 89% of water samples from deep wells and private wells, respectively, at concentrations of up to 990 copies/liter. The modified method was also used to extract bacterial DNA from the membrane (recovery rate of inoculated Escherichia coli K-12 was 22%). The Bacteroidales genetic markers specific to ruminants (BacR) and pigs (Pig2Bac) were detected in samples from a deep well and a private well, respectively. The modified virus concentration method has important implications for the management of microbiological safety in the groundwater supply. IMPORTANCE We investigated the presence of enteric viruses and bacterial genetic markers to determine fecal contamination in groundwater samples from deep wells used for the public drinking water supply and private wells in Japan. Groundwater is often subjected to chlorination; malfunctions in chlorine treatment result in waterborne disease outbreaks. The modified method successfully concentrated both viruses and bacteria in 20-liter groundwater samples. Norovirus genogroup II (GII), rotavirus A, Pepper mild mottle virus, and Bacteroidales genetic markers specific to ruminants and pigs were detected. Frequent flooding caused by increased incidences of extreme rainfall events promotes the infiltration of surface runoff containing livestock wastes and untreated wastewater into wells, possibly increasing groundwater contamination risk. The practical and efficient method developed in this study will enable waterworks and the environmental health departments of municipal/prefectural governments to monitor water quality. Additionally, the modified method will contribute to improving the microbiological safety of groundwater.
Schistosomiasis is a water-borne parasitic disease distributed worldwide, while schistosomiasis japonica localizes in the People’s Republic of China, the Philippines, and a few regions of Indonesia. Although significant achievements have been obtained in these endemic countries, great challenges still exist to reach the elimination of schistosomiasis japonica, as the occurrence of flooding can lead to several adverse consequences on the prevalence of schistosomiasis. This review summarizes the influence of flooding on the transmission of schistosomiasis japonica and interventions responding to the adverse impacts from the One Health perspective in human beings, animals, and the environment. For human and animals, behavioral changes and the damage of water conservancy and sanitary facilities will increase the intensity of water contact. For the environment, the density of Oncomelania snails significantly increases from the third year after flooding, and the snail habitats can be enlarged due to active and passive diffusion. With more water contact of human and other reservoir hosts, and larger snail habitats with higher density of living snails, the transmission risk of schistosomiasis increases under the influence of flooding. With the agenda set for global schistosomiasis elimination, interventions from the One Health perspective are put forward to respond to the impacts of increased flooding. For human beings, conducting health education to increase the consciousness of self-protection, preventive chemotherapy for high-risk populations, supply of safe water, early case finding, timely reporting, and treating cases will protect people from infection and prevent the outbreak of schistosomiasis. For animals, culling susceptible domestic animals, herding livestock in snail-free areas, treating livestock with infection or at high risk of infection, harmless treatment of animal feces to avoid water contamination, and monitoring the infection status of wild animals in flooding areas are important to cut off the transmission chain from the resources. For the environment, early warning of flooding, setting up warning signs and killing cercaria in risk areas during and post flooding, reconstructing damaged water conservancy facilities, developing hygiene and sanitary facilities, conducting snail surveys, using molluscicide, and predicting areas with high risk of schistosomiasis transmission after flooding all contribute to reducing the transmission risk of schistosomiasis. These strategies need the cooperation of the ministry of health, meteorological administration, water resources, agriculture, and forestry to achieve the goal of minimizing the impact of flooding on the transmission of schistosomiasis. In conclusion, flooding is one of the important factors affecting the transmission of schistosomiasis japonica. Multi-sectoral cooperation is needed to effectively prevent and control the adverse impacts of flooding on human beings, animals, and the environment.
BACKGROUND: Flooding is considered to be one of the most important factors contributing to the rebound of Oncomelania hupensis, a small tropical freshwater snail and the only intermediate host of Schistosoma japonicum, in endemic foci. The aim of this study was to assess the risk of intestinal schistosomiasis transmission impacted by flooding in the region around Poyang Lake using multi-source remote sensing images. METHODS: Normalized Difference Vegetation Index (NDVI) data collected by the Landsat 8 satellite were used as an ecological and geographical suitability indicator of O. hupensis habitats in the Poyang Lake region. The expansion of the water body due to flooding was estimated using dual-polarized threshold calculations based on dual-polarized synthetic aperture radar (SAR). The image data were captured from the Sentinel-1B satellite in May 2020 before the flood and in July 2020 during the flood. A spatial database of the distribution of snail habitats was created using the 2016 snail survey in Jiangxi Province. The potential spread of O. hupensis snails after the flood was predicted by an overlay analysis of the NDVI maps in the flood-affected areas around Poyang Lake. The risk of schistosomiasis transmission was classified based on O. hupensis snail density data and the related NDVI. RESULTS: The surface area of Poyang Lake was approximately 2207 km(2) in May 2020 before the flood and 4403 km(2) in July 2020 during the period of peak flooding; this was estimated to be a 99.5% expansion of the water body due to flooding. After the flood, potential snail habitats were predicted to be concentrated in areas neighboring existing habitats in the marshlands of Poyang Lake. The areas with high risk of schistosomiasis transmission were predicted to be mainly distributed in Yongxiu, Xinjian, Yugan and Poyang (District) along the shores of Poyang Lake. By comparing the predictive results and actual snail distribution, we estimated the predictive accuracy of the model to be 87%, which meant the 87% of actual snail distribution was correctly identified as snail habitats in the model predictions. CONCLUSIONS: Data on water body expansion due to flooding and environmental factors pertaining to snail breeding may be rapidly extracted from Landsat 8 and Sentinel-1B remote sensing images. Applying multi-source remote sensing data for the timely and effective assessment of potential schistosomiasis transmission risk caused by snail spread during flooding is feasible and will be of great significance for more precision control of schistosomiasis.
INTRODUCTION: Skin and soft tissue infections have the potential to affect every patient admitted to a surgical service. Changes to the microbiota colonizing wounds during natural disasters, such as the Townsville floods of 2019, could impact empiric antibiotic choice and need for return to theatre. METHODS: This retrospective observational cohort study reviews culture data and demographics for patients undergoing surgical debridement of infected wounds over a six-month period starting in November 2018 to May 2019 at the Townsville Hospital. RESULTS: Of the 408 patients requiring operative intervention, only 61 patients met the inclusion criteria. The groups were comparative in terms of age and gender, but a greater proportion of patients (40.5% versus 29.1%, P = 0.368) in the post-flood group were diabetic. Common skin commensals, such as Staphylococcus aureus, were the most common pathogen in both groups, however the post-flood group had a higher proportion of atypical organisms (14 versus 8 patients), and an increased need for repeated debridement for infection control (24 versus 14 patients). CONCLUSION: Wound swabs and tissue culture are imperative during surgical debridement and may guide the use of more broad-spectrum coverage following a significant flooding event.
Surveillance programs are essential for the prevention and control of mosquito-borne arboviruses that cause serious human and animal diseases. Viral metatranscriptomic sequencing can enhance surveillance by enabling untargeted, high-throughput arbovirus detection. We used metatranscriptomic sequencing to screen field-collected mosquitoes for arboviruses to better understand how metatranscriptomics can be utilised in routine surveillance. Following a significant flood event in 2016, more than 56,000 mosquitoes were collected over seven weeks from field traps set up in Victoria, Australia. The traps were split into samples of 1000 mosquitoes or less and sequenced on the Illumina HiSeq. Five arboviruses relevant to public health (Ross River virus, Sindbis virus, Trubanaman virus, Umatilla virus, and Wongorr virus) were detected a total of 33 times in the metatranscriptomic data, with 94% confirmed using reverse transcription quantitative PCR (RT-qPCR). Analysis of metatranscriptomic cytochrome oxidase I (COI) sequences enabled the detection of 12 mosquito and two biting midge species. Screening of the same traps by an established public health arbovirus surveillance program corroborated the metatranscriptomic arbovirus and mosquito species detections. Assembly of genome sequences from the metatranscriptomic data also led to the detection of 51 insect-specific viruses, both known and previously undescribed, and allowed phylogenetic comparison to past strains. We have demonstrated how metatranscriptomics can enhance surveillance by enabling untargeted arbovirus detection, providing genomic epidemiological data, and simultaneously identifying vector species from large, unsorted mosquito traps.
Freshwater reservoirs are a crucial source of urban drinking water worldwide; thus, long-term evaluations of critical water quality determinants are essential. We conducted this study in a large drinking water reservoir for 11 years (2010-2020). The variabilities of ambient nutrients and total suspended solids (TSS) throughout the seasonal monsoon-mediated flow regime influenced algal chlorophyll (Chl-a) levels. The study determined the role of the monsoon-mediated flow regime on reservoir water chemistry. The reservoir conditions were mesotrophic to eutrophic based on nitrogen (N) and phosphorus (P) concentrations. An occasional total coliform bacteria (TCB) count of 16,000 MPN per 100 mL was recorded in the reservoir, presenting a significant risk of waterborne diseases among children. A Mann-Kendall test identified a consistent increase in water temperature, conductivity, and chemical oxygen demand (COD) over the study period, limiting a sustainable water supply. The drought and flood regime mediated by the monsoon resulted in large heterogeneities in Chl-a, TCB, TSS, and nutrients (N, P), indicating its role as a key regulator of the ecological functioning of the reservoir. The ambient N:P ratio is a reliable predictor of sestonic Chl-a productivity, and the reservoir was P-limited. Total phosphorus (TP) had a strong negative correlation (R(2) = 0.59, p < 0.05) with the outflow from the dam, while both the TSS (R(2) = 0.50) and Chl-a (R(2) = 0.32, p < 0.05) had a strong positive correlation with the outflow. A seasonal trophic state index revealed oligo-mesotrophic conditions, indicating a limited risk of eutrophication and a positive outcome for long-term management. In conclusion, the Asian monsoon largely controlled the flood and drought conditions and manipulated the flow regime. Exceedingly intensive crop farming in the basin may lead to oligotrophic nutrient enrichment. Although the reservoir water quality was good, we strongly recommend stringent action to alleviate sewage, nutrient, and pollutant inflows to the reservoir.
Drought is a global threat to public health. Increasingly, the impact of drought on mental health and wellbeing is being recognized. This paper investigates the relationship between drought and well-being to determine which drought indices most effectively capture well-being outcomes. A thorough understanding of the relationship between drought and well-being must consider the (i) three aspects of drought (duration, frequency, and magnitude); (ii) different types of drought (meteorological, agricultural, etc.); and (iii) the individual context of specific locations, communities, and sectors. For this reason, we used a variety of drought types, drought indices, and time windows to identify the thresholds for wet and dry epochs that enhance and suppress impacts to well-being. Four postcodes in New South Wales (NSW), Australia, are used as case studies in the analysis to highlight the spatial variability in the relationship between drought and well-being. The results demonstrate that the relationship between drought indices and well-being outcomes differs temporally, spatially, and according to drought type. This paper objectively tests the relationship between commonly used drought indices and wellbeing outcomes to establish whether current methods of quantifying drought effectively capture well-being outcomes. For funding, community programs, and interventions to result in successful adaptation, it is essential to critically choose which drought index, time window, and well-being outcome to use in empirical studies. The uncertainties associated with these relationships must be accounted for, and it must also be realized that results will differ on the basis of these decisions.
BACKGROUND: Despite concerns regarding increasingly frequent and intense heat waves due to global warming, there is still a lack of information on the effects of extremely high temperatures on the adult abundance of mosquito species that are known to transmit vector-borne diseases. This study aimed to evaluate the effects of extremely high temperatures on the abundance of mosquitoes by analyzing time series data for temperature and mosquito abundance in Incheon Metropolitan City (IMC), Republic of Korea, for the period from 2015 to 2020. METHODS: A generalized linear model with Poisson distribution and overdispersion was used to model the nonlinear association between temperature and mosquito count for the whole study area and for its constituent urban and rural regions. The association parameters were pooled using multivariate meta-regression. The temperature-mosquito abundance curve was estimated from the pooled estimates, and the ambient temperature at which mosquito populations reached maximum abundance (TMA) was estimated using a Monte Carlo simulation method. To quantify the effect of extremely high temperatures on mosquito abundance, we estimated the mosquito abundance ratio (AR) at the 99th temperature percentile (AR(99th)) against the TMA. RESULTS: Culex pipiens was the most common mosquito species (51.7%) in the urban region of the IMC, while mosquitoes of the genus Aedes (Ochlerotatus) were the most common in the rural region (47.8%). Mosquito abundance reached a maximum at 23.5 °C for Cx. pipiens and 26.4 °C for Aedes vexans. Exposure to extremely high temperatures reduced the abundance of Cx. pipiens mosquitoes {AR(99th) 0.34 [95% confidence interval (CI) 0.21-0.54]} to a greater extent than that of Anopheles spp. [AR(99th) 0.64 (95% CI 0.40-1.03)]. When stratified by region, Ae. vexans and Ochlerotatus koreicus mosquitoes showed higher TMA and a smaller reduction in abundance at extreme heat in urban Incheon than in Ganghwa, suggesting that urban mosquitoes can thrive at extremely high temperatures as they adapt to urban thermal environments. CONCLUSIONS: We confirmed that the temperature-related abundance of the adult mosquitoes was species and location specific. Tailoring measures for mosquito prevention and control according to mosquito species and anticipated extreme temperature conditions would help to improve the effectiveness of mosquito-borne disease control programs.
BACKGROUND: Rigorous assessment of the effect of malaria control strategies on local malaria dynamics is a complex but vital step in informing future strategies to eliminate malaria. However, the interactions between climate forcing, mass drug administration, mosquito control and their effects on the incidence of malaria remain unclear. METHODS: Here, we analyze the effects of interventions on the transmission dynamics of malaria (Plasmodium vivax and Plasmodium falciparum) on Hainan Island, China, controlling for environmental factors. Mathematical models were fitted to epidemiological data, including confirmed cases and population-wide blood examinations, collected between 1995 and 2010, a period when malaria control interventions were rolled out with positive outcomes. RESULTS: Prior to the massive scale-up of interventions, malaria incidence shows both interannual variability and seasonality, as well as a strong correlation with climatic patterns linked to the El Nino Southern Oscillation. Based on our mechanistic model, we find that the reduction in malaria is likely due to the large scale rollout of insecticide-treated bed nets, which reduce the infections of P. vivax and P. falciparum malaria by 93.4% and 35.5%, respectively. Mass drug administration has a greater contribution in the control of P. falciparum (54.9%) than P. vivax (5.3%). In a comparison of interventions, indoor residual spraying makes a relatively minor contribution to malaria control (1.3%-9.6%). CONCLUSIONS: Although malaria transmission on Hainan Island has been exacerbated by El Nino Southern Oscillation, control methods have eliminated both P. falciparum and P. vivax malaria from this part of China.
BACKGROUND: In many areas of the Greater Mekong Subregion (GMS), malaria endemic regions have shrunk to patches of predominantly low-transmission. With a regional goal of elimination by 2030, it is important to use appropriate methods to analyze and predict trends in incidence in these remaining transmission foci to inform planning efforts. Climatic variables have been associated with malaria incidence to varying degrees across the globe but the relationship is less clear in the GMS and standard methodologies may not be appropriate to account for the lag between climate and incidence and for locations with low numbers of cases. METHODS: In this study, a methodology was developed to estimate the spatio-temporal lag effect of climatic factors on malaria incidence in Thailand within a Bayesian framework. A simulation was conducted based on ground truth of lagged effect curves representing the delayed relation with sparse malaria cases as seen in our study population. A case study to estimate the delayed effect of environmental variables was used with malaria incidence at a fine geographic scale of sub-districts in a western province of Thailand. RESULTS: From the simulation study, the model assumptions which accommodated both delayed effects and excessive zeros appeared to have the best overall performance across evaluation metrics and scenarios. The case study demonstrated lagged climatic effect estimation of the proposed modeling with real data. The models appeared to be useful to estimate the shape of association with malaria incidence. CONCLUSIONS: A new method to estimate the spatiotemporal effect of climate on malaria trends in low transmission settings is presented. The developed methodology has potential to improve understanding and estimation of past and future trends in malaria incidence. With further development, this could assist policy makers with decisions on how to more effectively distribute resources and plan strategies for malaria elimination.
Environmental temperature is a key driver of malaria transmission dynamics. Using detailed temperature records from four sites: low elevation (1800), mid elevation (2200 m), and high elevation (2600-3200 m) in the western Himalaya, we model how temperature regulates parasite development rate (the inverse of the extrinsic incubation period, EIP) in the wild. Using a Briére parametrization of the EIP, combined with Bayesian parameter inference, we study the thermal limits of transmission for avian (Plasmodium relictum) and human Plasmodium parasites (P. vivax and P. falciparum) as well as for two malaria-like avian parasites, Haemoproteus and Leucocytozoon. We demonstrate that temperature conditions can substantially alter the incubation period of parasites at high elevation sites (2600-3200 m) leading to restricted parasite development or long transmission windows. The thermal limits (optimal temperature) for Plasmodium parasites were 15.62-34.92°C (30.04°C) for P. falciparum, 13.51-34.08°C (29.02°C) for P. vivax, 12.56-34.46°C (29.16°C) for P. relictum and for two malaria-like parasites, 12.01-29.48°C (25.16°C) for Haemoproteus spp. and 11.92-29.95°C (25.51°C) for Leucocytozoon spp. We then compare estimates of EIP based on measures of mean temperature versus hourly temperatures to show that EIP days vary in cold versus warm environments. We found that human Plasmodium parasites experience a limited transmission window at 2600 m. In contrast, for avian Plasmodium transmission was not possible between September and March at 2600 m. In addition, temperature conditions suitable for both Haemoproteus and Leucocytozoon transmission were obtained from June to August and in April, at 2600 m. Finally, we use temperature projections from a suite of climate models to predict that by 2040, high elevation sites (~2600 m) will have a temperature range conducive for malaria transmission, albeit with a limited transmission window. Our study highlights the importance of accounting for fine-scale thermal effects in the expansion of the range of the malaria parasite with global climate change.
Malaria elimination is a global priority, which India has also adopted as a target. Despite the malaria control efforts like long-lasting insecticidal nets distribution, rounds of indoor residual spray, the introduction of bi-valent rapid diagnostic tests and artemisinin combination therapy, malaria remained consistent in Dolonibasti sub-center of Orang block primary health center (BPHC) under the district Udalguri, Assam state followed by abrupt rise in cases in 2018. Therefore, we aimed to investigate the factors driving the malaria transmission in the outbreak area of Dolonibasti sub-center. Malaria epidemiological data (2008-2018) of Udalguri district and Orang BPHC was collected. The annual (2011-2018) and monthly (2013-2018) malaria and meteorological data of Dolonibasti sub-center was collected. An entomological survey, Knowledge, Attitude and Practices study among malaria cases (n = 120) from Dolonibasti was conducted. In 2018, 26.1 % (2136/ 8188) of the population of Dolonibasti were found to be malaria positive, of which 55% were adults (n = 1176). Majority of cases were from tea tribe populations (90%), either asymptomatic or with fever only, 67.5 % (81/120) had experienced malaria infection during past years. The outbreak was characterized by a strong increase in cases in June 2018, high proportion of slide falciparum rate of 26.1% (other years average, 15.8%) and high proportion of P. falciparum of 81.2 % (other years average, 84.3%). Anopheles minimus s.l. was the major vector with 28.6% positivity and high larval density in paddy fields/ drainage area. Annual relative humidity was associated with rise in malaria cases, annual parasite incidence (r(s) = 0.69, 90%CI; p = 0.06) and slide positivity rate (r(s) = 0.83, 95%CI; p = 0.01). Older people were less educated (r(s) = -0.66; p < 0.001), had lesser knowledge about malaria cause (r(s) = -0.42; χ(2)=21.80; p < 0.001) and prevention (r(s) = -0.18; p = 0.04). Malaria control practices were followed by those having knowledge about cause of malaria (r(s) = 0.36; χ(2) = 13.50; p < 0.001) and prevention (r(s) = 0.40; χ(2) = 17.71; p < 0.001). Altogether, 84.6% (44/52) of the respondents did not use protective measures. We described a sudden increase in malaria incidence in a rural, predominantly tea tribe population group with high illiteracy rate and ignorance on protective measures against malaria. More efforts that are concerted needed to educate the community about malaria control practices.
Already climate-related hazards are impacting sanitation systems in Indonesia and elsewhere, and climate models indicate these hazards are likely to increase in frequency and intensity. Without due attention, to maintain existing progress on Sustainable Development Goal 6’s target 6.2 and to increase it to meet ambitions for 2030 will be difficult. City governments need new forms of evidence to respond, as well as approaches to enable them to consider sufficient breadth of strategies to adapt effectively. This paper describes a co-production research process which engaged local governments in four cities in Indonesia experiencing different climate hazards. Local government engagement took place across three stages of (i) inception and design, (ii) participation as key informants and (iii) joint analysis and engagement on the findings. We adapted and simplified a risk prioritisation process based on current literature and employed a novel framework of a ‘climate resilient sanitation system’ to prompt articulation of current and proposed climate change adaptation response actions. In contrast to many current framings of climate resilience in sanitation that focus narrowly on technical responses, the results paint a rich picture of efforts needed by city governments across all domains, including planning, institutions, financing, infrastructure and management options, user awareness, water cycle management and monitoring and evaluation. Local government commitment and improved comprehension on the implications of climate change for sanitation service delivery were key outcomes arising from the co-production process. With strengthened policy and capacity building initiatives from national level, this foundation can be supported, and Indonesian city governments will be equipped to move forward with adaptation actions that protect on-going access to sanitation services, public health and the environment.
BACKGROUND: Intensification of land use threatens to increase the emergence and prevalence of zoonotic diseases, with an adverse impact on human wellbeing. Understanding how the interaction between agriculture, natural systems, climate and socioeconomic drivers influence zoonotic disease distribution is crucial to inform policy planning and management to limit the emergence of new infections. OBJECTIVES: Here we assess the relative contribution of environmental, climatic and socioeconomic factors influencing reported cryptosporidiosis across Australia from 2001 to 2018. METHODS: We apply a Bayesian spatio-temporal analysis using Integrated Nested Laplace Approximation (INLA). RESULTS: We find that area-level risk of reported disease are associated with the proportions of the population under 5 and over 65 years of age, socioeconomic disadvantage, annual rainfall anomaly, and the proportion of natural habitat remaining. This combination of multiple factors influencing cryptosporidiosis highlights the benefits of a sophisticated spatio-temporal statistical approach. Two key findings from our model include: an estimated 4.6% increase in the risk of reported cryptosporidiosis associated with 22.8% higher percentage of postal area covered with original habitat; and an estimated 1.8% increase in disease risk associated with a 77.99 mm increase in annual rainfall anomaly at the postal area level. DISCUSSION: These results provide novel insights regarding the predictive effects of extreme rainfall and the proportion of remaining natural habitat, which add unique explanatory power to the model alongside the variance associated with other predictive variables and spatiotemporal variation in reported disease. This demonstrates the importance of including perspectives from land and water management experts for policy making and public health responses to manage environmentally mediated diseases, including cryptosporidiosis.
BACKGROUND: Many studies have reported the interactive effects between relative humidity and temperature on infectious diseases. However, evidence regarding the combined effects of relative humidity and temperature on bacillary dysentery (BD) is limited, especially for large-scale studies. To address this research need, humidex was utilized as a comprehensive index of relative humidity and temperature. We aimed to estimate the effect of humidex on BD across mainland China, evaluate its heterogeneity, and identify potential effect modifiers. METHODS: Daily meteorological and BD surveillance data from 2014 to 2016 were obtained for 316 prefecture-level cities in mainland China. Humidex was calculated on the basis of relative humidity and temperature. A multicity, two-stage time series analysis was then performed. In the first stage, a common distributed lag non-linear model (DLNM) was established to obtain city-specific estimates. In the second stage, a multivariate meta-analysis was conducted to pool these estimates, assess the significance of heterogeneity, and explore potential effect modifiers. RESULTS: The pooled cumulative estimates showed that humidex could promote the transmission of BD. The exposure-response relationship was nearly linear, with a maximum cumulative relative risk (RR) of 1.45 [95% confidence interval (CI): 1.29-1.63] at a humidex value of 40.94. High humidex had an acute adverse effect on BD. The humidex-BD relationship could be modified by latitude, urbanization rate, the natural growth rate of population, and the number of primary school students per thousand persons. CONCLUSIONS: High humidex could increase the risk of BD incidence. Thus, it is suitable to incorporate humidex as a predictor into the early warning system of BD and to inform the general public in advance to be cautious when humidex is high. This is especially true for regions with higher latitude, higher urbanization rates, lower natural growth rates of population, and lower numbers of primary school students per thousand persons.
The construction of spatio-temporal models can be either descriptive or dynamic. In this study we aim to evaluate the differences in model fitting between a descriptive model and a dynamic model of the transmission for intestinal schistosomiasis caused by Schistosoma japonicum in Guichi, Anhui Province, China. The parasitological data at the village level from 1991 to 2014 were obtained by cross-sectional surveys. We used the fixed rank kriging (FRK) model, a descriptive model, and the integro-differential equation (IDE) model, a dynamic model, to explore the space-time changes of schistosomiasis japonica. In both models, the average daily precipitation and the normalized difference vegetation index are significantly positively associated with schistosomiasis japonica prevalence, while the distance to water bodies, the hours of daylight and the land surface temperature at daytime were significantly negatively associated. The overall root mean square prediction error of the IDE and FRK models was 0.0035 and 0.0054, respectively, and the correlation reflected by Pearson’s correlation coefficient between the predicted and observed values for the IDE model (0.71; p<0.01) was larger than that for the FRK model (0.53; p=0.02). The IDE model fits better in capturing the geographic variation of schistosomiasis japonica. Dynamic spatio-temporal models have the advantage of quantifying the process of disease transmission and may provide more accurate predictions.
Meteorological factors and the increase in extreme weather events are closely related to the incidence rate of infectious diarrhea. However, few studies have explored whether the impact of the same meteorological factors on the incidence rate of infectious diarrhea in different climate regions has changed and quantified these changes. In this study, the time series fixed-effect Poisson regression model guided by climate was used to quantify the relationships between the incidence rate of various types of infectious diarrhea and meteorological factors in different climate regions of China from 2004 to 2018, with a lag of 0-2 months. In addition, six social factors, including per capita Gross Domestic Product (GDP), population density, number of doctors per 1000 people, proportion of urbanized population, proportion of children aged 0-14 years old, and proportion of elderly over 65 years old, were included in the model for confounding control. Additionally, the intercept of each province in each model was analyzed by a meta-analysis. Four climate regions were considered in this study: tropical monsoon areas, subtropical monsoon areas, temperate areas and alpine plateau areas. The results indicate that the influence of meteorological factors and extreme weather in different climate regions on diverse infectious diarrhea types is distinct. In general, temperature was positively correlated with all infectious diarrhea cases (0.2 ≤ r ≤ 0.6, p < 0.05). After extreme rainfall, the incidence rate of dysentery in alpine plateau area in one month would be reduced by 18.7% (95% confidence interval (CI): -27.8--9.6%). Two months after the period of extreme sunshine duration happened, the incidence of dysentery in the alpine plateau area would increase by 21.9% (95% CI: 15.4-28.4%) in that month, and the incidence rate of typhoid and paratyphoid in the temperate region would increase by 17.2% (95% CI: 15.5-18.9%) in that month. The meta-analysis showed that there is no consistency between different provinces in the same climate region. Our study indicated that meteorological factors and extreme weather in different climate areas had different effects on various types of infectious diarrhea, particularly extreme rainfall and extreme sunshine duration, which will help the government develop disease-specific and location-specific interventions, especially after the occurrence of extreme weather.
Abnormal climate changes have resulted in over-precipitation in many regions. The occurrence and contamination levels of mycotoxins in crops and cereals have been elevated largely. From 2017 to 2019, we did investigation targeting 15 mycotoxins shown in the wheat samples collected from Shandong, a region suffering over-precipitation in China. We found that deoxynivalenol (DON) was the dominant mycotoxin contaminating wheats, with detection rates 304/340 in 2017 (89.41%), 303/330 in 2018 (91.82%), and 303/340 in 2019 (89.12%). The ranges of DON levels were <4 to 580 mu g/kg in 2017, <4 to 3070 mu g/kg in 2018, and <4 to 1540 mu g/kg in 2019. The exposure levels were highly correlated with local precipitation. Male exposure levels were generally higher than female's, with significant difference found in 2017 (1.89-fold, p = 0.023). Rural exposure levels were higher than that of cities but not statistically significant (1.41-fold, p = 0.13). Estimated daily intake (EDI) and margin of exposure (MoE) approaches revealed that 8 prefecture cities have probabilistically extra adverse health effects (vomiting or diarrhea) cases > 100 patients in 100,000 residents attributable to DON exposure. As a prominent wheat-growing area, Dezhou city reached similar to 300/100,000 extra cases while being considered as a major regional contributor to DON contamination. Our study suggests that more effort should be given to the prevention and control of DON contamination in major wheat-growing areas, particularly during heavy precipitation year. The mechanistic association between DON and chronic intestinal disorder/diseases should be further investigated.
BACKGROUND: Although previous studies have shown that meteorological factors such as temperature are related to the incidence of bacillary dysentery (BD), researches about the non-linear and interaction effect among meteorological variables remain limited. The objective of this study was to analyze the effects of temperature and other meteorological variables on BD in Beijing-Tianjin-Hebei region, which is a high-risk area for BD distribution. METHODS: Our study was based on the daily-scale data of BD cases and meteorological variables from 2014 to 2019, using generalized additive model (GAM) to explore the relationship between meteorological variables and BD cases and distributed lag non-linear model (DLNM) to analyze the lag and cumulative effects. The interaction effects and stratified analysis were developed by the GAM. RESULTS: A total of 147,001 cases were reported from 2014 to 2019. The relationship between temperature and BD was approximately liner above 0 °C, but the turning point of total temperature effect was 10 °C. Results of DLNM indicated that the effect of high temperature was significant on lag 5d and lag 6d, and the lag effect showed that each 5 °C rise caused a 3% [Relative risk (RR) = 1.03, 95% Confidence interval (CI): 1.02-1.05] increase in BD cases. The cumulative BD cases delayed by 7 days increased by 31% for each 5 °C rise in temperature above 10 °C (RR = 1.31, 95% CI: 1.30-1.33). The interaction effects and stratified analysis manifested that the incidence of BD was highest in hot and humid climates. CONCLUSIONS: This study suggests that temperature can significantly affect the incidence of BD, and its effect can be enhanced by humidity and precipitation, which means that the hot and humid environment positively increases the incidence of BD.
Bacterial pathogens in surface waters may threaten human health, especially in developing countries, where untreated surface water is often used for domestic needs. The objective of the long-term multiscale monitoring of Escherichia coli ([E. coli]) concentration in stream water, and that of associated variables (temperature ( T), electrical conductance (EC), dissolved oxygen concentration ([DO]) and saturation (DO%), pH (pH), oxidation-reduction potential (ORP), turbidity (Turb), and total suspended sediment concentration ([TSS])), was to identify the drivers of bacterial dissemination across tropical catchments. This data description paper presents three datasets (see “Data availability” section) collected at 31 sampling stations located within the Mekong River and its tributaries in Lao PDR (0.6-25 946 km(2)) from 2011 to 2021. The 1602 records have been used to describe the hydrological processes driving in-stream E. coli concentration during flood events, to understand the land-use impact on bacterial dissemination on small and large catchment scales, to relate stream water quality and diarrhea outbreaks, and to build numerical models. The database may be further used, e.g., to interpret new variables measured in the monitored catchments, or to map the health risk posed by fecal pathogens.
The spatial distribution of environmental conditions may influence the dynamics of vectorborne diseases like leptospirosis. This study aims to investigate the global and localised relationships between leptospirosis with selected environmental variables. The association between environmental variables and the spatial density of geocoded leptospirosis cases was determined using global Poisson regression (GPR) and geographically weighted Poisson regression (GWPR). A higher prevalence of leptospirosis was detected in areas with higher water vapour pressure (exp(â): 1.12; 95% CI: 1.02 – 1.25) and annual precipitation (exp(â): 1.15; 95% CI: 1.02 – 1.31), with lower precipitation in the driest month (exp(â): 0.85; 95% CI: 0.75 – 0.96) and the wettest quarter (exp(â): 0.88; 95% CI: 0.77 – 1.00). Water vapor pressure (WVP) varied the most in the hotspot regions with a standard deviation of 0.62 (LQ: 0.15; UQ; 0.99) while the least variation was observed in annual precipitation (ANNP) with a standard deviation of 0.14 (LQ: 0.11; UQ; 0.30). The reduction in AICc value from 519.73 to 443.49 indicates that the GWPR model is able to identify the spatially varying correlation between leptospirosis and selected environmental variables. The results of the localised relationships in this study could be used to formulate spatially targeted interventions. This would be particularly useful in localities with a strong environmental or socio-demographical determinants for the transmission of leptospirosis.
Epidemiological studies have quantified the association between ambient temperature and diarrhoea. However, to our knowledge, no study has quantified the temperature association for severe diarrhoea cases. In this study, we quantified the association between mean temperature and two severe diarrhoea outcomes, which were mortality and hospital admissions accompanied with dehydration and/or co-morbidities. Using a 12-year dataset of three urban districts of the National Capital Region, Philippines, we modelled the non-linear association between weekly temperatures and weekly severe diarrhoea cases using a two-stage time series analysis. We computed the relative risks at the 95th (30.4 °C) and 5th percentiles (25.8 °C) of temperatures using minimum risk temperatures (MRTs) as the reference to quantify the association with high- and low-temperatures, respectively. The shapes of the cumulative associations were generally J-shaped with greater associations towards high temperatures. Mortality risks were found to increase by 53.3% [95% confidence interval (CI): 29.4%; 81.7%)] at 95th percentile of weekly mean temperatures compared with the MRT (28.2 °C). Similarly, the risk of hospitalised severe diarrhoea increased by 27.1% (95% CI: 0.7%; 60.4%) at 95th percentile in mean weekly temperatures compared with the MRT (28.6 °C). With the increased risk of severe diarrhoea cases under high ambient temperature, there may be a need to strengthen primary healthcare services and sustain the improvements made in water, sanitation, and hygiene, particularly in poor communities.
Leptospirosis is a zoonotic bacterial disease that remains an important public health problem, especially in tropical developing countries. Many previous studies in Thailand have revealed the outbreak of human leptospirosis after heavy rainfall, but research determining its quantitative risks associated with rainfall, especially at the national level, remains limited. This study aims to examine the association between rainfall and human leptospirosis across 60 provinces of Thailand. A quasi-Poisson regression framework combined with the distributed lag non-linear model was used to estimate province-specific association between rainfall and human leptospirosis, adjusting for potential confounders. Province-specific estimates were then pooled to derive regional and national estimates using random-effect meta-analysis. The highest risk of leptospirosis associated with rainfall at national level was observed at the same month (lag 0). Using 0 cm/month of rainfall as a reference, the relative risks of leptospirosis associated with heavy (90th percentile), very heavy (95th percentile), and extremely heavy (99th percentile) rainfall at the national level were 1.0994 (95% CI 0.9747, 1.2401), 1.1428 (95% CI 1.0154, 1.2862), and 1.1848 (95% CI 1.0494, 1.3378), respectively. The highest risk of human leptospirosis associated with rainfall was observed in the northern and north-eastern regions. Specifically, the relative risks of leptospirosis associated with extremely heavy rainfall in northern and north-eastern regions were 1.2362 (95% CI 0.9110, 1.6775) and 1.2046 (95% CI 0.9728, 1.4918), respectively. Increasing rainfall was associated with increased risks of leptospirosis, especially in the northern and northeastern regions of Thailand. This finding could be used for precautionary warnings against heavy rainfall. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00477-022-02250-x.
Leptospirosis has been recognized as a major public health concern in Thailand following dramatic outbreaks. We analyzed human leptospirosis incidence between 2004 and 2014 in Mahasarakham province, Northeastern Thailand, in order to identify the agronomical and environmental factors likely to explain incidence at the level of 133 sub-districts and 1982 villages of the province. We performed general additive modeling (GAM) in order to take the spatial-temporal epidemiological dynamics into account. The results of GAM analyses showed that the average slope, population size, pig density, cow density and flood cover were significantly associated with leptospirosis occurrence in a district. Our results stress the importance of livestock favoring leptospirosis transmission to humans and suggest that prevention and control of leptospirosis need strong intersectoral collaboration between the public health, the livestock department and local communities. More specifically, such collaboration should integrate leptospirosis surveillance in both public and animal health for a better control of diseases in livestock while promoting public health prevention as encouraged by the One Health approach.
This study evaluated the experience of implementing water safety plans (WSPs) in Vietnam. WSPs were introduced in Vietnam by the World Health Organization (WHO) in collaboration with the Ministry of Construction in 2006 and have been a mandatory requirement for municipal water supplies since 2012. Using a mixed-methods approach, we collected data on the perceived benefits and challenges of WSP implemen-tation from 23 provincial water companies between August and November 2021. Potential public health benefits of improved water quality were a key motivation; 87% of the water utilities were also motivated by the risk of climate change and prepared response plans to climate-related extreme events as part of WSPs. A decrease in E. coli and an improvement in disinfectant residual in treated water were reported by 61 and 83% of the water supplies, respectively. Sixty-five percent of the water supplies also reported improved revenue and cost recovery. Key barriers to WSP implementation were a lack of WSP guidance suitable for the local context (87%) and insufficient funds for WSP implementation (43%). Our study highlights the need for improved support and capacity building along with locally suited guidance on WSP implementation and audit.
The degradation of coastal water quality from fecal pollution poses a health risk to visitors at recreational beaches. Fecal indicator bacteria (FIB) are a proxy for fecal pollution; however the accuracy of their representation of fecal pollution health risks at recreational beaches impacted by non-point sources is disputed due to non-human derivation. This study aimed to investigate the relationship between FIB and a range of culturable and molecular-based microbial source tracking (MST) markers and pathogenic bacteria, and physicochemical parameters and rainfall. Forty-two marine water samples were collected from seven sampling stations during six events at two tourist beaches in Thailand. Both beaches were contaminated with fecal pollution as evident from the GenBac3 marker at 88%-100% detection and up to 8.71 log(10) copies/100 mL. The human-specific MST marker human polyomaviruses JC and BK (HPyVs) at up to 4.33 log(10) copies/100 mL with 92%-94% positive detection indicated that human sewage was likely the main contamination source. CrAssphage showed lower frequencies and concentrations; its correlations with the FIB group (i.e., total coliforms, fecal coliforms, and enterococci) and GenBac3 diminished its use as a human-specific MST marker for coastal water. Human-specific culturable AIM06 and SR14 bacteriophages and general fecal indicator coliphages also showed less sensitivity than the human-specific molecular assays. The applicability of the GenBac3 endpoint PCR assay as a lower-cost prescreening step prior to the GenBac3 qPCR assay was supported by its 100% positive predictive value, but its limited negative predictive values required subsequent qPCR confirmation. Human enteric adenovirus and Vibrio cholerae were not found in any of the samples. The HPyVs related to Vibrio parahaemolyticus, Vibrio vulnificus, and 5-d rainfall records, all of which were more prevalent and concentrated during the wet season. More monitoring is therefore recommended during wet periods. Temporal differences but no spatial differences were observed, suggesting the need for a sentinel site at each beach for routine monitoring. The exceedance of FIB water quality standards did not indicate increased prevalence or concentrations of the HPyVs or Vibrio spp. pathogen group, so the utility of FIB as an indicator of health risks at tropical beaches maybe challenged. Accurate assessment of fecal pollution by incorporating MST markers could lead to developing a more effective water quality monitoring plan to better protect human health risks in tropical recreational beaches.
Drinking water on isolated islands includes treated rainwater, water shipped from the mainland, and desalinated seawater. However, marine transportation and desalination plants are vulnerable to emergencies, such as extreme weather. making self-sustaining stand-by water for emergency response essential. Rainwater is ideal for producing the stand-by water, and rainwater harvesting is sustainable and clean, and prolonged biostability can be ensured by managing biological and chemical parameters. The present study applied a stand-by drinking water purification system (primarily including nanofiltration and low-dose chlorination) to explore the feasibility of producing and storing cleaner drinking water from rainwater and the following conclusions were drawn. First, treatment of rainwaters ensures biosafety for seven days, which is longer than that for untreated rainwater; the proportion of opportunistic pathogens decreased from 23.40-7.77% after nanofiltration, and it was proposed that the microbial community converges after advanced water treatment. Second, chemical qualities were improved. Local resource coral sand prevents pH in rainwater from decreasing below 6.5, and treated rainwater had lower disinfection by-product potential and higher disinfection efficiency, allowing periodical rainwater recycling. Third, harvesting rainwater was extremely cost-effective, with an operation cost of 1.5-2.5 RMB/m(3). From biosafety, chemical safety, and economic cost perspectives, self-sustaining water from rainwater can contributes to the development of sustainable and cost-effective water supply systems on isolated islands. Mixing treated rainwater and desalinated seawater reasonably guarantees sufficiency and safety. (C) 2021 Elsevier B.V. All rights reserved.
The tropical climate of Thailand encourages very high mosquito densities in certain areas and is ideal for dengue transmission, especially in the southern region where the province Nakhon Si Thammarat is located. It has the longest dengue fever transmission duration that is affected by some important climate predictors, such as rainfall, number of rainy days, temperature and humidity. We aimed to explore the relationship between weather variables and dengue and to analyse transmission hotspots and coldspots at the district-level. Poisson probability distribution of the generalized linear model (GLM) was used to examine the association between the monthly weather variable data and the reported number of dengue cases from January 2002 to December 2018 and geographic information system (GIS) for dengue hotspot analysis. Results showed a significant association between the environmental variables and dengue incidence when comparing the seasons. Temperature, sea-level pressure and wind speed had the highest coefficients, i.e. β=0.17, β= -0.12 and β= -0.11 (P<0.001), respectively. The risk of dengue incidence occurring during the rainy season was almost twice as high as that during monsoon. Statistically significant spatial clusters of dengue cases were observed all through the province in different years. Nabon was identified as a hotspot, while Pak Phanang was a coldspot for dengue fever incidence, explained by the fact that the former is a rubber-plantation hub, while the agricultural plains of the latter lend themselves to the practice of pisciculture combined with rice farming. This information is imminently important for planning apt sustainable control measures for dengue epidemics.
BACKGROUND: Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a prioritised health adaptation measure to climate change in Vietnam. OBJECTIVE: This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change. METHODS: Convolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997-2013 were used to train models, which were then evaluated using data from 2014-2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). RESULTS AND DISCUSSION: LSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features. CONCLUSION: This study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years.
OBJECTIVE: The aim research was to analyze the association between temperature and humidity and the incidence of dengue fever in Manado Municipality. METHODS: The research design used analytical descriptive with a cross-sectional survey approach. Data were analyzed using the Spearman rank test. RESULT: The highest temperature was in August (28.7 °C), the highest humidity was January (88%), and the most DHF incidence was in January (409 cases). There is a significant association between temperature and the prevalence of DHF (p=0.000, r=-0.845). Humidity with the prevalence of DHF (p=0.000, r=0.873). CONCLUSION: It was found that two variables had a significant association between temperature and humidity on the prevalence of DHF in Manado Municipality based on observations of patterns of temperature and humidity characteristics every month during 2019.
BACKGROUND: Dengue fever (DF) is a mosquito-borne infectious disease that has threatened tropical and subtropical regions in recent decades. An early and targeted warning of a dengue epidemic is important for vector control. Current studies have primarily determined weather conditions to be the main factor for dengue forecasting, thereby neglecting that environmental suitability for mosquito breeding is also an important factor, especially in fine-grained intra-urban settings. Considering that street-view images are promising for depicting physical environments, this study proposes a framework for facilitating fine-grained intra-urban dengue forecasting by integrating the urban environments measured from street-view images. METHODS: The dengue epidemic that occurred in 167 townships of Guangzhou City, China, between 2015 and 2019 was taken as a study case. First, feature vectors of street-view images acquired inside each township were extracted by a pre-trained convolutional neural network, and then aggregated as an environmental feature vector of the township. Thus, townships with similar physical settings would exhibit similar environmental features. Second, the environmental feature vector is combined with commonly used features (e.g., temperature, rainfall, and past case count) as inputs to machine-learning models for weekly dengue forecasting. RESULTS: The performance of machine-learning forecasting models (i.e., MLP and SVM) integrated with and without environmental features were compared. This indicates that models integrating environmental features can identify high-risk urban units across the city more precisely than those using common features alone. In addition, the top 30% of high-risk townships predicted by our proposed methods can capture approximately 50-60% of dengue cases across the city. CONCLUSIONS: Incorporating local environments measured from street view images is effective in facilitating fine-grained intra-urban dengue forecasting, which is beneficial for conducting spatially precise dengue prevention and control.
In 2014 and 2015, Southern Taiwan experienced two unprecedented outbreaks, with more than 10,000 laboratory-confirmed dengue cases in each outbreak. The present study was aimed to investigate the influence of meteorological and spatial factors on dengue outbreaks in Southern Taiwan and was conducted in Kaohsiung City, which is the most affected area in Taiwan. The distributed lag nonlinear model was used to investigate the role of climatic factors in the 2014 and 2015 dengue outbreaks. Spatial statistics in the Geographic Information System was applied to study the relationship between the dengue spreading pattern and locations of traditional markets (human motility) in the 2015 dengue outbreak. Meteorological analysis results suggested that the relative risk of dengue fever increased when the weekly average temperature was more than 15°C at lagged weeks 5 to 18. Elevated relative risk of dengue was observed when the weekly average rainfall was more than 150 mm at lagged weeks 12 to 20. The spatial analysis revealed that approximately 83% of dengue cases were located in the 1000 m buffer zone of traditional market, with statistical significance. These findings support the influence of climatic factors and human motility on dengue outbreaks. Furthermore, the study analysis may help authorities to identify hotspots and decide the timing for implementation of dengue control programs.
Dengue fever is a mosquito-borne infection with a rising trend, expected to increase further with the rise in global temperature. The study aimed to use the environmental and dengue data 2015-2018 to examine the seasonal variation and establish a probabilistic model of environmental predictors of dengue using the generalized linear model (GLM). In Delhi, dengue cases started emerging in the monsoon season, peaked in the post-monsoon, and thereafter, declined in early winter. The annual trend of dengue cases declined, but the seasonal pattern remained alike (2015-18). The Spearman correlation coefficient of dengue was significantly high with the maximum and minimum temperature at 2 months lag, but it was negatively correlated with the difference of average minimum and maximum temperature at lag 1 and 2. The GLM estimated β coefficients of environmental predictors such as temperature difference, cumulative rainfall, relative humidity and maximum temperature were significant (p < 0.01) at different lag (0 to 2), and maximum temperature at lag 2 was having the highest effect (IRR 1.198). The increasing temperature of two previous months and cumulative rainfall are the best predictors of dengue incidence. The vector control should be implemented at least 2 months ahead of disease transmission (August-November).
The susceptibility of Asian tiger mosquitoes to DENV-2 in different seasons was observed in simulated field environments as a reference to design dengue fever control strategies in Guangzhou. The life table experiments of mosquitoes in four seasons were carried out in the field. The susceptibility of Ae. albopictus to dengue virus was observed in both environments in Guangzhou in summer and winter. Ae. albopictus was infected with dengue virus by oral feeding. On day 7 and 14 after infection, the viral load in the head, ovary, and midgut of the mosquito was detected using real-time fluorescent quantitative PCR. Immune-associated gene expression in infected mosquitoes was performed using quantitative real-time reverse transcriptase PCR. The hatching rate and pupation rate of Ae. albopictus larvae in different seasons differed significantly. The winter hatching rate of larvae was lower than that in summer, and the incubation time was longer than in summer. In the winter field environment, Ae. albopictus still underwent basic growth and development processes. Mosquitoes in the simulated field environment were more susceptible to DENV-2 than those in the simulated laboratory environment. In the midgut, viral RNA levels on day 7 in summer were higher than those on day 7 in winter (F = 14.459, P = 0.01); ovarian viral RNA levels on day 7 in summer were higher than those on day 7 in winter (F = 8.656, P < 0.001), but there was no significant difference in the viral load at other time points (P > 0.05). Dicer-2 mRNA expression on day 7 in winter was 4.071 times than that on day 7 in summer: the viral load and Dicer-2 expression correlated moderately. Ae. albopictus could still develop and transmit dengue virus in winter in Guangzhou. Mosquitoes under simulated field conditions were more susceptible to DENV-2 than those under simulated laboratory conditions.
Dengue is of great public health concern regarding the number of people affected. In addition, climate change is associated with the recent spread of dengue fever. Effects of meteorological factors on dengue incidence from 2003 to 2019 in Bangkok city: a model for dengue prediction. Mathematical statistical applied were principal component analysis (PCA), Poisson regression model (PRM), Mann-Kendall (MK), and Sen’s slope. PRM considers dengue incidence as the dependent variable and climate variables as independent variables. Meteorological factors are maximum temperature (T-max), minimum temperature (T-min), relative humidity (RH), and rainfall. The rainy season showed a high significant probability of occurrence for new patients. Most trends were statistically significant at 1% for seasonal and annual dengue cases. Another finding was that for every 5-50% of RH variation, there was an average increase (73.33-24,369.19%) in the number of dengue cases. Therefore, RH was the best predictor for increasing dengue incidence in Bangkok. In addition, predictions for dengue incidence were evaluated. This study is a significant result to warn the government, providing valuable information for human health protection.
OBJECTIVES: This study aimed to forecast the morbidity and mortality of dengue fever using a time series analysis from 2006 to 2016. METHODS: Data were compiled from the Jeddah Dengue Fever Operations Room (RFOR) in a primary health care centre. A time series analysis was conducted for all confirmed cases of dengue fever between 2006 and 2016. RESULTS: The results showed a significant seasonal association, particularly from May to September, and a time-varying behaviour. Air temperature was significantly associated with the incidence of dengue fever (p < 0.001) but was not correlated with its mortality. Similarly, relative humidity was not significantly associated with the incidence of dengue fever (p = 0.237). CONCLUSION: The strong seasonal association of dengue fever during May to September and its relation to air temperature should be communicated to all stakeholders. This will help improve the control interventions of dengue fever during periods of anticipated high incidence.
Meteorological exposures are well-documented factors underlying the dengue pandemics, and air pollution was reported to have the potential to change the behaviors and health conditions of mosquitos. However, it remains unclear whether air pollution could modify the association of meteorological exposures and the incidence of dengue fever. We matched the dengue surveillance data with the meteorological and air pollution data collected from monitoring sites from 2015 through 2019 in Guangzhou area. We developed generalized additive models with Poisson distribution to regress the daily counts of dengue against four meteorological exposures, while controlling for pollution and normalized difference vegetation index to evaluate the risk ratio (RR) of dengue for each unit increase in different exposures. The interaction terms of meteorological exposures and air pollution were then included to assess the modification effect of different pollution on the associations. Daily dengue cases were nonlinearly associated with one-week cumulative temperature and precipitation, while not associated with humidity and wind speed. RRs were 1.07 (1.04, 1.11) and 0.95 (0.88, 1.03) for temperature below and above 27.1 degrees C, 0.97 (0.96, 0.98) and 1.05 (1.01, 1.08) for precipitation below and above 20.3 mm, respectively. For the modification effect, the RRs of low-temperature, wind speed on higher SO2 days and low-precipitation on both higher PM2.5 and SO2 days were greater compared to the low-pollution days with P (interaction) being 0.037, 0.030, 0.022 and 0.018. But the RRs of both high-temperature on higher SO2 days and high-precipitation on higher PM2.5 d were smaller with P (interaction) being 0.001 and 0.043. Air pollution could alter the meteorology-dengue associations. The impact of low-temperature, low-precipitation and wind speed on dengue occurrence tended to increase on days with high SO2 levels while the impact of high-temperature decreased. The impact of low-precipitation increased on high-PM2.5 d while the impact of high-precipitation decreased.
BACKGROUND: Dengue fever is a widespread viral disease and one of the world’s major pandemic vector-borne infections, causing serious hazard to humanity. The World Health Organisation (WHO) reported that the incidence of dengue fever has increased dramatically across the world in recent decades. WHO currently estimates an annual incidence of 50-100 million dengue infections worldwide. To date, no tested vaccine or treatment is available to stop or prevent dengue fever. Thus, the importance of predicting dengue outbreaks is significant. The current issue that should be addressed in dengue outbreak prediction is accuracy. A limited number of studies have conducted an in-depth analysis of climate factors in dengue outbreak prediction. METHODS: The most important climatic factors that contribute to dengue outbreaks were identified in the current work. Correlation analyses were performed in order to determine these factors and these factors were used as input parameters for machine learning models. Top five machine learning classification models (Bayes network (BN) models, support vector machine (SVM), RBF tree, decision table and naive Bayes) were chosen based on past research. The models were then tested and evaluated on the basis of 4-year data (January 2010 to December 2013) collected in Malaysia. RESULTS: This research has two major contributions. A new risk factor, called the TempeRain factor (TRF), was identified and used as an input parameter for the model of dengue outbreak prediction. Moreover, TRF was applied to demonstrate its strong impact on dengue outbreaks. Experimental results showed that the Bayes Network model with the new meteorological risk factor identified in this study increased accuracy to 92.35% for predicting dengue outbreaks. CONCLUSIONS: This research explored the factors used in dengue outbreak prediction systems. The major contribution of this study is identifying new significant factors that contribute to dengue outbreak prediction. From the evaluation result, we obtained a significant improvement in the accuracy of a machine learning model for dengue outbreak prediction.
Dengue hemorrhagic fever (DHF) is one of the most widespread and deadly diseases in several parts of Indonesia. An accurate forecast-based model is required to reduce the incidence rate of this disease. Time-series methods such as autoregressive integrated moving average (ARIMA) models are used in epidemiology as statistical tools to study and forecast DHF and other infectious diseases. The present study attempted to forecast the monthly confirmed DHF cases via a time-series approach. The ARIMA, seasonal ARIMA (SARIMA), and long short-term memory (LSTM) models were compared to select the most accurate forecasting method for the deadly disease. The data were obtained from the Surabaya Health Office covering January 2014 to December 2016. The data were partitioned into the training and testing sets. The best forecasting model was selected based on the lowest values of accuracy metrics such as the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). The findings demonstrated that the SARIMA (2,1,1) (1,0,0) model was able to forecast the DHF outbreaks in Surabaya City compared to the ARIMA (2,1,1) and LSTM models. We further forecasted the DHF cases for 12 month horizons starting from January 2017 to December 2017 using the SARIMA (2,1,1) (1,0,0), ARIMA (2,1,1), and LSTM models. The results revealed that the SARIMA (2,1,1) (1,0,0) model outperformed the ARIMA (2,1,1) and LSTM models based on the goodness-of-fit measure. The results showed significant seasonal outbreaks of DHF, particularly from March to September. The highest cases observed in May suggested a significant seasonal correlation between DHF and air temperature. This research is the first attempt to analyze the time-series model for DHF cases in Surabaya City and forecast future outbreaks. The findings could help policymakers and public health specialists develop efficient public health strategies to detect and control the disease, especially in the early phases of outbreaks.
This study assessed the impact of weather factors, including novel predictors-pollutant standards index (PSI) and wind speed-on dengue incidence in Singapore between 2012 and 2019. Autoregressive integrated moving average (ARIMA) model was fitted to explore the autocorrelation in time series and quasi-Poisson model with a distributed lag non-linear term (DLNM) was set up to assess any non-linear association between climatic factors and dengue incidence. In DLNM, a PSI level of up to 111 was positively associated with dengue incidence; incidence reduced as PSI level increased to 160. A slight rainfall increase of up to 7 mm per week gave rise to higher dengue risk. On the contrary, heavier rainfall was protective against dengue. An increase in mean temperature under around 28.0 °C corresponded with increased dengue cases whereas the association became negative beyond 28.0 °C; the minimum temperature was significantly positively associated with dengue incidence at around 23-25 °C, and the relationship reversed when temperature exceed 27 °C. An overall positive association, albeit insignificant, was observed between maximum temperature and dengue incidence. Wind speed was associated with decreasing relative risk (RR). Beyond prevailing conclusions on temperature, this study observed that extremely poor air quality, high wind speed, minimum temperature 27 °C, and rainfall volume beyond 12 mm per week reduced the risk of dengue transmission in an urbanized tropical environment.
BACKGROUND: The mosquitoes Aedes aegypti and Ae. albopictus are the primary vectors of dengue virus, and their geographic distributions are predicted to expand further with economic development, and in response to climate change. We aimed to estimate the impact of future climate change on dengue transmission through the development of a Suitable Conditions Index (SCI), based on climatic variables known to support vectorial capacity. We calculated the SCI based on various climate change scenarios for six countries in the Asia-Pacific region (Australia, China, Indonesia, The Philippines, Thailand and Vietnam). METHODS: Monthly raster climate data (temperature and precipitation) were collected for the period January 2005 to December 2018 along with projected climate estimates for the years 2030, 2050 and 2070 using Representative Concentration Pathway (RCP) 4·5, 6·0 and 8·5 emissions scenarios. We defined suitable temperature ranges for dengue transmission of between 17·05-34·61 °C for Ae. aegypti and 15·84-31·51 °C for Ae. albopictus and then developed a historical and predicted SCI based on weather variability to measure the expected geographic limits of dengue vectorial capacity. Historical and projected SCI values were compared through difference maps for the six countries. FINDINGS: Comparing different emission scenarios across all countries, we found that most South East Asian countries showed either a stable pattern of high suitability, or a potential decline in suitability for both vectors from 2030 to 2070, with a declining pattern particularly evident for Ae. albopictus. Temperate areas of both China and Australia showed a less stable pattern, with both moderate increases and decreases in suitability for each vector in different regions between 2030 and 2070. INTERPRETATION: The SCI will be a useful index for forecasting potential dengue risk distributions in response to climate change, and independently of the effects of human activity. When considered alongside additional correlates of infection such as human population density and socioeconomic development indicators, the SCI could be used to develop an early warning system for dengue transmission.
The rapid spread of dengue fever (DF) infection has posed severe threats to global health. Environmental factors, such as weather conditions, are believed to regulate DF spread. While previous research reported inconsistent change of DF risk with varying weather conditions, few of them evaluated the impact of extreme weather conditions on DF infection risk. This study aims to examine the short-term associations between extreme temperatures, extreme rainfall, and DF infection risk in South and Southeast Asia. A total of 35 locations in Singapore, Malaysia, Sri Lanka, and Thailand were included, and weekly DF data, as well as the daily meteorological data from 2012 to 2020 were collected. A two-stage meta-analysis was used to estimate the overall effect of extreme weather conditions on the DF infection risk. Location-specific associations were obtained by the distributed lag nonlinear models. The DF infection risk appeared to increase within 1-3 weeks after extremely high temperature (e.g. lag week 2: RR = 1.074, 95 % CI: 1.022-1.129, p = 0.005). Compared with no rainfall, extreme rainfall was associated with a declined DF risk (RR = 0.748, 95 % CI: 0.620-0.903, p = 0.003), and most of the impact was across 0-3 weeks lag. In addition, the DF risk was found to be associated with more intensive extreme weathers (e.g. seven extreme rainfall days per week: RR = 0.338, 95 % CI: 0.120-0.947, p = 0.039). This study provides more evidence in support of the impact of extreme weather conditions on DF infection and suggests better preparation of DF control measures according to climate change.
BACKGROUND: Global incidence of dengue has surged rapidly over the past decade. Each year, an estimated 390 million infections occur worldwide, with Asia-Pacific countries bearing about three-quarters of the global dengue disease burden. Global warming may influence the pattern of dengue transmission. While previous studies have shown that extremely high temperatures can impede the development of the Aedes mosquito, the effect of such extreme heat over a sustained period, also known as heatwaves, has not been investigated in a tropical climate setting. AIM: We examined the short-term relationships between maximum ambient temperature and heatwaves and reported dengue infections in Singapore, via ecological time series analysis, using data from 2009 to 2018. METHODS: We studied the effect of two measures of extreme heat – (i) heatwaves and (ii) maximum ambient temperature. We used a negative binomial regression, coupled with a distributed lag nonlinear model, to examine the immediate and lagged associations of extreme temperature on dengue infections, on a weekly timescale. We adjusted for long-term trend, seasonality, rainfall and absolute humidity, public holidays and autocorrelation. RESULTS: We observed an overall inhibitive effect of heatwaves on the risk of dengue infections, and a parabolic relationship between maximum temperature and dengue infections. A 1 °C increase in maximum temperature from 31 °C was associated with a 13.1% (Relative Risk (RR): 0.868, 95% CI: 0.798, 0.946) reduction in the cumulative risk of dengue infections over six weeks. Weeks with 3 heatwave days were associated with a 28.3% (RR: 0.717, 95% CI: 0.608, 0.845) overall reduction compared to weeks with no heatwave days. Adopting different heatwaves specifications did not substantially alter our estimates. CONCLUSION: Extreme heat was associated with decreased dengue incidence. Findings from this study highlight the importance of understanding the temperature dependency of vector-borne diseases in resource planning for an anticipated climate change scenario.
BACKGROUND: Dengue dynamics result from the complex interactions between the virus, the host and the vector, all being under the influence of the environment. Several studies explored the link between weather and dengue dynamics and some investigated the impact of climate change on these dynamics. Most attempted to predict incidence rate at a country scale or assess the environmental suitability at a global or regional scale. Here, we propose a new approach which consists in modeling the risk of dengue outbreak at a local scale according to climate conditions and study the evolution of this risk taking climate change into account. We apply this approach in New Caledonia, where high quality data are available. METHODS: We used a statistical estimation of the effective reproduction number (R(t)) based on case counts to create a categorical target variable : epidemic week/non-epidemic week. A machine learning classifier has been trained using relevant climate indicators in order to estimate the probability for a week to be epidemic under current climate data and this probability was then estimated under climate change scenarios. RESULTS: Weekly probability of dengue outbreak was best predicted with the number of days when maximal temperature exceeded 30.8°C and the mean of daily precipitation over 80 and 60 days prior to the predicted week respectively. According to scenario RCP8.5, climate will allow dengue outbreak every year in New Caledonia if the epidemiological and entomological contexts remain the same. CONCLUSION: We identified locally relevant climatic factor driving dengue outbreaks in New Caledonia and assessed the inter-annual and seasonal risk of dengue outbreak under different climate change scenarios up to the year 2100. We introduced a new modeling approach to estimate the risk of dengue outbreak depending on climate conditions. This approach is easily reproducible in other countries provided that reliable epidemiological and climate data are available.
BACKGROUND: Studies have shown that tropical cyclones are associated with several infectious diseases, while very few evidence has demonstrated the relationship between tropical cyclones and dengue fever. This study aimed to examine the potential impact of tropical cyclones on dengue fever incidence in the Pearl River Delta, China. METHODS: Data on daily dengue fever incidence, occurrence of tropical cyclones and meteorological factors were collected between June and October, 2013-2018 from nine cities in the Pearl River Delta. Multicollinearity of meteorological variables was examined via Spearman correlation, variables with strong correlation (r>0.7) were not included in the model simultaneously. A time-stratified case-crossover design combined with conditional Poisson regression model was performed to evaluate the association between tropical cyclones and dengue fever incidence. Stratified analyses were performed by intensity grades of tropical cyclones (tropical storm and typhoon), sex (male and female) and age-groups (<18, 18-59, ≥60 years). RESULTS: During the study period, 20 tropical cyclones occurred and 47,784 dengue fever cases were reported. Tropical cyclones were associated with an increased risk of dengue fever in the Pearl River Delta region, with the largest relative risk of 1.62 with the 95% confidence interval (1.45-1.80) occurring on the lag 5 day. The strength of association was greater and lasted longer for typhoon than for tropical storm. There was no difference in effect estimates between males and females. However, individuals aged over 60 years were more vulnerable than others. CONCLUSIONS: Tropical cyclones are associated with increased risk of local dengue fever incidence in south China, with the elderly more vulnerable than other population subgroups. Health protective strategies should be developed to reduce the potential risk of dengue epidemic after tropical cyclones.
Climate change is a global challenge expected to affect water-related diseases (WRDs). The present systematic study tried to review literature examining the relationship between meteorological conditions and WRDs in developing countries located in Western Asia. We searched Scopus, PubMed and Embase for studies describing the relationship between WRDs and climate variables (ambient temperature, rainfall and humidity) plus extreme events, drought and flooding. A total of 27 articles met the inclusion criteria. The key findings presented a positive association between temperature and WRDs in most of the evaluated records. However, rainfall and humidity showed inconsistent relationships with WRDs. No evidence was found reporting the effect of climate variables on water-based or water-washed diseases. Yemen is the only country in the studied region that still has major issues controlling WRDs and might be at greater risk of climate change. It is recommended that future researches evaluate the delayed effects of environmental factors on WRDs and multidimensional interactions of climate variables on each other or on socioeconomic variables affecting WRDs. Increased health risks due to climate change add additional value to the investigations studying the proven adaptation strategies such as improvements in water, sanitation and hygiene (WaSH) and effective early warning systems.
Japanese encephalitis (JE) is an important mosquito-borne infectious disease in rural areas of Asia that is caused by Japanese encephalitis virus (JEV). Culex tritaeniorhynchus is the major vector of JEV, nevertheless there are other mosquitoes that may be able to transmit JEV. This study confirms that the midgut, head tissue, salivary glands, and reproductive tissue of Aedes albopictus, Armigeres subalbatus, and Culex quinquefasciatus are all able to be infected with JEV after a virus-containing blood meal was ingested by female mosquitoes. Even though the susceptibility to JEV of the different tissues varies, the virus-positive rate increased with the number of days after JEV infection. Moreover, once JEV escapes the midgut barrier, the oral transmission rates of JEV were 16%, 2%, and 21% for Ae. albopictus, Ar. subalbatus, and Cx. quinquefasciatus at 14 days after infection at 30 °C, respectively. There is no supporting evidence to suggest vertical transmission of JEV by the tested mosquitoes. Collectively, raising the temperature enhances JEV replication in the salivary gland of the three mosquito species, suggesting that global warming will enhance mosquito vector competence and that this is likely to lead to an increase in the probability of JEV transmission.
OBJECTIVE: Dengue fever is a global burden because of high cases number. Climate factors became determinant of the mosquito’s growth. This study aimed to analyze the relationship between climate factors (humidity, temperature, wind speed, rainfall) and dengue cases in Makassar during 2011-2017. METHODS: It was quantitative study located in Makassar. Data were analyzed by General Estimating Equation (GEE). Gee was used to showing the model of variables. This study used secondary data from Health District Office of Makassar to get Dengue Cases Data and Meteorological, Climatological, and Geophysical Agency of Makassar for monthly climate data. RESULTS: The result showed significant correlation between climate variables that have been researched which were temperature, humidity, rainfall, and wind speed to dengue fever cases. CONCLUSIONS: As conclusion, the humidity had strongest correlation to dengue fever cases. It also showed positive correlation, while others showed negative correlation
For forecasting the spread of dengue, monitoring climate change and its effects specific to the disease is necessary. Dengue is one of the most rapidly spreading vector-borne infectious diseases. This paper proposes a forecasting model for predicting dengue incidences considering climatic variability across nine cities of Maharashtra state of India over 10 years. The work involves the collection of five climatic factors such as mean minimum temperature, mean maximum temperature, relative humidity, rainfall, and mean wind speed for 10 years. Monthly incidences of dengue for the same locations are also collected. Different regression models such as random forest regression, decision trees regression, support vector regress, multiple linear regression, elastic net regression, and polynomial regression are used. Time-series forecasting models such as holt’s forecasting, autoregressive, Moving average, ARIMA, SARIMA, and Facebook prophet are implemented and compared to forecast the dengue outbreak accurately. The research shows that humidity and mean maximum temperature are the major climate factors and exhibit strong positive and negative correlation, respectively, with dengue incidences for all locations of Maharashtra state. Mean minimum temperature and rainfall are moderately positively correlated with dengue incidences. Mean wind speed is a less significant factor and is weakly negatively correlated with dengue incidences. Root mean square error (RMSE), mean absolute error (MAE), and R square error (R (2)) evaluation metrics are used to compare the performance of the prediction model. Random Forest Regression is the best-fit regression model for five out of nine cities, while Support Vector Regression is for two cities. Facebook Prophet Model is the best fit time series forecasting model for six out of nine cities. Based on the prediction, Mumbai, Thane, Nashik, and Pune are the high-risk regions, especially in August, September, and October. The findings exhibit an effective early warning system that would predict the outbreak of other infectious diseases. It will help the relevant authorities to take accurate preventive measures.
Zika virus (ZIKV) recently reemerged in the Americas and rapidly expanded in global range. It is posing significant concerns of public health due to its link to birth defects and its complicated transmission routes. Southeast Asia is badly hit by ZIKV, but limited information was found on the transmission potential of ZIKV in the region. In this paper, we develop a new dynamic process-based mathematical model, which incorporates the interactions among humans (sexual transmissibility), and between human and mosquitoes (biting transmissibility), as well as the essential impacts of temperature. The model is first validated by fitting the 2016 ZIKV outbreak in Singapore via Markov chain Monte Carlo method. Based on that, we demonstrate the effects of temperature on mosquito ecology and ZIKV transmission, and further clarify the potential risk of ZIKV outbreak in Southeast Asian countries. The results show that (i) the estimated infection reproduction number [Formula: see text] in Singapore fell from 6.93 (in which the contribution of sexual transmission was 0.89) to 0.24 after the deployment of control strategies; (ii) the optimal temperature for the reproduction of ZIKV infections and adult mosquitoes are estimated to be [Formula: see text]C and [Formula: see text]C, respectively; and (iii) the [Formula: see text] in Southeast Asia could be between 3 and 7, with an inverted-U shape around the year. The large values of [Formula: see text] and the simulative patterns of ZIKV transmission in each country highlights the high risk of ZIKV attack in Southeast Asia.
BACKGROUND: Seasonal activity patterns of mosquitoes are essential as baseline knowledge to understand the transmission dynamics of vector-borne diseases. This study was conducted to evaluate the monthly dynamics of the mosquito populations and their relation to meteorological factors in Mazandaran Province, north of Iran. METHODS: Mosquito adults and larvae were collected from 16 counties of Mazandaran Province using different sampling techniques, once a month from May to December 2014. Index of Species Abundance (ISA) along with Standardized ISA (SISA) was used for assessing the most abundant species of mosquitoes based on the explanations of Robert and Hsi. Pearson’s correlation coefficient (R) was used to assess the relationships between the monthly population fluctuations and meteorological variables. RESULTS: Overall, 23750 mosquitoes belonging to four genera and nineteen species were collected and identified. The highest population density of mosquitoes was in July and the lowest in May. The ISA/SISA indices for Culex pipiens were both 1 for larvae and 1.25/0.973 for adults in total catch performed in human dwellings. For Cx. tritaeniorhynchus, the ISA/SISA were 1.68/0.938 in pit shelter method. A significant positive correlation was observed between population fluctuations of Cx. tritaeniorhynchus and mean temperature (R: 0.766, P< 0.027). CONCLUSION: The results indicated that the mosquitoes are more active in July, and Cx. pipiens and Cx. tritaeniorhynchus were the most abundant species. Considering the potential of these species as vectors of numerous pathogens, control programs can be planed based on their monthly activity pattern in the area.
Ross River virus (RRV) infection is one of the emerging and prevalent arboviral diseases in Australia and the Pacific Islands. Although many studies have been conducted to establish the relationship between temperature and RRV infection, there has been no comprehensive review of the association so far. In this study, we performed a systematic review and meta-analysis to assess the effect of temperature on RRV transmission. We searched PubMed, Scopus, Embase, and Web of Science with additional lateral searches from references. The quality and strength of evidence from the included studies were evaluated following the Navigation Guide framework. We have qualitatively synthesized the evidence and conducted a meta-analysis to pool the relative risks (RRs) of RRV infection per 1 °C increase in temperature. Subgroup analyses were performed by climate zones, temperature metrics, and lag periods. A total of 17 studies met the inclusion criteria, of which six were included in the meta-analysis The meta-analysis revealed that the overall RR for the association between temperature and the risk of RRV infection was 1.09 (95% confidence interval (CI): 1.02, 1.17). Subgroup analyses by climate zones showed an increase in RRV infection per 1 °C increase in temperature in humid subtropical and cold semi-arid climate zones. The overall quality of evidence was “moderate” and we rated the strength of evidence to be “limited”, warranting additional evidence to reduce uncertainty. The results showed that the risk of RRV infection is positively associated with temperature. However, the risk varies across different climate zones, temperature metrics and lag periods. These findings indicate that future studies on the association between temperature and RRV infection should consider local and regional climate, socio-demographic, and environmental factors to explore vulnerability at local and regional levels.
BACKGROUND: Echinococcosis is a global enzootic disease influenced by different biological and environmental factors and causes a heavy financial burden on sick families and governments. Currently, government subsidies for the treatment of patients with echinococcosis are only a fixed number despite patients’ finical income or cost of treatment, and health authorities are demanded to supply an annual summary of only endemic data. The risk to people in urban areas or non-endemic is increasing with climate, landscape, and lifestyle changes. METHODS: We conducted retrospective descriptive research on inpatients with human echinococcosis (HE) in Lanzhou hospitals and analyzed the healthcare expenditure on inpatient treatment and examined the financial inequalities relating to different levels of gross domestic product. The livestock losses were also estimated by infection ratio. The occurrence records of Echinococcus spp. composed of hospitalized patients and dogs infected in the Gansu province were collected for Ecological niche modeling (ENM) to estimate the current suitable spatial distribution for the parasite in Gansu province. Then, we imported the resulting current niche model into future global Shared Socioeconomic Pathways scenarios for estimation of future suitable habitat areas. RESULTS: Between 2000 to 2020, 625 hospitalized HE patients (51% men and 49% women) were identified, and 48.32 ± 15.62 years old. The average cost of hospitalization expenses per case of HE in Gansu Province was ￥24,370.2 with an increasing trend during the study period and was negative with different counties’ corresponding gross domestic product (GDP). The trend of livestock losses was similar to the average cost of hospitalization expenses from 2015 to 2017. The three factors with the strongest correlation to echinococcosis infection probability were (1) global land cover (GLC, 56.6%), (2) annual precipitation (Bio12, 21.2%), and (3) mean temperature of the Wettest Quarter (Bio12, 8.5% of variations). We obtained a robust model that provides detail on the distribution of suitable areas for Echinococcus spp. including areas that have not been reported for the parasite. An increasing tendency was observed in the highly suitable areas of Echinococcus spp. indicating that environmental changes would affect the distributions. CONCLUSION: This study may help in the development of policies for at-risk populations in geographically defined areas and monitor improvements in HE control strategies by allowing targeted allocation of resources, including spatial analyses of expenditure and the identification of non-endemic areas or risk for these parasites, and a better comprehension of the role of the environment in clarifying the transmission dynamics of Echinococcus spp. Raising healthcare workers’ and travelers’ disease awareness and preventive health habits is an urgent agenda. Due to unpredictable future land cover types, prediction of the future with only climatic variables involved needs to be treated cautiously.
Ross River virus (RRV) has recently been suggested to be a potential emerging infectious disease worldwide. RRV infection remains the most common human arboviral disease in Australia, with a yearly estimated economic cost of $4.3 billion. Infection in humans and horses can cause chronic, long-term debilitating arthritogenic illnesses. However, current knowledge of immunopathogenesis remains to be elucidated and is mainly inferred from a murine model that only partially resembles clinical signs and pathology in human and horses. The epidemiology of RRV transmission is complex and multifactorial and is further complicated by climate change, making predictive models difficult to design. Establishing an equine model for RRV may allow better characterization of RRV disease pathogenesis and immunology in humans and horses, and could potentially be used for other infectious diseases. While there are no approved therapeutics or registered vaccines to treat or prevent RRV infection, clinical trials of various potential drugs and vaccines are currently underway. In the future, the RRV disease dynamic is likely to shift into temperate areas of Australia with longer active months of infection. Here, we (1) review the current knowledge of RRV infection, epidemiology, diagnostics, and therapeutics in both humans and horses; (2) identify and discuss major research gaps that warrant further research.
The eastern paralysis tick, Ixodes holocyclus, is an ectoparasite of medical and veterinary importance in Australia. The feeding of I. holocyclus is associated with an ascending flaccid paralysis which kills many dogs and cats each year, with the development of mammalian meat allergy in some humans, and with the transmission of Rickettsia australis (Australian scrub typhus) to humans. Although I. holocyclus has been well studied, it is still not known exactly why this tick cannot establish outside of its present geographic distribution. Here, we aim to account for the presence as well as the absence of I. holocyclus in regions of Australia. We modelled the climatic requirements of I. holocyclus with two methods, CLIMEX, and a new envelope-model approach which we name the ‘climatic-range method’. These methods allowed us to account for 93% and 96% of the geographic distribution of I. holocyclus, respectively. Our analyses indicated that the geographic range of I. holocyclus may not only shift south towards Melbourne, but may also expand in the future, depending on which climate-change scenario comes to pass.
The southern paralysis tick, Ixodes cornuatus, is a tick of veterinary and medical importance in Australia. We use two methods, CLIMEX, and an envelope-model approach which we name the ‘climatic-range method’ to study the climatic requirements of I. cornuatus and thus to attempt to account for the geographic distribution of I. cornuatus. CLIMEX and our climatic-range method allowed us to account for 94% and 97% of the records of I. cornuatus respectively. We also studied the host preferences of I. cornuatus which we subsequently used in conjunction with our species distribution methods to account for the presence and the absences of I. cornuatus across Australia. Our findings indicate that the actual geographic distribution of I. cornuatus is smaller than the potential geographic range of this tick, and thus, that there are regions in Australia which may be suitable for I. cornuatus where this tick has not been recorded. Although our findings indicate that I. cornuatus might be able to persist in these currently unoccupied regions, our findings also indicate that the potential geographic range of I. cornuatus may shrink by 51 to 76% by 2090, depending on which climate change scenario comes to pass.
The identification of the key factors influencing dengue occurrence is critical for a successful response to the outbreak. It was interesting to consider possible differences in meteorological factors affecting dengue incidence during epidemic and non-epidemic periods. In this study, the overall correlation between weekly dengue incidence rates and meteorological variables were conducted in southern Taiwan (Tainan and Kaohsiung cities) from 2007 to 2017. The lagged-time Poisson regression analysis based on generalized estimating equation (GEE) was also performed. This study found that the best-fitting Poisson models with the smallest QICu values to characterize the relationships between dengue fever cases and meteorological factors in Tainan (QICu = −8.49 × 10−3) and Kaohsiung (−3116.30) for epidemic periods, respectively. During dengue epidemics, the maximum temperature with 2-month lag (β = 0.8400, p < 0.001) and minimum temperature with 5-month lag (0.3832, p < 0.001). During non-epidemic periods, the minimum temperature with 3-month lag (0.1737, p < 0.001) and mean temperature with 2-month lag (2.6743, p < 0.001) had a positive effect on dengue incidence in Tainan and Kaohsiung, respectively.
Hong Kong is an Asia-Pacific City with low incidence but periodic local outbreaks of dengue. A mixed-method assessment of the risk of expansion of dengue endemicity in such setting was conducted. Archived blood samples of healthy adult blood donors were tested for anti-dengue virus IgG at 2 time-points of 2014 and 2018/2019. Data on the monthly notified dengue cases, meteorological and vector (ovitrap index) variables were collected. The dengue virus (DENV) IgG seroprevalence of healthy adults in 2014 was 2.2% (95%C.I. = 1.8-2.8%, n = 3827) whereas that in 2018/2019 was 1.7% (95%C.I. = 1.2-2.3%, n = 2320). Serotyping on 42 sera in 2018/2019 showed that 22 (52.4%) were DENV-2. In 2002-2019, importation accounted for 95.3% of all reported cases. By wavelet analysis, local cases were in weak or no association with meteorological and vector variables. Without strong association between local cases and meteorological/vector variables, there was no evidence of increasing level of dengue infection in Hong Kong.
BACKGROUND: Previous studies have shown associations between local weather factors and dengue incidence in tropical and subtropical regions. However, spatial variability in those associations remains unclear and evidence is scarce regarding the effects of weather extremes. OBJECTIVES: We examined spatial variability in the effects of various weather conditions on the unprecedented dengue outbreak in Guangdong province of China in 2014 and explored how city characteristics modify weather-related risk. METHODS: A Bayesian spatial conditional autoregressive model was used to examine the overall and city-specific associations of dengue incidence with weather conditions including (1) average temperature, temperature variation, and average rainfall; and (2) weather extremes including numbers of days of extremely high temperature and high rainfall (both used 95th percentile as the cut-off). This model was run for cumulative dengue cases during five months from July to November (accounting for 99.8% of all dengue cases). A further analysis based on spatial variability was used to validate the modification effects by economic, demographic and environmental factors. RESULTS: We found a positive association of dengue incidence with average temperature in seven cities (relative risk (RR) range: 1.032 to 1.153), a positive association with average rainfall in seven cities (RR range: 1.237 to 1.974), and a negative association with temperature variation in four cities (RR range: 0.315 to 0.593). There was an overall positive association of dengue incidence with extremely high temperature (RR:1.054, 95% credible interval (CI): 1.016 to 1.094), without evidence of variation across cities, and an overall positive association of dengue with extremely high rainfall (RR:1.505, 95% CI: 1.096 to 2.080), with seven regions having stronger associations (RR range: 1.237 to 1.418). Greater effects of weather conditions appeared to occur in cities with higher economic level, lower green space coverage and lower elevation. CONCLUSIONS: Spatially varied effects of weather conditions on dengue outbreaks necessitate area-specific dengue prevention and control measures. Extremes of temperature and rainfall have strong and positive associations with dengue outbreaks.
Transmission of dengue virus is a complex process with interactions between virus, mosquitoes and humans, influenced by multiple factors simultaneously. Studies have examined the impact of climate or socio-ecological factors on dengue, or only analyzed the individual effects of each single factor on dengue transmission. However, little research has addressed the interactive effects by multiple factors on dengue incidence. This study uses the geographical detector method to investigate the interactive effect of climate and socio-ecological factors on dengue incidence from two perspectives: over a long-time series and during outbreak periods; and surmised on the possibility of dengue outbreaks in the future. Results suggest that the temperature plays a dominant role in the long-time series of dengue transmission, while socio-ecological factors have great explanatory power for dengue outbreaks. The interactive effect of any two factors is greater than the impact of single factor on dengue transmission, and the interactions of pairs of climate and socio-ecological factors have more significant impact on dengue. Increasing temperature and surge in travel could cause dengue outbreaks in the future. Based on these results, three recommendations are offered regarding the prevention of dengue outbreaks: mitigating the urban heat island effect, adjusting the time and frequency of vector control intervention, and providing targeted health education to travelers at the border points. This study hopes to provide meaningful clues and a scientific basis for policymakers regarding effective interventions against dengue transmission, even during outbreaks.
As a common vector-borne disease, dengue fever remains challenging to predict due to large variations in epidemic size across seasons driven by a number of factors including population susceptibility, mosquito density, meteorological conditions, geographical factors, and human mobility. An ensemble forecast system for dengue fever is first proposed that addresses the difficulty of predicting outbreaks with drastically different scales. The ensemble forecast system based on a susceptible-infected-recovered (SIR) type of compartmental model coupled with a data assimilation method called the ensemble adjusted Kalman filter (EAKF) is constructed to generate real-time forecasts of dengue fever spread dynamics. The model was informed by meteorological and mosquito density information to depict the transmission of dengue virus among human and mosquito populations, and generate predictions. To account for the dramatic variations of outbreak size in different seasons, the effective population size parameter that is sequentially updated to adjust the predicted outbreak scale is introduced into the model. Before optimizing the transmission model, we update the effective population size using the most recent observations and historical records so that the predicted outbreak size is dynamically adjusted. In the retrospective forecast of dengue outbreaks in Guangzhou, China during the 2011-2017 seasons, the proposed forecast model generates accurate projections of peak timing, peak intensity, and total incidence, outperforming a generalized additive model approach. The ensemble forecast system can be operated in real-time and inform control planning to reduce the burden of dengue fever.
BACKGROUND: Dengue has become an increasing public health threat around the world, and climate conditions have been identified as important factors affecting the transmission of dengue, so this study was aimed to establish a prediction model of dengue epidemic by meteorological methods. METHODS: The dengue case information and meteorological data were collected from Guangdong Provincial Center for Disease Prevention and Control and Guangdong Meteorological Bureau, respectively. We used spatio-temporal analysis to characterize dengue epidemics. Spearman correlation analysis was used to analyze the correlation between lagged meteorological factors and dengue fever cases and determine the maximum lagged correlation coefficient of different meteorological factors. Then, Generalized Additive Models were used to analyze the non-linear influence of lagged meteorological factors on local dengue cases and to predict the number of local dengue cases under different weather conditions. RESULTS: We described the temporal and spatial distribution characteristics of dengue fever cases and found that sporadic single or a small number of imported cases had a very slight influence on the dengue epidemic around. We further created a forecast model based on the comprehensive consideration of influence of lagged 42-day meteorological factors on local dengue cases, and the results showed that the forecast model has a forecast effect of 98.8%, which was verified by the actual incidence of dengue from 2005 to 2016 in Guangzhou. CONCLUSION: A forecast model for dengue epidemic was established with good forecast effects and may have a potential application in global dengue endemic areas after modification according to local meteorological conditions. High attention should be paid on sites with concentrated patients for the control of a dengue epidemic.
BACKGROUND: In recent years, frequent outbreaks of dengue fever (DF) have become an increasingly serious public health issue in China, especially in the Pearl River Delta (PRD) with fast socioeconomic developments. Previous studies mainly focused on the historic DF epidemics, their influencing factors, and the prediction of DF risks. However, the future risks of this disease under both different socioeconomic development and representative concentration pathways (RCPs) scenarios remain little understood. METHODOLOGY AND PRINCIPAL FINDINGS: In this study, a spatial dataset of gross domestic product (GDP), population density, and land use and land coverage (LULC) in 2050 and 2070 was obtained by simulation based on the different shared socioeconomic pathways (SSPs), and the future climatic data derived from the RCP scenarios were integrated into the Maxent models for predicting the future DF risk in the PRD region. Among all the variables included in this study, socioeconomics factors made the dominant contribution (83% or so) during simulating the current spatial distribution of the DF epidemics in the PRD region. Moreover, the spatial distribution of future DF risk identified by the climatic and socioeconomic (C&S) variables models was more detailed than that of the climatic variables models. Along with global warming and socioeconomic development, the zones with DF high and moderate risk will continue to increase, and the population at high and moderate risk will reach a maximum of 48.47 million (i.e., 63.78% of the whole PRD) under the RCP 4.5/SSP2 in 2070. CONCLUSIONS: The increasing DF risk may be an inevitable public health threat in the PRD region with rapid socioeconomic developments and global warming in the future. Our results suggest that curbs in emissions and more sustainable socioeconomic growth targets offer hope for limiting the future impact of dengue, and effective prevention and control need to continue to be strengthened at the junction of Guangzhou-Foshan, north-central Zhongshan city, and central-western Dongguan city. Our study provides useful clues for relevant hygienic authorities making targeted adapting strategies for this disease.
The aim of this study was to assess the role of climate variability on the incidence of dengue fever (DF), an endemic arboviral infection existing in Jakarta, Indonesia. The work carried out included analysis of the spatial distribution of confirmed DF cases from January 2007 to December 2018 characterising the sociodemographical and ecological factors in DF high-risk areas. Spearman’s rank correlation was used to examine the relationship between DF incidence and climatic factors. Spatial clustering and hotspots of DF were examined using global Moran’s I statistic and the local indicator for spatial association analysis. Classification and regression tree (CART) analysis was performed to compare and identify demographical and socio-ecological characteristics of the identified hotspots and low-risk clusters. The seasonality of DF incidence was correlated with precipitation (r=0.254, P<0.01), humidity (r=0.340, P<0.01), dipole mode index (r= -0.459, P<0.01) and Tmin (r= -0.181, P<0.05). DF incidence was spatially clustered at the village level (I=0.294, P<0.001) and 22 hotspots were identified with a concentration in the central and eastern parts of Jakarta. CART analysis showed that age and occupation were the most important factors explaining DF clustering. Areaspecific and population-targeted interventions are needed to improve the situation among those living in the identified DF high-risk areas in Jakarta.
Dengue fever is a leading cause of illness and death in the tropics and subtropics, and the disease has become a threat to many nonendemic countries where the competent vectors such as Aedes albopictus and Aedes aegypti are abundant. The dengue epidemic in Tokyo, 2014, poses the critical importance to accurately model and predict the outbreak risk of dengue fever in nonendemic regions. Using climatological datasets and traveler volumes in Japan, where dengue was not seen for 70 years by 2014, we investigated the outbreak risk of dengue in 47 prefectures, employing the temperature-dependent basic reproduction number and a branching process model. Our results show that the effective reproduction number varies largely by season and by prefecture, and, moreover, the probability of outbreak if an untraced case is imported varies greatly with the calendar time of importation and location of destination. Combining the seasonally varying outbreak risk with time-dependent traveler volume data, the unconditional outbreak risk was calculated, illustrating different outbreak risks between southern coastal areas and northern tourist cities. As the main finding, the large travel volume with nonnegligible risk of outbreak explains the reason why a summer outbreak in Tokyo, 2014, was observed. Prefectures at high risk of future outbreak would be Tokyo again, Kanagawa or Osaka, and highly populated prefectures with large number of travelers.
Dengue is a complex disease with an increasing number of infections worldwide. This study aimed to analyse spatiotemporal dengue outbreaks using geospatial techniques and examine the effects of the weather on dengue outbreaks in the Klang Valley area, Kuala Lumpur, Malaysia. Daily weather variables including rainfall, temperature (maximum and minimum) and wind speed were acquired together with the daily reported dengue cases data from 2001 to 2011 and converted into geospatial format to identify whether there was a specific pattern of the dengue outbreaks. The association between these variables and dengue outbreaks was assessed using Spearman’s correlation. The result showed that dengue outbreaks consistently occurred in the study area during a 11-year study period. And that the strongest outbreaks frequently occurred in two high-rise apartment buildings located in Kuala Lumpur City centre. The results also show significant negative correlations between maximum temperature and minimum temperature on dengue outbreaks around the study area as well as in the area of the high-rise apartment buildings in Kuala Lumpur City centre.
Dengue fever is a mosquito-borne disease that affects nearly 3.9 billion people globally. Dengue remains endemic in Malaysia since its outbreak in the 1980’s, with its highest concentration of cases in the state of Selangor. Predictors of dengue fever outbreaks could provide timely information for health officials to implement preventative actions. In this study, five districts in Selangor, Malaysia, that demonstrated the highest incidence of dengue fever from 2013 to 2017 were evaluated for the best machine learning model to predict Dengue outbreaks. Climate variables such as temperature, wind speed, humidity and rainfall were used in each model. Based on results, the SVM (linear kernel) exhibited the best prediction performance (Accuracy = 70%, Sensitivity = 14%, Specificity = 95%, Precision = 56%). However, the sensitivity for SVM (linear) for the testing sample increased up to 63.54% compared to 14.4% for imbalanced data (original data). The week-of-the-year was the most important predictor in the SVM model. This study exemplifies that machine learning has respectable potential for the prediction of dengue outbreaks. Future research should consider boosting, or using, nature inspired algorithms to develop a dengue prediction model.
BACKGROUND: This study aimed to explore whether the transmission routes of severe fever with thrombocytopenia syndrome (SFTS) will be affected by tick density and meteorological factors, and to explore the factors that affect the transmission of SFTS. We used the transmission dynamics model to calculate the transmission rate coefficients of different transmission routes of SFTS, and used the generalized additive model to uncover how meteorological factors and tick density affect the spread of SFTS. METHODS: In this study, the time-varying infection rate coefficients of different transmission routes of SFTS in Jiangsu Province from 2017 to 2020 were calculated based on the previous multi-population multi-route dynamic model (MMDM) of SFTS. The changes in transmission routes were summarized by collecting questionnaires from 537 SFTS cases in 2018-2020 in Jiangsu Province. The incidence rate of SFTS and the infection rate coefficients of different transmission routes were dependent variables, and month, meteorological factors and tick density were independent variables to establish a generalized additive model (GAM). The optimal GAM was selected using the generalized cross-validation score (GCV), and the model was validated by the 2016 data of Zhejiang Province and 2020 data of Jiangsu Province. The validated GAMs were used to predict the incidence and infection rate coefficients of SFTS in Jiangsu province in 2021, and also to predict the effect of extreme weather on SFTS. RESULTS: The number and proportion of infections by different transmission routes for each year and found that tick-to-human and human-to-human infections decreased yearly, but infections through animal and environmental transmission were gradually increasing. MMDM fitted well with the three-year SFTS incidence data (P<0.05). The best intervention to reduce the incidence of SFTS is to reduce the effective exposure of the population to the surroundings. Based on correlation tests, tick density was positively correlated with air temperature, wind speed, and sunshine duration. The best GAM was a model with tick transmissibility to humans as the dependent variable, without considering lagged effects (GCV = 5.9247E-22, R2 = 96%). Reported incidence increased when sunshine duration was higher than 11 h per day and decreased when temperatures were too high (>28°C). Sunshine duration and temperature had the greatest effect on transmission from host animals to humans. The effect of extreme weather conditions on SFTS was short-term, but there was no effect on SFTS after high temperature and sunshine hours. CONCLUSIONS: Different factors affect the infection rate coefficients of different transmission routes. Sunshine duration, relative humidity, temperature and tick density are important factors affecting the occurrence of SFTS. Hurricanes reduce the incidence of SFTS in the short term, but have little effect in the long term. The most effective intervention to reduce the incidence of SFTS is to reduce population exposure to high-risk environments.
Lyme borreliosis, recognized as one of the most important tick-borne diseases worldwide, has been increasing in incidence and spatial extent. Currently, there are few geographic studies about the distribution of Lyme borreliosis risk across China. Here we established a nationwide database that involved Borrelia burgdorferi sensu lato (B. burgdorferi) detected in humans, vectors, and animals in China. The eco-environmental factors that shaped the spatial pattern of B. burgdorferi were identified by using a two-stage boosted regression tree model and the model-predicted risks were mapped. During 1986-2020, a total of 2,584 human confirmed cases were reported in 25 provinces. Borrelia burgdorferi was detected from 35 tick species with the highest positive rates in Ixodes granulatus, Hyalomma asiaticum, Ixodes persulcatus, and Haemaphysalis concinna ranging 20.1%-24.0%. Thirteen factors including woodland, NDVI, rainfed cropland, and livestock density were determined as important drivers for the probability of B. burgdorferi occurrence based on the stage 1 model. The stage 2 model identified ten factors including temperature seasonality, NDVI, and grasslands that were the main determinants used to distinguish areas at high or low-medium risk of B. burgdorferi, interpreted as potential occurrence areas within the area projected by the stage 1 model. The projected high-risk areas were not only concentrated in high latitude areas, but also were distributed in middle and low latitude areas. These high-resolution evidence-based risk maps of B. burgdorferi was first created in China and can help as a guide to future surveillance and control and help inform disease burden and infection risk estimates.
BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS), one kind of tick-borne acute infectious disease, is caused by a novel bunyavirus. The relationship between meteorological factors and infectious diseases is a hot topic of current research. Liaoning Province has reported a high incidence of SFTS in recent years. However, the epidemiological characteristics of SFTS and its relationship with meteorological factors in the province remain largely unexplored. METHODS: Data on reported SFTS cases were collected from 2011 to 2019. Epidemiological characteristics of SFTS were analyzed. Spearman’s correlation test and generalized linear models (GLM) were used to identify the relationship between meteorological factors and the number of SFTS cases. RESULTS: From 2011 to 2019, the incidence showed an overall upward trend in Liaoning Province, with the highest incidence in 2019 (0.35/100,000). The incidence was slightly higher in males (55.9%, 438/783), and there were more SFTS patients in the 60-69 age group (31.29%, 245/783). Dalian City and Dandong City had the largest number of cases of SFTS (87.99%, 689/783). The median duration from the date of illness onset to the date of diagnosis was 8 days [interquartile range (IQR): 4-13 days]. Spearman correlation analysis and GLM showed that the number of SFTS cases was positively correlated with monthly average rainfall (r(s) = 0.750, P < 0.001; β = 0.285, P < 0.001), monthly average relative humidity (r(s) = 0.683, P < 0.001; β = 0.096, P < 0.001), monthly average temperature (r(s) = 0.822, P < 0.001; β = 0.154, P < 0.001), and monthly average ground temperature (r(s) = 0.810, P < 0.001; β = 0.134, P < 0.001), while negatively correlated with monthly average air pressure (r(s) = -0.728, P < 0.001; β = -0.145, P < 0.001), and monthly average wind speed (r(s) = -0.272, P < 0.05; β = -1.048, P < 0.001). By comparing both correlation coefficients and regression coefficients between the number of SFTS cases (dependent variable) and meteorological factors (independent variables), no significant differences were observed when considering immediate cases and cases with lags of 1 to 5 weeks for dependent variables. Based on the forward and backward stepwise GLM regression, the monthly average air pressure, monthly average temperature, monthly average wind speed, and time sequence were selected as relevant influences on the number of SFTS cases. CONCLUSION: The annual incidence of SFTS increased year on year in Liaoning Province. Incidence of SFTS was affected by several meteorological factors, including monthly average air pressure, monthly average temperature, and monthly average wind speed.
Ticks are known as vectors of several pathogens causing various human and animal diseases including Lyme borreliosis, tick-borne encephalitis, and Crimean-Congo hemorrhagic fever. While China is known to have more than 100 tick species well distributed over the country, our knowledge on the likely distribution of ticks in the future remains very limited, which hinders the prevention and control of the risk of tick-borne diseases. In this study, we selected four representative tick species which have different regional distribution foci in mainland China. i.e., Dermacentor marginatus, Dermacentor silvarum, Haemaphysalis longicornis and Ixodes granulatus. We used the MaxEnt model to identify the key environmental factors of tick occurrence and map their potential distributions in 2050 under four combined climate and socioeconomic scenarios (i.e., SSP1-RCP2.6, SSP2-RCP4.5, SSP3-RCP7.0 and SSP5-RCP8.5). We found that the extent of the urban fabric, cropland and forest, temperature annual range and precipitation of the driest month were the main determinants of the potential distributions of the four tick species. Under the combined scenarios, with climate warming, the potential distributions of ticks shifted to further north in China. Due to a decrease in the extent of forest, the distribution probability of ticks declined in central and southern China. In contrast with previous findings on an estimated amplification of tick distribution probability under the extreme emission scenario (RCP8.5), our studies projected an overall reduction in the distribution probability under RCP8.5, owing to an expected effect of land use. Our results could provide new data to help identify the emerging risk areas, with amplifying suitability for tick occurrence, for the prevention and control of tick-borne zoonoses in mainland China. Future directions are suggested towards improved quantity and quality of the tick occurrence database, comprehensiveness of factors and integration of different modelling approaches, and capability to model pathogen spillover at the human-tick interface.
Climate is widely known as an important driver to transmit vector-borne diseases (VBD). However, evidence of the role of climate variability on VBD risk in Indonesia has not been adequately understood. We conducted a systematic literature review to collate and critically review studies on the relationship between climate variability and VBD in Indonesia. We searched articles on PubMed, Scopus, and Google Scholar databases that are published until December 2021. Studies that reported the relationship of climate and VBD, such as dengue, chikungunya, Zika, and malaria, were included. For the reporting, we followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A total of 66 out of 284 studies were reviewed. Fifty-two (78.8%) papers investigated dengue, 13 (19.7%) papers studied malaria, one (1.5%) paper discussed chikungunya, and no (0%) paper reported on Zika. The studies were predominantly conducted in western Indonesian cities. Most studies have examined the short-term effect of climate variability on the incidence of VBD at national, sub-national, and local levels. Rainfall (n = 60/66; 90.9%), mean temperature (T(mean)) (n = 50/66; 75.8%), and relative humidity (RH) (n = 50/66; 75.8%) were the common climatic factors employed in the studies. The effect of climate on the incidence of VBD was heterogenous across locations. Only a few studies have investigated the long-term effects of climate on the distribution and incidence of VBD. The paucity of high-quality epidemiological data and variation in methodology are two major issues that limit the generalizability of evidence. A unified framework is required for future research to assess the impacts of climate on VBD in Indonesia to provide reliable evidence for better policymaking.
BACKGROUND: Scrub typhus (ST) and murine typhus (MT) are common but poorly understood causes of fever in Laos. We examined the spatial and temporal distribution of ST and MT, with the intent of informing interventions to prevent and control both diseases. METHODOLOGY AND PRINCIPLE FINDINGS: This study included samples submitted from 2003 to 2017 to Mahosot Hospital, Vientiane, for ST and MT investigation. Serum samples were tested using IgM rapid diagnostic tests. Patient demographic data along with meteorological and environmental data from Laos were analysed. Approximately 17% of patients were positive for either ST (1,337/8,150 patients tested) or MT (1,283/7,552 patients tested). While both diseases occurred in inhabitants from Vientiane Capital, from the univariable analysis MT was positively and ST negatively associated with residence in Vientiane Capital. ST was highly seasonal, with cases two times more likely to occur during the wet season months of July-September compared to the dry season whilst MT peaked in the dry season. Multivariable regression analysis linked ST incidence to fluctuations in relative humidity whereas MT was linked to variation in temperature. Patients with ST infection were more likely to come from villages with higher levels of surface flooding and vegetation in the 16 days leading up to diagnosis. CONCLUSIONS: The data suggest that as cities expand, high risk areas for MT will also expand. With global heating and risks of attendant higher precipitation, these data suggest that the incidence and spatial distribution of both MT and ST will increase.
Plasmodium knowlesi is an emerging species for malaria in Malaysia, particularly in East Malaysia. This infection contributes to almost half of all malaria cases and deaths in Malaysia and poses a challenge in eradicating malaria. The aim of this study was to develop a predictive model for P. knowlesi susceptibility areas in Sabah, Malaysia, using geospatial data and artificial neural networks (ANNs). Weekly malaria cases from 2013 to 2014 were used to identify the malaria hotspot areas. The association of malaria cases with environmental factors (elevation, water bodies, and population density, and satellite images providing rainfall, land surface temperature, and normalized difference vegetation indices) were statistically determined. The significant environmental factors were used as input for the ANN analysis to predict malaria cases. Finally, the malaria susceptibility index and zones were mapped out. The results suggested integrating geospatial data and ANNs to predict malaria cases, with overall correlation coefficient of 0.70 and overall accuracy of 91.04%. From the malaria susceptibility index and zoning analyses, it was found that areas located along the Crocker Range of Sabah and the East part of Sabah were highly susceptible to P. knowlesi infections. Following this analysis, targetted entomological mapping and malaria control programs can be initiated.
Simple Summary The globalization of trade and travel, in combination with climate change, have resulted in the geographical expansion of mosquito-borne diseases. Moreover, over-reliance on chemical pesticides to control mosquitoes has resulted in resistance, which threatens the management of disease risk. We show, for the first time, that mosquito traps baited with human odors, in combination with controlling mosquito larvae in breeding sites, resulted in the near elimination of mosquito populations on two small islands, and the elimination of Aedes mosquitoes for 6+ months on a third island, in the Maldives. The levels of control achieved are comparable to current genetic control methods that are far more costly and impractical for implementation on small islands. The approach presented here poses the first alternative in decades to manage mosquito-borne disease risk on small (tropical) islands in an affordable and environmentally friendly manner. Globally, environmental impacts and insecticide resistance are forcing pest control organizations to adopt eco-friendly and insecticide-free alternatives to reduce the risk of mosquito-borne diseases, which affect millions of people, such as dengue, chikungunya or Zika virus. We used, for the first time, a combination of human odor-baited mosquito traps (at 6.0 traps/ha), oviposition traps (7.2 traps/ha) and larval source management (LSM) to practically eliminate populations of the Asian tiger mosquito Aedes albopictus (peak suppression 93.0% (95% CI 91.7-94.4)) and the Southern house mosquito Culex quinquefasciatus (peak suppression 98.3% (95% CI 97.0-99.5)) from a Maldivian island (size: 41.4 ha) within a year and thereafter observed a similar collapse of populations on a second island (size 49.0 ha; trap densities 4.1/ha and 8.2/ha for both trap types, respectively). On a third island (1.6 ha in size), we increased the human odor-baited trap density to 6.3/ha and then to 18.8/ha (combined with LSM but without oviposition traps), after which the Aedes mosquito population was eliminated within 2 months. Such suppression levels eliminate the risk of arboviral disease transmission for local communities and safeguard tourism, a vital economic resource for small island developing states. Terminating intense insecticide use (through fogging) benefits human and environmental health and restores insect biodiversity, coral reefs and marine life in these small and fragile island ecosystems. Moreover, trapping poses a convincing alternative to chemical control and reaches impact levels comparable to contemporary genetic control strategies. This can benefit numerous communities and provide livelihood options in small tropical islands around the world where mosquitoes pose both a nuisance and disease threat.
Japanese encephalitis (JE) is the major cause of viral encephalitis (VE) in most Asian-Pacific countries. In Vietnam, there is no nationwide surveillance system for JE due to lack of medical facilities and diagnoses. Culex tritaeniorhynchus, Culex vishnui, and Culex quinquefasciatus have been identified as the major JE vectors in Vietnam. The main objective of this study was to forecast a risk map of Culex mosquitoes in Hanoi, which is one of the most densely populated cities in Vietnam. A total of 10,775 female adult Culex mosquitoes were collected from 513 trapping locations. We collected temperature and precipitation information during the study period and its preceding month. In addition, the other predictor variables (e.g., normalized difference vegetation index [NDVI], land use/land cover and human population density), were collected for our analysis. The final model selected for estimating the Culex mosquito abundance included centered rainfall, quadratic term rainfall, rice cover ratio, forest cover ratio, and human population density variables. The estimated spatial distribution of Culex mosquito abundance ranged from 0 to more than 150 mosquitoes per 900m2. Our model estimated that 87% of the Hanoi area had an abundance of mosquitoes from 0 to 50, whereas approximately 1.2% of the area showed more than 100 mosquitoes, which was mostly in the rural/peri-urban districts. Our findings provide better insight into understanding the spatial distribution of Culex mosquitoes and its associated environmental risk factors. Such information can assist local clinicians and public health policymakers to identify potential areas of risk for JE virus. Risk maps can be an efficient way of raising public awareness about the virus and further preventive measures need to be considered in order to prevent outbreaks and onwards transmission of JE virus.
Murine typhus is a flea-borne zoonotic disease that has been recently reported on Reunion Island, an oceanic volcanic island located in the Indian Ocean. Five years of survey implemented by the regional public health services have highlighted a strong temporal and spatial structure of the disease in humans, with cases mainly reported during the humid season and restricted to the dry southern and western portions of the island. We explored the environmental component of this zoonosis in an attempt to decipher the drivers of disease transmission. To do so, we used data from a previously published study (599 small mammals and 175 Xenopsylla fleas from 29 sampling sites) in order to model the spatial distribution of rat fleas throughout the island. In addition, we carried out a longitudinal sampling of rats and their ectoparasites over a 12 months period in six study sites (564 rats and 496 Xenopsylla fleas) in order to model the temporal dynamics of flea infestation of rats. Generalized Linear Models and Support Vector Machine classifiers were developed to model the Xenopsylla Genus Flea Index (GFI) from climatic and environmental variables. Results showed that the spatial distribution and the temporal dynamics of fleas, estimated through the GFI variations, are both strongly controlled by abiotic factors: rainfall, temperature and land cover. The models allowed linking flea abundance trends with murine typhus incidence rates. Flea infestation in rats peaked at the end of the dry season, corresponding to hot and dry conditions, before dropping sharply. This peak of maximal flea abundance preceded the annual peak of human murine typhus cases by a few weeks. Altogether, presented data raise novel questions regarding the ecology of rat fleas while developed models contribute to the design of control measures adapted to each micro region of the island with the aim of lowering the incidence of flea-borne diseases.
The population dynamics of mosquitoes in temperate regions are not as well understood as those in tropical and subtropical regions, despite concerns that vector-borne diseases may be prevalent in future climates. Aedes albopictus, a vector mosquito in temperate regions, undergoes egg diapause while overwintering. To assess the prevalence of mosquito-borne diseases in the future, this study aimed to simulate and predict mosquito population dynamics under estimated future climatic conditions. In this study, we tailored the physiology-based climate-driven mosquito population (PCMP) model for temperate mosquitoes to incorporate egg diapauses for overwintering. We also investigated how the incorporation of the effect of rainfall on larval carrying capacity (into a model) changes the population dynamics of this species under future climate conditions. The PCMP model was constructed to simulate mosquito population dynamics, and the parameters of egg diapause and rainfall effects were estimated for each model to fit the observed data in Tokyo. We applied the global climate model data to the PCMP model and observed an increase in the mosquito population under future climate conditions. By applying the PCMP models (with or without the rainfall effect on the carrying capacity of the A. albopictus), our projections indicated that mosquito population dynamics in the future could experience changes in the patterns of their active season and population abundance. According to our results, the peak population number simulated using the highest CO2 emission scenario, while incorporating the rainfall effect on the carrying capacity, was approximately 1.35 times larger than that predicted using the model that did not consider the rainfall effect. This implies that the inclusion of rainfall effects on mosquito population dynamics has a major impact on the risk assessments of mosquito-borne diseases in the future.
Dengue is a viral borne disease with complex transmission dynamics. Disease outbreak can exert an increasing pressure on the health system with high mortality. Understanding and predicting the outbreaks of dengue transmission is vital in controlling the spread. Mathematical models have become important tool in predicting the dynamics of dengue. Due to the complexity of the disease, general time series models do not describe the impact of the external parameters. In this work, we propose a generalised linear regression model to understand the dynamics of the dengue disease and predict the future outbreaks. To moderate the model, cross-correlation between reported dengue cases and climatic factors were identified using Pearson cross-correlation formula. Then threshold value was defined based on reported data in order to identify minimum risk level for the states of dengue outbreaks. Further, obtained results were compared.
INTRODUCTION: Numerous studies on the mosquito life cycle and transmission efficacy were performed under constant temperatures. Mosquito in wild, however, is not exposed to constant temperature but is faced with temperature variation on a daily basis. METHODS: In the present study, the mosquito life cycle and Zika virus transmission efficiency were conducted at daily fluctuating temperatures and constant temperatures. Aedes albopictus was infected with the Zika virus orally. The oviposition and survival of the infected mosquitoes and hatching rate, the growth cycle of larvae at each stage, and the infection rate (IR) of the progeny mosquitoes were performed at two constant temperatures (23°C and 31°C) and a daily temperature range (DTR, 23-31°C). RESULTS: It showed that the biological parameters of mosquitoes under DTR conditions were significantly different from that under constant temperatures. Mosquitoes in DTR survived longer, laid more eggs (mean number: 36.5 vs. 24.2), and had a higher hatching rate (72.3% vs. 46.5%) but a lower pupation rate (37.9% vs. 81.1%) and emergence rate (72.7% vs. 91.7%) than that in the high-temperature group (constant 31°C). When compared to the low-temperature group (constant 23°C), larvae mosquitoes in DTR developed faster (median days: 9 vs. 23.5) and adult mosquitoes carried higher Zika viral RNA load (median log(10) RNA copies/μl: 5.28 vs. 3.86). However, the temperature or temperature pattern has no effect on transovarial transmission. DISCUSSION: Those results indicated that there are significant differences between mosquito development and reproductive cycles under fluctuating and constant temperature conditions, and fluctuating temperature is more favorable for mosquitos’ survival and reproduction. The data would support mapping and predicting the distribution of Aedes mosquitoes in the future and establishing an early warning system for Zika virus epidemics.
Cutaneous leishmaniasis (CL) is one of the most important health challenges in hyperendemic countries like Iran. Geospatial information systems-based studies have shown that factors, including land cover, altitude, slope temperature, rainfall and animal livestock, affect CL distribution in Kohgyloyeh and Boyerahmad province, southwestern Iran. However, the question of the influence of nomadic tribes, who travel with their goats and sheep, on CL is unanswered. We, therefore, investigated their role in CL epidemiology from 2008 to 2017 and compare them with geoclimatic factors. CL patient demographic data and their village/city addresses were retrieved from Provincial Health Center and mapped on the geographic information system (GIS) layer of the province’s political divisions. Nomadic travel routes (NTRs) with a 2 km buffer were generated and their effect on CL was investigated together with the interpolated layers of rainfall, temperatures, humidity, slope, elevation, land covers, by binary regression. CL was significantly more common in villages/cities in the 2 km NTR zone (p value < .001; OR = 1.96; 95% CI = 1.4-2.745). Geoclimatic factors, including slope, elevation, rainfall, temperatures, humidity and most of the landcovers, were not significantly different inside and outside the NTR. Areas of irrigated farm were the only effective landcover on CL (p value = .049; OR = 2.717; 95% CI = 1.003-7.361) within the NTR versus non-NTR. Living within NTRs almost doubled the risk of acquiring CL. Several factors for this include passage through areas of high sand fly activity, increased contact between sandflies and humans, sheep and goats, and feeding on their blood and faeces, and low availability of health facilities that should be more investigated and considered in the future control programs.
Trypanosomes are the hemoflagellate kinetoplastid protozoan parasites affecting a wide range of vertebrate hosts having insufficient host specificity. Climatic change, deforestation, globalization, trade agreements, close association and genetic selection in links with environmental, vector, reservoir and potential susceptible hosts’ parameters have led to emergence of atypical human trypanosomosis (a-HT). Poor recording of such neglected tropical disease, low awareness in health professions and farming community has approached a serious intimidation for mankind. Reports of animal Trypanosoma species are now gradually increasing in humans, and lack of any compiled literature has diluted the issue. In the present review, global reports of livestock and rodent trypanosomes reported from human beings are assembled and discrepancies with the available literature are discussed along with morphological features of Trypanosoma species. We have described 21 human cases from the published information. Majority of cases 10 (47%) are due to T. lewisi, followed by 5 (24%) cases of T. evansi, 4 (19%) cases of T. brucei and 1 (5%) case each of T. vivax and T. congolense. Indian subcontinent witnessed 13 cases of a-HT, of which 9 cases are reported from India, which includes 7 cases of T. lewisi and 2 cases of T. evansi. Apart from, a-HT case reports, epidemiological investigation and treatment aspects are also discussed. An attempt has been made to provide an overview of the current situation of atypical human trypanosomosis caused by salivarian animal Trypanosoma globally. The probable role of Trypanosoma lytic factors (TLF) present in normal human serum (NHS) in providing innate immunity against salivarian animal Trypanosoma species and the existing paradox in medical science after the finding on intact functional apolipoprotein L1 (ApoL1) in Vietnam T. evansi Type A case is also discussed to provide an update on all aspects of a-HT. Insufficient data and poor reporting in Asian and African countries are the major hurdle resulting in under-reporting of a-HT, which is a potential emerging threat. Therefore, concerted efforts must be directed to address attentiveness, preparedness and regular surveillance in suspected areas with training of field technicians, medical health professionals and veterinarians. Enhancing a one health approach is specifically important in case of trypanosomosis.
Zoonotic cutaneous leishmaniasis (ZCL) is an important vector-borne disease with an incidence of 15.8 cases per 100,000 people in Iran in 2019. Despite all efforts to control the disease, ZCL has expanded into new areas during the last decades. The aim of this study was to predict the best ecological niches for both vectors and reservoirs of ZCL under climate change scenarios in Iran. Several online scientific databases were searched. In this study, various scientific sources (Google Scholar, PubMed, SID, Ovid Medline, Web of Science, Irandoc, Magiran) were searched. The inclusion criteria for this study included all records with spatial information about vectors and reservoirs of ZCL which were published between 1980 and 2019. The bioclimatic data were downloaded from online databases. MaxEnt model was used to predict the ecological niches for each species under two climate change scenarios in two periods: the 2030s and 2050s. The results obtained from the model were analysed in ArcMap to find the vulnerability of different provinces for the establishment of ZCL foci. The area under the curve (AUC) for all models was >0.8, which suggests the models are able to make an accurate prediction. The distribution of all studied species in different climatic conditions showed changes. The variables affecting each of the studied species are introduced in the article. The predicted maps show that by 2050 there will be more suitable areas for the co-occurrence of vector and reservoir(s) of ZCL in Iran compared to the current climate condition and RCP2.6 scenario. An area in the northwest of Iran is predicted to have suitable environmental conditions for both vectors and reservoirs of ZCL, although the disease has not yet been reported in this area. These areas should be considered for field studies to confirm these results and to prevent the establishment of new ZCL foci in Iran.
Leishmania parasites can cause zoonotic cutaneous leishmaniasis (CL) by circulating between humans, rodents, and sandflies in Iran. In this study, published data were collected from scientific sources such as Web of Science, Scopus, PubMed, Springer, ResearchGate, Wiley Online, Ovid, Ebsco, Cochrane Library, Google scholar, and SID. Keywords searched in the articles, theses, and abstracts from 1983 to 2021 were cutaneous leishmaniasis, epidemiology, reservoir, vector, climatic factors, identification, and Iran. This review revealed that CL was prevalent in the west of Iran, while the center and south of Iran were also involved in recent years. The lack of facilities in suburban regions was an aggravating factor in the human community. Some parts of southern Iran were prominent foci of CL due the presence of potential rodent hosts in these regions. Rhombomys opimus, Meriones lybicus, and Tatera indica were well-documented species for hosting the Leishmania species in Iran. Moreover, R. opimus has been found with a coinfection of Leishmania major and L. turanica from the northeast and center of Iran. Mashhad, Kerman, Yazd, and sometimes Shiraz and Tehran foci were distinct areas for L. tropica. Molecular identifications using genomic diagnosis of kDNA and ITS1 fragments of the parasite indicated that there is heterogeneity in leishmaniasis in different parts of the country. Although cutaneous leishmaniasis has been a predicament for the health system, it is relatively under control in Iran.
INTRODUCTION: Cutaneous leishmaniasis (CL) is currently a health problem in several parts of Iran, particularly Kerman. This study was conducted to determine the incidence and trend of CL in Kerman during 2014-2020 and its forecast up to 2023. The effects of meteorological variables on incidence was also evaluated. MATERIALS AND METHODS: 4993 definite cases of CL recorded from January 2014 to December 2020 by the Vice-Chancellor for Health at Kerman University of Medical Sciences were entered. Meteorological variables were obtained from the national meteorological site. The time series SARIMA methods were used to evaluate the effects of meteorological variables on CL. RESULTS: Monthly rainfall at the lag 0 (β = -0.507, 95% confidence interval:-0.955,-0.058) and monthly sunny hours at the lag 0 (β = -0.214, 95% confidence interval:-0.308,-0.119) negatively associated with the incidence of CL. Based on the Akaike information criterion (AIC) the multivariable model (AIC = 613) was more suitable than univariable model (AIC = 690.66) to estimate the trend and forecast the incidence up to 36 months. CONCLUSION: The decreasing pattern of CL in Kerman province highlights the success of preventive, diagnostic and therapeutic interventions during the recent years. However, due to endemicity of disease, extension and continuation of such interventions especially before and during the time periods with higher incidence is essential.
Leishmaniasis is the most important parasitic infection in Iran. The aim of this study was to model the changing suitability patterns of Leishmania infantum, the causative agent of visceral leishmaniasis for the 21(st) century in the country. Temperature, precipitation, and aridity-nature distribution limiting bioclimatic variables were involved in the ecological modelling. The altitudinal trends were considered by using 100 m bars. In Iran, the topographical patterns strongly impact the changing patterns of the suitability of L. infantum due to climate change. In general, climate change will decrease the parasite’s suitability in the areas at low altitudes and increase in the middle and higher elevation regions. Increasing values are mainly predicted in the West, the decreasing suitability values in the East part of Iran. The altitudinal shifts and the reduced spatial distribution of L. infantum in the arid regions of East and Central Iran were modelled.
In this paper, a Chikungunya dynamical model with virus mutation and transovarial transmission is developed, which incorporates the effect of seasonal temperature changes on disease transmission through time-dependent parameters. Firstly, the threshold parameter (Rm) that determines the persistence and ex -0 tinction of mosquito populations is given, and then the disease reproduction number R-0 is defined. Sec-ondly, it is proved that if (R-0(m)) > 1 and R-0 < 1, the disease disappears; if (R-0(m)) > 1 and R-0 > 1, then 0 0 Chikungunya with mutants and non-mutants will persist simultaneously. Finally, a case study is carried out with the data in Kerala, India, where the virus mutation causes the outbreak of Chikungunya. Data on newly confirmed human cases in the state between 2007 and 2010 is fitted and the theoretical results obtained in the previous section are validated. In addition, the effects of seasonal temperature change, virus mutation and transovarial transmission on the prevalence of the disease are studied by numerical simulations from different aspects. 2020 MSC: 34K13; 37N25; 92D30.(C) 2022 Elsevier Ltd. All rights reserved.
As incidences of food poisoning, especially norovirus-induced diarrhea, are associated with climate change, there is a need for an approach that can be used to predict the risks of such illnesses with high accuracy. In this paper, we predict the winter norovirus incidence rate in Korea compared to that of other diarrhea-causing viruses using a model based on B-spline added to logistic regression to estimate the long-term pattern of illness. We also develop a risk index based on the estimated probability of occurrence. Our probabilistic analysis shows that the risk of norovirus-related food poisoning in winter will remain stable or increase in Korea based on various Representative Concentration Pathway (RCP) scenarios. Our approach can be used to obtain an overview of the changes occurring in regional and seasonal norovirus patterns that can help assist in making appropriate policy decisions.
In the Southeast Asian region, the Philippines and Malaysia are two of the most affected by Harmful Algal Blooms (HABs). Using long-term observations of HAB events, we determined if these are increasing in frequency and duration, and expanding across space in each country. Blooms of Paralytic Shellfish Toxin (PST)-producing species in the Philippines did increase in frequency and duration during the early to mid-1990s, but have stabilized since then. However, the number of sites affected by these blooms continue to expand though at a slower rate than in the 1990s. Furthermore, the type of HABs and causative species have diversified for both toxic blooms and fish kill events. In contrast, Malaysia showed no increasing trend in the frequency of toxic blooms over the past three decades since Pyrodinium bahamense was reported in 1976. However, similar to the Philippines, other PST producers such as Alexandrium minutum and Alexandrium tamiyavanichii have become a concern. No amnesic shellfish poisoning (ASP) has been confirmed in either Philippines or Malaysia thus far, while ciguatera fish poisoning cases are known from the Philippines and Malaysia but the causative organisms remain poorly studied. Since the 1990s and early 2000s, recognition of the distribution of other PST-producing species such as species of Alexandrium and Gymnodinium catenatum in Southeast Asia has grown, though there has been no significant expansion in the known distributions within the last decade. A major more recent problem in the two countries and for Southeast Asia in general are the frequent fish-killing algal blooms of various species such as Prorocentrum cordatum, Margalefidinium polykrikoides, Chattonella spp., and unarmored dinoflagellates (e.g., Karlodinium australe and Takayama sp.). These new sites affected and the increase in types of HABs and causative species could be attributed to various factors such as introduction through mariculture and eutrophication, and partly because of increased scientific awareness. These connections still need to be more concretely investigated. The link to the El Niño Southern Oscillation (ENSO) should also be better understood if we want to discern how climate change plays a role in these patterns of HAB occurrences.
This study aimed at, and developed, a climate-driven model for predicting the abundance of V. parahaemolyticus in oysters based on the local climatological and environmental conditions in Taiwan. The predictive model was constructed using the elastic net machine learning method, and the most influential predictors were evaluated using a permutation-based approach. The abundance of V. parahaemolyticus in oysters in different seasons, time horizons, and representative concentration pathways (RCPs) were predicted using the Elastic-net machine learning model. The results showed: (1) the variation in wind speed or gust wind speed, sea surface temperature, precipitation, and pH influenced the prediction of V. parahaemolyticus concentration in oysters, and (2) the level of V. parahaemolyticus in oysters in Taiwan was projected to be increased by 40-67% in the near future (2046-2065) and by 39-86% by the end of twentieth-century (2081-2100) if the global temperature continues to increase due to climate change. The findings in this study may be used as inputs for quantifying the V. parahaemolyticus infection risk from eating this seafood in Taiwan.
BACKGROUND: The incidence of Escherichia coli bloodstream infections (BSI) is high and increasing. We aimed to describe the effect of season and temperature on the incidence of E. coli BSI and antibiotic-resistant E. coli BSI and to determine differences by place of BSI onset. METHODS: All E. coli BSI in adult Israeli residents between January 1, 2018 and December 19, 2019 were included. We used the national database of mandatory BSI reports and outdoor temperature data. Monthly incidence and resistance were studied using multivariable negative binomial regressions with season (July-October vs. other) and temperature as covariates. RESULTS: We included 10,583 events, 9012 (85%) community onset (CO) and 1571 (15%) hospital onset (HO). For CO events, for each average monthly temperature increase of 5.5 °C, the monthly number of events increased by 6.2% (95% CI 1.6-11.1%, p = 0.008) and the monthly number of multidrug-resistant events increased by 4.9% (95% CI 0.3-9.7%, p = 0.04). The effect of season was not significant. For HO events, incidence of BSI and resistant BSI were not associated with temperature or season. CONCLUSION: Temperature increases the incidence of CO E. coli BSI and CO antibiotic-resistant E. coli BSI. Global warming threatens to increase the incidence of E. coli BSI.
Previous studies have explored the effect between ambient temperature and infectious diarrhea (ID) mostly using relative risk, which provides limited information in practical applications. Few studies have focused on the disease burden of ID caused by temperature, especially for different subgroups and cities in a multi-city setting. This study aims to estimate the effects and attributable risks of temperature on category C ID and explore potential modifiers among various cities in Guangdong. First, distributed lag non-linear models (DLNMs) were used to explore city-specific associations between daily mean temperature and category C ID from 2014 to 2016 in Guangdong and pooled by applying multivariate meta-analysis. Then, multivariate meta-regression was implemented to analyze the potential heterogeneity among various cities. Finally, we assessed the attributable burden of category C ID due to temperature, low (below the 5th percentile of temperature) and high temperature (above the 95th percentile of temperature) for each city and subgroup population. Compared with the 50th percentile of daily mean temperature, adverse effects on category C ID were found when the temperature was lower than 12.27 ℃ in Guangdong Province. Some city-specific factors (longitude, urbanization rate, population density, disposable income per capita, and the number of medical technicians and beds per thousand persons) could modify the relationship of temperature-category C ID. During the study period, there were 60,505 category C ID cases (17.14% of total cases) attributable to the exposure of temperature, with the attributable fraction (AF) of low temperature (4.23%, 95% empirical confidence interval (eCI): 1.79-5.71%) higher than high temperature (1.34%, 95% eCI: 0.86-1.64%). Males, people under 5 years, and workers appeared to be more vulnerable to temperature, with AFs of 29.40%, 19.25%, and 21.49%, respectively. The AF varied substantially at the city level, with the largest AF of low temperature occurring in Shaoguan (9.58%, 95% eCI: 8.36-10.09%), and that of high temperature occurring in Shenzhen (3.16%, 95% eCI: 2.70-3.51%). Low temperature was an important risk factor for category C ID in Guangdong Province, China. The exposure-response relationship could be modified by city-specific characteristics. Considering the whole population, the attributable risk of low temperature was much higher than that of high temperature, and males, people under 5 years, and workers were vulnerable populations.
Infectious diarrhea in China showed a significant pattern. Many researchers have tried to reveal the drivers, yet usually only meteorological factors were taken into consideration. Furthermore, the diarrheal data they analyzed were incomplete and the algorithms they exploited were inefficient of adapting realistic relationships. Here, we investigate the impacts of meteorological and social factors on the number of infectious diarrhea cases in China. A machine learning algorithm called the Random Forest is utilized. Our results demonstrate that nearly half of infectious diarrhea occurred among children under 5 years old. Generally speaking, increasing temperature or relative humidity leads to increased cases of infectious diarrhea in China. Nevertheless, people from different age groups or different regions own different sensitivities to meteorological factors. The weight of feces that are harmfully treated could be a possible reason for infectious diarrhea of the elderly as well as children under 5 years old. These findings indicate that infectious diarrhea prevention for children under 5 years old remains a primary task in China. Personalized prevention countermeasures ought to be provided to different age groups and different regions. It is essential to bring the weight of feces that are harmfully treated to the forefront when considering infectious diarrhea prevention.
No study has ever investigated how ambient temperature and PM(2.5) mediate rotavirus infection (RvI) in children. We used insurance claims data from Taiwan in 2006-2012 to evaluate the RvI characteristics in children aged ≤ 9. The RvI incidence rates were higher in colder months, reaching the highest in March (117.0/100 days), and then declining to the lowest in July (29.2/100 days). The age-sex-specific average incident cases were all higher in boys than in girls. Stratified analysis by temperature (<20, 20-24, and ≥25 °C) and PM(2.5) (<17.5, 17.5-31.4, 31.5-41.9, and ≥42.0 μg/m^3) showed that the highest incidence was 16.4/100 days at average temperatures of <20 °C and PM(2.5) of 31.5–41.9 μg/m^3, with Poisson regression analysis estimating an adjusted relative risk (aRR) of 1.26 (95% confidence interval (CI) = 1.11-1.43), compared to the incidence at the reference condition (<20 °C and PM2.5 < 17.5 μg/m^3). As the temperature increased, the incident RvI cases reduced to 4.84 cases/100 days (aRR = 0.40, 95% CI = 0.35-0.45) when it was >25 °C with PM(2.5) < 17.5 μg/m^3, or to 9.84/100 days (aRR = 0.81, 95% CI = 0.77-0.93) when it was >25 °C with PM2.5 > 42 μg/m^3). The seasonal RvI is associated with frequent indoor personal contact among children in the cold months. The association with PM(2.5) could be an alternative assessment due to temperature inversion.
Vibrio infection was rarely reported in Tasmania prior to 2016, when a multistate outbreak of Vibrio parahaemolyticus associated with Tasmanian oysters was identified and 11 people reported ill. Since then, sporadic foodborne cases have been identified following consumption of commercially- and recreationally-harvested oysters. The increases in both foodborne and non-foodborne Vibrio infections in Tasmania are likely associated with increased sea water temperatures. As oyster production increases and climate change raises the sea surface temperature of our coastline, Tasmania expects to see more vibriosis cases. Vibriosis due to oyster consumption has been reported in other Australian states, but the variability in notification requirements between jurisdictions makes case and outbreak detection difficult and potentially hampers any public health response to prevent further illness.
BACKGROUND: High atmospheric temperature has been associated with the occurrence of bacillary dysentery (BD). Recent studies have suggested that hot extremes may influence health outcomes, however, none have examined the association between hot extremes and BD risk, especially at the national level. OBJECTIVES: To assess the effect and attributable burden of hot extremes on BD cases and to identify populations at high risk of BD. METHODS: Daily incident BD data of 31 provincial capital cities from 2010 to 2018 were collected from the Chinese Center for Disease Control and Prevention, weather data was obtained from the fifth generation of the European Re-Analysis Dataset. Three types of hot extremes, including hot day, hot night, and hot day and night, were defined according to single or sequential occurrence of daytime hot and nighttime hot within 24 h. A two-stage analytical strategy combined with distributed lag non-linear models (DLNM) was used to evaluate city-specific associations and national pooled estimates. RESULTS: Hot extremes were significantly associated with the risk of BD on lagged 1-6 days. The overall cumulative relative risk (RR) was 1.136 [95% confidence interval (CI): 1.022, 1.263] for hot day, 1.181 (95% CI: 1.019, 1.369) for hot night, and 1.154 (95% CI: 1.038, 1.283) for hot day and night. Northern residents, females, and children younger than or equal to 14 years old were vulnerable under hot night, southern residents were vulnerable under hot day, and males were vulnerable under hot day and night. 1.854% (95% CI: 1.294%, 2.205%) of BD cases can be attributable to hot extremes, among which, hot night accounted for a large proportion. CONCLUSIONS: Hot extremes may significantly increase the incidence risk and disease burden of BD. Type-specific protective measures should be taken to reduce the risk of BD, especially in those we found to be particularly vulnerable.
BACKGROUND: Typhoid fever is endemic in some Pacific Island Countries including Fiji and Samoa yet genomic surveillance is not routine in such settings. Previous studies suggested imports of the global H58 clade of Salmonella enterica var Typhi (Salmonella Typhi) contribute to disease in these countries which, given the MDR potential of H58, does not auger well for treatment. The objective of the study was to define the genomic epidemiology of Salmonella Typhi in Fiji. METHODS: Genomic sequencing approaches were implemented to study the distribution of 255 Salmonella Typhi isolates from the Central Division of Fiji. We augmented epidemiological surveillance and Bayesian phylogenomic approaches with a multi-year typhoid case-control study to define geospatial patterns among typhoid cases. FINDINGS: Genomic analyses showed Salmonella Typhi from Fiji resolved into 2 non-H58 genotypes with isolates from the two dominant ethnic groups, the Indigenous (iTaukei) and non-iTaukei genetically indistinguishable. Low rates of international importation of clones was observed and overall, there were very low levels an antibiotic resistance within the endemic Fijian typhoid genotypes. Genomic epidemiological investigations were able to identify previously unlinked case clusters. Bayesian phylodynamic analyses suggested that genomic variation within the larger endemic Salmonella Typhi genotype expanded at discreet times, then contracted. INTERPRETATION: Cyclones and flooding drove ‘waves’ of typhoid outbreaks in Fiji which, through population aggregation, poor sanitation and water safety, and then mobility of the population, spread clones more widely. Minimal international importations of new typhoid clones suggest that targeted local intervention strategies may be useful in controlling endemic typhoid infection. These findings add to our understanding of typhoid transmission networks in an endemic island country with broad implications, particularly across Pacific Island Countries. FUNDING: This work was supported by the Coalition Against Typhoid through the Bill and Melinda Gates Foundation [grant number OPP1017518], the Victorian Government, the National Health and Medical Research Council Australia, the Australian Research Council, and the Fiji Ministry of Health and Medical Services.
BACKGROUND: Reported monthly scrub typhus (ST) cases in Thailand has an increase in the number of cases during 2009-2014. Humidity is a crucial climatic factor for the survival of chiggers, which is the disease vectors. The present study was to determine the role of humidity in ST occurrence in Thailand and its delayed effect. METHODS: We obtained the climate data from the Department of Meteorology, the disease data from Ministry of Public Health. Negative binomial regression combined with a distributed lag non-linear model (NB-DLNM) was employed to determine the non-linear effects of different types of humidity on the disease. This model controlled overdispersion and confounder, including seasonality, minimum temperature, and cumulative total rainwater. RESULTS: The occurrence of the disease in the 6-year period showed the number of cases gradually increased summer season (Mid-February – Mid-May) and then reached a plateau during the rainy season (Mid-May – Mid-October) and then steep fall after the cold season (Mid-October – Mid-February). The high level (at 70%) of minimum relative humidity (RHmin) was associated with a 33% (RR 1.33, 95% CI 1.13-1.57) significant increase in the number of the disease; a high level (at 14 g/m(3)) of minimum absolute humidity (AHmin) was associated with a 30% (RR 1.30, 95% CI 1.14-1.48); a high level (at 1.4 g/kg) of minimum specific humidity (SHmin) was associated with a 28% (RR 1.28, 95% CI 1.04-1.57). The significant effects of these types of humidity occurred within the past month. CONCLUSION: Humidity played a significant role in enhancing ST cases in Thailand, particularly at a high level and usually occurred within the past month. NB-DLNM had good controlled for the overdispersion and provided the precise estimated relative risk of non-linear associations. Results from this study contributed the evidence to support the Ministry of Public Health on warning system which might be useful for public health intervention and preparation in Thailand.
Scrub typhus is a zoonotic disease caused by the bacterium Orientia tsutsugamushi. In this study, the epidemiological characteristics of scrub typhus in Taiwan, including gender, age, seasonal variation, climate factors, and epidemic trends from 2010 to 2019 were investigated. Information about scrub typhus in Taiwan was extracted from annual summary data made publicly available on the internet by the Taiwan Centers for Disease Control. From 2010 to 2019, there were 4352 confirmed domestic and 22 imported cases of scrub typhus. The incidence of scrub typhus ranged from 1.39 to 2.30 per 100,000 from 2010-2019, and peaked in 2013 and 2015-2016. Disease incidence varied between genders, age groups, season, and residence (all p < 0.001) from 2010 to 2019. Risk factors were being male (odds ratio (OR) =1.358), age 40 to 64 (OR = 1.25), summer (OR = 1.96) or fall (OR = 1.82), and being in the Penghu islands (OR = 1.74) or eastern Taiwan (OR = 1.92). The occurrence of the disease varied with gender, age, and place of residence comparing four seasons (all p < 0.001). Weather, average temperature (°C) and rainfall were significantly correlated with confirmed cases. The number of confirmed cases increased by 3.279 for every 1 °C (p = 0.005) temperature rise, and 0.051 for every 1 mm rise in rainfall (p = 0.005). In addition, the total number of scrub typhus cases in different geographical regions of Taiwan was significantly different according to gender, age and season (all p < 0.001). In particular, Matsu islands residents aged 20-39 years (OR = 2.617) and residents of the Taipei area (OR = 3.408), northern Taiwan (OR = 2.268) and eastern Taiwan (OR = 2.027) were affected during the winter. Males and females in the 50-59 age group were at high risk. The total number of imported cases was highest among men, aged 20-39, during the summer months, and in Taipei or central Taiwan. The long-term trend of local cases of scrub typhus was predicted using the polynomial regression model, which predicted the month of most cases in a high-risk season according to the seasonal index (1.19 in June by the summer seasonal index, and 1.26 in October by the fall seasonal index). The information in this study will be useful for policy-makers and clinical experts for direct prevention and control of chigger mites with O. tsutsugamushi that cause severe illness and are an economic burden to the Taiwan medical system. These data can inform future surveillance and research efforts in Taiwan.
Vector-borne diseases have posed a heavy threat to public health, especially in the context of climate change. Currently, there is no comprehensive review of the impact of meteorological factors on all types of vector-borne diseases in China. Through a systematic review of literature between 2000 and 2021, this study summarizes the relationship between climate factors and vector-borne diseases and potential mechanisms of climate change affecting vector-borne diseases. It further examines the regional differences of climate impact. A total of 131 studies in both Chinese and English on 10 vector-borne diseases were included. The number of publications on mosquito-borne diseases is the largest and is increasing, while the number of studies on rodent-borne diseases has been decreasing in the past two decades. Temperature, precipitation, and humidity are the main parameters contributing to the transmission of vector-borne diseases. Both the association and mechanism show vast differences between northern and southern China resulting from nature and social factors. We recommend that more future research should focus on the effect of meteorological factors on mosquito-borne diseases in the era of climate change. Such information will be crucial in facilitating a multi-sectorial response to climate-sensitive diseases in China.
The geographic expansion of mosquitos is associated with a rising frequency of outbreaks of mosquito-borne diseases (MBD) worldwide. We collected occurrence locations and times of mosquito species, mosquito-borne arboviruses, and MBDs in the mainland of China in 1954-2020. We mapped the spatial distributions of mosquitoes and arboviruses at the county level, and we used machine learning algorithms to assess contributions of ecoclimatic, socioenvironmental, and biological factors to the spatial distributions of 26 predominant mosquito species and two MBDs associated with high disease burden. Altogether, 339 mosquito species and 35 arboviruses were mapped at the county level. Culex tritaeniorhynchus is found to harbor the highest variety of arboviruses (19 species), followed by Anopheles sinensis (11) and Culex pipiens quinquefasciatus (9). Temperature seasonality, annual precipitation, and mammalian richness were the three most important contributors to the spatial distributions of most of the 26 predominant mosquito species. The model-predicted suitable habitats are 60-664% larger in size than what have been observed, indicating the possibility of severe under-detection. The spatial distribution of major mosquito species in China is likely to be under-estimated by current field observations. More active surveillance is needed to investigate the mosquito species in specific areas where investigation is missing but model-predicted probability is high.
BACKGROUND: Anopheles philippinensis and Anopheles nivipes are morphologically similar and are considered to be effective vectors of malaria transmission in northeastern India. Environmental factors such as temperature and rainfall have a significant impact on the temporal and spatial distribution of disease vectors driven by future climate change. METHODS: In this study, we used the maximum entropy model to predict the potential global distribution of the two mosquito species in the near future and the trend of future distribution in China. Based on the contribution rate of environmental factors, we analyzed the main environmental factors affecting the distribution of the two mosquito species. We also constructed a disease vector risk assessment index system to calculate the comprehensive risk value of the invasive species. RESULTS: Precipitation has a significant effect on the distribution of potentially suitable areas for Anopheles philippinensis and Anopheles nivipes. The two mosquito species may spread in the suitable areas of China in the future. The results of the risk assessment index system showed that the two mosquito species belong to the moderate invasion risk level for China. CONCLUSIONS: China should improve the mosquito vector monitoring system, formulate scientific prevention and control strategies and strictly prevent foreign imports.
Scrub typhus is a climate-sensitive and life-threatening vector-borne disease that poses a growing public health threat. Although the climate-epidemic associations of many vector-borne diseases have been studied for decades, the impacts of climate on scrub typhus remain poorly understood, especially in the context of global warming. Here we incorporate Chinese national surveillance data on scrub typhus from 2010 to 2019 into a climate-driven generalized additive mixed model to explain the spatiotemporal dynamics of this disease and predict how it may be affected by climate change under various representative concentration pathways (RCPs) for three future time periods (the 2030s, 2050s, and 2080s). Our results demonstrate that temperature, precipitation, and relative humidity play key roles in driving the seasonal epidemic of scrub typhus in mainland China with a 2-month lag. Our findings show that the change of projected spatiotemporal dynamics of scrub typhus will be heterogeneous and will depend on specific combinations of regional climate conditions in future climate scenarios. Our results contribute to a better understanding of spatiotemporal dynamics of scrub typhus, which can help public health authorities refine their prevention and control measures to reduce the risks resulting from climate change.
Background: Scrub typhus (ST) is a climate-sensitive infectious disease. However, the nonlinear relationship between important meteorological factors and ST incidence is not clear. The present study identified the quantitative relationship between ST incidence and meteorological factors in southern China. Methods: The weekly number of ST cases and simultaneous meteorological variables in central Guangdong Province from 2006 to 2018 were obtained from the National Notifiable Infectious Disease Reporting Information System and the Meteorological Data Sharing Service System, respectively. A quasi-Poisson generalized additive model combined with a distributed lag nonlinear model (DLNM) was constructed to analyze the lag-exposure-response relationship between meteorological factors and the incidence of ST. Results: A total of 18,415 ST cases were reported in the study area. The estimated effects of meteorological factors on ST incidence were nonlinear and exhibited obvious lag characteristics. A J-shaped nonlinear association was identified between weekly mean temperature and ST incidence. A reversed U-shaped nonlinear association was noted between weekly mean relative humidity and ST incidence. The risk of ST incidence increased when the temperature ranged from 24 & DEG;C to 28 & DEG;C, the relative humidity was between 78% and 82%, or the precipitation was between 50 mm and 150 mm, using the medians as references. For high temperatures (75th percentile of temperature), the highest relative risk (RR) was 1.18 (95% CI: 1.10-1.27), with a lag effect that lasted 5 weeks. High relative humidity (75th percentile of relative humidity) and high precipitation (75th percentile of precipitation) could also increase the risk of ST. Conclusion: This study demonstrated the nonlinear relationship and the significant positive lag effects of temperature, relative humidity, and precipitation on the incidence of ST. Between particular thresholds, temperature, humidity, and levels of precipitation increased the risk of ST. These findings suggest that relevant government departments should address climate change and develop a meteorological conditions-depend strategy for ST prevention and control.
BACKGROUND: Scrub Typhus (ST) is a rickettsial disease caused by Orientia tsutsugamushi. The number of ST cases has been increasing in China during the past decades, which attracts great concerns of the public health. METHODS: We obtained monthly documented ST cases greater than 54 cases in 434 counties of China during 2012-2020. Spatiotemporal wavelet analysis was conducted to identify the ST clusters with similar pattern of the temporal variation and explore the association between ST variation and El Niño and La Niña events. Wavelet coherency analysis and partial wavelet coherency analysis was employed to further explore the co-effects of global and local climatic factors on ST. RESULTS: Wavelet cluster analysis detected seven clusters in China, three of which are mainly distributed in Eastern China, while the other four clusters are located in the Southern China. Among the seven clusters, summer and autumn-winter peak of ST are the two main outbreak periods; while stable and fluctuated periodic feature of ST series was found at 12-month and 4-(or 6-) month according to the wavelet power spectra. Similarly, the three-character bands were also found in the associations between ST and El Niño and La Niña events, among which the 12-month period band showed weakest climate-ST association and the other two bands owned stronger association, indicating that the global climate dynamics may have short-term effects on the ST variations. Meanwhile, 12-month period band with strong association was found between the four local climatic factors (precipitation, pressure, relative humidity and temperature) and the ST variations. Further, partial wavelet coherency analysis suggested that global climatic dynamics dominate annual ST variations, while local climatic factors dominate the small periods. CONCLUSION: The ST variations are not directly attributable to the change in large-scale climate. The existence of these plausible climatic determinants stimulates the interests for more insights into the epidemiology of ST, which is important for devising prevention and early warning strategies.
Scrub typhus, caused by Orientia tsutsugamushi, is a serious public health problem in the Asia-Pacific region, threatening the health of more than one billion people. China is one of the countries with the most serious disease burden of scrub typhus. Previous epidemiological evidence indicated that meteorological factors may affect the incidence of scrub typhus, but there was limited evidence for the correlation between local natural environment factors dominated by meteorological factors and scrub typhus. This study aimed to evaluate the correlation between monthly scrub typhus incidence and meteorological factors in areas with high scrub typhus prevalence using a distributed lag non-linear model (DLNM). The monthly data on scrub typhus cases in ten provinces from 2006 to 2018 and meteorological parameters were obtained from the Public Health Science Data Center and the National Meteorological Data Sharing Center. The results of the single-variable and multiple-variable models showed a non-linear relationship between incidence and meteorological factors of mean temperature (Tmean), rainfall (RF), sunshine hours (SH), and relative humidity (RH). Taking the median of meteorological factors as the reference value, the relative risks (RRs) of monthly Tmean at 0°C, RH at 46%, and RF at 800 mm were most significant, with RRs of 2.28 (95% CI: 0.95-5.43), 1.71 (95% CI: 1.39-2.09), and 3.33 (95% CI: 1.89-5.86). In conclusion, relatively high temperature, high humidity, and favorable rainfall were associated with an increased risk of scrub typhus.
Thirty-nine years ago, scrub typhus (ST), a disease, was not among the China’s notifiable diseases. However, ST has reemerged to become a growing public health issue in the southwest part of China. The major factors contributing to an increased incidence and prevalence of this disease include rapid globalization, urbanization, expansion of humans into previously uninhabited areas, and climate change. The clinical manifestation of ST also consists of high fever, headache, weakness, myalgia, rash, and an eschar. In severe cases, complications (e.g. multi-organ failure, jaundice, acute renal failure, pneumonitis, myocarditis, and even death) can occur. The diagnosis of ST is mainly based on serological identification by indirect immunofluorescence assay and other molecular methods. Furthermore, several groups of antibiotics (e.g. tetracycline, chloramphenicol, macrolides, and rifampicin) are currently effective in treating this disease. This fact suggests the need for robust early diagnostic techniques, increased surveillance, and prompt treatment, and develop future vaccine.
BACKGROUND: The impacts of non-pharmaceutical interventions (NPIs) and vaccine boosters on the transmission of the largest outbreak of COVID-19 (the fifth wave) in Hong Kong have not been reported. The outbreak, dominated by the Omicron BA.2 subvariant, began to spread substantially after the Spring Festival in February, 2022, when the temperature varied greatly (e.g. a cold surge event). Tightening social distancing measures did not succeed in containing the outbreak until later with the use of rapid antigen tests (RAT) and increased vaccination rates. Temperature has been previously found to have significant impact on the transmissibility. Understanding how the public health interventions influence the number of infections in this outbreak provide important insights on prevention and control of COVID-19 during different seasons. METHODS: We developed a transmission model incorporating stratified immunity with vaccine-induced antibody responses and the daily changes in population mobility, vaccination and weather factors (i.e. temperature and relative humidity). We fitted the model to the daily reported cases detected by either PCR or RAT between 1 February and 31 March using Bayesian statistics, and quantified the effects of individual NPIs, vaccination and weather factors on transmission dynamics. RESULTS: Model predicted that, with the vaccine uptake, social distancing reduced the cumulative incidence (CI) from 58.2% to 44.5% on average. The use of RAT further reduced the CI to 39.0%. Without vaccine boosters in these two months, the CI increased to 49.1%. While public health interventions are important in reducing the total infections, the outbreak was temporarily driven by the cold surge. If the coldest two days (8.5 °C and 8.8 °C) in February were replaced by the average temperature in that month (15.2 °C), the CI would reduce from 39.0% to 28.2%. CONCLUSION: Preventing and preparing for the transmission of COVID-19 considering the change in temperature appears to be a cost-effective preventive strategy to lead people to return to normal life.
Evidence regarding the effects of environmental factors on COVID-19 transmission is mixed. We aimed to explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases during the outbreak period throughout China. The number of COVID-19 confirmed cases, air pollutant concentrations, and meteorological factors in China from January 25 to February 29, 2020, (36 days) were extracted from authoritative electronic databases. The associations were estimated for a single-day lag as well as moving averages lag using generalized additive mixed models. Region-specific analyses and meta-analysis were conducted in 5 selected regions from the north to south of China with diverse air pollution levels and weather conditions and sufficient sample size. Nonlinear concentration-response analyses were performed. An increase of each interquartile range in PM(2.5), PM(10), SO(2), NO(2), O(3), and CO at lag4 corresponded to 1.40 (1.37-1.43), 1.35 (1.32-1.37), 1.01 (1.00-1.02), 1.08 (1.07-1.10), 1.28 (1.27-1.29), and 1.26 (1.24-1.28) ORs of daily new cases, respectively. For 1°C, 1%, and 1 m/s increase in temperature, relative humidity, and wind velocity, the ORs were 0.97 (0.97-0.98), 0.96 (0.96-0.97), and 0.94 (0.92-0.95), respectively. The estimates of PM(2.5), PM(10), NO(2), and all meteorological factors remained significantly after meta-analysis for the five selected regions. The concentration-response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily new cases increasing. Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. Controlling ambient air pollution, especially for PM(2.5), PM(10), NO(2), may be an important component of reducing risk of COVID-19 infection. In addition, as winter months are arriving in China, the meteorological factors may play a negative role in prevention. Therefore, it is significant to implement the public health control measures persistently in case another possible pandemic.
Allergic diseases are increasing globally. Air pollution, climate change, and reduced biodiversity are major threats to human health with detrimental effects on chronic noncommunicable diseases. Outdoor and indoor air pollution and climate change are increasing. Asia has experienced rapid economic growth, a deteriorating environment, and an increase in allergic diseases to epidemic proportions. Air pollutant levels in Asian countries are substantially higher than in developed countries. Moreover, industrial, traffic-related, and household biomass combustion and indoor pollutants from chemicals and tobacco are major sources of air pollutants. We highlight the major components of pollutants and their impacts on respiratory allergies.
Objective To examine countries’engagement with the health impacts of climate change in their formal statements to intergovernmental organizations, and the factors driving engagement. Methods We obtained the texts of countries’annual statements in United Nations (UN) general debates from 2000 to 2019 and their nationally determined contributions at the Paris Agreement in 2016. To measure countries’ engagement, we used a keyword-in-context text search with relevant search terms to count the total number of references to the relationship of health to climate change. We used a machine learning model (random forest predictions) to identify the most important country-level predictors of engagement. The predictors included political and economic factors, health outcomes, climate change-related variables and membership of political negotiating groups in the UN. Findings For both UN general debate statements and nationally determined contributions, low-and middle-income countries discussed the health impacts of climate change much more than did high-income countries. The most important predictors of engagement were health outcomes (infant mortality, maternal deaths, life expectancy), countries’ income levels (gross domestic product per capita), and fossil fuel consumption. Membership of political negotiating groups (such as the Group of 77 and Small Island Developing States) was a less important predictor. Conclusion Our analysis indicated a higher engagement in countries that carry the heaviest climate-related health burdens, but lack necessary resources to address the impacts of climate change. These countries are shouldering responsibility for reminding the global community of the implications of climate change for people’s health. Climate change is taking an increasing toll on people’s health. The increase in heatwaves, drought, floods and other climate hazards is increasing the risk of climate-related illness and death as well as reversing gains made in reducing food insecurity and global hunger.1,2 Air pollution, primarily driven by fossil fuel emissions, is the major environmental risk factor for premature death and has impacts on child health and survival.3-5 Highlighting these human impacts is seen as a way of accelerating climate action
Worldwide, over half of the global population is living in urban areas. The metropolitan areas are highly populated and environmentally non-green regions on the planet. In green space regions, plants, grass, and green vegetation prevent soil erosion, absorb air pollutants, provide fresh and clean air, and minimize the burden of diseases. Presently, the entire world is facing a turmoil situation due to the COVID-19 pandemic. This study investigates the effect of the green space environment on air pollutants particulate matter PM2.5, PM10, carbon monoxide (CO), ozone (O(3)), incidence and mortality of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) in environmentally highly green and less-green countries. We randomly selected 17 countries based on the Environmental Performance Index (EPI) data. The 60% of the EPI score is based on seven categories: biodiversity and habitat, ecosystem, fisheries, climate change, pollution emissions, agriculture, and water resources. However, 40% of the score is based on four categories: air quality, sanitation and drinking water, heavy metals, and waste management. The air pollutants and SARS-CoV-2 cases and deaths were recorded from 25 January 2020, to 11 July 2021. The air pollutants PM2.5, PM10, CO, and O(3) were recorded from the metrological websites, Air Quality Index-AQI, 2021. The COVID-19 daily cases and deaths were obtained from the World Health Organization. The result reveals that air pollutants mean values for PM2.5 110.73 ± 1.09 vs. 31.35 ± 0.29; PM10 80.43 ± 1.11 vs. 17.78 ± 0.15; CO 7.92 ± 0.14 vs. 2.35 ± 0.03 were significantly decreased (p < 0.0001) in environmentally highly green space countries compared to less-green countries. Moreover, SARS-CoV-2 cases 15,713.61 ± 702.42 vs. 3445.59 ± 108.09; and deaths 297.56 ± 11.27 vs. 72.54 ± 2.61 were also significantly decreased in highly green countries compared to less-green countries. The green environment positively impacts human wellbeing. The policymakers must implement policies to keep the living areas, surroundings, towns, and cities clean and green to minimize air pollution and combat the present pandemic of COVID-19.
The COVID-19 pandemic continues to expand, while the relationship between weather conditions and the spread of the virus remains largely debatable. In this paper, we attempt to examine this question by employing a flexible econometric model coupled with fine-scaled hourly temperature variations and a rich set of covariates for 291 cities in the Chinese mainland. More importantly, we combine the baseline estimates with climate-change projections from 21 global climate models to understand the pandemic in different scenarios. We found a significant negative relationship between temperatures and caseload. A one-hour increase in temperatures from 25 degrees C to 28 degrees C tends to reduce daily cases by 15.1%, relative to such an increase from -2 degrees C to 1 degrees C. Our results also suggest an inverted U-shaped nonlinear relationship between relative humidity and confirmed cases. Despite the negative effects of heat, we found that rising temperatures induced by climate change are unlikely to contain a hypothesized pandemic in the future. In contrast, cases would tend to increase by 10.9% from 2040 to 2059 with a representative concentration pathway (RCP) of 4.5 and by 7.5% at an RCP of 8.5, relative to 2020, though reductions of 1.8% and 18.9% were projected for 2080-2099 for the same RCPs, respectively. These findings raise concerns that the pandemic could worsen under the climate-change framework.
Australia’s summer bushfires of 2020-2021 were catastrophic, negatively impacting people, and the natural environment. This climate change-related event exacerbated the influence of the COVID-19 pandemic on public health. Young people are a priority population whose health and livelihoods are significantly impacted by these events. At the same time, young people are active agents for climate action. This exploratory mixed-method study draws on descriptive analyses of survey data (n = 46) and thematic analyses of interview data (n = 6) which demonstrated that some young people, whilst concerned about existential and real impacts of climate change, use contact with nature to cope and as motivation for taking climate actions.
BACKGROUND: From November 2019 to January 2020, eastern Australia experienced the worst bushfires in recorded history. Two months later, Sydney and surrounds were placed into lockdown for six weeks due to the COVID-19 pandemic, followed by ongoing restrictions. Many pregnant women at this time were exposed to both the bushfires and COVID-19 restrictions. OBJECTIVE: To assess the impact of exposure to bushfires and pandemic restrictions on perinatal outcomes. METHODS: The study included 60 054 pregnant women who gave birth between November 2017 and December 2020 in South Sydney. Exposure cohorts were based on conception and birthing dates: 1) bushfire late pregnancy, born before lockdown; 2) bushfires in early-mid pregnancy, born during lockdown or soon after; 3) conceived during bushfires, lockdown in second trimester; 4) conceived after bushfires, pregnancy during restrictions. Exposure cohorts were compared with pregnancies in the matching periods in the two years prior. Associations between exposure cohorts and gestational diabetes, preeclampsia, hypertension, stillbirth, mode of birth, birthweight, preterm birth and small for gestational age were assessed using generalised estimating equations, adjusting for covariates. RESULTS: A decrease in low birth weight was observed for cohort 1 (aOR 0.81, 95%CI 0.69, 0.95). Conversely, cohort 2 showed an increase in low birth weight, and increases in prelabour rupture of membranes, and caesarean sections (aOR 1.18, 95%CI 1.03, 1.37; aOR 1.21, 95%CI 1.07, 1.37; aOR 1.10 (1.02, 1.18) respectively). Cohort 3 showed an increase in unplanned caesarean sections and high birth weight babies (aOR 1.15, 95%CI 1.04, 1.27 and aOR 1.16, 95%CI 1.02, 1.31 respectively), and a decrease in gestational diabetes mellitus was observed for both cohorts 3 and 4. CONCLUSION: Pregnancies exposed to both severe climate events and pandemic disruptions appear to have increased risk of adverse perinatal outcomes beyond only experiencing one event, but further research is needed.
Henan Province in Central China was hit by unprecedented, rain-triggered floods in July 2021 and experienced a recurrence of the COVID-19 pandemic. The current study aims to identify the latent profiles of psychological status and acceptance of change among Henan residents who have been cumulatively exposed to these floods and the COVID-19 pandemic. A total of 977 participants were recruited. Latent profile analysis (LPA) was used to explore underlying patterns of psychological status (i.e., perceived risk of the COVID-19 pandemic, post-traumatic stress symptoms, anxiety and rumination) and acceptance of change. The predictors were evaluated with multinomial logistic regression. LPA identified four patterns of psychological status and acceptance of change: high distress/high acceptance (5.1%), moderate distress/moderate acceptance (20.1%), mild distress/mild acceptance (45.5%), and resilience (29.3%). The additive impact of the floods and COVID-19 pandemic and negative emotion during the floods were the risk factors, while flood coping efficacy, trust, and a closer psychological distance change were the protective factors. The present study therefore provides novel evidence on psychological status after both a natural disaster and a major public health event. The cumulative effects of the floods and the COVID-19 pandemic may have heightened the risk of post-disaster maladaptation. A complex relationship between psychological outcomes and acceptance of change was also found. The findings of this study thus provide a foundation for both disaster management and psychological assistance for particular groups.
Since the outbreak of COVID-19, wearing masks, vaccinations, and maintaining a safe distance has become social behaviors advocated by the government and widely adopted by the public. At the same time, unpredictable natural disaster risks brought by extreme climate change compound difficulties during epidemics and cause systemic risks that influence the existing pattern of epidemic prevention. Therefore, it is necessary to explore the effect of natural disaster risk caused by climate change on the response to outbreaks in the context of the COVID-19 epidemic. This study will focus on individual-level epidemic prevention behaviors, taking as an example the significant risk of severe destructive flooding caused by heavy rains in Henan, China, on July 20, 2021, which claimed 398 lives, to explore the effect of floods on the preventive behaviors of residents in the hardest hit areas against COVID-19. Through the multi-stage stratified random sampling of the affected residents in Zhengzhou, Xinxiang, Hebi, Luoyang, Anyang, and other cities in Henan Province, 2,744 affected people were surveyed via questionnaires. Through the linear regression model and moderating effect analysis, the study found that after floods, the individual’s flood risk perception and response behaviors significantly correlated with the individual’s prevention behaviors against COVID-19. Specifically, both flood risk perception and response behaviors strengthened the individual’s prevention behaviors. Furthermore, the study also found that community risk preparation behavior and social capital can moderate the above relationship to a certain extent. The research can guide risk communication under the compound risk scenario and prevent risky public behavior under the consistent presence of COVID-19 in the community.
OBJECTIVE: This research seeks to identify climate-sensitive infectious diseases of concern with a present and future likelihood of increased occurrence in the geographically vulnerable Torres Strait Islands, Australia. The objective is to contribute evidence to the need for adequate climate change responses. METHODS: Case data of infectious diseases with proven, potential and speculative climate sensitivity were compiled. RESULTS: Five climate-sensitive diseases in the Torres Strait and Cape York region were identified as of concern: tuberculosis, dengue, Ross River virus, melioidosis and nontuberculous mycobacterial infection. The region constitutes 0.52% of Queensland’s population but has a disproportionately high proportion of the state’s cases: 20.4% of melioidosis, 2.4% of tuberculosis and 2.1% of dengue. CONCLUSIONS: The Indigenous Torres Strait Islander peoples intend to remain living on their traditional country long-term, yet climate change brings risks of both direct and indirect human health impacts. Implications for public health: Climate-sensitive infections pose a disproportionate burden and ongoing risk to Torres Strait Islander peoples. Addressing the causes of climate change is the responsibility of various agencies in parallel with direct action to minimise or prevent infections. All efforts should privilege Torres Strait Islander peoples’ voices to self-determine response actions.
BACKGROUND: The effects of extreme temperature on infectious diseases are complex and far-reaching. There are few studies to access the relationship of pulmonary tuberculosis (PTB) with extreme temperature. The study aimed to identify whether there was association between extreme temperature and the reported morbidity of PTB in Shandong Province, China, from 2005 to 2016. METHODS: A generalized additive model (GAM) was firstly conducted to evaluate the relationship between daily reported incidence rate of PTB and extreme temperature events in the prefecture-level cities. Then, the effect estimates were pooled using meta-analysis at the provincial level. The fixed-effect model or random-effect model was selected based on the result of heterogeneity test. RESULTS: Among the 446,016 PTB reported cases, the majority of reported cases occurred in spring. The higher reported incidence rate areas were located in Liaocheng, Taian, Linyi and Heze. Extreme low temperature had an impact on the reported incidence of PTB in only one prefecture-level city, i.e., Binzhou (RR = 0.903, 95% CI: 0.817-0.999). While, extreme high temperature was found to have a positive effect on reported morbidity of PTB in Binzhou (RR = 0.924, 95% CI: 0.856-0.997) and Weihai (RR = 0.910, 95% CI: 0.843-0.982). Meta-analysis showed that extreme high temperature was associated with a decreased risk of PTB (RR = 0.982, 95% CI: 0.966-0.998). However, extreme low temperature was no relationship with the reported incidence of PTB. CONCLUSION: Our findings are suggested that extreme high temperature has significantly decreased the risk of PTB at the provincial levels. The findings have implications for developing strategies to response to climate change.
The aim of this study was to explore the effect of temperature on tuberculosis (TB) incidence using the distributed lag non-linear model (DLNM) from 2017 to 2021 in Kashgar city, the region with higher TB incidence than national levels, and assist public health prevention and control measures. From January 2017 to December 2021, a total of 8730 cases of TB were reported, with the higher incidence of male than that of female. When temperature was below 1 °C, it was significantly correlated with TB incidence compared to the median observed temperature (15 °C) at lag 7, 14, and 21, and lower temperatures showed larger RR (relative risk) values. High temperature produced a protective effect on TB transmission, and higher temperature from 16 to 31 °C has lower RR. In discussion stratified by gender, the maximum RRs were achieved for both male group and female group at - 15 °C with lag 21, reporting 4.28 and 2.02, respectively. At high temperature (higher than 20 °C), the RR value of developing TB for female group was significantly larger than 1. In discussion stratified by age, the maximum RRs were achieved for all age groups (≤ 35, 36-64, ≥ 65) at - 15 °C with lag 21, reporting 3.20, 2.07, and 3.45, respectively. When the temperature was higher than 20 °C, the RR of the 36-64-year-old group and the ≥ 65-year-old group was significantly larger than 1 at lag 21, while significantly smaller than 1 for cumulative RR at lag 21, reporting 0.11, 95% confidence interval (CI) (0.01, 0.83) and 0.06, 95% CI (0.01, 0.44), respectively. In conclusion, low temperature, especially in extreme level, acts as a high-risk factor inducing TB transmission in Kashgar city. Males exhibit a significantly higher RR of developing TB at low temperature than female, as well as the elderly group in contrast to the young or middle-aged groups. High temperature has a protective effect on TB transmission in the total population, but female and middle-aged and elderly groups are also required to be alert to the delayed RR induced by it.
BACKGROUND: The association between the incidence of hand, foot, and mouth disease (HFMD) and ambient temperature has been well documented. Although the severity of symptoms is an important indicator of disease burden and varies significantly across cases, it usually was ignored in previous studies, potentially leading to biased estimates of the health impact of temperature. METHODS: We estimated the disability-adjusted life year (DALY) by considering the severity of symptoms for each HFMD case reported during 2010-2012 in Guangdong and used distributed lag-nonlinear models to estimate the association between the daily average temperature and daily DALY of HFMD cases at the city-level. We investigated the potential effect modifiers on the pathway between temperature and DALY and pooled city-specific estimates to a provincial association using a meta-regression. The overall impact of temperature was further evaluated by estimates of DALYs that could be attributed to HFMD. RESULTS: The overall cumulative effect of daily mean temperature on the DALY of HFMD showed an inverse-U shape, with the maximum effect estimated to be β = 0.0331 (95%CI: 0.0199-0.0463) DALY at 23.8°C. Overall, a total of 6.432 (95%CI: 3.942-8.885) DALYs (attributable fraction = 2.721%, 95%CI: 1.660-3.759%) could be attributed to temperature exposure. All the demographic subgroups had a similar trend as the main analysis, while the magnitude of the peak of the temperature impact tended to be higher among the males, those aged ≥3yrs or from the Pear-River Delta region. Additionally, the impact of temperature on DALY elevated significantly with the increasing population density, per capita GDP, and per capita green space in parks. CONCLUSIONS: Temperature exposure was associated with increased burden of HFMD nonlinearly, with certain groups such as boys and those from areas with greater population density being more vulnerable.
The burden of disease caused by ambient high temperature has become a public health concern, but the associations between high temperature and hand, foot, and mouth disease (HFMD) remain indistinct. We used distributed lag non-linear model (DLNM) to estimate the burden of disease attribute to high temperature, adjusting for long-term trend and weather confounders. Total 18,167,455 cases were reported in 31 Chinese provinces, the incidence of HFMD showed a gradually increasing trend from 2008 to 2017 in China. Minimum morbidity temperature (MMT) was mainly concentrated at 17 to 23 °C in ≤ 5 years old group, 18 to 25 °C in 6 ~ 10 years old group and 19 to 27 °C in > 10 years old group. The greatest relative risk (RR) in age group ≤ 5 years old was 2.06 (95% CI: 1.85 ~ 2.30) in Heilongjiang, and the lowest RR was 1.02 (95% CI: 1.00 ~ 1.05) in Guangdong; the greatest RR in age group 6 ~ 10 years old was 2.24 (95% CI: 1.72 ~ 2.91) in Guizhou, and the lowest RR was 1.01 (95% CI: 0.97 ~ 1.12) in Tianjin; the greatest RR in the age group > 10 years old was 2.53 (95% CI: 1.66 ~ 3.87) in Heilongjiang, and the lowest RR was 1.02 (95% CI: 0.71 ~ 1.46) in Henan. We found the positive association between high temperature and HFMD in China.
BACKGROUND: Hand, foot and mouth disease (HFMD) is one of the common intestinal infectious diseases worldwide and has caused huge economic and disease burdens in many countries. The average annual incidence rate of HFMD was 11.66% in Shaanxi during the time span from 2009 to 2018. There are distinct differences within Shaanxi, as it is a special region that crosses three temperature zones. Hence, in this study, a spatiotemporal analysis of Shaanxi was performed to reveal the characteristics of the distribution of HFMD and to explore the meteorological determinants of HFMD. METHODS: The county-level and municipal data from Shaanxi Province from 2009 to 2018 were applied to research the spatiotemporal characteristics of HFMD and its meteorological determinants. Time series and spatial autocorrelation analyses were applied to assess the spatiotemporal characteristics of HFMD. This study used spatial econometric panel models to explore the relationship between HFMD and meteorological factors based on the data of 107 counties and 10 municipalities. RESULTS: The incidence rate of HFMD displayed no variable trend throughout the whole research period. A high incidence rate of HFMD was observed from June to September, corresponding to a time when the climate is characterized by heavy rain, high temperature, and high humidity. The high-incidence areas were mainly located in the central region in Shaanxi, whereas the low-incidence spots were mainly found in Northern Shaanxi. Regarding the meteorological factors analysed in this study, in general, the incidence rate of HFMD in specific regions was positively associated with the rainfall, temperature and humidity. CONCLUSION: These results could be applied by the government and the general public to take effective measures to prevent disease. Region-targeted policies could be enacted and implemented in the future according to specific situations in different areas and the relevant meteorological determinants. Additionally, meteorological conditions normally extend to a wide-ranging region; thus, cooperation among surrounding regions is necessary.
Salmonellosis is a climate-sensitive gastroenteritis with over 92 million cases and over 50,000 deaths a year globally. Australia has high rates of salmonellosis compared with other industrialised nations. This study used a negative binomial time-series regression model to investigate the association between Australian salmonellosis notifications and monthly climate variables including El Niño Southern Oscillation (ENSO) and mean temperature anomaly from 1991 to 2019. Between 1991 and 2019 in Australia there were 275,753 salmonellosis notifications and the median annual rate for salmonellosis was 40.1 per 100,000 population. Salmonellosis notifications exhibited strong seasonality, reaching a peak in summer and a minimum in winter. There was an estimated increase of 3.4 % in salmonellosis cases nationally per 1 °C increase in monthly mean temperature anomaly (incidence rate ratio [IRR] of 1.034, 95 % confidence interval [CI]: 1.009, 1.059). Similar associations between salmonellosis and mean temperature anomaly were found for some states. Mean temperature anomaly exhibited an upward trend of 0.9 °C over the period 1991 to 2019. Additionally, a positive association was found between salmonellosis in Australia and ENSO whereby El Niño periods were associated with 7.9 % more salmonellosis cases compared to neutral periods (IRR 1.079, 95 % CI: 1.019, 1.143). A similar ENSO association was detected in the two eastern states of New South Wales and Queensland. This study suggests public health preventative measures to reduce salmonellosis could be enhanced in some regions during El Niño as well as during times of increased temperatures.
Weather can impact infectious disease transmission, particularly for heat-sensitive pathogens, such as Salmonella. We conducted an ecological time-series analysis to estimate short-term associations between nonoutbreak-related notifications of Salmonella and weather conditions-temperature and rainfall-in Melbourne, Australia from 2000 to 2019. Distributed lag nonlinear models were created to analyze weather-salmonellosis associations and potential lag times on a weekly time scale, controlling for seasonality and long-term trends. Warmer temperatures were associated with increased risk of notification. Effects were temporally lagged, with the highest associations observed for warm temperatures 2-6 (greatest at 4) weeks before notification. The overall estimated relative risk of salmonellosis increased twofold at 33°C compared to the average weekly temperature (20.35°C) for the 8-week period preceding the disease notification. For Salmonella Typhimurium alone, this occurred at temperatures over 32°C. There were no statistically significant associations with rainfall and notification rates in any of the analyses performed. This study demonstrates the short-term influences of warm temperatures on Salmonella infections in Melbourne over a 20-year period. Salmonelloses are already the second most notified gastrointestinal diseases in Victoria, and these findings suggest that notifications may increase with increasing temperatures. This evidence contributes to previous findings that indicate concerns for public health with continued warm weather.
Bacterial dysentery (BD) brings a major disease burden to developing countries. Exploring the influence of temperature and its interaction with other meteorological factors on BD is significant for the prevention and early warning of BD in the context of climate change. Daily BD cases and meteorological data from 2008 to 2018 were collected in all nine prefecture-level cities in Jilin Province. A one-stage province-level model and a two-stage city-specific multivariate meta-pooled level distributed lag non-linear model were established to explore the correlation between temperature and BD, then the weather-stratified generalised additive model was used to test the interaction. During the study period, a total of 26 971 cases of BD were developed. The one-stage and two-stage cumulative dose-response ‘J’ curves overlapped, and results showed a positive correlation between temperature and BD with a 1-6 days lag effect. Age group ⩾5 years was found to be more sensitive to the effects. Moreover, there was a significant interaction between temperature, humidity and precipitation (P = 0.004, 0.002, respectively) on BD under high temperature (>0 °C), reminding residents and policymakers to pay attention to the prevention of BD in situations with both high temperature and humidity, high temperature and precipitation during the temperate monsoon climate.
ABSTRACT: Norovirus food poisoning outbreaks in Korea (South) appeared in the 2000s and have been increasing since then. We aimed to investigate the epidemiological features of norovirus food poisoning outbreaks in Korea from 2002 to 2017, on the basis of official food poisoning statistics and publically reliable reports, and to find any associations with climate factors. Norovirus was the most common cause of food poisoning among known causative substances in Korea during the study period. More than one-third of the outbreaks occurred in group meal service facilities, including school lunch programs. A few of these facilities used groundwater contaminated with noroviruses to wash or cook food, which contributed to outbreaks. Norovirus occurrences showed strong seasonality: cold and relatively dry winter air may help norovirus to flourish. Both norovirus genotypes GI and GII that are infectious to humans were detected, with GII becoming more prevalent than GI. According to our correlation analysis in connection with climate factors, average temperatures, the highest and lowest temperatures, precipitation, the number of rain days, and humidity showed a significant negative correlation with a monthly norovirus occurrence (P < 0.05). The lowest temperature and average temperature had higher coefficients of correlation, -0.377 and -0.376, respectively. The norovirus outbreaks in Korea showed complex etiological characteristics, although more prevailed in wintertime, and are now a major public health problem. The use of groundwater in group meal service settings is a public health issue, as well as a norovirus concern; therefore, groundwater used in food service facilities and businesses should be treated for safety.
OBJECTIVES: Evidence of the relationship between climate variability, air pollution and human parainfluenza virus (HPIV) infections has been inconsistent. We assessed this in a paediatric population from a highly urbanized tropical city-state. METHODS: We analysed all reports of HPIV infections in children <5 years old obtained from a major specialist women and children's hospital in Singapore. Assuming a negative binomial distribution and using multivariable fractional polynomial modelling, we examined the relations between climate variability, air quality and the risk of HPIV infections, adjusting for time-varying confounders. RESULTS: We identified 6393 laboratory-confirmed HPIV infections from 2009 to 2019. Every 1 °C decline in temperature was associated with a 5.8% increase (RR: 0.943, 95% Confidence Interval [95% CI]: 0.903-0.984) in HPIV infection risk 6 days later. Every 10% decrease in relative humidity was associated with a 15.8% cumulative increase in HPIV risk over the next 6 days (cumulative RR: 0.842, 95% CI: 0.771-0.919). Rainfall was positively associated with HPIV risk 2 days later (RR: 1.021, 95% CI: 1.000-1.043). A within-year seasonal rise of HPIV was driven by HPIV-3 and HPIV-1 and preceded by a seasonal decline in temperature. Gender was an effect modifier of the climate-HPIV relationship. Air quality was not associated with HPIV risk. CONCLUSIONS: This study demonstrates a close association between HPIV infection risk and tropical climate variability. The climate dependence and seasonal predictability of HPIV can inform the timing of community campaigns aimed at reducing infection risk and the development of hospital resources and climate adaption plans.
BACKGROUND: Acute respiratory infections (ARIs) are among the most common human illnesses globally. Previous studies that examined the associations between climate variability and ARIs or ARI pathogens have reported inconsistent findings. Few studies have been conducted in Southeast Asia to date, and the impact of climatic factors are not well-understood. This study aimed to investigate the short-term associations between climate variability and ARIs in Singapore. METHODS: We obtained reports of ARIs from all government primary healthcare services from 2005 to 2019 and analysed their dependence on mean ambient temperature, minimum temperature and maximum temperature using the distributed lag non-linear framework. Separate negative binomial regression models were used to estimate the association between each temperature (mean, minimum, maximum temperature) and ARIs, adjusted for seasonality and long-term trend, rainfall, relative humidity, public holidays and autocorrelations. For temperature variables and relative humidity we reported cumulative relative risks (RRs) at 10th and 90th percentiles compared to the reference value (centered at their medians) with corresponding 95% confidence intervals (CIs). For rainfall we reported RRs at 50th and 90th percentiles compared to 0 mm with corresponding 95% CIs. RESULTS: Statistically significant inverse S-curve shaped associations were observed between all three temperature variables (mean, minimum, maximum) and ARIs. A decrease of 1.1 °C from the median value of 27.8 °C to 26.7 °C (10th percentile) in the mean temperature was associated with a 6% increase (RR: 1.06, 95% CI: 1.03 to 1.09) in ARIs. ARIs also increased at 23.9 °C (10th percentile) compared to 24.9 °C of minimum temperature (RR: 1.11, 95% CI: 1.07 to 1.16). The effect of maximum temperature for the same comparison (30.5 °C vs 31.7 °C) was non-significant (RR: 1.02, 95% CI: 0.99 to 1.05). An increase in ambient temperature to 28.9 °C (90th percentile) was associated with an 18% decrease (RR: 0.82, 95% CI: 0.80 to 0.83) in ARIs. Similarly, ARIs decreased with the same increase to 90th percentile in minimum (RR: 0.84, 95% CI: 0.80 to 0.87) and maximum (RR: 0.89, 95% CI: 0.86 to 0.93) temperatures. Rainfall was inversely associated with ARIs and displayed similar shape in all three temperature models. Relative humidity, on the other hand, exhibited a U-shaped relationship with ARIs. CONCLUSION: Our findings suggest that lower temperatures increase the risk of ARIs. Anticipated extreme weather events that reduce ambient temperature can be used to inform increased healthcare resource allocation for ARIs.
Tuberculosis (TB) cases have increased drastically over the last two decades and it remains as one of the deadliest infectious diseases in Malaysia. This cross-sectional study aimed to establish the spatial distribution of TB cases and its association with the sociodemographic and environmental factors in the Gombak district. The sociodemographic data of 3325 TB cases such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency, and smoking status from 1st January 2013 to 31st December 2017 in Gombak district were collected from the MyTB web and Tuberculosis Information System (TBIS) database at the Gombak District Health Office and Rawang Health Clinic. Environmental data consisting of air pollution such as air quality index (AQI), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter 10 (PM10,) were obtained from the Department of Environment Malaysia from 1st July 2012 to 31st December 2017; whereas weather data such as rainfall were obtained from the Department of Irrigation and Drainage Malaysia and relative humidity, temperature, wind speed, and atmospheric pressure were obtained from the Malaysia Meteorological Department in the same period. Global Moran’s I, kernel density estimation, Getis-Ord Gi* statistics, and heat maps were applied to identify the spatial pattern of TB cases. Ordinary least squares (OLS) and geographically weighted regression (GWR) models were used to determine the spatial association of sociodemographic and environmental factors with the TB cases. Spatial autocorrelation analysis indicated that the cases was clustered (p<0.05) over the five-year period and year 2016 and 2017 while random pattern (p>0.05) was observed from year 2013 to 2015. Kernel density estimation identified the high-density regions while Getis-Ord Gi* statistics observed hotspot locations, whereby consistently located in the southwestern part of the study area. This could be attributed to the overcrowding of inmates in the Sungai Buloh prison located there. Sociodemographic factors such as gender, nationality, employment status, health care worker status, income status, residency, and smoking status as well as; environmental factors such as AQI (lag 1), CO (lag 2), NO2 (lag 2), SO2 (lag 1), PM10 (lag 5), rainfall (lag 2), relative humidity (lag 4), temperature (lag 2), wind speed (lag 4), and atmospheric pressure (lag 6) were associated with TB cases (p<0.05). The GWR model based on the environmental factors i.e. GWR2 was the best model to determine the spatial distribution of TB cases based on the highest R2 value i.e. 0.98. The maps of estimated local coefficients in GWR models confirmed that the effects of sociodemographic and environmental factors on TB cases spatially varied. This study highlighted the importance of spatial analysis to identify areas with a high TB burden based on its associated factors, which further helps in improving targeted surveillance.
The unfavorable effects of global climate change, which are mostly the result of human activities, have had a particularly negative effect on human health and the planet’s ecosystems. This study attempted to determine the seasonality and association of air pollution, in addition to climate conditions, with two respiratory infections, influenza and pneumonia, in Chiang Mai, Thailand, which has been considered the most polluted city on Earth during the hot season. We used a seasonal-trend decomposition procedure based on loess regression (STL) and a seasonal cycle subseries (SCS) plot to determine the seasonality of the two diseases. In addition, multivariable negative binomial regression (NBR) models were used to assess the association between the diseases and environmental variables (temperature, precipitation, relative humidity, PM(2.5), and PM(10)). The data revealed that influenza had a clear seasonal pattern during the cold months of January and February, whereas the incidence of pneumonia showed a weak seasonal pattern. In terms of forecasting, the preceding month’s PM(2.5) and temperature (lag1) had a significant association with influenza incidence, while the previous month’s temperature and relative humidity influenced pneumonia. Using air pollutants as an indication of respiratory disease, our models indicated that PM(2.5) lag1 was correlated with the incidence of influenza, but not pneumonia. However, there was a linear association between PM(10) and both diseases. This research will help in allocating clinical and public health resources in response to potential environmental changes and forecasting the future dynamics of influenza and pneumonia in the region due to air pollution.
The relationship between meteorological factors and the risk of hand, foot, and mouth disease (HFMD) has been well documented. However, researchers have failed to consider the complex interactive relationships among meteorological factors. The weekly number of HFMD cases along with meteorological factors were collected between 2009 to 2017 in four cities in Guangdong Province. We used Bayesian kernel machine regression to investigate the nonlinear and interactive relationship between meteorological factors, such as temperature and humidity, on the risk of HFMD. Multivariate meta-analysis was used to pool the city-specific effect estimates and identify factors underlying the inter-city heterogeneity. The risk ratios (RRs) for each percentile increase in temperature from the 50th percentile value, while humidity was at its 10th, 50th, and 90th percentile values, were 1.621(95%CI: 1.226, 2.141), 2.638(2.169, 3.208), and 3.734(2.908, 4.792), respectively (Q= 19.132, P (interaction)< 0.001). In contrast, the RRs for each percentile increase in humidity from its 50th percentile, while holding temperature at its 10th, 50th, and 90th percentile values, were 0.901(95%CI: 0.592, 1.369), 2.026(1.679, 2.448), and 0.884(0.632, 1.238), respectively (Q= 24.876, P (interaction) < 0.001). Increased wind speed and sunshine duration were also observed to strengthen the impact of other meteorological factors. Furthermore, we found increased gross domestic product per capita and per capital area of parks and green land in city tended to significantly strengthen the interactive effects of humidity on other meteorological factors including sunshine duration (P = 0.013 and 0.042), rainfall (P = 0.017 and 0.035), temperature (P = 0.021 and 0.031), win speed (P = 0.011 and 0.045), and pressure (P = 0.013 and 0.042). Our study contributed further understanding of complex interactions between meteorological factors on the risk of HFMD. Our findings provide epidemiological evidence for meteorological interactions on HFMD, which may provide knowledge for future research on the health effects of meteorological factors.
BACKGROUND: Hand, foot, and mouth disease (HFMD) is a febrile rash infection caused by enteroviruses, spreading mainly via the respiratory tract and close contact. In the past two decades, HFMD has been prevalent mainly in Asia, including China and South Korea, causing a huge disease burden and putting the lives and health of children at risk. Therefore, a further study of the factors influencing HFMD incidences has far-reaching implications. In existing studies, the environmental factors affecting such incidences are mainly divided into two categories: meteorological and air. Among these studies, the former are the majority of studies on HFMD. Some scholars have studied both factors at the same, but the number is not large and the findings are quite different. METHODS: We collect monthly cases of HFMD in children, meteorological factors and atmospheric pollution in Urumqi from 2014 to 2020. Trend plots are used to understand the approximate trends between meteorological factors, atmospheric pollution and the number of HFMD cases. The association between meteorological factors, atmospheric pollution and the incidence of HFMD in the Urumqi region of northwest China is then investigated using multiple regression models. RESULTS: A total of 16,168 cases in children are included in this study. According to trend plots, the incidence of HFMD shows a clear seasonal pattern, with O(3) (ug/m(3)) and temperature (°C) showing approximately the same trend as the number of HFMD cases, while AQI, PM(2.5) (ug/m(3)), PM(10) (ug/m(3)) and NO(2) (ug/m(3)) all show approximately opposite trends to the number of HFMD cases. Based on multiple regression results, O(3) (P = 0.001) and average station pressure (P = 0.037) are significantly and negatively associated with HFMD incidences, while SO(2) (P = 0.102), average dew point temperature (P = 0.072), hail (P = 0.077), and thunder (P = 0.14) have weak significant relationships with them.
Hand, foot, and mouth disease (HFMD) is a global infectious disease severely threatening children’s health. It has been recognized that climate factors play an important role in the transmission of HFMD. In this paper, the bootstrap test in the geographically weighted regression (GWR) literature is extended to geographically and temporally weighted regression (GTWR) models for identifying homogeneous explanatory variables and spatiotemporally heterogeneous ones. The resulting mixed GTWR model is then used to investigate spatiotemporal effect of climate factors on the HFMD incidence in Inner Mongolia, China, a provincial autonomous region with extensive area and different climatic conditions. The results demonstrate that the effect of relative humidity is global over space and time, while that of air temperature, air pressure and wind speed varies spatiotemporally. The extended bootstrap test provides a solid statistical basis for model selection. The findings from the study may provide not only a deep understanding of spatiotemporal variation characteristics of the climatic effect on the HFMD incidence, but also some useful evidences for taking measures of the disease prevention and control at the county level in different seasons.
Seasonal cycles of AHF are causally attributed to the seasonal pattern of respiratory tract infections. However, this assumption has never been formally validated. We aimed to determine whether the increase in winter admissions for acute heart failure (AHF) can be explained by seasonal infectious diseases. We studied 12,147 patients admitted for AHF over a period of 11 years (2005-2015). Detailed virology and bacteriology data were collected on each patient. Meteorological information including daily temperature and relative humidity was obtained for the same period. The peak-to-low ratio, indicating the intensity of seasonality, was calculated using negative binomial regression-derived incidence rate ratios (IRR). AHF admissions occurred with a striking annual periodicity, peaking in winter (December-February) and were lowest in summer (June-August), with a seasonal amplitude (January vs. August) of 2.00 ([95% CI 1.79-2.24]. Occurrence of confirmed influenza infections was low (1.59%). Clinical diagnoses of respiratory infections, confirmed influenza infections, and influenza-like infections also followed a strong seasonal pattern (P < 0.0001; Peak/low ratio 2.42 [95% CI 1.394-3.03]). However, after exclusion of all respiratory infections, the seasonal variation in AHF remained robust (Peak/low ratio January vs. August, 1.81 [95% CI 1.60-2.05]; P < 0.0001). There was a strong inverse association between AHF admissions and average monthly temperature (IRR 0.95 per 1℃ increase; 95% CI 0.94 to 0.96). In conclusion, these is a dominant seasonal modulation of AHF admissions which is only partly explained by the incidence of winter respiratory infections. Environmental factors modify the susceptibility of heart failure patients to decompensation.
Despite high incidence of acute kidney injury (AKI) among patients hospitalised for influenza, no previous work has attempted to analyse and quantify the association between the two. Herein, we made use of Hong Kong’s surveillance data to evaluate the time-varying relationship between seasonal influenza and risk of AKI with adjustment for potential environmental covariates. Generalized additive model was used in conjunction with distributed-lag non-linear model to estimate the association of interest with daily AKI admissions as outcome and daily influenza admissions as predictor, while controlling for environmental variables (i.e. temperature, relative humidity, total rainfall, nitrogen dioxide, and ozone). Results suggested a positive association between risk of AKI admission and number of influenza hospitalisation cases, with relative risk reaching 1.12 (95% confidence interval, 1.10-1.15) at the 95th percentile. Using median as reference, an almost U-shaped association between risk of AKI admission and temperature was observed; the risk increased significantly when the temperature was low. While ozone was not shown to be a risk factor for AKI, moderate-to-high levels of nitrogen dioxide (50-95th percentile) were significantly associated with increased risk of AKI admission. This study mentioned the possibility that AKI hospitalisations are subject to environmental influences and offered support for a positive association between seasonal influenza and AKI occurrence in Hong Kong. Authorities are urged to extend the influenza vaccination program to individuals with pre-existing renal conditions to safeguard the health of the vulnerable. Given that adverse health effects are evident at current ambient levels of nitrogen dioxide, the government is recommended to adopt clean-air policies at the earliest opportunity to protect the health of the community.
Many studies have shown that the relationship between ambient temperature, relative humidity and mumps has been highlighted. However, these studies showed inconsistent results. Therefore, the goal of our study is to conduct a meta-analysis to clarify this relationship and to quantify the size of these effects as well as the potential factors. Systematic literature researches on PubMed, Embase.com, Web of Science Core Collection, Cochrane library, Chinese BioMedical Literature Database (CBM) and China National Knowledge Infrastructure (CNKI) were performed up to February 7, 2022 for articles analyzing the relationships between ambient temperature, relative humidity and incidence of mumps. Eligibility assessment and data extraction were conducted independently by two researchers, and meta-analysis was performed to synthesize these data. We also assessed sources of heterogeneity by study region, regional climate, study population. Finally, a total of 14 studies were screened out from 1154 records and identified to estimate the relationship between ambient temperature, relative humidity and incidence of mumps. It was found that per 1 °C increase and decrease in the ambient temperature were significantly associated with increased incidence of mumps with RR of 1.0191 (95% CI: 1.0129-1.0252, I(2) = 92.0%, Egger’s test P = 0.001, N = 13) for per 1 °C increase and 1.0244 (95% CI: 1.0130-1.0359, I(2) = 86.6%, Egger’s test P = 0.077, N = 9) for per 1 °C decrease. As to relative humidity, only high effect of relative humidity was slightly significant (for per 1 unit increase with RR of 1.0088 (95% CI: 1.0027-1.0150), I(2) = 72.6%, Egger’s test P = 0.159, N = 9). Subgroup analysis showed that regional climate with temperate areas may have a higher risk of incidence of mumps than areas with subtropical climate in cold effect of ambient temperature and low effect of relative humidity. In addition, meta-regression analysis showed that regional climate may affect the association between incidence of mumps and cold effect of ambient temperature. Our results suggest ambient temperature could affect the incidence of mumps significantly, of which both hot and cold effect of ambient temperature may increase the incidence of mumps. Further studies are still needed to clarify the relationship between the incidence of mumps and ambient temperature outside of east Asia, and many other meteorological factors. These results of ambient temperature are important for establishing preventive measures on mumps, especially in temperate areas. The policy-makers should pay more attention to ambient temperature changes and take protective measures in advance.
Mumps is an acute and common childhood disease caused by paramyxovirus. It has been reported that the occurrence of mumps is influenced by seasonality. However, the role of meteorological variables in the incidence of mumps remains unclear. The purpose of this study was to explore the relationship between meteorological factors and the incidence of mumps infection. Poisson regression analysis was used to study the relationship between weather variability and the incidence of mumps in Taiwan. Between 2012 and 2018, 5459 cases of mumps cases were reported to the Centers for Disease Control, Taiwan (Taiwan CDC). The occurrence of mumps virus infections revealed significant seasonality in the spring and summer seasons in Taiwan. The incidence of mumps virus infections began to increase at temperatures of 15°C and started to decline if the temperature was higher than 29°C (r2 = 0.387, P = .008). Similarly, the number of mumps cases began to increase at a relative humidity of 65% to 69% (r2 = 0.838, P < .029). The number of mumps cases was positively associated with temperature and relative humidity during the period preceding the infection. This study showed that the occurrence of mumps is significantly associated with increasing temperature and relative humidity in Taiwan. Therefore, these factors could be regarded as early warning signals and indicate the need to strengthen the intervention and prevention of mumps.
OBJECTIVE: In this study, we aimed to investigate the clinical epidemiology of lower respiratory tract infections with different respiratory syncytial virus (RSV) subtypes in hospitalized children in Suzhou and their correlation with climatic and environmental factors. METHOD: In this retrospective cross-sectional study, we collected nasopharyngeal secretion samples from children hospitalized with acute lower respiratory tract infection. We collected the clinical data of children with RSV infection, and compared and analyzed their epidemiological characteristics. RESULTS: RSV-B was the dominant strain in 2016. In 2018, RSV-A was the dominant strain. The positive detection rate of RSV-A was negatively correlated with monthly mean temperature, monthly mean wind speed, total monthly rainfall, and O(3) concentration and positively correlated with PM2.5, PM10, and NO(2), SO(2), and CO concentrations. The positive detection rate of RSV-B was negatively correlated with monthly average temperature, monthly total rainfall, monthly sunshine duration, and O(3) concentration and positively correlated with CO concentration. CONCLUSIONS: RSV-A was the main subtype detected in this study. The positive detection rate of RSV-A was related to temperature, wind speed, rainfall, PM2.5. PM10, and NO(2), SO(2), CO, and O(3) concentrations. The positive detection rate of RSV-B was related to temperature, rainfall, sunshine time, and O(3) concentration.
BACKGROUND: While influenza infections and environmental factors have been documented as potential drivers of tuberculosis, no investigations have simultaneously examined their impact on tuberculosis at a population level. This study thereby made use of Hong Kong’s surveillance data over 22 years to elucidate the temporal association between environmental influences, influenza infections, and tuberculosis activity. METHODS: Weekly total numbers of hospital admissions due to tuberculosis, meteorological data, and outdoor air pollutant concentrations in Hong Kong during 1998-2019 were obtained. All-type influenza-like illness positive (ILI+) rate and type-specific ILI+ rates were used as proxies for influenza activity. Quasi-Poisson generalized additive models together with distributed lag non-linear models were used to assess the association of interest. RESULTS: A total of 164,116 hospital admissions due to tuberculosis were notified in public settings over a period of 22 years. The cumulative adjusted relative risk (ARR) of hospital admission due to tuberculosis was 1.07 (95% CI, 1.00-1.14) when the mean ambient temperature increased from 15.1 °C (the 5th percentile) to 24.5 °C (median). Short-term exposure to air pollutants was not found to be statistically significantly related to tuberculosis hospitalization. Accounting for the environmental covariates in the analysis, the cumulative ARR of tuberculosis admission was elevated to 1.05 (95% CI, 1.01-1.08) when the rate of ILI+ total increased from zero to 19.9 per 1000 consultations, the 95th percentile. CONCLUSION: Our findings demonstrated that increased influenza activity and higher temperature were related to a higher risk of tuberculosis admissions. Stepping up the promotion of influenza vaccination, especially before the summer season, may lower the risk of tuberculosis infection/reactivation for vulnerable groups (e.g. elderly born before the launch of Bacillus Calmette-Guérin vaccination programme).
Background: Existing evidence suggests that mumps epidemics, a global public health issue, are associated with meteorological factors and air pollutants at the population scale. However, the interaction effect of meteorological factors and air pollutants on mumps remains underexplored.Methods: Daily cases of mumps, meteorological factors, and air pollutants were collected in Ningxia, China, from 2015 to 2019. First, a distributed lag nonlinear model (DLNM) was employed to assess the confounding-adjusted relationship between meteorological factors, ambient air pollutants, and mumps incidences. According to the results of DLNM, stratification in both air pollutants and meteorological factors was adopted to further explore the interaction effect of particulate matter less than or equal to 2.5 mu m in aerodynamic diameter (PM2.5) and ground-level ozone (O-3) with temperature and relative humidity (RH).Results: We reported significant individual associations between mumps incidences and environmental factors, including temperature, relative humidity, PM2.5, and O-3. Evident multiplicate and additive interactions between meteorological factors and PM2.5 were found with interaction relative risk (IRR) of 1.14 (95%CI: 1.01, 1.29) and relative excess risk due to interaction (RERI) of 0.17 (95%CI: 0.02, 0.32) for a moderate level of temperature at 12 degrees C, and IRR of 1.37 (95%CI: 1.14, 1.66), RERI of 0.36 (95%CI: 0.11, 0.60) for a high level of temperature at 20 degrees C, respectively. These results indicated that PM2.5 and temperature have a significant synergistic effect on the cases of mumps, while no interaction between relative humidity and PM2.5 is observed. Regarding O-3 and meteorological factors (temperature = 12 degrees C, 20 degrees C), IRR and RERI were 1.33 (95%CI: 1.17, 1.52) and 0.30 (95%CI: 0.16, 0.45), 1.91 (95%CI: 1.46, 2.49) and 0.69 (95%CI: 0.32, 1.07), respectively. And IRR of 1.17 (95%CI: 1.06, 1.29), RERI of 0.13 (95%CI: 0.04, 0.21) for a middle level of relative humidity at 48%.Conclusion: Our findings indicated that meteorological factors and air pollutants imposed a significantly lagged and nonlinear effect on the incidence of mumps. The interaction between low temperature and O-3 showed antagonistic effects, while temperature (medium and high) with PM2.5 and O-3 presented synergistic effects. For relative humidity, the interaction with O-3 is synergistic. These results provide scientific evidence to relevant health authorities for the precise disease control and prevention of mumps in arid and semi-arid areas.
Big data can be used to correlate diseases and climatic factors. The prevalence of influenza (flu) virus, accounting for a large proportion of respiratory infections, suggests that the effect of climate variables according to seasonal dynamics of influenza virus infections should be investigated. Here, trends in flu virus detection were analyzed using data from 9,010 tests performed between January 2012 and December 2018 at Dankook University Hospital, Cheonan, Korea. We compared the detection of the flu virus in Cheonan area and its association with climate change. The flu virus detection rate was 9.9% (894/9,010), and the detection rate was higher for flu virus A (FLUAV; 6.9%) than for flu virus B (FLUBV; 3.0%). Both FLUAV and FLUBV infections are considered an epidemic each year. We identified 43.1% (n = 385) and 35.0% (n = 313) infections in children aged < 10 years and adults aged > 60 years, respectively. The combination of these age groups encompassed 78.1% (n = 698/894) of the total data. Flu virus infections correlated with air temperature, relative humidity, vapor pressure, atmospheric pressure, particulate matter, and wind chill temperature (P < 0.001). However, the daily temperature range did not significantly correlate with the flu detection results. This is the first study to identify the relationship between long-term flu virus infection with temperature in the temperate region of Cheonan.
BACKGROUND: Sentinel physician surveillance in communities has played an important role in detecting early signs of epidemics. The traditional approach is to let the primary care physician voluntarily and actively report diseases to the health department on a weekly basis. However, this is labor-intensive work, and the spatio-temporal resolution of the surveillance data is not precise at all. In this study, we built up a clinic-based enhanced sentinel surveillance system named “Sentinel plus” which was designed for sentinel clinics and community hospitals to monitor 23 kinds of syndromic groups in Taipei City, Taiwan. The definitions of those syndromic groups were based on ICD-10 diagnoses from physicians. METHODS: Daily ICD-10 counts of two syndromic groups including ILI and EV-like syndromes in Taipei City were extracted from Sentinel plus. A negative binomial regression model was used to couple with lag structure functions to examine the short-term association between ICD counts and meteorological variables. After fitting the negative binomial regression model, residuals were further rescaled to Pearson residuals. We then monitored these daily standardized Pearson residuals for any aberrations from July 2018 to October 2019. RESULTS: The results showed that daily average temperature was significantly negatively associated with numbers of ILI syndromes. The ozone and PM2.5 concentrations were significantly positively associated with ILI syndromes. In addition, daily minimum temperature, and the ozone and PM2.5 concentrations were significantly negatively associated with the EV-like syndromes. The aberrational signals detected from clinics for ILI and EV-like syndromes were earlier than the epidemic period based on outpatient surveillance defined by the Taiwan CDC. CONCLUSIONS: This system not only provides warning signals to the local health department for managing the risks but also reminds medical practitioners to be vigilant toward susceptible patients. The near real-time surveillance can help decision makers evaluate their policy on a timely basis.
The bacteria (including pathogenic bacteria) attached to road deposited sediments (RDS) may interrelate with the microbe in the atmosphere, soil and water through resuspension and wash-off, and is of great significance to human and ecological health. However, the characteristics of bacterial communities with different time scale on RDS were unknown to dates. Climate change prolonged the dry days between rain events in many areas, making the varied trend of bacterial communities might be more significant in short term. This study revealed the characteristics of bacterial communities on RDS in urban and suburban areas through seasonal and daily scale. The correlations between other factors (land use, particle size, and chemical components) and the bacterial communities were also analyzed. It was found that the season showed a higher association with the bacterial community diversity than land use and particle size in urban areas. The bacterial community diversity increased substantially throughout the short-term study period (41 days) and the variation of dominant bacteria could be fitted by quadratic function in suburbs. In addition, urbanization notably increased the bacterial community diversity, while the potential pathogenic bacteria were more abundant in the suburban areas, coarse RDS (>75 μm), and in spring. The chemical components on RDS showed special correlations with the relative abundance of dominant bacteria. The research findings would fill the knowledge gap on RDS bacterial communities and be helpful for the future research on the assembly process of bacterial communities.
This study proposed a novel ensemble analysis strategy to improve hand, foot and mouth disease (HFMD) prediction by integrating environmental data. The approach began by establishing a vector autoregressive model (VAR). Then, a dynamic Bayesian networks (DBN) model was used for variable selection of environmental factors. Finally, a VAR model with constraints (CVAR) was established for predicting the incidence of HFMD in Chengdu city from 2011 to 2017. DBN showed that temperature was related to HFMD at lags 1 and 2. Humidity, wind speed, sunshine, PM10, SO2 and NO2 were related to HFMD at lag 2. Compared with the autoregressive integrated moving average model with external variables (ARIMAX), the CVAR model had a higher coefficient of determination (R2, average difference: + 2.11%; t = 6.2051, P = 0.0003 < 0.05), a lower root mean-squared error (-24.88%; t = -5.2898, P = 0.0007 < 0.05) and a lower mean absolute percentage error (-16.69%; t = -4.3647, P = 0.0024 < 0.05). The accuracy of predicting the time-series shape was 88.16% for the CVAR model and 86.41% for ARIMAX. The CVAR model performed better in terms of variable selection, model interpretation and prediction. Therefore, it could be used by health authorities to identify potential HFMD outbreaks and develop disease control measures.
BACKGROUND: Although exposure to air pollution has been linked to many health issues, few studies have quantified the modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China. METHODS: The data of daily incidence of influenza and the relevant meteorological data and air pollution data in Ningbo from 2014 to 2017 were retrieved. Low, medium and high temperature layers were stratified by the daily mean temperature with 25th and 75th percentiles. The potential modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo was investigated through analyzing the effects of air pollutants stratified by temperature stratum using distributed lag non-linear model (DLNM). Stratified analysis by sex and age were also conducted. RESULTS: Overall, a 10 μg/m(3) increment of O(3), PM(2.5), PM(10) and NO(2) could increase the incidence risk of influenza with the cumulative relative risk of 1.028 (95% CI 1.007, 1.050), 1.061 (95% CI 1.004, 1.122), 1.043 (95% CI 1.003, 1.085), and 1.118 (95% CI 1.028, 1.216), respectively. Male and aged 7-17 years were more sensitive to air pollutants. Through the temperature stratification analysis, we found that temperature could modify the impacts of air pollution on daily incidence of influenza with high temperature exacerbating the impact of air pollutants. At high temperature layer, male and the groups aged 0-6 years and 18-64 years were more sensitive to air pollution. CONCLUSION: Temperature modified the relationship between air pollution and daily incidence of influenza and high temperature would exacerbate the effects of air pollutants in Ningbo.
Airborne bacteria have an important role in atmospheric processes and human health. However, there is still little information on the transmission and distribution of bacteria via the airborne route. To characterize the impact of foggy, haze, haze-fog (HF) and dust days on the concentration and viability of bacteria in atmospheric aerosols, size-segregated bioaerosol samples were collected in the Qingdao coastal region from March 2018 to February 2019. The total airborne microbes and viable/non-viable bacteria in the bioaerosol samples were measured using an epifluorescence microscope after staining with DAPI (4′, 6-diamidino-2-phenylindole) and a LIVE/DEAD® BacLight Bacterial Viability Kit. The average concentrations of total airborne microbes on haze and dust days were 6.75 × 10(5) and 1.03 × 10(6) cells/m(3), respectively, which increased by a factor of 1.3 and 2.5 (on average), respectively, relative to those on sunny days. The concentrations of non-viable bacteria on haze and dust days increased by a factor of 1.2 and 3.6 (on average), respectively, relative to those on sunny days. In contrast, the concentrations of viable bacteria on foggy and HF days were 7.13 × 10(3) and 5.74 × 10(3) cells/m(3), decreases of 38% and 50%, respectively, compared with those on sunny days. Foggy, haze, dust and HF days had a significant effect on the trend of the seasonal variation in the total airborne microbes and non-viable bacteria. Bacterial viability was 20.8% on sunny days and significantly higher than the 14.1% on foggy days, 11.2% on haze days, 8.6% during the HF phenomenon and 6.1% on dust days, indicating that special weather is harmful to some bacterial species. Correlation analysis showed that the factors that influenced the bacterial concentration and viability depended on different weather conditions. The main influential factors were temperature, NO(2) and SO(2) concentrations on haze days, and temperature, particulate matter (PM(2.5)) and NO(2) concentrations on foggy days. The median size of particles containing viable bacteria was 1.94 μm on sunny days and decreased to 1.88 μm and 1.74 μm on foggy and haze days, respectively, but increased to 2.18 μm and 2.37 μm on dust and HF days, respectively.
BACKGROUND: As the global climate changes, the number of cases of hand-foot-and-mouth disease (HFMD) is increasing year by year. This study comprehensively considers the association of time and space by analyzing the temporal and spatial distribution changes of HFMD in the Ili River Valley in terms of what climate factors could affect HFMD and in what way. METHODS: HFMD cases were obtained from the National Public Health Science Data Center from 2013 to 2018. Monthly climate data, including average temperature (MAT), average relative humidity (MARH), average wind speed (MAWS), cumulative precipitation (MCP), and average air pressure (MAAP), were obtained from the National Meteorological Information Center. The temporal and spatial distribution characteristics of HFMD from 2013 to 2018 were obtained using kernel density estimation (KDE) and spatiotemporal scan statistics. A regression model of the incidence of HFMD and climate factors was established based on a geographically and temporally weighted regression (GTWR) model and a generalized additive model (GAM). RESULTS: The KDE results show that the highest density was from north to south of the central region, gradually spreading to the whole region throughout the study period. Spatiotemporal cluster analysis revealed that clusters were distributed along the Ili and Gongnaisi river basins. The fitted curves of MAT and MARH were an inverted V-shape from February to August, and the fitted curves of MAAP and MAWS showed a U-shaped change and negative correlation from February to May. Among the individual climate factors, MCP coefficient values varied the most while MAWS values varied less from place to place. There was a partial similarity in the spatial distribution of coefficients for MARH and MAT, as evidenced by a significant degree of fit performance in the whole region. MCP showed a significant positive correlation in the range of 15-35 mm, and MAAP showed a positive correlation in the range of 925-945 hPa. HFMD incidence increased with MAT in the range of 15-23 °C, and the effective value of MAWS was in the range of 1.3-1.7 m/s, which was positively correlated with incidences of HFMD. CONCLUSIONS: HFMD incidence and climate factors were found to be spatiotemporally associated, and climate factors are mostly non-linearly associated with HFMD incidence.
Hand, foot, and mouth disease (HFMD) remains a serious health threat to young children. Urumqi is one of the most severely affected cities in northwestern China. This study aims to identify the spatiotemporal distribution characteristics of HFMD, and explore the relationships between driving factors and HFMD in Urumqi, Xinjiang. METHODS: HFMD surveillance data from 2014 to 2018 were obtained from the China Center for Disease Control and Prevention. The center of gravity and geographical detector model were used to analyze the spatiotemporal distribution characteristics of HFMD and identify the association between these characteristics and socioeconomic and meteorological factors. RESULTS: A total of 10,725 HFMD cases were reported in Urumqi during the study period. Spatially, the morbidity number of HFMD differed regionally and the density was higher in urban districts than in rural districts. Overall, the development of HFMD in Urumqi expanded toward the southeast. Temporally, we observed that the risk of HFMD peaked from June to July. Furthermore, socioeconomic and meteorological factors, including population density, road density, GDP, temperature and precipitation were significantly associated with the occurrence of HFMD. CONCLUSIONS: HFMD cases occurred in spatiotemporal clusters. Our findings showed strong associations between HFMD and socioeconomic and meteorological factors. We comprehensively considered the spatiotemporal distribution characteristics and influencing factors of HFMD, and proposed some intervention strategies that may assist in predicting the morbidity number of HFMD.
The study aims to depict the temporal and spatial distributions of hand-foot-and-mouth disease (HFMD) in Xinjiang, China and reveal the relationships between the incidence of HFMD and meteorological factors in Xinjiang. With the national surveillance data of HFMD in Xinjiang and meteorological parameters in the study area from 2008 to 2016, in GeoDetector Model, we examined the effects of meteorological factors on the incidence of HFMD in Xinjiang, China, tested the spatial-temporal heterogeneity of HFMD risk, and explored the temporal-spatial patterns of HFMD through the spatial autocorrelation analysis. From 2008 to 2016, the HFMD distribution showed a distinct seasonal pattern and HFMD cases typically occurred from May to July and peaked in June in Xinjiang. Relative humidity, precipitation, barometric pressure and temperature had the more significant influences on the incidence of HFMD than other meteorological factors with the explanatory power of 0.30, 0.29, 0.29 and 0.21 (P<0.000). The interaction between any two meteorological factors had a nonlinear enhancement effect on the risk of HFMD. The relative risk in Northern Xinjiang was higher than that in Southern Xinjiang. Global spatial autocorrelation analysis results indicated a fluctuating trend over these years: the positive spatial dependency on the incidence of HFMD in 2008, 2010, 2012, 2014 and 2015, the negative spatial autocorrelation in 2009 and a random distribution pattern in 2011, 2013 and 2016. Our findings revealed the correlation between meteorological factors and the incidence of HFMD in Xinjiang. The correlation showed obvious spatiotemporal heterogeneity. The study provides the basis for the government to control HFMD based on meteorological information. The risk of HFMD can be predicted with appropriate meteorological factors for HFMD prevention and control.
Hand, foot and mouth (HFM) disease is a common childhood illness. The paper aims to capture the spatiotemporal characters, and investigate the influence factors of the HFM epidemic in 15 regions of Xinjiang province from 2008 to 2017, China. Descriptive statistical analysis shows that the children aged 0-5 years have a higher HFM incidence, mostly boys. The male-female ratio is 1.5:1. Through the scanning method, we obtain the first cluster high-risk areas. The cluster time is usually from May to August every year. A spatiotemporal model is proposed to analyze the impact of meteorological factors on HFM disease. Comparing with the spatial model, the model is more effective in terms of R2, AIC, deviation, and mean-square error. Among meteorological factors, the number of HFM cases generally increases with the intensity of rainfall. As the temperature increases, there are more HFM patients. Some regions are mostly influenced by wind speed. Further, another spatiotemporal model is introduced to investigate the relationship between HFM disease and socioeconomic factors. The results show that socioeconomic factors have significant influence on the disease. In most areas, the risk of HFM disease tends to rise with the increase of the gross domestic product, the ratios of urban population and tertiary industry. The incidence is closely related to the number of beds and population density in some regions. The higher the ratio of primary school, the lower the number of HFM cases. Based on the above analysis, it is the key measure to prevent and control the spread of the HFM epidemic in high-risk areas, and influence factors should not be ignored.
Previous studies have reported that temperature is the main meteorological factor associated with influenza activity. This study used generalized additive models (GAMs) to explore the relationship between temperature and influenza activity in China. From the national perspective, the average temperature (AT) had an approximately negative linear correlation with the incidence of influenza, as well as a positive rate of influenza H1N1 virus (A/H1N1). Every degree that the monthly AT rose, the influenza cases decreased by 2.49% (95%CI: 1.24%-3.72%). The risk of influenza cases reached a peak at -5.35 °C with RRs of 2.14 (95%CI: 1.38-3.33) and the monthly AT in the range of -5.35 °C to 18.31 °C had significant effects on the incidence of influenza. Every degree that the weekly AT rose, the positive rate of A/H1N1 decreased by 5.28% (95%CI: 0.35%-9.96%). The risk of A/H1N1 reached a peak at -3.14 °C with RRs of 4.88 (95%CI: 1.01-23.75) and the weekly AT in the range of -3.14 °C to 17.25 °C had significant effects on the incidence of influenza. Our study found that AT is negatively associated with influenza activity, especially for A/H1N1. These findings indicate that temperature could be integrated into the current influenza surveillance system to develop early warning systems to better predict and prepare for the risks of influenza.
BACKGROUND: The effects of multiple meteorological factors on influenza activity remain unclear in Chongqing, the largest municipality in China. We aimed to fix this gap in this study. METHODS: Weekly meteorological data and influenza surveillance data in Chongqing were collected from 2012 to 2019. Distributed lag nonlinear models (DLNMs) were conducted to estimate the effects of multiple meteorological factors on influenza activity. RESULTS: Inverted J-shaped nonlinear associations between mean temperature, absolute humidity, wind speed, sunshine and influenza activity were found. The relative risks (RRs) of influenza activity increased as weekly average mean temperature fell below 18.18°C, average absolute humidity fell below 12.66 g/m3, average wind speed fell below 1.55 m/s and average sunshine fell below 2.36 hours. Taking the median values as the references, lower temperature, lower absolute humidity and windless could significantly increase the risks of influenza activity and last for 4 weeks. A J-shaped nonlinear association was observed between relative humidity and influenza activity; the risk of influenza activity increased with rising relative humidity with 78.26% as the break point. Taking the median value as the reference, high relative humidity could increase the risk of influenza activity and last for 3 weeks. In addition, we found the relationship between aggregate rainfall and influenza activity could be described with a U-shaped curve. Rainfall effect has significantly higher RR than rainless effect. CONCLUSIONS: Our study shows that multiple meteorological factors have strong associations with influenza activity in Chongqing, providing evidence for developing a meteorology-based early warning system for influenza to facilitate timely response to upsurge of influenza activity.
BACKGROUND: Influenza is a seasonal infectious disease, and meteorological parameters critically influence the incidence of influenza. However, the meteorological parameters linked to influenza occurrence in semi-arid areas are not studied in detail. This study aimed to clarify the impact of meteorological parameters on influenza incidence during 2010-2019 in Lanzhou. The results are expected to facilitate the optimization of influenza-related public health policies by the local healthcare departments. METHODS: Descriptive data related to influenza incidence and meteorology during 2010-2019 in Lanzhou were analyzed. The exposure-response relationship between the risk of influenza occurrence and meteorological parameters was explored according to the distributed lag no-linear model (DLNM) with Poisson distribution. The response surface model and stratified model were used to estimate the interactive effect between relative humidity (RH) and other meteorological parameters on influenza incidence. RESULTS: A total of 6701 cases of influenza were reported during 2010-2019. DLNM results showed that the risk of influenza would gradually increase as the weekly mean average ambient temperature (AT), RH, and absolute humidity (AH) decrease at lag 3 weeks when they were lower than 12.16°C, 51.38%, and 5.24 g/m(3), respectively. The low Tem (at 5th percentile, P(5)) had the greatest effect on influenza incidence; the greatest estimated relative risk (RR) was 4.54 (95%CI: 3.19-6.46) at cumulative lag 2 weeks. The largest estimates of RRs for low RH (P(5)) and AH (P(5)) were 4.81 (95%CI: 3.82-6.05) and 4.17 (95%CI: 3.30-5.28) at cumulative lag 3 weeks, respectively. An increase in AT by 1°C led to an estimates of percent change (95%CI) of 3.12% (-4.75% to -1.46%) decrease in the weekly influenza case counts in a low RH environment. In addition, RH showed significant interaction with AT and AP on influenza incidence but not with wind speed. CONCLUSION: This study indicated that low AT, low humidity (RH and AH), and high air pressure (AP) increased the risk of influenza. Moreover, the interactive effect of low RH with low AT and high AP can aggravate the incidence of influenza.
Under the variant climate conditions in the transitional regions between tropics and subtropics, the impacts of climate factors on influenza subtypes have rarely been evaluated. With the available influenza A (Flu-A) and influenza B (Flu-B) outbreak data in Shenzhen, China, which is an excellent example of a transitional marine climate, the associations of multiple climate variables with these outbreaks were explored in this study. Daily laboratory-confirmed influenza virus and climate data were collected from 2009 to 2015. Potential impacts of daily mean/maximum/minimum temperatures (T/T(max)/T(min)), relative humidity (RH), wind velocity (V), and diurnal temperature range (DTR) were analyzed using the distributed lag nonlinear model (DLNM) and generalized additive model (GAM). Under its local climate partitions, Flu-A mainly prevailed in summer months (May to June), and a second peak appeared in early winter (December to January). Flu-B outbreaks usually occurred in transitional seasons, especially in autumn. Although low temperature caused an instant increase in both Flu-A and Flu-B risks, its effect could persist for up to 10 days for Flu-B and peak at 17 C (relative risk (RR) = 14.16, 95% CI: 7.46-26.88). For both subtypes, moderate-high temperature (28 C) had a significant but delayed effect on influenza, especially for Flu-A (RR = 26.20, 95% CI: 13.22-51.20). The Flu-A virus was sensitive to RH higher than 76%, while higher Flu-B risks were observed at both low (< 65%) and high (> 83%) humidity. Flu-A was active for a short term after exposure to large DTR (e.g., DTR = 10 C, RR = 12.45, 95% CI: 6.50-23.87), whereas Flu-B mainly circulated under stable temperatures. Although the overall wind speed in Shenzhen was low, moderate wind (2-3 m/s) was found to favor the outbreaks of both subtypes. This study revealed the thresholds of various climatic variables promoting influenza outbreaks, as well as the distinctions between the flu subtypes. These data can be helpful in predicting seasonal influenza outbreaks and minimizing the impacts, based on integrated forecast systems coupled with short-term climate models.
BACKGROUND: Influenza epidemics occur during winter in temperate zones, but have less regular seasonality in the subtropics and tropics. Here we quantified the role of environmental drivers of influenza seasonality in temperate and subtropical China. METHODS: We used weekly surveillance data on influenza virus activity in mainland China and Hong Kong from 2005 through 2016. We estimated the transmissibility via the instantaneous reproduction number (R(t)), a real-time measure of transmissibility, and examined its relationship with different climactic drivers and allowed for the timing of school holidays and the decline in susceptibility in the population as an epidemic progressed. We developed a multivariable regression model for R(t) to quantify the contribution of various potential environmental drivers of transmission. FINDINGS: We found that absolute humidity is a potential driver of influenza seasonality and had a U-shaped association with transmissibility and hence can predict the pattern of influenza virus transmission across different climate zones. Absolute humidity was able to explain up to 15% of the variance in R(t), and was a stronger predictor of R(t) across the latitudes. Other climatic drivers including mean daily temperature explained up to 13% of variance in R(t) and limited to the locations where the indoor measures of these factors have better indicators of outdoor measures. The non-climatic driver, holiday-related school closures could explain up to 7% of variance in R(t). INTERPRETATION: A U-shaped association of absolute humidity with influenza transmissibility was able to predict seasonal patterns of influenza virus epidemics in temperate and subtropical locations.
OBJECTIVES: From 2013 to 2017, the avian influenza A (H7N9) virus frequently infected people in China, which seriously affected the public health of society. This study aimed to analyze the spatial characteristics of human infection with the H7N9 virus in China and assess the risk areas of the epidemic. METHODS: Using kernel density estimation, standard deviation ellipse analysis, spatial and temporal scanning cluster analysis, and Pearson correlation analysis, the spatial characteristics and possible risk factors of the epidemic were studied. Meteorological factors, time (month), and environmental factors were combined to establish an epidemic risk assessment proxy model to assess the risk range of an epidemic. RESULTS: The epidemic situation was significantly correlated with atmospheric pressure, temperature, and daily precipitation (P < 0.05), and there were six temporal and spatial clusters. The fitting accuracy of the epidemic risk assessment agent-based model for lower-risk, low-risk, medium-risk, and high-risk was 0.795, 0.672, 0.853, 0.825, respectively. CONCLUSIONS: This H7N9 epidemic was found to have more outbreaks in winter and spring. It gradually spread to the inland areas of China. This model reflects the risk areas of human infection with the H7N9 virus.
(1) Background: To explore whether meteorological factors have an impact on the prevalence of mumps, and to make a short−term prediction of the case number of mumps in Chongqing. (2) Methods: K−means clustering algorithm was used to divide the monthly mumps cases of each year into the high and low case number clusters, and Student t−test was applied for difference analysis. The cross−correlation function (CCF) was used to evaluate the correlation between the meteorological factors and mumps, and an ARIMAX model was constructed by additionally incorporating meteorological factors as exogenous variables in the ARIMA model, and a short−term prediction was conducted for mumps in Chongqing, evaluated by MAE, RMSE. (3) Results: All the meteorological factors were significantly different (p < 0.05), except for the relative humidity between the high and low case number clusters. The CCF and ARIMAX model showed that monthly precipitation, temperature, relative humidity and wind velocity were associated with mumps, and there were significant lag effects. The ARIMAX model could accurately predict mumps in the short term, and the prediction errors (MAE, RMSE) were lower than those of the ARIMA model. (4) Conclusions: Meteorological factors can affect the occurrence of mumps, and the ARIMAX model can effectively predict the incidence trend of mumps in Chongqing, which can provide an early warning for relevant departments.
BACKGROUND: Small-scale studies have identified temperature and other meteorological factors as risk factors for human health. However, only a few have quantified the specific impact of meteorological factors on mumps. A quantitative examination of the exposure-response relationship between meteorological factors and mumps is needed to provide new insights for multi-city analysis. METHODS: The daily recorded number of mumps cases and meteorological data in 17 cities of Shandong Province from 2009 to 2017 were collected. A two-stage model was built to explore the relationship between meteorological factors and mumps. RESULTS: A total of 104,685 cases of mumps were recorded from 2009 to 2017. After controlling for seasonality and long-term trends, the effect of low temperature on mumps was significant at the provincial level, with a cumulative RR of 1.035 (95%CI: 1.002-1.069) with a 1-day lagged effect. The proportion of primary and middle school students was determined as an effect modifier, which had a significant impact on mumps (Stat = 8.374, p = 0.039). There was heterogeneity in the combined effect of temperature on mumps (Q = 95.447, p = 0.000), and its size was I(2) = 49.7%. CONCLUSIONS: We have identified a non-linear relationship between mumps and temperature in Shandong Province. In particular, low temperatures could bring more cases of mumps, with certain lagged effects. More public health measures should be taken to reduce the risks when temperatures are low, especially for cities with a high proportion of primary and secondary school students.
Varicella (chickenpox) is a serious public health problem in China, with the most reported cases among childhood vaccine-preventable infectious diseases, and its reported incidence has increased over 20-fold since 2005. Few previous studies have explored the association of multiple meteorological factors with varicella and considered the potential confounding effects of air pollutants. It is the first study to investigate and analyze the effects of multiple meteorological factors on varicella incidence, controlling for the confounding effects of various air pollutants. Daily meteorological and air pollution data and varicella cases were collected from January 1, 2015, to December 31, 2020, in Lu’an, Eastern China. A combination of the quasi-Poisson generalized additive model (GAM) and distributed lag nonlinear model (DLNM) was used to evaluate the meteorological factor-lag-varicella relationship, and the risk of varicella in extreme meteorological conditions. The maximum single-day lag effects of varicella were 1.288 (95%CI, 1.201-1.381, lag 16 day), 1.475 (95%CI, 1.152-1.889, lag 0 day), 1.307 (95%CI, 1.196-1.427, lag 16 day), 1.271 (95%CI, 0.981-1.647, lag 4 day), and 1.266 (95%CI, 1.162-1.378, lag 21 day), when mean temperature, diurnal temperature range (DTR), mean air pressure, wind speed, and sunshine hours were -5.8°C, 13.5°C, 1035.5 hPa, 6 m/s, and 0 h, respectively. At the maximum lag period, the overall effects of mean temperature and pressure on varicella showed W-shaped curves, peaked at 17.5°C (RR=2.085, 95%CI: 1.480-2.937) and 1035.5 hPa (RR=5.481, 95%CI: 1.813-16.577), while DTR showed an M-shaped curve and peaked at 4.4°C (RR=6.131, 95%CI: 1.120-33.570). Sunshine hours were positively correlated with varicella cases at the lag of 0-8 days and 0-9 days when sunshine duration exceeded 10 h. Furthermore, the lag effects of extreme meteorological factors on varicella cases were statistically significant, except for the extremely high wind speed. We found that mean temperature, mean air pressure, DTR, and sunshine hours had significant nonlinear effects on varicella incidence, which may be important predictors of varicella early warning.
OBJECTIVE: To analyze the spatiotemporal dynamic distribution and detect the related meteorological factors of scarlet fever from an ecological perspective, which could provide scientific information for effective prevention and control of this disease. METHODS: The data on scarlet fever cases in mainland China were downloaded from the Data Center of the China Public Health Science, while monthly meteorological data were extracted from the official website of the National Bureau of Statistics. Global Moran’s I, local Getis-Ord G(i)(⁎) hotspot statistics, and Kulldorff’s retrospective space-time scan statistical analysis were used to detect the spatial and spatiotemporal clusters of scarlet fever across all settings. A spatial panel data model was conducted to estimate the impact of meteorological factors on scarlet fever incidence. RESULTS: Scarlet fever in China had obvious spatial, temporal, and spatiotemporal clustering, high-incidence spatial clusters were located mainly in the north and northeast of China. Nine spatiotemporal clusters were identified. A spatial lag fixed effects panel data model was the best fit for regression analysis. After adjusting for spatial individual effects and spatial autocorrelation (ρ = 0.5623), scarlet fever incidence was positively associated with a one-month lag of average temperature, precipitation, and total sunshine hours (all P-values < 0.05). Each 10 °C, 2 cm, and 10 h increase in temperature, precipitation, and sunshine hours, respectively, was associated with a 6.41% increment and 1.04% and 1.41% decrement in scarlet fever incidence, respectively. CONCLUSION: The incidence of scarlet fever in China showed an upward trend in recent years. It had obvious spatiotemporal clustering, with the high-risk areas mainly concentrated in the north and northeast of China. Areas with high temperature and with low precipitation and sunshine hours tended to have a higher scarlet fever incidence, and we should pay more attention to prevention and control in these places.
The relationship between air temperature and the hospital admission of adult patients with community-acquired pneumonia (CAP) was analyzed. The hospitalization data pertaining to adult CAP patients (age ≥ 18 years) in two tertiary comprehensive hospitals in Baotou, Inner Mongolia Autonomous Region, China from 2014 to 2018 and meteorological data there in the corresponding period were collected. The exposure-response relationship between the daily average temperature and the hospital admission of adult CAP patients was quantified by using a distributed lag non-linear model. A total of 4466 cases of adult patients with CAP were admitted. After eliminating some confounding factors such as relative humidity, wind speed, air pressure, long-term trend, and seasonal trend, a lower temperature was found to be associated with a higher risk of adult CAP. Compared to 21 °C, lower temperature range of 4 to -12 °C was associated with a greater number of CAP hospitalizations among those aged ≥ 65 years, and the highest relative risk (RR) was 2.80 (95% CI 1.15-6.80) at a temperature of - 10 °C. For those < 65 years, lower temperature was not related to CAP hospitalizations. Cumulative lag RRs of low temperature with CAP hospitalizations indicate that the risk associated with colder temperatures appeared at a lag of 0-7 days. For those ≥ 65 years, the cumulative RR of CAP hospitalizations over lagging days 0-5 was 1.89 (95% CI 1.01-3. 56). In brief, the lower temperature had age-specific effects on CAP hospitalizations in Baotou, China, especially among those aged ≥ 65 years.
BACKGROUND: Most existing studies have only investigated the delayed effect of meteorological factors on pulmonary tuberculosis (PTB). However, the effect of extreme climate and the interaction between meteorological factors on PTB has been rarely investigated. METHODS: Newly diagonsed PTB cases and meteorological factors in Urumqi in each week between 2013 and 2019 were collected. The lag-exposure-response relationship between meteorological factors and PTB was analyzed using the distributed lag non-linear model (DLNM). The generalized additive model (GAM) was used to visualize the interaction between meteorological factors. Stratified analysis was used to explore the impact of meteorological factors on PTB in different stratification and RERI, AP and SI were used to quantitatively evaluate the interaction between meteorological factors. RESULTS: A total of 16,793 newly diagnosed PTB cases were documented in Urumqi, China from 2013 to 2019. The median (interquartile range) temperature, relative humidity, wind speed, and PTB cases were measured as 11.3°C (-5.0-20.5), 57.7% (50.7-64.2), 4.1m/s (3.4-4.7), and 47 (37-56), respectively. The effects of temperature, relative humidity and wind speed on PTB were non-linear, which were found with the “N”-shaped, “L”-shaped, “N”-shaped distribution, respectively. With the median meteorological factor as a reference, extreme low temperature was found to have a protective effect on PTB. However, extreme high temperature, extreme high relative humidity, and extreme high wind speed were found to increase the risk of PTB and peaked at 31.8°C, 83.2%, and 7.6 m/s respectively. According to the existing monitoring data, no obvious interaction between meteorological factors was found, but low temperature and low humidity (RR = 1.149, 95%CI: 1.003-1.315), low temperature and low wind speed (RR = 1.273, 95%CI: 1.146-1.415) were more likely to cause the high incidence of PTB. CONCLUSION: Temperature, relative humidity and wind speed were found to play vital roles in PTB incidence with delayed and non-linear effects. Extreme high temperature, extreme high relative humidity, and extreme high wind speed could increase the risk of PTB. Moreover, low temperature and low humidity, low temperature and low wind speed may increase the incidence of PTB.
In the present paper, an association between the growth rate of PTB and the environmental impacting elements in the pearl river delta region and the closed industry related cities in China is studied. We summarized the characteristics of different industry characteristics in this region by three echelons of urban agglomerations conducted by K-means clustering model on the time series of their monthly AQI data. To determine the impact of environmental factors on the increase of PTB, the SMLR in GLM has been applied. We then measured the seasonal effect and suggest the spring to be the leading season which keep the highest possibility of the incidence of PTB. Besides giving the analysis by fixed meteorological factors, we presented a sensitive analysis with a variation of precipitation. The Genetic algorithms (GAs) is used to determine the “tolerant” interval and as the results, the width of “tolerant” almost keep a declining trend as the precipitation increasing except when the precipitation comes the interval [68,74]. In addition, with the precipitation increasing higher than 64 mm, the “tolerant” for the AQI values from the first and the second echelon both trend to decline, and a lenient environmental policy currently may easily cause a rapid development of PTB growth rate.
BACKGROUND: Most studies on associations between meteorological factors and tuberculosis (TB) were conducted in a single city, used different lag times, or merely explored the qualitative associations between meteorological factors and TB. Thus, we performed a multicenter study to quantitatively evaluate the effects of meteorological factors on the risk of pulmonary tuberculosis (PTB). METHODS: We collected data on newly diagnosed PTB cases in 13 study sites in Jiangsu Province between January 1, 2014, and December 31, 2019. Data on meteorological factors, air pollutants, and socioeconomic factors at these sites during the same period were also collected. We applied the generalized additive mixed model to estimate the associations between meteorological factors and PTB. RESULTS: There were 20,472 newly diagnosed PTB cases reported in the 13 study sites between 2014 and 2019. The median (interquartile range) weekly average temperature, weekly average wind speed, and weekly average relative humidity of these sites were 17.3 °C (8.0-24.1), 2.2 m/s (1.8-2.7), and 75.1% (67.1-82.0), respectively. In the single-meteorological-factor models, for a unit increase in weekly average temperature, weekly average wind speed, and weekly average relative humidity, the risk of PTB decreased by 0.9% [lag 0-13 weeks, 95% confidence interval (CI): -1.5, -0.4], increased by 56.2% (lag 0-16 weeks, 95% CI: 32.6, 84.0) when average wind speed was <3 m/s, and decreased by 28.1% (lag 0-14 weeks, 95% CI: -39.2, -14.9) when average relative humidity was ≥72%, respectively. Moreover, the associations remained significant in the multi-meteorological-factor models. CONCLUSIONS: Average temperature and average relative humidity (≥72%) are negatively associated with the risk of PTB. In contrast, average wind speed (<3 m/s) is positively related to the risk of PTB, suggesting that an environment with low temperature, relatively high wind speed, and low relative humidity is conducive to the transmission of PTB.
The autoregressive integrated moving average with exogenous regressors (ARIMAX) modeling studies of pulmonary tuberculosis (PTB) are still rare. This study aims to explore whether incorporating air pollution and meteorological factors can improve the performance of a time series model in predicting PTB. We collected the monthly incidence of PTB, records of six air pollutants and six meteorological factors in Ningbo of China from January 2015 to December 2019. Then, we constructed the ARIMA, univariate ARIMAX, and multivariate ARIMAX models. The ARIMAX model incorporated ambient factors, while the ARIMA model did not. After prewhitening, the cross-correlation analysis showed that PTB incidence was related to air pollution and meteorological factors with a lag effect. Air pollution and meteorological factors also had a correlation. We found that the multivariate ARIMAX model incorporating both the ozone with 0-month lag and the atmospheric pressure with 11-month lag had the best performance for predicting the incidence of PTB in 2019, with the lowest fitted mean absolute percentage error (MAPE) of 2.9097% and test MAPE of 9.2643%. However, ARIMAX has limited improvement in prediction accuracy compared with the ARIMA model. Our study also suggests the role of protecting the environment and reducing pollutants in controlling PTB and other infectious diseases.
Few studies have examined the effects of inbound overseas travelers and meteorological conditions on the shift in human respiratory syncytial virus (HRSV) season in Japan. This study aims to test whether the number of inbound overseas travelers and meteorological conditions are associated with the onset week of HRSV epidemic season. The estimation of onset week for 46 prefectures (except for Okinawa prefecture) in Japan for 4-year period (2014-2017) was obtained from previous papers based on the national surveillance data. We obtained data on the yearly number of inbound overseas travelers and meteorological (yearly mean temperature and relative humidity) conditions from Japan National Tourism Organization (JNTO) and Japan Meteorological Agency (JMA), respectively. Multi-level mixed-effects linear regression analysis showed that every 1 person (per 100,000 population) increase in number of overall inbound overseas travelers led to an earlier onset week of HRSV epidemic season in the year by 0.02 week (coefficient -0.02; P<0.01). Higher mean temperature and higher relative humidity were also found to contribute to an earlier onset week by 0.30 week (coefficient -0.30; P<0.05) and 0.18 week (coefficient -0.18; P<0.01), respectively. Additionally, models that included the number of travelers from individual countries (Taiwan, South Korea, and China) except Australia showed that both the number of travelers from each country and meteorological conditions contributed to an earlier onset week. Our analysis showed the earlier onset week of HRSV epidemic season in Japan is associated with increased number of inbound overseas travelers, higher mean temperature, and relative humidity. The impact of international travelers on seasonality of HRSV can be further extended to investigations on the changes of various respiratory infectious diseases especially after the coronavirus disease 2019 (COVID-19) pandemic.
Extreme heat and poor air quality arising from landscape fires are an increasing global concern driven by anthropogenic climate change. Previous studies have shown these environmental conditions are associated with negative health outcomes for vulnerable people. Managing and adapting to these conditions in a warming climate can present substantial difficulties, especially in climates already challenging for human habitation. This study was set in the tropical city of Darwin, Australia. We recruited individuals from population groups vulnerable to outdoor hazards: outdoor workers, teachers and carers, and sportspeople, to participate in focus group discussions. We aimed to gain an understanding of the impacts of extreme heat and poor air quality and how individuals perceived and managed these environmental conditions. We identified a number of key themes relating to impacts on health, work and activity, and adaptive behaviors, while identifying gaps in policy and infrastructure that could improve the lives and protect the health of vulnerable people living, working, and playing in this region. In addition, these outcomes potentially provide direction for other regions with similar environmental challenges. Extreme heat and poor air quality place an additional burden on the lives of people in high-risk settings, such as outdoor workers, teachers and carers, and sportspeople.
Dust storms have already become the most serious environmental problem on the south edge of the Taklimakan desert because of their frequent occurrences. To investigate the health effects of dust storms on public health in Moyu County, one of the most severe dust-storm-affected areas located at the south edge of the Taklimakan desert, China, primary data were collected from 1200 respondents by using a questionnaire survey for 15 health symptoms. The data were analyzed by comparing the mean tool (independent t-test and ANOVA) and the severity of different symptoms among different age groups. Principal component analysis (PCA) was applied to further analyze the multivariate relationships between meteorological factors, dust storm intensity, air pollution level, and severity degree of the different symptoms. The results show that significant correlations exist between dust storm intensity, air pollutants (PM(2.5), PM(10), O(3), SO(2), NO(2), and CO), meteorological factors, and health symptoms. During dusty weather, no matter the age group, the number of respondents who suffered from different health symptoms was higher compared to non-dusty days. Three types of dusty days were considered in this study: suspended dust, blowing dust, and sand storms. The impacts of sand storm weather on public health are stronger than those from blowing dust weather, suspended dust weather (haze), and non-dust weather. The people in the age groups above 60 years and below 15 years were more sensitive to different dust weather than people in the age groups between 15 and 60. “Dry throat with bitter taste”, “Depression”, “Dry and itchy throat”, and “Mouth ulcer” are the main symptoms caused by dust storms.
Dust storms are an important component of the global climate system. At the same time, they also bear a risk for human health by causing pulmonary diseases. Today, East Asian dust storms account for as much as half of the global dust emissions and temporarily affect highly populated areas. Therefore, under-standing their mechanisms and predicting their evolution under warmer near-future climate conditions is of major interest. The mid-Pliocene Warm Period (mPWP; 3.264-3.025 Ma) is considered one of the best analogues from the past for anthropogenic climate change. Consequently, understanding the climate dynamics and associated environmental change during the mPWP can help with predicting the envi-ronmental effects of warmer-than-present climates. In order to reconstruct Asian dust storm evolution during the mPWP we have analyzed a sediment core from the northern South China Sea (SCS) for its elemental composition, grain-size variations and radiogenic isotope signature for the interval spanning from 3.69 to 2.96 Ma. We show that shortly after the first strong northern hemisphere glaciation (Marine Isotope Stage [MIS] M2; 3.25 Ma) atmospherically transported dust appeared in the northern SCS and this dust deposition prevailed throughout the mPWP. Atmospheric dust input further intensified with the onset of the MIS KM2 glaciation at 3.15 Ma, with distinct and strong dust storms occurring periodically from that time onwards. The increase in atmospherically transported dust can be attributed to the cooling and drying of interior Asia over the course of the mPWP along with an intensification of the East Asian Winter Monsoon and a potential southward shift of the westerlies.(c) 2022 Elsevier Ltd. All rights reserved.
PURPOSE: Previous studies found that silicosis was majorly associated with occupation-related risks. However, little evidence was available to clarify the relation between Asian dust storm (ADS) and silicosis hospital admissions. This present paper aims to investigate the association between ADS events and hospital admissions for silicosis. METHODS: We applied a Poisson time-series regression on the 2000-2012 National Health Insurance Research Database in Taiwan, linking air quality data and ambient temperature data to estimate the impact of ADS on silicosis hospital admissions in the age-specific groups. RESULTS: A total of 2154 hospital admissions were recorded for silicosis in Taiwan, for a daily average number of 0.45. The number rises from 0.43 on a day without ADS to 0.70 on the outbreak day and continues increasing to 0.83 one day after outbreak. Among patients under 45, the effect of ADS appears on the event day as well as several post-event days (lag2-6) at the significant level of p < 0.1. There is also a significant lag effect on post-event day 2 (p < 0.05) for those aged above 74. CONCLUSION: Asian dust storms do result in a rise of silicosis hospital admissions, particularly for those above 74, those under 45, and for females.
Although dust storms have been associated with adverse health outcomes, studies on the burden of dust storms on deaths are limited. As global warming has induced significant climate changes in recent decades, which have accelerated desertification worldwide, it is necessary to evaluate the burden of dust storm-induced premature mortality using a critical measure of disease burden, such as the years of life lost (YLL). The YLL attributable to dust storms have not been examined to date. This study investigated the association between Asian dust storms (ADS) and the YLL in Seoul, South Korea, during 2002-2013. We conducted a time-series study using a generalized additive model assuming a Gaussian distribution and applied a distributed lag model with a maximum lag of 5 days to investigate the delayed and cumulative effects of ADS on the YLL. We also conducted stratified analyses using the cause of death (respiratory and cardiovascular diseases) and sociodemographic status (sex, age, education level, occupation, and marital status). During the study period, 108 ADS events occurred, and the average daily YLL was 1511 years due to non-accidental causes. The cumulative ADS exposure over the 6-day lag period was associated with a significant increase of 104.7 (95% CI, 31.0-178.5 years) and 34.4 years (4.0-64.7 years) in the YLL due to non-accidental causes and cardiovascular mortality, respectively. Sociodemographic analyses revealed associations between ADS exposure and the YLL in males, both <65 and ≥65 years old, those with middle-level education, and the unemployed, unmarried, and widowed (26.5-83.8 years). This study provides new evidence suggesting that exposure to dust storms significantly increases the YLL. Our findings suggest that dust storms are a critical environmental risk affecting premature mortality. These results could contribute to the establishment of public health policies aimed at managing dust storm exposure and reducing premature deaths.
Ultra-fine dust refers to particulate matter from external sources, and modernization contributes toward increasing the presence of ultra-fine dust. Young children are particularly vulnerable to the ill effects of ultra-fine dust. Educational buildings, where young children spend the longest duration after their houses, are typically difficult to retrofit. Consequently, they are often used for a long time in the same state as they were when first completed. The buildings deteriorate due to long-term use, particularly because the openings are opened and closed frequently by occupants. Hence, architectural retrofits were performed during vacation, and the effects were evaluated. The evaluation factors include the temperature, relative humidity, and presence of ultra-fine dust. It was confirmed that the temperature and humidity inside the room decreased after the retrofit, while the airtightness performance was strengthened, thereby reducing the I/O ratio. To evaluate the sustainability of architectural remodeling with regard to not only the indoor air environment but also the enhancement of airtightness and insulation performance through the retrofit, a representative scenario was selected with reference to the Intergovernmental Panel on Climate Change’s Future Climate Report. Although it was found that improving both the main entrance and the outdoor window was appropriate, replacing only the outdoor window was the adjudged the optimal retrofit scenario in consideration of the recovery of the investment cost.
Biomass burning and dust storm have significant impacts on air pollution, aerosol properties and potential human health. In order to investigate the influences of them on the chemical component and sources of aerosols, PM2.5 are collected in spring and summer in Beijing. There are two special periods in the whole campaign. (1) Event I, from 16 to 18 April. Air quality is extremely poor during this period mainly affected by biomass burning. (2) Event II, from 4 to 5 May, the biggest dust storm happened on 4 May. In addition, we choose a relative clean period as (3) Event III, from 24 to 29 July, with the lowest PM2.5 levels (16-31 mu g m(-3)) in the whole campaign. Contributions of NO3, SO42-, and NH4+ to PM2.5 in Event I are 22.1%, 11.3%, and 8.3%, respectively, and decreased dramatically to 2.4%, 5.4%, and 0.9% in Event II, suggesting secondary aerosols are more significant in haze period. Both ratios of phytane & pristane and PAHs to OC in Event I and II are comparable, indicating contribution of local primary organic aerosols from fossil fuel combustions to PM2.5 are not significant differences between polluted and dust period. In contrast, ratio of levoglucosan to OC is much higher in Event I and ratio of trehalose to OC is much higher in Event II, suggesting the contribution of regional primary organic aerosols from biomass burning to PM2.5 is important during polluted period, while contribution of regional primary organic aerosols from dust to PM2.5 is significant in dust storm. Based on the organic markers, this work also estimates the source apportionment of PM2.5. Dust and biomass burning are the main contributors in polluted period, while vehicle and cooking are the main contributors in clean period.
PURPOSE: The characteristic topography and climate often affect the occurrence of large-scale wildfires in the Eastern Gangwon-do region of Korea. However, there are no studies on the health effects of these wildfires in Korea. This study aimed to analyze the differences in medical use between a wildfire-affected area and an adjacent non-affected area before and after a wildfire in 2019 in Gangwon-do, Korea. MATERIALS AND METHODS: We used medical usage data from the Korean National Health Insurance Corporation. Rates of medical use were determined for citizens of a wildfire-affected area in the Eastern Yeongdong region and a non-affected area in the Western Yeongseo region. Logistic regression analysis was performed considering an increase in medical use per individual as a dependent variable; age, sex, income, smoking, drinking, and exercise were included as confounding variables. RESULTS: The odds ratio for medical use in Yeongdong region increased significantly after 3 days, 3 months, and 1 year after a fire occurred, compared with Yeongseo region. CONCLUSION: The results of this study confirmed that the use of medical care increased for residents of a wildfire-affected area, compared with those of an adjacent non-affected area. This is the first study on the relationship between wildfires and inpatient medical use in Korea.
We investigated the association between climate variables and pulmonary tuberculosis (PTB) incidence in Brunei-Muara district, Brunei Darussalam. Weekly PTB case counts and climate variables from January 2001 to December 2018 were analysed using distributed lag non-linear model framework. After adjusting for long-term trend and seasonality, we observed positive but delayed relationship between PTB incidence and minimum temperature, with significant adjusted relative risk (adj.RR) at 25.1 °C (95th percentile) when compared to the median, from lag 30 onwards (adj.RR = 1.17 [95% Confidence Interval (95% CI): 1.01, 1.36]), suggesting effect of minimum temperature on PTB incidence after 30 weeks. Similar results were observed from a sub-analysis on smear-positive PTB case counts from lag 29 onwards (adj.RR = 1.21 [95% CI: 1.01, 1.45]), along with positive and delayed association with total rainfall at 160.7 mm (95th percentile) when compared to the median, from lag 42 onwards (adj.RR = 1.23 [95% CI: 1.01, 1.49]). Our findings reveal evidence of delayed effects of climate on PTB incidence in Brunei, but with varying degrees of magnitude, direction and timing. Though explainable by environmental and social factors, further studies on the relative contribution of recent (through primary human-to-human transmission) and remote (through reactivation of latent TB) TB infection in equatorial settings is warranted.
OBJECTIVES: The aim of this study was to explore whether indoor or outdoor relative humidity (RH) modulates the influenza epidemic transmission in temperate and subtropical climates. METHODS: In this study, the daily temperature and RH in 1558 households from March 2017 to January 2019 in five cities across both temperate and subtropical regions in China were collected. City-level outdoor temperature and RH from 2013 to 2019 were collected from the weather stations. We first estimated the effective reproduction number (R(t)) of influenza and then used time-series analyses to explore the relationship between indoor/outdoor RH/absolute humidity and the R(t) of influenza. Furthermore, we expanded the measured 1-year indoor temperature and the RH data into 5 years and used the same method to examine the relationship between indoor/outdoor RH and the R(t) of influenza. RESULTS: Indoor RH displayed a seasonal pattern, with highs during the summer months and lows during the winter months, whereas outdoor RH fluctuated with no consistent pattern in subtropical regions. The R(t) of influenza followed a U-shaped relationship with indoor RH in both temperate and subtropical regions, whereas a U-shaped relationship was not observed between outdoor RH and R(t). In addition, indoor RH may be a better indicator for R(t) of influenza than indoor absolute humidity. CONCLUSION: The findings indicated that indoor RH may be the driver of influenza seasonality in both temperate and subtropical locations in China.
The early identification and prediction of hand-foot-and-mouth disease (HFMD) play an important role in the disease prevention and control. However, suitable models are different in regions due to the differences in geography, social economy factors. We collected data associated with daily reported HFMD cases and weather factors of Zibo city in 2010 similar to 2019 and used the generalised additive model (GAM) to evaluate the effects of weather factors on HFMD cases. Then, GAM, support vectors regression (SVR) and random forest regression (RFR) models are used to compare predictive results. The annual average incidence was 129.72/100 000 from 2010 to 2019. Its distribution showed a unimodal trend, with incidence increasing from March, peaking from May to September. Our study revealed the nonlinear relationship between temperature, rainfall and relative humidity and HFMD cases and based on the predictive result, the performances of three models constructed ranked in descending order are: SVR > GAM > RFR, and SVR has the smallest prediction errors. These findings provide quantitative evidence for the prediction of HFMD for special high-risk regions and can help public health agencies implement prevention and control measures in advance.
OBJECTIVES: Hand, foot, and mouth disease (HFMD) is a viral infectious disease that poses a substantial threat in the Asia-Pacific region. It is widely reported that meteorological factors are associated with HFMD. However, the relationships between air pollutants and HFMD are still controversial. In addition, the interactive effects between meteorological factors and air pollutants on HFMD remain unknown. To fill this research gap, we conducted a time-series study. DESIGN: A time-series study. SETTING AND PARTICIPANTS: Daily cases of HFMD as well as meteorological and air pollution data were collected in Chengdu from 2011 to 2017. A total of 184 610 HFMD cases under the age of 15 were included in our study. OUTCOME MEASURES: Distributed lag nonlinear models were used to investigate the relationships between HFMD and environmental factors, including mean temperature, relative humidity, SO(2), NO(2), and PM(10). Then, the relative excess risk due to interaction (RERI) and the proportion attributable to interaction were calculated to quantitatively evaluate the interactions between meteorological factors and air pollutants on HFMD. Bivariate response surface models were used to visually display the interactive effects. RESULTS: The cumulative exposure-response curves of SO(2) and NO(2) were inverted ‘V’-shaped and ‘M’-shaped, respectively, and the risk of HFMD gradually decreased with increasing PM(10) concentrations. We found that there were synergistic interactions between mean temperature and SO(2), relative humidity and SO(2), as well as relative humidity and PM(10) on HFMD, with individual RERIs of 0.334 (95% CI 0.119 to 0.548), 0.428 (95% CI 0.214 to 0.642) and 0.501 (95% CI 0.262 to 0.741), respectively, indicating that the effects of SO(2) and PM(10) on HFMD were stronger under high temperature (>17.3°C) or high humidity (>80.0%) conditions. CONCLUSIONS: There were interactive effects between meteorological factors and air pollutants on HFMD. Our findings could provide guidance for targeted and timely preventive and control measures for HFMD.
Despite a conspicuous exacerbation of asthma among patients hospitalized due to influenza infection, no study has attempted previously to elucidate the relationship between environmental factors, influenza activity, and asthma simultaneously in adults. In this study, we examined this relationship using population-based hospitalization records over 22 years. Daily numbers of hospitalizations due to asthma in adults of 41 public hospitals in Hong Kong during 1998-2019 were obtained. The data were matched with meteorological records and air pollutant concentrations. We used type-specific and all-type influenza-like illness plus (ILI+) rates as proxies for seasonal influenza activity. Quasi-Poisson generalized additive models together with distributed-lag non-linear models were used to examine the association. A total of 212,075 hospitalization episodes due to asthma were reported over 22 years. The cumulative adjusted relative risk (ARR) of asthma hospitalizations reached 1.15 (95 % confidence interval [CI], 1.12-1.18) when the ILI+ total rate increased from zero to 20.01 per 1000 consultations. Compared with the median temperature, a significantly increased risk of asthma hospitalization (cumulative ARR = 1.10, 95 % CI, 1.05-1.15) was observed at the 5(th) percentile of temperature (i.e., 14.6 °C). Of the air pollutants, oxidant gas was significantly associated with asthma, but only at its extreme level of concentrations. In conclusion, cold conditions and influenza activities are risk factors to asthma exacerbation in adult population. Influenza-related asthma exacerbation that appeared to be more common in the warm and hot season, is likely to be attributable to influenza A/H3N2. The heavy influence of both determinants on asthma activity implies that climate change may complicate the asthma burden.
Varicella is a rising public health issue. Several studies have tried to quantify the relationships between meteorological factors and varicella incidence but with inconsistent results. We aim to investigate the impact of temperature and relative humidity on varicella, and to further explore the effect modification of these relationships. In this study, the data of varicella and meteorological factors from 2011 to 2019 in 21 cities of Guangdong Province, China were collected. Distributed lag nonlinear models (DLNM) were constructed to explore the relationship between meteorological factors (temperature and relative humidity) and varicella in each city, controlling in school terms, holidays, seasonality, long-term trends, and day of week. Multivariate meta-analysis was applied to pool the city-specific estimations. And the meta-regression was used to explore the effect modification for the spatial heterogeneity of city-specific meteorological factors and social factors (such as disposable income per capita, vaccination coverage, and so on) on varicella. The results indicated that the relationship between temperature and varicella in 21 cities appeared nonlinear with an inverted S-shaped. The relative risk peaked at 20.8 ℃ (RR = 1.42, 95% CI: 1.22, 1.65). The relative humidity-varicella relationship was approximately L-shaped, with a peaking risk at 69.5% relative humidity (RR = 1.25, 95% CI: 1.04, 1.50). The spatial heterogeneity of temperature-varicella relationships may be caused by income or varicella vaccination coverage. And varicella vaccination coverage may contribute to the spatial heterogeneity of the relative humidity-varicella relationship. The findings can help us deepen the understanding of the meteorological factors-varicella association and provide evidence for developing prevention strategy for varicella epidemic.
Hand, foot, and mouth disease (HFMD) poses a great disease burden in China. However, there are few studies on the relationship between temperature variability (TV) and HFMD. Moreover, whether air pollutions have modified effects on this relationship is still unknown. Therefore, this study aims to explore the modified effects of air pollutants on TV-HFMD association in Zibo City, China. Daily data of HFMD cases, meteorological factors, and air pollutants from 2015 to 2019 were collected for Zibo City. TV was estimated by calculating standard deviation of minimum and maximum temperatures over the exposure days. We used generalized additive model to estimate the association between TV and HFMD. The modified effects of air pollutants were assessed by comparing the estimated TV-HFMD associations between different air stratums. We found that TV increased the risk of HFMD. The effect was strongest at TV03 (4 days of exposure), when the incidence of HFMD increased by 3.6% [95% CI: 1.3-5.9%] for every 1℃ increases in TV. Males, children aged 0-4 years, were more sensitive to TV. We found that sulfur dioxide (SO(2)) enhanced TV’s effects on all considered exposure days, while ozone (O(3)) reduced TV’s effects on some exposure days in whole concerned population. However, we did not detect significant effect modification by particulate matter less than 10 microns in aerodynamic diameter (PM(10)). These findings are of significance in developing policies and public health practices to reduce the risks of HFMD by integrating changes in temperatures and air pollutants.
Respiratory infectious diseases (RID) are the major form of infectious diseases in China, and are highly susceptible to climatic conditions. Current research mainly focuses on the impact of weather on RID, but there is a lack of research on the effect of El Niño-Southern Oscillation (ENSO) on RID. Therefore, this paper uses the system generalized method of moments (SYS-GMM) and the data of 31 provinces in China from 2007 to 2018 to construct a dynamic panel model to empirically test the causality between ENSO and RID morbidity. Moreover, this paper considers the moderating effects of per capita disposable income and average years of education on this causality. The results show that ENSO can positively and significantly impact RID morbidity, which is 5.842% higher during El Niño years than normal years. In addition, per capita disposable income and average years of education can effectively weaken the relationship between ENSO and RID morbidity. Thus, this paper is of great significance for improving the RID early climate warning system in China and effectively controlling the spread of RID.
BACKGROUND: Acute lower respiratory infections (ALRIs) caused by respiratory viruses are common and persistent infectious diseases worldwide and in China, which have pronounced seasonal patterns. Meteorological factors have important roles in the seasonality of some major viruses, especially respiratory syncytial virus (RSV) and influenza virus. Our aim was to identify the dominant meteorological factors and to model their effects on common respiratory viruses in different regions of China. METHODS: We analysed monthly virus data on patients hospitalised with ALRI from 81 sentinel hospitals in 22 provinces in mainland China from Jan 1, 2009, to Sept 30, 2013. We considered seven common respiratory viruses: RSV, influenza virus, human parainfluenza virus, adenovirus, human metapneumovirus, human bocavirus, and human coronavirus. Meteorological data of the same period were used to analyse relationships between virus seasonality and seven meteorological factors according to region (southern vs northern China). The geographical detector method was used to quantify the explanatory power of each meteorological factor, individually and interacting in pairs, on the respiratory viruses. FINDINGS: 28 369 hospitalised patients with ALRI were tested, 10 387 (36·6%) of whom were positive for at least one virus, including RSV (4091 [32·0%] patients), influenza virus (2665 [20·8%]), human parainfluenza virus (2185 [17·1%]), adenovirus (1478 [11·6%]), human bocavirus (1120 [8·8%]), human coronavirus (637 [5·0%]), and human metapneumovirus (615 [4·8%]). RSV and influenza virus had annual peaks in the north and biannual peaks in the south. Human parainfluenza virus and human bocavirus had higher positive rates in the spring-summer months. Human metapneumovirus had an annual peak in winter-spring, especially in the north. Adenovirus and human coronavirus exhibited no clear annual seasonality. Temperature, atmospheric pressure, vapour pressure, and rainfall had most explanatory power on most respiratory viruses in each region. Relative humidity was only dominant in the north, but had no significant explanatory power for most viruses in the south. Hours of sunlight had significant explanatory power for RSV and influenza virus in the north, and for most viruses in the south. Wind speed was the only factor with significant explanatory power for human coronavirus in the south. For all viruses, interactions between any two of the paired factors resulted in enhanced explanatory power, either bivariately or non-linearly. INTERPRETATION: Spatiotemporal heterogeneity was detected for most viruses in this study, and interactions between pairs of meteorological factors were found to enhance their influence on virus variation. These findings might be helpful to guide government planning, such as public health interventions, infection control practice, and timing of passive immunoprophylaxis, and might facilitate the development of future vaccine strategies. FUNDING: National Natural Science Foundation of China, the Ministry of Science and Technology of China, and the Technology Major Project of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.
BACKGROUND: This study reports a systematic review of association between meteorological parameters and hand, foot and mouth disease (HFMD) in mainland China. METHODS: Using predefined study eligibility criteria, three electronic databases (PubMed, Web of Science, and Embase) were searched for relevant articles. Using a combination of search terms, including “Hand foot and mouth disease,” “HFMD,” “Meteorological,” “Climate,” and “China,” After removal of duplicates, our initial search generated 2435 studies published from 1990 to December 31, 2019. From this cohort 51 full-text articles were reviewed for eligibility assessment. The meta-analysis was devised in accordance with the published guidelines of the Cochrane Collaboration and Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA). Effect sizes, heterogeneity estimates and publication bias were computed using R software and Review Manager Software. RESULTS: The meta-analysis of 18 eligible studies showed that the meteorological parameters played an important role in the prevalence of HFMD. Lower air pressure may be the main risk factor for the incidence of HFMD in Chinese mainland, and three meteorological parameters (mean temperature, rainfall and relative humidity) have a significant association with the incidence of HFMD in subtropical regions. CONCLUSION: Lower air pressure might be the main risk factor for the incidence of HFMD in Chinese mainland. The influence of meteorological parameters on the prevalence of HFMD is mainly through changing virus viability in aerosols, which may be different in different climate regions. In an environment with low air pressure, wearing a mask that filters the aerosol outdoors may help prevent HFMD infection.
(1) Background: Assignment of pathogens to the correct genus, species, and type is vital for controlling infectious epidemics. However, the role of different enteroviruses during hand, foot, and mouth disease (HFMD) epidemics and the major contributing factors remain unknown. (2) Methods: HFMD cases from 2016 to 2018 in Guangzhou, China were collected. The relationship between HFMD cases and genotype frequency, as well as the association between genotype frequency and climate factors, were studied using general linear models. We transformed the genotype frequency to the isometric log-ratio (ILR) components included in the model. Additionally, vaccination rates were adjusted in the climate-driven models. (3) Results: We observed seasonal trends in HFMD cases, genotype frequency, and climate factors. The model regressing case numbers on genotype frequency revealed negative associations with both the ILRs of CAV16 (RR = 0.725, p < 0.001) and EV71 (RR = 0.421, p < 0.001). The model regressing genotype frequency on driven factors showed that the trends for EV71 proportions were inversely related to vaccination rate (%, β = -0.152, p = 0.098) and temperature (°C, β = -0.065, p = 0.004). Additionally, the trends for CVA16 proportions were inversely related to vaccination rate (%, β = -0.461, p = 0.004) and temperature (°C, β = -0.068, p = 0.031). The overall trends for genotype frequency showed that EV71 decreased significantly, while the trends for CVA16 increased annually. (4) Conclusions: Our findings suggest a potential pathway for climate factors, genotype frequency, and HFMD cases. Our study is practical and useful for targeted prevention and control, and provides environmental-based evidence.
Background: As an emerging infectious disease, the prevention and control of hand, foot, and mouth disease (HFMD) poses a significant challenge to the development of public health in China. In this study, we aimed to explore the mechanism of the seasonal transmission characteristics of HFMD and to reveal the correlation and potential path between key meteorological factors and the transmissibility of HFMD. Methods: Combined with daily meteorological data such as average temperature, average relative humidity, average wind velocity, amount of precipitation, average air pressure, evaporation capacity, and sunshine duration, a database of HFMD incidence and meteorological factors was established. Spearman rank correlation was used to calculate the correlation between the various meteorological factors and the incidence of HFMD. The effective reproduction number (R (eff) ) of HFMD was used as an intermediate variable to further quantify the dynamic relationship between the average temperature and R (eff) . Results: A total of 43,659 cases of HFMD were reported in Xiamen from 2014 to 2018. There was a significantly positive correlation between the average temperature and the incidence of HFMD (r = 0.596, p < 0.001), and a significantly negative correlation between the average air pressure and the incidence of HFMD (r = -0.511, p < 0.001). There was no correlation between the average wind velocity (r = 0.045, p > 0.05) or amount of precipitation (r = 0.043, p > 0.05) and incidence. There was a temperature threshold for HFMD’s transmissibility. Owing to the seasonal transmission characteristics of HFMD in Xiamen, the temperature threshold of HFMD’s transmissibility was 13.4-18.4°C and 14.5-29.3°C in spring and summer and in autumn and winter, respectively. Conclusions: HFMD’s transmissibility may be affected by the average temperature; the temperature threshold range of transmissibility in autumn and winter is slightly wider than that in spring and summer. Based on our findings, we suggest that the relevant epidemic prevention departments should pay close attention to temperature changes in Xiamen to formulate timely prevention strategies before the arrival of the high-risk period.
OBJECTIVES: In April 2000, a series of wildfires occurred simultaneously in five adjacent small cities located on the eastern coast of Korea. These wildfires burned approximately 23,794 hectares of forestland over several days. We investigated the effects of prenatal exposure to the by-products generated by wildfire disasters on birth weight. METHODS: Birth weight data were obtained for 1999-2001 from the birth registration database of the Korean National Statistical Office and matched with the zip code and exposed/unexposed pregnancy week for days of the wildfires. Generalized linear models were then used to assess the associations between birth weight and exposure to wildfires after adjusting for fetal sex, gestational age, parity, maternal age, maternal education, paternal education, and average exposed atmospheric temperature. RESULTS: Compared with unexposed pregnancies before and after the wildfires, mean birth weight decreased by 41.4 g (95% confidence interval [CI], -72.4 to -10.4) after wildfire exposure during the first trimester, 23.2 g (95% CI, -59.3 to 13.0) for exposure during the second trimester, and 27.0 g (95% CI, -63.8 to 9.8) during the third trimester. In the adjusted model for infants exposed in utero during any trimester, the mean birth weight decreased by 32.5 g (95% CI, -53.2 to -11.7). CONCLUSIONS: We observed a 1% reduction in birth weight after wildfire exposure. Thus, exposure to by-products generated during a wildfire disaster during pregnancy may slow fetal growth and cause developmental delays.
BACKGROUND: Studies on the association between smoke haze (hereafter ‘haze’) and adverse health effects have increased in recent years due to extreme weather conditions and the increased occurrence of vegetation fires. The possible adverse health effects on under-five children (U5Y) is especially worrying due to their vulnerable condition. Despite continuous repetition of serious haze occurrence in Southeast Asia, epidemiological studies in this region remained scarce. Furthermore, no study had examined the association accounting for three important aspects (time lag, duration and intensity) concurrently. OBJECTIVE: This study aimed to examine the association between haze and U5Y mortality in Malaysia, considering time lag, duration and intensity of exposure. METHODS: We performed a time-stratified case-crossover study using a generalized additive model to examine the U5Y mortality related to haze in 12 districts in Malaysia, spanning from 2014 to 2016. A ‘haze day’ was characterized by intensity [based on concentrations of particulate matter (PM)] and duration (continuity of haze occurrence, up to 3 days). RESULTS: We observed the highest but non-significant odds ratios (ORs) of U5Y mortality at lag 4 of Intensity-3. Lag patterns revealed the possibility of higher acuteness at prolonged and intensified haze. Stratifying the districts by the 95th-percentile of PM distribution, the ‘low’ category demonstrated marginal positive association at Intensity-2 Duration-3 [OR: 1.210 (95% confidence interval: 1.000, 1.464)]. CONCLUSIONS: We found a null association between haze and U5Y mortality. The different lag patterns of the association observed over different duration and intensity suggest consideration of these aspects in future studies.
Interactions between climate change and anthropogenic activities result in increasing numbers of open fires, which have been shown to harm maternal health. However, few studies have examined the association between open fire and pregnancy loss. We conduct a self-comparison case-control study including 24,876 mothers from South Asia, the region with the heaviest pregnancy-loss burden in the world. Exposure is assessed using a chemical transport model as the concentrations of fire-sourced PM(2.5) (i.e., fire PM(2.5)). The adjusted odds ratio (OR) of pregnancy loss for a 1-μg/m(3) increment in averaged concentration of fire PM(2.5) during pregnancy is estimated as 1.051 (95% confidence intervals [CI]: 1.035, 1.067). Because fire PM(2.5) is more strongly linked with pregnancy loss than non-fire PM(2.5) (OR: 1.014; 95% CI: 1.011, 1.016), it contributes to a non-neglectable fraction (13%) of PM(2.5)-associated pregnancy loss. Here, we show maternal health is threaten by gestational exposure to fire smoke in South Asia.
Wildfires are increasing and cause health effects. The immediate and ongoing health impacts of prolonged wildfire smoke exposure in severe asthma are unknown. This longitudinal study examined the experiences and health impacts of prolonged wildfire (bushfire) smoke exposure in adults with severe asthma during the 2019/2020 Australian bushfire period. Participants from Eastern/Southern Australia who had previously enrolled in an asthma registry completed a questionnaire survey regarding symptoms, asthma attacks, quality of life and smoke exposure mitigation during the bushfires and in the months following exposure. Daily individualized exposure to bushfire particulate matter (PM(2.5)) was estimated by geolocation and validated modelling. Respondents (n = 240) had a median age of 63 years, 60% were female and 92% had severe asthma. They experienced prolonged intense PM(2.5) exposure (mean PM(2.5) 32.5 μg/m(3) on 55 bushfire days). Most (83%) of the participants experienced symptoms during the bushfire period, including: breathlessness (57%); wheeze/whistling chest (53%); and cough (50%). A total of 44% required oral corticosteroid treatment for an asthma attack and 65% reported reduced capacity to participate in usual activities. About half of the participants received information/advice regarding asthma management (45%) and smoke exposure minimization strategies (52%). Most of the participants stayed indoors (88%) and kept the windows/doors shut when inside (93%), but this did not clearly mitigate the symptoms. Following the bushfire period, 65% of the participants reported persistent asthma symptoms. Monoclonal antibody use for asthma was associated with a reduced risk of persistent symptoms. Intense and prolonged PM(2.5) exposure during the 2019/2020 bushfires was associated with acute and persistent symptoms among people with severe asthma. There are opportunities to improve the exposure mitigation strategies and communicate these to people with severe asthma.
Objective: Adults born either extremely preterm (EP, <28 weeks gestation) or extremely low birthweight (ELBW, <1000 g birthweight) have more obstructive airflow than controls of normal birthweight (>2499 g). We compared self-reported adverse respiratory health outcomes in young adults born EP/ELBW with controls following smoke exposure from the 2019/2020 wildfires in the Australian state of Victoria, and explored if any effects were mediated by airway obstruction, reflected in the forced expiratory volume in 1 second (FEV1). Methods: EP/ELBW participants were derived from all survivors born in the state of Victoria in 1991–92. Contemporaneous controls of normal birthweight (>2499 g) were recruited in the newborn period and matched for sociodemographic variables. Both groups had been assessed at intervals through childhood and into adulthood. Those who participated in the most recent follow-up assessment at 25 years of age, when FEV1 had been measured, were sent a survey when they were approximately 28 years of age asking about respiratory health related outcomes (respiratory symptoms, health services usage, medication uptake) following wildfire smoke exposure over the southern hemisphere summer of 2019–20. Results: A total of 296 participants (166 EP/ELBW; 130 controls) were sent the survey; 44% of the EP/ELBW group and 47% of the control group responded. Compared with controls, EP/ELBW respondents reported more overall respiratory problems (30%vs 20%) and specific respiratory symptoms (breathlessness, wheezing, cough and chest tightness) following wildfire smoke exposure, as well as higher health services usage (e.g. local health clinic, hospital emergency department) and medication uptake for respiratory-related problems. Higher FEV1 values were associated with lower odds of most self-reported respiratory symptoms; adjusting for FEV1 attenuated the differences between EP/ELW and control groups. Conclusion: Survivors born EP/ELBW may be at an increased risk of adverse respiratory health outcomes following wildfire smoke exposure in early adulthood, in part related to worse expiratory airflows.
INTRODUCTION: Numerous studies have reported the modification of particulate matters (PMs) on the association between cold temperature and health. However, it remains uncertain whether the modification effect may vary by size of PMs, especially in Shandong Province, China where the disease burdens associated with cold temperature and PMs are both substantial. This study aimed to examine various interactive effects of cold exposure and ambient PMs with diameters ≤1/2.5 μm (PM1 and PM2.5) on premature deaths in Shandong Province, China. METHODS: In the 2013-2018 cold seasons, data on daily mortality, PM1 and PM2.5, and weather conditions were collected from the 1822 sub-districts of Shandong Province. A time-stratified case-crossover study design was performed to quantify the cumulative association between ambient cold and mortality over lag 0-12 days, with a linear interactive term between temperature and PM1 and PM2.5 additionally added into the model. RESULTS: The mortality risk increased with temperature decline, with the cumulative OR of extreme cold (-16.9°C, the 1st percentile of temperature range) being 1.83 (95% CI: 1.66, 2.02), compared with the minimum mortality temperature. The cold-related mortality risk was 2.20 (95%CI: 1.83, 2.64) and 2.24 (95%CI: 1.78, 2.81) on high PM1 and PM2.5 days, which dropped to 1.60 (95%CI: 1.39, 1.84) and 1.60 (95%CI: 1.37, 1.88) on low PM1 and PM2.5 days. PM1 showed greater modification effect for per unit concentration increase than PM2.5. For example, for each 10?g/m3 increase in PM1 and PM2.5, the mortality risk associated with extreme cold temperature increased by 7.6% (95% CI: 1.3%, 14.2%) and 2.6% (95% CI: -0.7%, 5.9%), respectively. DISCUSSION: The increment of smaller PMs’ modification effect varied by population subgroups, which was particularly strong in the elderly aged over 75 years and individuals with middle school education and below. Specific health promotion strategies should be developed towards the greater modification effect of smaller PMs on cold effect.
Anxiety and depression are severe public health problems worldwide. The effects of ozone exposure on anxious and depressive symptoms remain largely unknown, especially in China. We evaluated the associations between ozone exposure and depression and anxiety among middle-aged and older adults across China. A multi-center community-based repeated measurement study among middle-aged and older adults was conducted from 2017 to 2018 in 11 provinces in China. The status of depression and anxiety was measured using Patient Health Questionnaire-9 (PHQ-9) and the generalized anxiety disorder seven-item (GAD-7) scale at the cut-off point of five, respectively. Concentrations of multiple ozone metrics were collected from real-time monitoring stations. The multilevel logistic regression model with random intercept was used to evaluate the effects of ambient ozone on anxiety and depression over different exposure windows. After adjusting for potential confounders, a 10 mu g /m(3) increase in the three months moving average of ozone was associated with the risk of anxiety [odds ratio (OR) = 1.25; 95% confidence interval (CI): 1.15; 1.37] and depression (OR = 1.17; 95% CI: 1.08; 1.27). A significantly positive modification effect of temperature on associations between ozone and anxiety was also found, while there is no interaction for depression. Exposure-response curves showed that there may be a threshold for the effect of ozone exposure on anxiety and depression over the three months moving average concentrations, with similar patterns observed at different temperature levels. People over 65 years old were at significantly higher risks of ozone-associated depression, while anxiety was more strongly associated with ozone in hypertensive patients. Our study supports the theory that anxiety and depression is associated with mid-term ozone exposure in China, and temperatures significantly enhanced their associations. These findings may have significant implications for promoting prevention activities regarding mental disorders and approaches in reducing the disease burden by simultaneously controlling air pollution and mitigating climate change.
WHAT IS ALREADY KNOWN ABOUT THIS TOPIC? Ozone (O(3)) is a weather-driven photochemical ambient pollutant, and its harm to human health may be affected by meteorological factors such as temperature. However, there is conflicting evidence regarding whether temperature can modify the effects of ozone on health. WHAT IS ADDED BY THIS REPORT? Short-term exposure to O(3) in the Beijing Municipality, Tianjin Municipality, Hebei Province, and surrounding areas was associated with an increased risk of human mortality and that association was positive modified by relatively higher (>75th 24 h-average temperature) or extreme cold temperature (<10th 24 h-average temperature). Under extreme temperatures (>90th 24 h-average temperature) modification, the associations were further increased. Cardiopulmonary diseases, as vulnerable diseases of air pollution, their mortality risks associated with O(3) were markedly strengthened by uncomfortable temperatures. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE? This study suggests that policymakers should pay attention to the synergistic effect between ozone and heat or extreme cold on human health, as well as provide evidence for establishing an integrated early-warning system to protect the public against both uncomfortable temperature and air pollution.
Heatwaves (HWs) paired with higher ozone (O-3) concentration at the surface level pose a serious threat to human health. Their combined modulation of synoptic patterns and urbanization remains unclear. Using 5 years of summertime temperature and O-3 concentration observation in Beijing, this study explored potential drivers of compound HWs and O-3 pollution events and their public health effects. Three favorable synoptic weather patterns were identified to dominate the compound HWs and O-3 pollution events. These weather patterns contributing to enhance those conditions are characterized by sinking air motion, low boundary layer height, and high temperatures. Under the synergy of HWs and O-3 pollution, the mortality risk from all non-accidental causes increased by approximately 12.31 % (95 % confidence interval: 4.66 %, 20.81 %). Urbanization caused a higher risk of HWs and O-3 in urban areas than at rural stations. Particularly, due to O(3 )depletion caused by NO titration at traffic and urban stations, the health risks related to O(3 )pollution in different regions are characterized as follows: suburban stations > urban stations > rural stations > traffic stations. In general, favorable synoptic patterns and urbanization enhanced the health risk of these compound events in Beijing by 33.09 % and 18.95 %, respectively. Our findings provide robust evidence and implications for forecasting compound HWs and O-3 pollution events and their health risks in Beijing or in other urban areas all over the world that have high concentrations of O-3 and high-density populations.
The 1.5 °C pathways initially promoted by the challenges presented by climate change could bring substantial air quality-related benefits. However, since there is a lack of comprehensive assessment on emissions of air pollutants, meteorology, air quality, and heatwave occurrences under different climate goals, how significant the clean air cobenefits compared with the direct climate-related impact is uncertain. In this study, we assess the cobenefits of 1.5 °C pathways for air quality in China by linking multiple shared socioeconomic pathways, ensembling simulations of regional climate-air quality dynamic downscaling and an air pollution and climate-related health assessment model, and compare different kinds of benefits: the health benefits from direct slowing climate (reduced heatwaves) versus the health cobenefits from air quality improvement (the improved air quality from reduced air pollutants versus meteorological changes). The benefit of reduced air pollution emissions associated with sustainable development under 1.5 °C pathways dominated the overall impact, which could avoid 1 589 000 PM(2.5)-related and 526 000 O(3)-related deaths in 2050. Correspondingly, the impact of changed meteorology on air quality would avoid additional 8000 PM(2.5)-related deaths in 2050 under 1.5 °C pathways yet would lead to 22 000 O(3)-related deaths. Also, the heatwave-related deaths could be avoided by 7000. The substantial anthropogenic emission reduction cobenefits of 1.5 °C pathways in improving air quality significantly exceed the direct climate (heatwave-related) benefits and completely offset the impact of meteorological changes’ impact on air pollution under climate change.
A multitude of epidemiological studies have demonstrated that both ambient temperatures and air pollution are closely related to health outcomes. However, whether temperature has modification effects on the association between ozone and health outcomes is still debated. In this study, three parallel time-series Poisson generalized additive models (GAMs) were used to examine the effects of modifying ambient temperatures on the association between ozone and mortality (including non-accidental, respiratory, and cardiovascular mortality) in Chengdu, China, from 2014 to 2016. The results confirmed that the ambient high temperatures strongly amplified the adverse effects of ozone on human mortality; specifically, the ozone effects were most pronounced at > 28 °C. Without temperature stratification conditions, a 10-μg/m(3) increase in the maximum 8-h average ozone (O(3-8hmax)) level at lag01 was associated with increases of 0.40% (95% confidence interval [CI] 0.15%, 0.65%), 0.61% (95% CI 0.27%, 0.95%), and 0.69% (95% CI 0.34%, 1.04%) in non-accidental, respiratory, and cardiovascular mortality, respectively. On days during which the temperature exceeded 28 °C, a 10-μg/m(3) increase in O(3-8hmax) led to increases of 2.22% (95% CI 1.21%, 3.23%), 2.67% (95% CI 0.57%, 4.76%), and 4.13% (95% CI 2.34%, 5.92%) in non-accidental, respiratory, and cardiovascular mortality, respectively. Our findings validated that high temperature could further aggravate the health risks of O(3-8hmax); thus, mitigating ozone exposure will be brought into the limelight especially under the context of changing climate.
Numerous epidemiological studies have reported that ozone (O(3)) and temperature are independently associated with health outcomes, but modification of the effects of O(3) on health outcomes by temperature, and vice versa, has not been fully described. This study aimed to investigate effect modification by temperature on the association between O(3) and emergency ambulance dispatches (EADs) in Japan. Data on daily air pollutants, ambient temperature, and EADs were obtained from eight Japanese cities from 2007 to 2015. A distributed lag non-linear model combined with Poisson regression was performed with temperature as a confounding factor and effect modifier to estimate the effects of O(3) on EADs at low (<25th percentile), moderate (25th-75th percentile), and high (>75th percentile) temperature for each city. The estimates obtained from each city were pooled by random-effects meta-analysis. When temperature was entered as a confounder, the estimated effects of O(3) on EADs for all acute, cardiovascular, and respiratory illnesses were largest at lag 0 (current-day lag). Therefore, this lag was used to further estimate the effects of O(3) on EADs in each temperature category. The estimated effects of O(3) on EADs for all acute, cardiovascular, and respiratory illnesses in all eight Japanese cities increased with increasing temperature. Specifically, a 10 ppb increase in O(3) was associated with 0.80 % (95 % CI: 0.25 to 1.35), 0.19 % (95 % CI: -0.85 to 1.25), and 1.14 % (95 % CI: -0.01 to 2.31) increases in the risk of EADs for all acute, cardiovascular, and respiratory illnesses, respectively, when city-specific daily temperature exceeded the 75th percentile. Our findings suggest that the association between O(3) and EADs for all acute, cardiovascular, and respiratory illnesses is the highest during high temperature. Finding of this study can be used to develop potential mitigation measures against O(3) exposure in high temperature environment to reduce its associated adverse health effects.
BACKGROUND: Numerous studies have confirmed the association of ambient temperature and air pollution with a higher risk of morbidities, yet few have addressed their effect on the ocular system. The purpose of this study was to assess the association between temperature, air pollution, and emergency room visits for conjunctivitis. METHODS: In this case-crossover study, the records of all emergency room visits to Soroka University Medical Center (SUMC) from 2009 to 2014 were reviewed for patients with conjunctivitis. Daily exposure to fine and coarse particulate matter and temperature were determined by a hybrid model involving satellite sensors. Mean relative humidity was obtained from the Ministry of Environmental Protection meteorological monitoring station located in Beer-Sheva. RESULTS: Six hundred one patients were diagnosed with conjunctivitis in the SUMC emergency room. We discovered a positive association between temperature increments and incidence of conjunctivitis. The strongest effect was found during summer and autumn, with an immediate (lag0) incidence increase of 8.1% for each 1 °C increase in temperature (OR = 1.088, 95%CI: 1.046-1.132) between 24 and 28 °C in the summer and 7.2% for each 1 °C increase in temperature (OR = 1.072, 95%CI: 1.036-1.108) between 13 and 23 °C in the autumn. There was no statistically significant association between fine and coarse particulate matter and conjunctivitis incidence. CONCLUSION: Temperature increases during summer and autumn are significantly associated with an increased risk of conjunctivitis. Conjunctivitis is not associated with non-anthropogenic air pollution. These findings may help community clinics and hospital emergency rooms better predict conjunctivitis cases and will hopefully lead to improved prevention efforts that will lower the financial burden on both the individual and the public.
The Australian 2019/2020 bushfires were unprecedented in their extent and intensity, causing a catastrophic loss of habitat, human and animal life across eastern-Australia. We use a regional air quality model to assess the impact of the bushfires on particulate matter with a diameter less than 2.5 μm (PM(2.5)) concentrations and the associated health impact from short-term population exposure to bushfire PM(2.5). The mean population Air Quality Index (AQI) exposure between September and February in the fires and no fires simulations indicates an additional ∼437,000 people were exposed to “Poor” or worse AQI levels due to the fires. The AQ impact was concentrated in the cities of Sydney, Newcastle-Maitland, Canberra-Queanbeyan and Melbourne. Between October and February 171 (95% CI: 66-291) deaths were brought forward due to short-term exposure to bushfire PM(2.5). The health burden was largest in New South Wales (NSW) (109 (95% CI: 41-176) deaths brought forward), Queensland (15 (95% CI: 5-24)), and Victoria (35 (95% CI: 13-56)). This represents 38%, 13% and 30% of the total deaths brought forward by short-term exposure to all PM(2.5). At a city-level 65 (95% CI: 24-105), 23 (95% CI: 9-38) and 9 (95% CI: 4-14) deaths were brought forward from short-term exposure to bushfire PM(2.5), accounting for 36%, 20%, and 64% of the total deaths brought forward from all PM(2.5.) Thus, the bushfires caused substantial AQ and health impacts across eastern-Australia. Climate change is projected to increase bushfire risk, therefore future fire management policies should consider this.
This study investigated the contributions of particulate matter (PM) from various emission sources during the dry season, which resulted from frequent fires occurring in degraded forests and peatlands in Indonesia. Samples of fine (PM2.5) and coarse (PM2.5-10) particles collected during the dry season in Riau, Indonesia were analyzed to determine the mass concentrations of metallic trace elements, ionic compound, black carbon (BC), and organic carbon (OC). The average concentrations of PM2.5 and PM2.5-10 at Riau, Indonesia were 63.85 +/- 3.22 mu g m(-3) and 27.72 +/- 2.40 mu g m(-3), respectively. The positive matrix factorization (PMF) model was adopted to identify possible PM sources and their contributions to the ambient PM level. The PMF results identified six major PM2.5 sources, including biomass burning (BB) (28.7%), secondary aerosols (SA) (26.9%), vehicle exhaust (VE) (12.8%), industrial emissions (IE) (12.3%), soil dust (SD) (11.9%), and sea salt (SS) (7.5%). Moreover, there were five primary PM2.5-10 sources, including VE (28.6%) and BB (24%), followed by IE (19.9%), SD (17.2%), and SA (15.3%). A conditional probability function (CPF) analysis revealed that the southeast sector dominated among source direction-dependent contributions. The noncarcinogenic health risks for both adults and children resulting from exposure to PM2.5 were mainly contributed by Co, Ni, and Mn, and carcinogenic risks were caused by the toxic metals Cr and Co. Both noncarcinogenic and carcinogenic health risks resulting from cumulative multielement exposure for both adults and children exceeded acceptable levels. Clearly, more attention should be devoted to reducing the noncarcinogenic and carcinogenic health risks caused by particulate-bound toxic elements through inhalation exposure.
Over the past 30 years, forest fire has been one of main ecological issues in Indonesia. Human-caused deforestation was accused to be the reason behind this matter, apart from the drastic changing in global climate. Palangkaraya is one of the citiesaffected by haze of the forest fire in 2015; considered to be the worst year of forest fire with the value of PM10 was above the normal threshold. As the impact to the community wellbeing, the prevalence of acute respiratory infection (ARI) in October 2015was increasing especially in children. The research aimed to analyse the spatial distribution of children with ARI in October 2015 at Palangkaraya City. Data onARI number were collected from Primary Care under Public Health Office of Palangkaraya City. The PM 10 value was collected bythe Environmental Agency of Palangkaraya City. The spatial analyse method was conducted using theAverage Nearest Neighbour (ANN) method. The result shows that the number of ANN ratio is 0.761801. It means that the distribution pattern of children with ARI in Central Kalimantan during the forest fire in October 2015 was in cluster form.
BACKGROUND: Climate change has resulted in an increase in ambient temperatures during the summer months as well as an increase in risk of associated air pollution and of potentially disastrous bushfires throughout much of the world. The increasingly frequent combination of elevated summer temperatures and bushfires may be associated with acute increases in risks of cardiovascular events, but this relationship remains unstudied. We evaluated the individual and cumulative impacts of daily fluctuations in temperature, fine particulate matter of less than 2.5 µm (PM(2.5)) pollution and presence of bushfires on incidence of acute coronary syndromes and Takotsubo syndrome. METHODS: From November 1, 2019, to February 28, 2020, all admissions with acute coronary syndromes or Takotsubo syndrome to South Australian tertiary public hospitals were evaluated. Univariate and combined associations were sought among each of 1) maximal daily temperature, 2) PM(2.5) concentrations, and 3) presence of active bushfires within 200 km of the hospitals concerned. RESULTS: A total of 504 patients with acute coronary syndromes and 35 with Takotsubo syndrome were studied. In isolation, increasing temperature was associated (r(s) = 0.26, P = .005) with increased incidence of acute coronary syndromes, while there were similar, but nonsignificant correlations for PM(2.5) and presence of bushfires. Combinations of all these risk factors were also associated with a doubling of risk of acute coronary syndromes. No significant associations were found for Takotsubo syndrome. CONCLUSION: The combination of high temperatures, presence of bushfires and associated elevation of atmospheric PM(2.5) concentrations represents a substantially increased risk for precipitation of acute coronary syndromes; this risk should be factored into health care planning including public education and acute hospital preparedness.
We investigated the association between respiratory symptoms and psychological distress in the context of a prolonged smoke event, and evaluated whether smoke exposure, or pre-existing respiratory and mental health conditions, influenced the association. Three thousand ninety-six residents of a rural town heavily exposed to smoke from the 6-week Hazelwood coal mine fire, and 960 residents of a nearby unexposed town, completed Kessler’s psychological distress questionnaire (K10) and a modified European Community Respiratory Health Survey. Logistic regression models evaluated associations between distress and respiratory symptoms, with interactions fitted to evaluate effect modification. Smoke exposed participants reported higher levels of distress than those unexposed, and participants reporting respiratory symptoms recorded higher levels of distress than participants without respiratory symptoms, irrespective of exposure. 5-unit increments in K10 scores were associated with 21%-48% increases in the odds of reporting respiratory symptoms. There were significant interactions with pre-existing asthma, chronic obstructive pulmonary disease and mental health conditions, but not with smoke exposure. Although participants with pre-existing conditions were more likely to report respiratory symptoms, increasing distress was most strongly associated with respiratory symptoms among those without pre-existing conditions. Communities exposed to landscape fire smoke could benefit from interventions to reduce both psychological and respiratory distress.
A sense of psychological connectedness with the natural world has important benefits for global health. In a time of environmental crisis, however, it may also be accompanied by mental health risks. We used national survey data collected after a severe Australian bushfire season (N = 3,875) to test a path model of the relationships between nature connectedness, worry about climate change, individual and collective climate action, and psychological distress (depression, anxiety, stress). We found that nature connectedness was positively associated with climate worry that, in turn, was positively associated with climate action and psychological distress. Whereas taking individual climate action was associated with reduced psychological distress, taking collective climate action had the opposite effect. Our findings provide new insights into potential processes underlying the association between nature connectedness and mental health in the climate change context and point to an urgent need to protect the well-being of people engaging in collective climate action.
This paper presents new evidence of the causal effect of air pollution on Australian health outcomes, using the Black Saturday bushfires (BSB) in 2009 as a natural experiment. This event was one of the largest bushfires in Australian history and emitted approximately four million tonnes of CO(2) into the atmosphere. We use data from the Household Income and Labour Dynamic Australia (HILDA) panel and compare the health status of individuals who were living in affected and unaffected regions before and after the event. Using a triple differences procedure, we further examine whether a difference in vulnerability to bushfire smoke exists comparing people living in urban or regional areas. We find that ambient air pollution had significant negative effects on health and that the magnitudes were actually larger for individuals residing in urban areas.
BACKGROUND: Air pollution including particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) increases the risk of acute myocardial infarction. However, whether short-term exposure to PM2.5 triggers the onset of myocardial infarction with nonobstructive coronary arteries, compared with myocardial infarction with coronary artery disease, has not been elucidated. This study aimed to estimate the association between short-term exposure to PM2.5 and admission for acute myocardial infarction, myocardial infarction with coronary artery disease, and myocardial infarction with nonobstructive coronary arteries. DESIGN: This was a time-stratified case-crossover study and multicenter validation study. METHODS: This study used a nationwide administrative database in Japan between April 2012-March 2016. Of 137,678 acute myocardial infarction cases, 123,633 myocardial infarction with coronary artery disease and 14,045 myocardial infarction with nonobstructive coronary arteries were identified by a validated algorithm combined with International Classification of Disease (10th revision), diagnostic, and procedure codes. Air pollutants and meteorological data were obtained from the monitoring station nearest to the admitting hospital. RESULTS: In spring (March-May), the short-term increase of 10 µg/m3 in PM2.5 2 days before admission was significantly associated with admission for acute myocardial infarction, myocardial infarction with nonobstructive coronary arteries, and myocardial infarction with coronary artery disease after adjustment for meteorological variables (odds ratio 1.060, 95% confidence interval 1.038-1.082; odds ratio 1.151, 1.079-1.227; odds ratio 1.049, 1.026-1.073, respectively), while the association was not significant in other variables. These associations were also observed after adjustment for other co-pollutants. The risk for myocardial infarction with nonobstructive coronary arteries (vs myocardial infarction with coronary artery disease) was associated with an even lower concentration of PM2.5 under the current environmental standards. CONCLUSIONS: This study showed the seasonal difference of acute myocardial infarction risk attributable to PM2.5 and the difference in the threshold of triggering the onset of acute myocardial infarction subtype.
BACKGROUND: Previous reports indicate an association between ambient temperature (Ta) and air pollution exposure during pregnancy and preterm birth (PTB). Nevertheless, information regarding the association between environmental factors and specific precursors of spontaneous preterm birth is lacking. We aimed to determine the association between Ta and air pollution during gestation and the precursors of spontaneous preterm parturition, i.e. preterm labor (PTL) and preterm prelabor rupture of membranes (PPROM). METHODS: From 2003 to 2013 there were 84,476 deliveries of singleton gestation that comprised the study cohort. Exposure data during pregnancy included daily measurements of temperature and particulate matter <2.5 μm and <10 μm, PM(2.5) and PM(10), respectively. Deliveries were grouped into PPROM, PTL and non-spontaneous preterm and term deliveries. Exposure effect was tested in windows of a week and two days prior to admission for delivery and adjusted to gestational age and socio-economic status. Poisson regression models were used for analyses. RESULTS: There is an association of environmental exposure with the precursors of spontaneous preterm parturition; PPROM was more sensitive to Ta fluctuations than PTL. This effect was modified by the ethnicity, Bedouin-Arabs were susceptible to elevated Ta, especially within the last day prior to admission with PPROM (Relative Risk (RR) =1.19 [95% CI, 1.03; 1.37]). Jews, on the other hand, were susceptible to ambient pollutants, two (RR=1.025 [1.010; 1.040]) and one (RR= 1.017 [1.002; 1.033]) days prior to spontaneous PTL with intact membranes resulting in preterm birth. CONCLUSION: High temperature is an independent risk factor for PPROM among Bedouin-Arabs; ambient pollution is an independent risk factor for spontaneous PTL resulting in preterm birth. Thus, the precursors of spontaneous preterm parturition differ in their association with environmental factors.
The differential effect of meteorological factors and air pollutants on pediatric epistaxis in younger and older children has not been evaluated. We evaluated the distribution of pediatric epistaxis cases between younger (0-5 years) and older children (6-18 years). Subsequently, we assessed and compared the effects of meteorological variables and the concentration of particulate matter measuring ≤ 10 μm in diameter (PM10) on hospital epistaxis presentation in younger and older children. This retrospective study included pediatric patients (n = 326) who presented with spontaneous epistaxis between January 2015 and August 2019. Meteorological conditions and PM10 concentration were the exposure variables, and data were obtained from Korea Meteorological Administration 75. The presence and cumulative number of epistaxis presentations per day were considered outcome variables. Air temperature, wind speed, sunshine duration, and PM10 concentration in younger children, and sunshine duration and air pressure in older children, significantly correlated with the presence of and cumulative number of epistaxis presentations per day. The PM10 concentration was not a significant factor in older children. Thus, meteorological factors and PM10 concentration may differentially affect epistaxis in younger (0-5-year-olds) and older (6-18-year-olds) children. Risk factors for pediatric epistaxis should be considered according to age.
BACKGROUND: Positive associations between ambient PM(2.5) and cardiorespiratory disease have been well demonstrated during the past decade. However, few studies have examined the adverse effects of PM(2.5) based on an entire population of a megalopolis. In addition, most studies in China have used averaged data, which results in variations between monitoring and personal exposure values, creating an inherent and unavoidable type of measurement error. METHODS: This study was conducted in Wuhan, a megacity in central China with about 10.9 million people. Daily hospital admission records, from October 2016 to December 2018, were obtained from the Wuhan Information center of Health and Family Planning, which administrates all hospitals in Wuhan. Daily air pollution concentrations and weather variables in Wuhan during the study period were collected. We developed a land use regression model (LUR) to assess individual PM(2.5) exposure. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate cardiorespiratory hospitalization risks associated with short-term exposure to PM(2.5). We also conducted stratification analyses by age, sex, and season. RESULTS: A total of 2,806,115 hospital admissions records were collected during the study period, from which we identified 332,090 cardiovascular disease admissions and 159,365 respiratory disease admissions. Short-term exposure to PM(2.5) was associated with an increased risk of a cardiorespiratory hospital admission. A 10 μg/m(3) increase in PM(2.5) (lag0-2 days) was associated with an increase in hospital admissions of 1.23% (95% CI 1.01-1.45%) and 1.95% (95% CI 1.63-2.27%) for cardiovascular and respiratory diseases, respectively. The elderly were at higher PM-induced risk. The associations appeared to be more evident in the cold season than in the warm season. CONCLUSIONS: This study contributes evidence of short-term effects of PM(2.5) on cardiorespiratory hospital admissions, which may be helpful for air pollution control and disease prevention in Wuhan.
Air Pollution is an emerging disaster and considered one of the biggest challenges of the world to effectively con-trol, mitigate and forecast due to abrupt variability, stochastic, and chaotic pattern of particulate matter (PM) in terms of time and space of the pollutants. Composition of ambient PM not only causes serious damage to public health but also emerging as a global hazard particularly for urban environment with negative impact on human health including morbidity. Mortality and ultimately towards unstable economy. In this study, hourly short-term trends of PM2.5 and air quality index (AQI) of Lahore city of Pakistan is monitored and mitigated by the design of fractional order Lorenz based physics informed hybrid computing paradigm SARFIMA-NARX for forecasting hourly pattern of next two days. The complex dynamics of earth system and its weather forecast are character-ized by combination of biological, physical, and chemical processes governed by the different laws of science that provides additional information for the climate variation in terms of physics inform intelligence. The perfor-mance index based on statistical indicator of RMSE confirmed the high accuracy and efficiency of designed model to predict the pattern. The early predictions based on computational intelligence paradigm may serve as a surveillance system to reduce the air pollution through cost-effectiveness planning by environmental monitor-ing agencies.(c) 2022 Elsevier Ltd. All rights reserved.
The rapid development of industrialization and urbanization has had a substantial impact on the increasing air pollution in many populated cities around the globe. Intensive research has shown that ambient aerosols, especially the fine particulate matter PM2.5, are highly correlated with human respiratory diseases. It is critical to analyze, forecast, and mitigate PM2.5 concentrations. One of the typical meteorological phenomena seducing PM2.5 concentrations to accumulate is temperature inversion which forms a warm-air cap to blockade the surface pollutants from dissipating. This paper analyzes the meteorological patterns which coincide with temperature inversion and proposes two machine learning classifiers for temperature inversion classification. A separate multivariate regression model is trained for the class with or without manifesting temperature inversion phenomena, in order to improve PM2.5 forecasting performance. We chose Puli township as the studied site, which is a basin city easily trapping PM2.5 concentrations. The experimental results with the dataset spanning from 1 January 2016 to 31 December 2019 show that the proposed temperature inversion classifiers exhibit satisfactory performance in F1-Score, and the regression models trained from the classified datasets can significantly improve the PM2.5 concentration forecast as compared to the model using a single dataset without considering the temperature inversion factor.
The impact of atmospheric concentration of particulate matter ≤10 μm in diameter (PM(10)) continues to attract research attention. This study aimed to evaluate the effects of meteorological factors, including PM(10) concentration, on epistaxis presentation in children and adults. We reviewed the data from 1557 days and 2273 cases of epistaxis between January 2015 and December 2019. Eligible patients were stratified by age into the children (age ≤17 years) and adult groups. The main outcome was the incidence and cumulative number of epistaxis presentations in hospital per day and month. Meteorological factors and PM(10) concentration data were obtained from the Korea Meteorological Administration. Several meteorological factors were associated with epistaxis presentation in hospital; however, these associations differed between children and adults. Only PM(10) concentration was consistently associated with daily epistaxis presentation in hospital among both children and adults. Additionally, PM(10) concentration was associated with the daily cumulative number of epistaxis presentations in hospital in children and adults. Furthermore, the monthly mean PM(10) concentration was significantly associated with the total number of epistaxis presentations in the corresponding month. PM(10) concentration should be regarded as an important environmental factor that may affect epistaxis in both children and adults.
OBJECTIVE: The associations between climate variables and diseases such as respiratory infections, influenza, pediatric seizure, and gastroenteritis have been long appreciated. Infection is the main reason for acute otitis media (AOM) incidence. However, few previous studies explored the correlation between climatic parameters and AOM infections. The most important meteorological factors, temperature, relative humidity, and fine particulate matter (PM2.5), were included in this study. We studied the relationship between these meteorological factors and the AOM visits. MATERIALS AND METHODS: It was a retrospective cross-sectional study. A linear correlation and a linear regression model were used to explore the AOM visits and meteorological factors. RESULTS: A total of 7075 emergency department visits for AOM were identified. Relative humidity was found an independent risk factor for the AOM visits in preschool children (regression coefficient = -10.841<0, P = .039 < .05), but not in infants and school-age children. Average temperature and PM2.5 were not correlated with AOM visits. CONCLUSION: Humidity may have a significant inverse impact on the incidence of AOM in preschool-age children.
Low-carbon pathways consistent with the 2 degrees C and 1.5 degrees C long-term climate goals defined in the Paris Agreement are likely to induce substantial co-benefits for air pollution and associated health impacts. In this analysis, using five global integrated assessment models, we quantify the emission reductions in key air pollutants resulting from the decarbonization of energy systems and the resulting changes in premature mortality attributed to the exposure to ambient concentrations of fine particulate matter. The emission reductions differ by sectors. Sulfur emissions are mainly reduced from power plants and industry, cuts in nitrogen oxides are dominated by the transport sector, and the largest abatement of primary fine particles is achieved in the residential sector. The analysis also shows that health benefits are the largest when policies addressing climate change mitigation and stringent air pollution controls are coordinated. We decompose the key factors that determine the extent of health co-benefits, focusing on Asia: changes in emissions, urbanization rates, population growth and ageing. Demographic processes, particularly due to ageing population, counteract in many regions the mortality reductions realized through lower emissions.
The objective of this study was to evaluate the influence of exposure to meteorological conditions, including air pollution, on thyroid cancer. A nested case-control study was conducted utilizing 4632 patients with thyroid cancer and 18,528 control subjects who were matched at a 1:4 ratio by age group, sex, income, and region of residence. Korean National Health Insurance Service-Health Screening Cohort data from 2002 to 2015 were used. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for thyroid cancer correlated with meteorological and air pollution exposure over a moving average of 3 years before the index dates. For all participants, the adjusted ORs associated with relative humidity (1.01, 95% CI 1.00-1.03, P value = 0.023), ambient atmospheric pressure (1.02, 95% CI 1.01-1.03, P value < 0.001), and sunshine duration (1.17, 95% CI 1.04-1.31, P value = 0.007) indicated correlations with the occurrence of thyroid cancer; however, these results were inconsistent in the subgroup analyses. Overall, exposure to nitrogen dioxide (NO(2)) (1.33, 95% CI 1.24-1.43, P value < 0.001) and particulate matter (PM(10)) (0.64, 95% CI 0.60-0.69, P value < 0.001) were related to thyroid cancer. These relationships persisted in the subgroup analyses. In conclusion, thyroid cancer occurrence was positively associated with NO(2) exposure and negatively associated with PM(10) exposure.
Meeting the Paris Agreement on climate change requires substantial investments in low-emissions energy and significant improvements in end-use energy efficiency. These measures can also deliver improved air quality and there is broad recognition of the health benefits of decarbonising energy. Monetising these health benefits is an important part of a robust assessment of the costs and benefits of renewable energy and energy efficiency programs (clean energy programs (CEP)) and a variety of methods have been used to estimate health benefits at national, regional, continental and global scales. Approaches, such as unit damage cost estimates and impact pathways, differ in complexity and spatial coverage and can deliver different estimates for air pollution costs/benefits. To date, the monetised health benefits of CEP in Australia have applied international and global estimates that can range from 2-229USD/tCO2 (USD 2016). Here, we calculate the current health damage costs of coal-fired power in New South Wales (NSW), Australia’s most populous state, and the health benefits of CEP. Focusing on PM2.5 pollution, we estimate the current health impacts of coal-fired power at 3.20USD/MWh, approximately 10% of the generation costs, and much lower than previous estimates. We demonstrate the need for locally specific assessment of the air pollution benefits of CEP and illustrate that without locally specific information, the relative costs/benefits of CEP may be significantly over- or understated. We estimate that, for NSW, the health benefits from CEP are 1.80USD/MWh and that the current air pollution health costs of coal-fired power in NSW represent a significant unpriced externality.
BACKGROUND: Bushfire smoke is a major ongoing environmental hazard in Australia. In the summer of 2019-2020 smoke from an extreme bushfire event exposed large populations to high concentrations of particulate matter (PM) pollution. In this study we aimed to estimate the effect of bushfire-related PM of less than 2.5 μm in diameter (PM(2.5)) on the risk of mortality in Sydney, Australia from 2010 to 2020. METHODS: We estimated concentrations of PM(2.5) for three subregions of Sydney from measurements at monitoring stations using inverse-distance weighting and cross-referenced extreme days (95th percentile or above) with satellite imagery to determine if bushfire smoke was present. We then used a seasonal and trend decomposition method to estimate the Non-bushfire PM(2.5) concentrations on those days. Daily PM(2.5) concentrations above the Non-bushfire concentrations on bushfire smoke days were deemed to be Bushfire PM(2.5). We used distributed-lag non-linear models to estimate the effect of Bushfire and Non-bushfire PM(2.5) on daily counts of mortality with sub-analyses by age. These models controlled for seasonal trends in mortality as well as daily temperature, day of week and public holidays. RESULTS: Within the three subregions, between 110 and 134 days were identified as extreme bushfire smoke days within the subregions of Sydney. Bushfire-related PM(2.5) ranged from 6.3 to 115.4 µg/m(3). A 0 to 10 µg/m(3) increase in Bushfire PM(2.5) was associated with a 3.2% (95% CI 0.3, 6.2%) increase in risk of all-cause death, cumulatively, in the 3 days following exposure. These effects were present in those aged 65 years and over, while no effect was observed in people under 65 years. CONCLUSION: Bushfire PM(2.5) exposure is associated with an increased risk of mortality, particularly in those over 65 years of age. This increase in risk was clearest at Bushfire PM(2.5) concentrations up to 30 µg/m(3) above background (Non-bushfire), with possible plateauing at higher concentrations of Bushfire PM(2.5).
We examine 512 Australian newspaper articles published over a five-year period (2016-2021) that report on air pollution due to bushfire smoke and resulting human health impacts. We analyze to what extent these articles provide information on the possible range of negative health impacts due to bushfire smoke pollution, and to what extent they report on climate change as a driver behind increased bushfire risk. A temporary surge in articles in our sample occurs during the unusually severe 2019/2020 Black Summer bushfires. However, most articles are limited to general statements about the health impacts of bushfire smoke, with only 50 articles in the sample (9%) mentioning an explicit link between bushfire smoke inhalation and cardiovascular and respiratory problems or increases in mortality risk. About 148 of the 512 articles in the sample (29%) established a connection between bushfire risk and climate change. We carry out a further keyword analysis to identify differences in reporting by Australia’s two main publishing groups (News Corp Australia and Nine Entertainment), which shows that articles in News Corp Australia outlets offered the lowest climate change coverage. We suggest that more detailed communication strategies are needed to strengthen public preparedness for future impacts.
Smoke from forest fires can reach hazardous levels for extended periods of time. We aimed to determine if there is an association between particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5) and living in a forest fire–prone province and cognitive function. We used data from the Indonesian Family and Life Survey. Cognitive function was assessed by the Ravens Colored Progressive Matrices (RCPM). We used regression models to estimate associations between PM2.5 and living in a forest fire–prone province and cognitive function. In multivariable models, we found very small positive relationships between PM2.5 levels and RCPM scores (PM2.5 level at year of survey: β = 0.1%; 95% confidence interval (CI) [0.01, 0.19%]). There were no differences in RCPM scores for children living in forest fire–prone provinces compared with children living in non-forest fire–prone provinces (mean difference = −1.16%, 95% CI [–2.53, 0.21]). RCPM scores were lower for children who had lived in a forest fire–prone province all their lives compared with children who lived in a non-forest fire–prone province all their life (β = −1.50%; 95% CI [–2.94, –0.07]). Living in a forest fire–prone province for a prolonged period of time negatively affected cognitive scores after adjusting for individual factors.
Smoke haze due to vegetation and peatland fires in Southeast Asia is a serious public health concern. Several approaches have been applied in previous studies; however, the concepts and interpretations of these approaches are poorly understood. In this scoping review, we addressed issues related to the application of epidemiology (EPI), health burden estimation (HBE), and health risk assessment (HRA) approaches, and discussed the interpretation of findings, and current research gaps. Most studies reported an air quality index exceeding the ‘unhealthy’ level, especially during smoke haze periods. Although smoke haze is a regional issue in Southeast Asia, studies on its related health effects have only been reported from several countries in the region. Each approach revealed increased health effects in a distinct manner: EPI studies reported excess mortality and morbidity during smoke haze compared to non-smoke haze periods; HBE studies estimated approximately 100,000 deaths attributable to smoke haze in the entire Southeast Asia considering all-cause mortality and all age groups, which ranged from 1,064-260,000 for specified mortality cause, age group, study area, and study period; HRA studies quantified potential lifetime cancer and non-cancer risks due to exposure to smoke-related chemicals. Currently, there is a lack of interconnection between these three approaches. The EPI approach requires extensive effort to investigate lifetime health effects, whereas the HRA approach needs to clarify the assumptions in exposure assessments to estimate lifetime health risks. The HBE approach allows the presentation of health impact in different scenarios, however, the risk functions used are derived from EPI studies from other regions. Two recent studies applied a combination of the EPI and HBE approaches to address uncertainty issues due to the selection of risk functions. In conclusion, all approaches revealed potential health risks due to smoke haze. Nonetheless, future studies should consider comparable exposure assessments to allow the integration of the three approaches.
Due to climate change, catastrophic events such as landscape fires are increasing in frequency and severity. However, relatively little is known about the longer-term mental health outcomes of such events. Follow-up was conducted of 709 adults exposed to smoke from the 2014 Hazelwood mine fire in Morwell, Victoria, Australia. Participants completed two surveys evaluating posttraumatic distress, measured using the Impact of Events Scale-Revised (IES-R), three and six years after the mine fire. Mixed-effects regression models were used to evaluate longitudinal changes in distress. IES-R total scores increased on average by 2.6 points (95%CI: 1.2 to 3.9 points) between the two survey rounds, with increases across all three posttraumatic distress symptom clusters, particularly intrusive symptoms. This increase in distress was evident across all levels of fine particulate matter (PM(2.5)) exposure to the mine fire smoke. Age was an effect modifier between mine fire PM(2.5) exposure and posttraumatic distress, with younger adults impacted more by exposure to the mine fire. Greater exposure to PM(2.5) from the mine fire was still associated with increased psychological distress some six years later, with the overall level of distress increasing between the two survey rounds. The follow-up survey coincided with the Black Summer bushfire season in south-eastern Australia and exposure to this new smoke event may have triggered distress sensitivities stemming from exposure to the earlier mine fire. Public health responses to disaster events should take into consideration prior exposures and vulnerable groups, particularly younger adults.
The 2019-20 bushfires that raged in eastern Australia were an overwhelming natural disaster leading to lives lost or upended, and communities destroyed. For almost a month, Canberra, Australia’s capital city in the Australian Capital Territory (ACT), was obscured by smoke from fires which threatened the outer suburbs. While smoke itself is experientially different from many natural disasters, it nevertheless poses a significant public health threat. As the impact of extended bushfire smoke in an urban setting is relatively unexplored we aimed to capture the individual and community-level experiences of the event and their importance for community and social functioning. We responded rapidly by conducting semi-structured interviews with a range of Canberra residents who, due to their personal or social circumstances, were potentially vulnerable to the effects of the smoke. Three major themes emerging from the narratives depicted disruption to daily life, physical and psychological effects, and shifting social connectedness. This study highlighted the ambiguous yet impactful nature of a bushfire smoke event, and identified four simple key messages that may be critically relevant to policy making in preparation for similar smoke events in the future.
The 2019-2020 summer wildfire event on the east coast of Australia was a series of major wildfires occurring from November 2019 to end of January 2020 across the states of Queensland, New South Wales (NSW), Victoria and South Australia. The wildfires were unprecedent in scope and the extensive character of the wildfires caused smoke pollutants to be transported not only to New Zealand, but also across the Pacific Ocean to South America. At the peak of the wildfires, smoke plumes were injected into the stratosphere at a height of up to 25 km and hence transported across the globe. The meteorological and air quality Weather Research and Forecasting with Chemistry (WRF-Chem) model is used together with the air quality monitoring data collected during the bushfire period and remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites to determine the extent of the wildfires, the pollutant transport and their impacts on air quality and health of the exposed population in NSW. The results showed that the WRF-Chem model using Fire Emission Inventory (FINN) from National Center for Atmospheric Research (NCAR) to simulate the dispersion and transport of pollutants from wildfires predicted the daily concentration of PM2.5 having the correlation (R-2) and index of agreement (IOA) from 0.6 to 0.75 and 0.61 to 0.86, respectively, when compared with the ground-based data. The impact on health endpoints such as mortality and respiratory and cardiovascular diseases hospitalizations across the modelling domain was then estimated. The estimated health impact on each of the Australian Bureau of Statistics (ABS) census districts (SA4) of New South Wales was calculated based on epidemiological assumptions of the impact function and incidence rate data from the 2016 ABS and NSW Department of Health statistical health records. Summing up all SA4 census district results over NSW, we estimated that there were 247 (CI: 89, 409) premature deaths, 437 (CI: 81, 984) cardiovascular diseases hospitalizations and 1535 (CI: 493, 2087) respiratory diseases hospitalizations in NSW over the period from 1 November 2019 to 8 January 2020. The results are comparable with a previous study based only on observation data, but the results in this study provide much more spatially and temporally detailed data with regard to the health impact from the summer 2019-2020 wildfires.
Persistent and intensive wildland dense-fires (DFs) release substantial amounts of airborne pollutants, resulting in a sharp increase in emissions and leading to serious impacts on the environment and human health over extensive geographical areas. It is challenging to thoroughly investigate patterns of fire occurrence and fire distribution for predicting wildfire behaviour, and it is especially difficult to distinguish the characteristics of human-caused and climate-driven fires. Here, we identify and assess dense-fire (DF) from the perspective of spatiotemporally integrated processes using a machine-learning method based on a density-based clustering algorithm with noise constraint ratio. DFs represent collections of fires with homogenous behaviour and therefore allow the study of their internal features, which can reveal fixed patterns of fire occurrence and dis-tribution as well as the evolution of fires over time. We estimated and labelled thousands of fire clusters on the Indochina Peninsula between 2010 and 2020, most of which occurred between December and May. For large-scale DFs, the number of fires contained and amount of atmospheric pollutants emitted were accounted for throughout most of the region, and the time, location and scale of their occurrence each year were relatively stable and predictable. Furthermore, the results of a secondary cluster analysis of fire interactions over the past decade showed two extreme fire events, labelled “north ” and “south ” groups, whose activities significantly impacted the atmospheric environment of the Indochina Peninsula. Additionally, we predicted their start/end dates and daily emissions. The study also found that the recurrence of high-density fires and the correlation between the DF edge and administrative border suggested a positive anthropogenic influence. To the authors’ knowledge, this study is the first to analyze fires in a spatiotemporal Euclidean space by using density-based clustering, with high-density fires as independent subjects to study fire behaviour. The method proposed in this study can provide a reference for wildfire prediction and emission forecasting and fire control work.
Evidence of the acute effects of air pollutants on ischemic heart disease (IHD) hospitalizations based on the entire population of a megacity in central China is lacking. All IHD hospitalization records from 2017 to 2018 were obtained from the Wuhan Information Center of Health and Family Planning. Daily air pollutant concentrations and meteorological data were synchronously collected from the Wuhan Environmental Protection Bureau. A time-series study using generalized additive models was conducted to systematically examine the associations between air pollutants and IHD hospitalizations. Stratified analyses by gender, age, season, hypertension, diabetes, and hyperlipidemia were performed. In total, 139,616 IHD hospitalizations were included. Short-term exposure to air pollutants was positively associated with IHD hospitalizations. The age group ≥ 76 was at higher exposure risk, and the associations appeared to be more evident in cold seasons. PM(2.5) and PM(10) appeared to have greater effects on males and those without hypertension or diabetes, whereas NO(2) and SO(2) had greater effects on females and those with hypertension or diabetes. The risk of IHD hospitalization due to air pollutants was greater in people without hyperlipidemia. Our study provides new evidence of the effects of air pollution on the increased incidence of IHD in central China.
Recent evidence shows that carbon emissions in China are likely to peak ahead of 2030. However, the social and economic impacts of such an early carbon peak have rarely been assessed. Here we focus on the economic costs and health benefits of different carbon mitigation pathways, considering both possible socio-economic futures and varying ambitions of climate policies. We find that an early peak before 2030 in line with the 1.5 °C target could avoid ~118,000 and ~614,000 PM(2.5) attributable deaths under the Shared Socioeconomic Pathway 1, in 2030 and 2050, respectively. Under the 2 °C target, carbon mitigation costs could be more than offset by health co-benefits in 2050, bringing a net benefit of $393-$3,017 billion (in 2017 USD value). This study not only provides insight into potential health benefits of an early peak in China, but also suggests that similar benefits may result from more ambitious climate targets in other countries.
Background: Previous studies suggested that exposure to air pollution could increase risk of asthma attacks in children. The aim of this study is to investigate the short-term effects of exposure to ambient air pollution on asthma hospital admissions in children in Beijing, a city with serious air pollution and high-quality medical care at the same time. Methods: We collected hospital admission data of asthma patients aged ?ëñ 18 years old from 56 hospitals from 2013 to 2016 in Beijing, China. Time-stratified case-crossover design and conditional Poisson regression were applied to explore the association between risk of asthma admission in children and the daily concentration of six air pollutants [particulate matter ?ëñ 2.5 ??m (PM(2.5)), particulate matter ≤ μm (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), carbon monoxide (CO), and ozone (O(3))], adjusting for meteorological factors and other pollutants. Additionally, stratified analyses were performed by age, gender, and season. Results: In the single-pollutant models, higher levels of PM(2.5), SO(2), and NO(2) were significantly associated with increased risk of hospital admission for asthma in children. The strongest effect was observed in NO(2) at lag06 (RR = 1.25, 95%CI: 1.06-1.48), followed by SO(2) at lag05 (RR = 1.17, 95%CI: 1.05-1.31). The robustness of effects of SO(2) and NO(2) were shown in two-pollutant models. Stratified analyses further indicated that pre-school children (aged ≤ 6 years) were more susceptible to SO(2). The effects of SO(2) were stronger in the cold season, while the effects of NO(2) were stronger in the warm season. No significant sex-specific differences were observed. Conclusions: These results suggested that high levels of air pollution had an adverse effect on childhood asthma, even in a region with high-quality healthcare. Therefore, it will be significant to decrease hospital admissions for asthma in children by controlling air pollution emission and avoiding exposure to air pollution.
Electric vehicle (EV) adoption promises potential air pollutant and greenhouse gas (GHG) reduction co-benefits. As such, China has aggressively incentivized EV adoption, however much remains unknown with regard to EVs’ mitigation potential, including optimal vehicle type prioritization, power generation contingencies, effects of Clean Air regulations, and the ability of EVs to reduce acute impacts of extreme air quality events. Here, we present a suite of scenarios with a chemistry transport model that assess the potential co-benefits of EVs during an extreme winter air quality event. We find that regardless of power generation source, heavy-duty vehicle (HDV) electrification consistently improves air quality in terms of NO2 and fine particulate matter (PM2.5), potentially avoiding 562 deaths due to acute pollutant exposure during the infamous January 2013 pollution episode (similar to 1% of total premature mortality). However, HDV electrification does not reduce GHG emissions without enhanced emission-free electricity generation. In contrast, due to differing emission profiles, light-duty vehicle (LDV) electrification in China consistently reduces GHG emissions (similar to 2 Mt CO2), but results in fewer air quality and human health improvements (145 avoided deaths). The calculated economic impacts for human health endpoints and CO2 reductions for LDV electrification are nearly double those of HDV electrification in present-day (155M vs. 87M US$), but are within similar to 25% when enhanced emission-free generation is used to power them. Overall, we find only a modest benefit for EVs to ameliorate severe wintertime pollution events, and that continued emission reductions in the power generation sector will have the greatest human health and economic benefits.
The epidemiological evidence on relationships between air pollution, temperature, and stroke remains inconclusive. Limited evidence is available for the effect modification by apparent temperature, an indicator reflecting reactions to the thermal environment, on short-term associations between air pollution and hospital admissions for stroke. We used a generalized additive model with Poisson regression to estimate the relative risk (RR) of stroke admissions in Shanghai, China, between 2014 and 2016 associated with air pollutants, with subgroup analyses by age, sex, apparent temperature, and season. During the study period, changes in the daily number of stroke admissions per 10 μg/m(3) increase in nitrogen dioxide (at lags 0, 1, 0-1, and 0-2) ranged from 1.05 (95% CI: 0.82%, 2.88%) to 2.24% (95% CI: 0.84%, 3.65%). For each 10 μg/m(3) increase in sulfur dioxide concentrations at lags 1, 2, 0-1, and 0-2, the RR of daily stroke admissions increased by 3.34 (95% CI: 0.955%, 5.79%), 0.32 (95% CI: -1.97%, 2.67%), 3.33 (95% CI: 0.38%, 6.37%), and 2.86% (95% CI: -0.45%, 6.28%), respectively. The associations of same-day exposure to nitrogen dioxide with stroke admissions remained significant after adjustment for ozone levels. These associations were not modified by sex, age, apparent temperature, or season. More research is warranted to determine whether apparent temperature modifies the associations between air pollution and stroke admissions.
Chronic obstructive pulmonary disease (COPD) is the fourth major cause of mortality and morbidity worldwide and is projected to be the third by 2030. However, there is little evidence available on the associations of COPD hospitalizations with meteorological factors and air pollutants in developing countries/regions of Asia. In particular, no study has been done in western areas of China considering the nonlinear and lagged effects simultaneously. This study aims to evaluate the nonlinear and lagged associations of COPD hospitalizations with meteorological factors and air pollutants using time-series analysis. The modified associations by sex and age were also investigated. The distributed lag nonlinear model was used to establish the association of daily COPD hospitalizations of all 441 public hospitals in Chengdu, China from Jan/2015-Dec/2017 with the ambient meteorological factors and air pollutants. Model parameters were optimized based on quasi Akaike Information Criterion and model diagnostics was conducted by inspecting the deviance residuals. Subgroup analysis by sex and age was also performed. Temperature, relative humidity, wind and Carbon Monoxide (CO) have statistically significant and consistent associations with COPD hospitalizations. The cumulative relative risk (RR) was lowest at a temperature of 19℃ (relative humidity of 67%). Both extremely high and low temperature (and relative humidity) increase the cumulative RR. An increase of wind speed above 4 mph (an increase of CO above 1.44 mg/m(3)) significantly decreases (increases) the cumulative RR. Female populations were more sensitive to low temperature and high CO level; elderly (74+) populations are more sensitive to high relative humidity; younger populations (< = 74) are more susceptible to CO higher than 1.44 mg/m(3). Therefore, people with COPD should avoid exposure to adverse environmental conditions of extreme temperatures and relative humidity, low wind speed and high CO level, especially for female and elderly patients who were more sensitive to extreme temperatures and relative humidity.
South Korea had the highest annual average PM2.5 exposure levels in the Organization for Economic Co-operation and Development (OECD) in 2019, and air pollution is consistently ranked as citizens’ top environmental concern. South Korea is also one of the world’s top ten emitter countries of CO2. Co-benefit mitigation policies can address both air pollution and climate change. Utilizing an alternative co-benefit approach, which views air pollution reduction as the primary goal and climate change mitigation as secondary, this research conducts a scenario analysis to forecast the health and climate benefits of fuel substitution in South Korea’s electricity generation sector. Health benefits are calculated by avoided premature mortality and years of life lost (YLL) due to ischemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lung cancer, and acute lower respiratory infections (ALRI). The study finds that use of liquefied natural gas (LNG) instead of coal over the 2022-2050 period would result in an average of 116 fewer premature deaths (1152 YLL) and 80.8 MTCO(2)e fewer emissions per year. Over the same period, maintaining and maximizing the use of its nuclear energy capacity, combined with replacing coal use with LNG, would result in an average of 161 fewer premature deaths (1608 YLL) and 123.7 MTCO(2)e fewer emissions per year.
This article quantifies the environmental, health, and economic co-benefits from the use of solar electricity and heat generation in the Ger area (a sub-district of traditional residences and private houses) in Ulaanbaatar (UB), Mongolia. The quantification of the featured co-benefits is based on calculating emissions reductions from the installation of the solar photovoltaic (PV) and solar water heaters. A user-friendly spreadsheet tool is developed to shed much-needed light on the steps involved in estimating these co-benefits. The tool simulates the hourly electricity and thermal energy generation, taking into account local meteorological conditions, local geographical data, and technical specifications of the solar power and heat generation systems. The tool is then employed to evaluate two intervention scenarios: (1) Installing 100 MW solar electricity, including both rooftop PV and community grids, to reduce the peak-load burden on the grid; (2) Providing solar thermal heaters for 20,000 households to replace the heating load demand from the existing heat only boilers (HOBs) in UB. The modelling results reveal a significant reduction in GHG emissions and fine particulate matter (PM(2.5)) (PM that is 2.5 microns or less in diameter) by 311,000 tons and 767 tons, respectively, as well as nearly 6500 disability-adjusted life years (DALYs) and an annual saving of USD 7.7 million for the local economy. The article concludes that the mainstreaming spreadsheet-based estimation tools like the one used in this article into decision-making processes can fill important research gaps (e.g., usability of assessment tools) and help translate co-benefits analyses into action in Mongolia and beyond.
Pollution of the environment is increasing and threatens the health and wellbeing of adults and children around the globe. The impact of air pollution on pulmonary and cardiovascular disease has been well documented, but it also has a deleterious effect on reproductive health. Ulaanbaatar, the capital city of Mongolia, has one of the highest levels of air pollution in the world. During the extreme winters when temperatures routinely fall below -20 degrees C the level of air pollution can reach 80 times the WHO recommended safe levels. Heating mainly comes from coal, which is burned both in power stations, and in stoves in the traditional Ger housing. We studied the impact of air pollution on conception rates and birth outcomes in Ulaanbaatar using a retrospective analysis of health data collected from the Urguu Maternity hospital in Ulaanbaatar, Mongolia. Daily levels of SO2, NO2, PM10, and PM2.5 were collected from the government Air Quality Monitoring Stations in Ulaanbaatar for the same period as the study. In January, the month of highest pollution, there is a 3.2-fold decrease in conceptions that lead to the successfully delivered infants compared to October. The seasonal variations in conceptions resulting in live births in this study in Ulaanbaatar are shown to be 2.03 +/- 0.20 (10-sigma) times greater than those in the Denmark/North America study of Wesselink et al., 2020. The two obvious differences between Ulaanbaatar and Europe/North America are pollution and temperature both of which are extreme in Ulaanbaatar. The extreme low temperature is mitigated by burning coal, which is the main source of domestic heat especially in the ger districts. This drives the level of pollution so the two are inextricably linked. Infants conceived in the months of June-October had the greatest cumulative PM2.5 pollution exposure over total gestation, yet these were also the pregnancies with the lowest PM2.5 exposure for the month of conception and three months prior to conception. The delivered-infant conception rate shows a markedly negative association with exposure to PM2.5 prior to and during the first month of pregnancy. This overall reduction in fecundity of the population of Ulaanbaatar is therefore a preventable health risk. It is of great consequence that the air pollution in Ulaanbaatar affects health over an entire lifespan including reproductive health. This could be remedied with a clean source of heating.
OBJECTIVES: To investigate associations between long-term exposure to PM(2.5), NO(2), mortality and morbidity in New Zealand, a country with low levels of exposure. DESIGN: Retrospective cohort study. SETTING: The New Zealand resident population. METHOD: The main analyses included all adults aged 30 years and over with complete data on covariates: N = 2,223,507. People who died, or were admitted to hospital, (2013-2016) were linked anonymously to the 2013 census, and to estimates of ambient PM(2.5), and NO(2) concentration. We fitted Poisson regression models of mortality and morbidity in adults (≥30) for all natural causes of death, and by sub- group of major cause. Person-time of exposure, censored at the time of death, was included as an offset. We adjusted for confounding by age, sex, ethnicity, income, education, smoking status and ambient temperature. Further analyses stratified by ethnic group, and investigated respiratory hospital admissions in children. RESULTS: There were statistically significant positive associations between pollutants and natural causes of death: RR (per 10 μg/m(3)) for PM(2.5) 1.11 (1.07 to 1.15) and for NO(2) 1.10 (1.07 to 1.12). For morbidity, the strongest associations were for PM(2.5) and ischaemic heart disease in adults, RR: 1.29 (1.23 to 1.35) and for NO(2) and asthma in children, RR: 1.18 (1.09 to 1.28). In models restricted to specific ethnic groups, we found no consistent differences in any of the associations. CONCLUSIONS: The results for NO(2) are higher than those published previously. Other studies have reported that the dose-response for PM(2.5) may be higher at low concentrations, but less is known about NO(2). It is possible NO(2) is acting as a proxy for other traffic-related pollutants that are causally related to health impacts. This study underlines the importance of controlling pollution caused by motor vehicles.
This study examines how human capital develops in response to early-life weather and pollution exposures in the Philippines. Both pollution and weather are examined in relation to short- and long-term human capital outcomes. We combine a three-decade longitudinal survey measuring human capital development, a database of historical weather, and multiple databases characterizing carbon monoxide and ozone in the Philippines during the 1980s. We find evidence that extreme precipitation and temperature affect short-term anthropometric outcomes, but long-term outcomes appear unaffected. For long-term cognitive outcomes, we find that early-life pollution exposures negatively affect test scores and schooling. These long-term responses to early-life pollution exposures extend to the labor market with reduced hours worked and earnings. The implication is that a 25 per cent reduction in early-life ozone exposure would increase per person discounted lifetime earnings by $1,367, which would scale to $2.05 billion at the national level (or 2 per cent of 2005 GDP).
There is a dearth of research on the hourly risk of ambulance dispatches with respect to ambient conditions. We evaluated hourly relative risks (RR) and 95% confidence interval (CI) of ambulance dispatches in Taiwan to treat respiratory distress, coma and unconsciousness, and out-of-hospital cardiac arrest (OHCA), from 2006 to 2015. We considered island-wide ambient temperatures, fine particulate matter (PM(2.5)), and ozone (O(3)) at lag 0-180 h while using a distributed lag nonlinear model and meta-analysis. Results showed the pooled risks peaked at lag 16-18 h for all ambulance dispatches at 99th percentile of hourly temperature (32 °C, versus reference temperature of 25 °C), with significant excess risk of 0.11% (95% CI; 0.06, 0.17) for coma and unconsciousness, and 0.06% (95% CI; 0.01, 0.11) for OHCA. The risks of exposure to 90th percentile of hourly O(3) of 52.3 ppb relative to the Q1 level of 17.3 ppb peaked at lag 14 h, with excess risk of 0.17% (95% CI; 0.11, 0.23) for respiratory distress, 0.11% (95% CI; 0.06, 0.16) for coma and unconsciousness, and 0.07% (95% CI; 0.01, 0.14) for OHCA. The population exposed to reference temperatures of 28 °C, 20 °C, and 26 °C were exposed to the lowest levels of ambulance dispatches risk for respiratory distress, coma and unconsciousness, and OHCA, respectively; the highest cumulative 0-96 h RRs of ambulance dispatches were 1.27 (95% CI; 1.19, 1.35) for OHCA at 5th percentile temperatures and 1.25 (95% CI; 1.11, 1.41) for OHCA at 99th percentile temperatures. Following an accumulating lag of 0-96 h, no significant risk was identified for hourly levels of PM(2.5) and O(3). In conclusion, the analytical results of hourly data speak to immediate and real-time responses to environmental changes, rather than to short-term relationships. In our analyses, we emphasized health events in extreme heat; thus, we recommend a comparative study of daily versus hourly associations.
OBJECTIVE: To determine the association of meteorological factors and air pollutants (MFAPs) with fracture and to estimate the effect size/time lag. DESIGN: This is a nationwide population-based ecological study from 2008 to 2017. SETTING: Eight large metropolitan areas in Korea. PARTICIPANTS: Of 8 093 820 patients with fractures reported in the Korea National Health Insurance database, 2 129 955 were analysed after the data set containing patient data (age, sex and site of fractures) were merged with MFAPs. Data on meteorological factors were obtained from the National Climate Data Center of the Korea Meteorological Administration. Additionally, data on air pollutants (atmospheric particulate matter ≤2.5 µm in diameter (PM(2.5)), PM(10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide) were obtained from the Air Korea database. PRIMARY AND SECONDARY OUTCOME MEASURES: We hypothesised that there would be an association between MFAPs and the incidence of fracture. A generalised additive model was used while factoring in the non-linear relationship between MFAPs and fractures as well as a time lag ≤7 days. Multivariate analysis was performed. Backward elimination with an Akaike information criterion was used to fit the multivariate model. RESULTS: Overall, in eight urban areas, 2 129 955 patients with fractures were finally analysed. These included 370 344, 187 370, 173 100, 140 358, 246 775, 6501, 228 346, 57 183 and 719 978 patients with hip, knee, shoulder, elbow, wrist, hand, ankle, foot and spine fractures, respectively. Various MFAPs (average temperature, daily rain, wind speed, daily snow and PM(2.5)) showed significant association with fractures, with positive correlations at time lags 7, 5-7, 5-7, 3-7 and 6-7 days, respectively. CONCLUSIONS: Various MFAPs could affect the occurrence of fractures. The average temperature, daily rain, wind speed, daily snow and PM(2.5) were most closely associated with fracture. Thus, improved public awareness on these MFAPs is required for clinical prevention and management of fractures.
The biological mechanisms underlying the associations between atmospheric ozone exposure and adverse cardiometabolic outcomes are yet to be identified. Imbalanced autonomic nervous system (ANS) as well as activations of the sympatho-adrenomedullary (SAM) and hypothalamic-pituitary-adrenal (HPA) axes are among possible early biological responses triggered by ozone, and may eventually lead to cardiometabolic abnormalities. To determine whether acute ozone exposure causes ANS imbalance and increases the secretion of neuroendocrine stress hormones, we conducted a randomized, double-blind, crossover trial, under controlled 2-hour exposure to either ozone (200 ppb) or clean air with intermittent exercise among 22 healthy young adults. Here we found that, compared to clean air exposure, acute ozone exposure significantly decreased the high-frequency band of heart rate variability, even after adjusting for heart rate and pre-exposure to ambient air pollutants and meteorological factors. Ozone exposure also significantly increased the serum levels of stress hormones, including corticotrophin-releasing factor, adrenocorticotropic hormone, adrenaline, and noradrenaline. Metabolomics analysis showed that acute ozone exposure led to alterations in stress hormones, systemic inflammation, oxidative stress, and energy metabolism. Our results suggest that acute ozone exposure may trigger ANS imbalance and activate the HPA and SAM axes, offering potential biological explanations for the adverse cardiometabolic effects following acute ozone exposure.
Air pollution causes adverse effects not only on the environment but also on human health. This study evaluated the excess mortalities in continental Southeast Asia that are related to future O-3 and PM2.5 ambient concentration changes attributed to future climate change and emission change. The Environmental Benefits Mapping and Analysis Program -Community Edition (BenMAP-CE) was applied as a health impact assessment tool. In BenMAP-CE simulations, baseline scenarios presenting for the present year (2014) were compared against the control scenarios presenting for the future year (2050). The air pollutant concentrations for the simulations were collected from modeled data. The future population data and baseline incidence rates were as same as the 2014 levels. In four calculating countries namely Laos, Cambodia, Thailand, and Vietnam, on average, impacted by climate change alone, the avoided mortalities of -1164 and -3358 under Representative Concentration Pathway (RCP) 4.5 scenario and the additional mortalities of +758 and +2562 under RCP8.5 scenario were calculated for O-3 and PM2.5, respectively. Future emission change alone under Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants current legislation (ECLIPSE CLE) scenario induces +7113 and +11072 additional O-3 and PM2.5 related mortalities, respectively. Combined change in climate and emission produces additional O-3 and PM2.5 related mortalities of +6067 and +7830 under RCP4.5 and ECLIPSE CLE combined scenario and +8763 and +14580 under RCP8.5 and ECLIPSE CLE combined scenario, respectively. The results of this study provided meaningful information for understanding the public health attributed to air pollution in the region.
BACKGROUND/AIMS: Weather and air pollution are associated with the exacerbation of respiratory diseases. We investigated patterns of medical care use according to meteorological factors and air pollution in patients with asthma or chronic obstructive pulmonary disease (COPD). METHODS: We analyzed the medical care utilization patterns of patients with asthma or COPD registered in the Korea Health Insurance Review and Assessment database for the period 2007 to 2013. The patterns were divided into hospitalization and emergency department (ED) use. RESULTS: The medical care use of patients with asthma or COPD increased when the mean temperature and relative humidity were lower, and the temperature difference and atmospheric pressure were greater. Medical care use increased with the concentrations of particulate matter and ozone. Among age groups, sensitivity to pollutants was greatest in patients aged ≥ 65 years. The effect of being elderly was greater for asthma than for COPD, with a higher hospitalization rate. ED utilization affected by environmental factors was significantly greater for females and hospitalization was significantly more common for males. CONCLUSION: Meteorological factors and air pollutants were shown to contribute to increased medical care utilization by patients with asthma and COPD, particularly elderly patients. The overall effect was greater for COPD, but the effect in elderly patients was greater for asthma. In addition, the patterns of change in medical care use due to environmental factors differed according to sex.
With the development of the economy and the accumulation of social wealth, urban residents have begun to give more attention to quality of life than to material needs. Consequently, environmental factors that affect human health, such as air quality, have become a new focus when traveling. A travel scheme with relatively low pollutant exposure to travelers can not only improve their health and satisfy their goals but also benefit social stability and sustained progress. However, low spatiotemporal resolution and coarse spatial details of the distribution of PM2.5 (particles with an aerodynamic diameter of 2.5 mu m or less) educe the success rate of short distance healthy travel route planning. This paper proposes a short-distance healthy route planning approach that is based on PM2.5 retrieval with high spatiotemporal resolution and a dynamic Dijkstra algorithm. First, fine spatial resolution images, meteorological data, and socioeconomic data are used to retrieve the spatial distribution of PM2.5 concentration in hourly intervals via a back-propagation neural network (BPNN). Second, a PM2.5 concentration value is obtained for each road section, and the harm degree to the human body is calculated as the weight of each road section. Then, the healthiest route is obtained based on the Dijkstra algorithm. Finally, the route planning effectiveness is verified by comparing the PM2.5 potential dose descending rate between the healthy route and the shortest route. The results show that the coefficient of determination (R2) of the PM2.5 retrieval approach that is based on multisource data and BPNN is 0.85, which can ensure the accuracy of the PM2.5 data at the street level. On this basis, the potential dose reduction rate of the healthy route can reach up to 20%, which proves that our approach can perform well. It can effectively improve the safety of travel and alleviate the anxiety that is caused by air pollution. In addition, it provides an easy implementation strategy for software for health management.
Over the past few decades, due to human activities, industrialization, and urbanization, air pollution has become a life-threatening factor in many countries around the world. Among air pollutants, Particulate Matter with a diameter of less than 2.5 μm ( PM2.5 ) is a serious health problem. It causes various illnesses such as respiratory tract and cardiovascular diseases. Hence, it is necessary to accurately predict the PM2.5 concentrations in order to prevent the citizens from the dangerous impact of air pollution beforehand. The variation of PM2.5 depends on a variety of factors, such as meteorology and the concentration of other pollutants in urban areas. In this paper, we implemented a deep learning solution to predict the hourly forecast of PM2.5 concentration in Beijing, China, based on CNN-LSTM, with a spatial-temporal feature by combining historical data of pollutants, meteorological data, and PM2.5 concentration in the adjacent stations. We examined the difference in performances among Deep learning algorithms such as LSTM, Bi-LSTM, GRU, Bi-GRU, CNN, and a hybrid CNN-LSTM model. Experimental results indicate that our method hybrid CNN-LSTM multivariate enables more accurate predictions than all the listed traditional models and performs better in predictive performance.
BACKGROUND: Smaller sizes of ambient particulate matter (PM) can be more toxic and can be breathed into lower lobes of a lung. Children are particularly vulnerable to PM air pollution because of their adverse effects on both lung functions and lung development. However, it remains unknown whether a smaller PM has a greater short-term impact on childhood pneumonia. AIMS: We compared the short-term effects on childhood pneumonia from PM with aerodynamic diameters ≤1 μm (PM(1)), ≤2.5 μm (PM(2.5)), and ≤10 μm (PM(10)), respectively. METHODS: Daily time-series data (2016-2018) on pneumonia hospitalizations in children aged 0-17 years, records of air pollution (PM(1), PM(2.5), PM(10), and gaseous pollutants), and weather conditions were obtained for Hefei, China. Effects of different PM were quantified using a quasi-Poisson generalized additive model after controlling for day of the week, holiday, seasonality and long-term time trend, and weather variables. Stratified analyses (gender, age, and season) were also performed. RESULTS: For each 10 μg/m(3) increase in PM(1), PM(2.5), and PM(10) concentrations over the past three days (lag 0-2), the risk of pneumonia hospitalizations increased by 10.28% (95%CI: 5.88%-14.87%), 1.21% (95%CI: 0.34%-2.09%), and 1.10% (95%CI: 0.44%-1.76%), respectively. Additionally, both boys and girls were at risk of PM(1) effects, while PM(2.5) and PM(10) effects were only seen in boys. Children aged ≤12 months and 1-4 years were affected by PM(1), but PM(2.5) and PM(10) were only associated with children aged 1-4 years. Furthermore, PM(1) effects were greater in autumn and winter, while greater PM(2.5) and PM(10) effects were evident only in autumn. CONCLUSION: This study suggests a greater short-term impact on childhood pneumonia from PM(1) in comparison to PM(2.5) and PM(10). Given the serious PM pollution in China and other rapid developing countries due to various combustions and emissions, more investigations are needed to determine the impact of different PM on childhood respiratory health.
OBJECTIVE: Acute tonsillitis is a common disease in otorhinolaryngology. Meteorological factors can affect the incidence of many infectious diseases. This study aims to analyze the correlation between acute tonsillitis and meteorological conditions. MATERIALS AND METHODS: We collected the meteorological data, including daily temperature, humidity, and fine particulate matter (PM(2.5)) of Shanghai, China, from 2014 to 2015. The monthly number of acute tonsillitis cases in our hospital was also calculated and used as the outcome variable. The associations between them were evaluated, respectively. RESULTS: The average number of patients diagnosed with acute tonsillitis in our hospital per month was 68.67 ± 18.67 from 2014 to 2015. The average temperature, humidity, and PM(2.5) of Shanghai during the defined period was 16.84 °C ± 7.80 °C, 75.93% ± 5.45%, and 52.38 ± 14.23 μg/m(3), respectively. The temperature was significantly positively associated with the acute tonsillitis cases number both in Pearson correlation analysis (R = 0.423, P = .039) and in multivariate regression analysis (coefficient =2.194, P = .012). However, no correlation between the acute tonsillitis cases number and relative humidity or PM(2.5) was found through a multivariate regression model (P = .225 and P = .243), respectively. CONCLUSION: The high temperature was associated with an increased incidence of acute tonsillitis.
An outdoor solar assisted large-scale cleaning system (SALSCS) was constructed to mitigate the levels of fine particulate matter (PM(2.5)) in urban areas of Xi’an China, providing a quasi-experimental opportunity to examine the biologic responses to the changes in pollution level. We conducted this outdoor SALSCS based real-world quasi-interventional study to examine the associations of the SALSCS intervention and changes in air pollution levels with the biomarkers of systemic inflammation and oxidative stress in healthy elders. We measured the levels of 8-hydrox-2-deoxyguanosine (8-OHdG), Interlukin-6 (IL-6), as well as tumor necrosis factor alpha (TNF-α) from urine samples, and IL-6 from saliva samples of 123 healthy retired participants from interventional/control residential areas in two sampling campaigns. We collected daily 24-h PM(2.5) samples in two residential areas during the study periods using mini-volume samplers. Data on PM(10), gaseous pollutants and weather factors were collected from the nearest national air quality monitoring stations. We used linear mixed-effect models to examine the percent change in each biomarker associated with the SALSCS intervention and air pollution levels, after adjusting for time trend, seasonality, weather factors and personal characteristics. Results showed that the SALSCS intervention was significantly associated with decreases in the geometric mean of biomarkers by 47.6% (95% confidence interval: 16.5-67.2%) for 8-OHdG, 66% (31.0-83.3%) for TNF-α, 41.7% (0.2-65.9%) and 43.4% (13.6-62.9%) for urinary and salivary IL-6, respectively. An inter-quartile range increase of ambient PM(2.5) exposure averaged on the day of the collection of bio-samples and the day before (34.1 μg/m(3)) was associated, albeit non-significantly so, with 22.8%-37.9% increases in the geometric mean of these biomarkers. This study demonstrated that the SALSCS intervention and decreased ambient air pollution exposure results in lower burden of systemic inflammation and oxidative stress in older adults.
BACKGROUND: Evidences have shown that the stroke risk associated with long-term exposure to particulate matter with an aerodynamic diameter of ≤2.5 μm (PM(2.5)) varies among people in North America, Europe and Asia, but studies in Asia rarely evaluated the association by stroke type. We examined whether long-term exposure to PM(2.5) is associated with developing all strokes, ischemic stroke and hemorrhagic stroke. METHODS: The retrospective cohort study consisted of 1,362,284 adults identified from beneficiaries of a universal health insurance program in 2011. We obtained data on air pollutants and meteorological measurements from air quality monitoring stations across Taiwan in 2010-2015. Annual mean levels of all environmental measurements in residing areas were calculated and assigned to cohort members. We used Cox proportional hazards models to estimate hazard ratio (HR) and 95% confidence interval (CI) of developing stroke associated with 1-year mean levels of PM(2.5) at baseline in 2010, and yearly mean levels from 2010 to 2015 as the time-varying exposure, adjusting for age, sex, income and urbanization level. RESULTS: During a median follow-up time of 6.0 years, 12,942 persons developed strokes, 9919 (76.6%) were ischemic. The adjusted HRs (95% CIs) per interquartile range increase in baseline 1-year mean PM(2.5) were 1.03 (1.00-1.06) for all stroke, 1.06 (1.02-1.09) for ischemic stroke, and 0.95 (0.89-1.10) for hemorrhagic stroke. The concentration-response curves estimated in the models with and without additional adjustments for other environmental measurements showed a positively linear association between baseline 1-year mean PM(2.5) and ischemic stroke at concentrations greater than 30 μg/m(3), under which no evidence of association was observed. There was an indication of an inverse association between PM(2.5) and hemorrhagic stroke, but the association no longer existed after controlling for nitrogen dioxide or ozone. We found similar shape of the concentration-response association in the Cox regression models with time-varying PM(2.5) exposures. CONCLUSION: Long-term exposure to PM(2.5) might be associated with increased risk of developing ischemic stroke. The association with high PM(2.5) concentrations remained significant after adjustment for other environmental factors.
What is already known about this topic? Climate change and air pollution are two important environmental issues in China. It is important to investigate particulate matter with aerodynamic diameter less than 2.5 μm (PM(2.5))-related health impacts from climate change and air pollution emission control. What is added by this report? Deaths and years of life lost related to PM(2.5) would increase in climate change scenario, although emission control would outweigh the influence of climate change. What are the implications for public health practice? More targeted actions should be taken to meet challenges of exacerbated PM(2.5) pollutions and its health impacts related to climate change in the future.
BACKGROUND: Scientific studies have identified various adverse effects of particulate matter (PM) on respiratory disease (RD) and type 2 diabetes (T2D). However, whether short-term exposure to PM triggers the onset of RD with T2D, compared with RD without T2D, has not been elucidated. METHODS: A two-stage time-series study was conducted to evaluate the acute adverse effects of PM on admission for RD and for RD with and without T2D in Beijing, China, from 2014 to 2020. District-specific effects of PM(2.5) and PM(10) were estimated using the over-dispersed Poisson generalized addictive model after adjusting for weather conditions, day of the week, and long-term and seasonal trends. Meta-analyses were applied to pool the overall effects on overall and cause-specific RD, while the exposure-response (E-R) curves were evaluated using a cubic regression spline. RESULTS: A total of 1550,154 admission records for RD were retrieved during the study period. Meta-analysis suggested that per interquartile range upticks in the concentration of PM(2.5) corresponded to 1.91% (95% CI: 1.33-2.49%), 2.16% (95% CI: 1.08-3.25%), and 1.92% (95% CI: 1.46-2.39%) increments in admission for RD, RD with T2D, and RD without T2D, respectively, at lag 0-8 days, lag 8 days, and lag 8 days. The effect size of PM(2.5) was statistically significantly higher in the T2D group than in the group without T2D (z = 3.98, P < 0.01). The effect sizes of PM(10) were 3.86% (95% CI: 2.48-5.27%), 3.73% (95% CI: 1.72-5.79%), and 3.92% (95% CI: 2.65-5.21%), respectively, at lag 0-13 days, lag 13 days, and lag 13 days, respectively, and no statistically significant difference was observed between T2D groups (z = 0.24, P = 0.81). Significant difference was not observed between T2D groups for the associations of PM and different RD and could be found between three groups for effects of PM(10) on RD without T2D. The E-R curves varied by sex, age and T2D condition subgroups for the associations between PM and daily RD admissions. CONCLUSIONS: Short-term PM exposure was associated with increased RD admission with and without T2D, and the effect size of PM(2.5) was higher in patients with T2D than those without T2D.
Most studies on the short-term local benefits of carbon mitigation technologies on air quality improvement and health focus on specific technologies such as biofuels or carbon sequestration technologies, while ignoring the overall role of the growing scale of low-carbon technologies. Based on STIRPAT model and EKC hypothesis, this paper takes 30 provinces in China from 2004 to 2016 as research samples. We builded the panel double fixed effect model to empirical analysis of climate change on carbon mitigation tech-innovation suppressing the influence of haze pollution, on this basis, the mediating effect model was used to explore the mediation function of industrial structure and energy structure. Meanwhile, we drawed on the existing studies on air quality and health benefits, and quantify the co-benefits of carbon mitigation tech-innovation on health through the equivalent substitution formula. It shows that a 1% increase in the number of low-carbon patent applications can reduce haze pollution by 0.066%. According to this estimate, to 2029, China’s carbon mitigation tech-innovation could reduce PM2.5 concentration to 15 μg/m(3) preventing 5.597 million premature deaths. Moreover, carbon mitigation tech-innovation can also indirectly inhibit haze pollution by triggering more systematic economic structure changes such as energy and industrial structure. Additionally, we found that the role of gray tech-innovation (GT) related to improving the efficiency of fossil energy is stronger than that of clean technology (CT) related to the use of renewable energy. This suggests that for a large economy such as China, where coal is still the dominant source of energy consumption, the short-term local benefits of improving air quality and health through the use of gray tech-innovation to improve energy and industrial structure are still important to balance the cost of carbon mitigation.
BACKGROUND: Pneumonia is one of the principal reasons for incidence and death in the world. The former research mainly concentrated on specific sources of patients. Besides, due to the heterogeneity among regions, there are inconsistencies in the outcome of these surveys. To explore the relationship between atmospheric pollution and hospital visits for pneumonia under the climate and pollution conditions in Qingdao, we carried out this study. METHODS: The medical records of pneumonia patients were gathered from the affiliated hospital of Qingdao University during Jan 1st, 2014, and Dec 31st,2018. Daily concentrations of PM(2.5), PM(10), SO(2), NO(2), as well as CO, were collected from the national air quality monitoring stations in Qingdao. Case-crossover study design and conditional logistic regression model were used to estimate the associations. Daily temperature, relative humidity, and atmospheric pressure were adjusted as the covariates in all models. A principal component analysis was used to solve the multicollinearity between atmospheric pollutants and investigate the relationship between various air pollutants and pneumonia occurs. RESULTS: In the single pollutant model, with interquartile range increment of the density of PM(2.5), PM(10), NO(2) and SO(2) at the lag2 days, the odds ratio of hospital visits for pneumonia patients increased by 6.4% (95%CI, 2.3-10.7%), 7.7% (95%CI, 3.2-12.4%), 6.7% (95%CI, 1.0-12.7%), and 7.2% (95%CI, 1.1-13.5%). Stratified analysis showed that pollutants were more significant in the cold period. Besides, the impact of atmospheric particulates on different ages mainly occurs in the young child (0 to 3-year-old). The odds ratio was 1.042 (95%CI, 1.012-1.072) when the principal components of atmospheric pollutants were included in the conditional logistic model. CONCLUSIONS: Our study found a significant relationship between short-term uncovering to PM(2.5), PM(10), NO(2), SO(2), and hospital visits for pneumonia in Qingdao. The effect of atmospheric pollutants mainly arose in a cold period. The particulate matter might be the principal reason in inducing hospital visits for pneumonia.
The national lockdown policies have drastically disrupted socioeconomic activities during the COVID-19 pandemic in China, which provides a unique opportunity to investigate the air quality response to such anthropogenic disruptions. And it is meaningful to evaluate the potential health impacts of air quality changes during the lockdown, especially for PM(2.5) with adverse health effects. In this study, by using PM(2.5) observations from 1388 monitoring stations nationwide in China, we examine the PM(2.5) variations between the COVID-19 lockdown (February and March in 2020) and the same period in 2015-2019, and find that the national average of PM(2.5) decreases by 18 μg/m(3), and mean PM(2.5) for most sites (about 75%) decrease by 30%-60%. The anthropogenic and meteorological contributions to these PM(2.5) variations are also determined by using a stepwise multiple linear regression (MLR) model combined with the Kolmogorov-Zurbenko filter. Our results show that the change of anthropogenic emissions is a leading contributor to those widespread PM(2.5) reductions, and meteorological conditions have the negative influence on PM(2.5) reductions for some regions, such as Beijing-Tianjin-Hebei (BTH). Additionally, the avoided premature death due to PM(2.5) reduction is estimated as a predicted number based on a log-linear concentration-response function. The total avoided premature death is 9952 in China, with dominant contribution (94%) from anthropogenic emission changes. For BTH, Yangtze River Delta, Pearl River Delta and Hubei regions, the reductions of PM(2.5) are 24.1, 24.3, 13.5 and 29.5 μg/m(3), with the avoided premature deaths of 1066, 1963, 454 and 583, respectively.
Interests in evaluation of the effect of air pollution and weather conditions on cardiovascular disease have increased. However, the relationship between short-term particulate matter (PM) exposure and first incident ST-elevation myocardial infarction (STEMI) remains unclear. Medical records were collected from December 2013 to December 2016. A total of 1354 patients with first incident STEMI were included. The daily average of air pollution and weather conditions were calculated. In this case-crossover study, conditional logistic regression was performed to assess the association between daily concentrations of PM and first incident STEMI. The daily average of PM(2.5) and PM(10) were 58.9 μg/m(3) and 80.2 μg/m(3), respectively. In this case-crossover study, single-pollutant models showed that each 10 μg/m(3) increase in PM(2.5) was associated with a percent change of 3.36, 95% confidence interval (CI): (1.01-5.77), or in PM(10) percent change of 2.1%, 95%CI: (0.2-4.04) for patients with first incident STEMI. The association remained stable after adjusting for ozone (O(3)). The results from subgroup analysis showed the association slightly enhanced in women, elder patients, patients with history of diabetes, patients without history of smoking, and cold seasons. The p values were not significant between these strata, which may be due to small sample size. This investigation showed that short-term PM exposure associated with first incident STEMI in Suzhou. Given the effect of PM on the first incident STEMI, strategies to decrease PM should be considered.
Purpose The association between atmospheric particulate matter and emergency room visits for cerebrovascular disease were evaluated in Beijing. Methods A generalized additive model was used to evaluate the associations between particulate matter and cerebrovascular disease, based on the daily data of meteorological elements, PM concentrations, and emergency room (ER) visits for cerebrovascular disease in Beijing from 2009 to 2012. Long-term trends and the effects of holidays, the day of the week, and confounding factors were controlled to determine the lag effect at 0-6 days. Single- and double-pollutant models were employed for different age and sex groups. Results The effect of PM2.5 concentration on the number of daily ER visits for cerebrovascular disease was much stronger than that of PM10 concentration. PM2.5 and PM10 had maximum RR values of 1.096 and 1.054 at lag 6 for patients aged 61-75 years. For each inter-quartile range (IQR) increase in PM10 concentration, the maximum RR values for the total, males, females, aged 15-60 years, aged 61-75 years, and aged > 75 years were 1.024, 1.044, 1.043, 1.038, 1.054, and 1.032, respectively. For each IQR increase in PM2.5 concentration, the maximum RR values for the total, males, females, aged 15-60 years, aged 61-75 years, and aged > 75 years were 1.038, 1.064, 1.076, 1.054, 1.096, and 1.049, respectively. The RR values of the double-pollutant models were lower than those of the single-pollutant models. Conclusion This study showed that the effects of PM pollution on cerebrovascular disease were different among different gender and age groups, and aged 61-75 years were mostly sensitive to particulate matters. The effects of PM2.5 on cerebrovascular disease were stronger than those of PM10. Our results can provide scientific evidence for the local government to take effective measures to improve air quality and the health of residents.
BACKGROUND: The hospitalization for asthma exacerbation has varied with seasons, however, the underlying weather reasons have not been fully explored yet. This study is aimed to explore the effect of weather factors on increased number of hospitalization due to worsening of asthma symptoms. This will provide more information to the relevant authorities to allocate appropriate medical resources as per the weather conditions in Qingdao, China. METHODS: All adult patients admitted for asthma exacerbation from 1 January, 2017 to 31 December, 2019 were enrolled from 13 main hospitals of Qingdao. The clinical data, including age, sex, smoking history, etc., were collected from the electronic medical record (EMR) systems. The hourly air quality of Qingdao from 2017-2019, including the air quality index (AQI), PM(2.5) and PM(10), was obtained from the China National Environmental Monitoring Centre. All these parameters during 2017-2019 were compared monthly. For meteorological data, the monthly horizontal wind at 850 hPa and vertical velocity at 500 hPa during 1960-2020 were obtained from National Center for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) global reanalysis dataset. The correlation analysis was applied to determine the association between asthma hospitalizations and the environmental factors, including atmospheric pressure, humidity, vertical visibility, and etc., monthly. RESULTS: In all, 10,549 asthmatic inpatients (45.7% males, 54.3% females) were included in the study. The inpatients number for asthma exacerbation had a plateau lasting from March to June of 2019, accompanied with high PM(2.5) and PM(10), as well as bad air quality from January to March of 2019, potentially governed by the El Niño event in 2018. However, there was no significance correlation between the number of asthma hospitalizations and the average value of all environmental factors. CONCLUSIONS: The high rate of hospitalization for asthma exacerbation in Qingdao during the spring of 2019 was associated with the unfavorable weather conditions, which might be linked to the atmospheric circulation in East Asia.
Particulate matter (PM) has been proved to be a risk factor for the development of circulatory system diseases (CSDs) around the world. In this study, we collected daily air pollutants, emergency room (ER) visits for CSDs, and meteorological data from 2009 to 2012 in Beijing, China. After controlling for the long-term trend and eliminating the influence of confounding factors, the generalized additive model (GAM) was used to evaluate the short-term effects of PM(10) on CSDs and cause-specific diseases. The results showed that for every 10 μg/m(3) increase in PM(10), the largest effect estimates in ER visits of total CSDs, arrhythmia, cerebrovascular diseases, high blood pressure, ischemic heart disease and other related diseases were 0.14% (95% CI: 0.06-0.23%), 0.37% (95% CI: – 0.23 to 0.97%), 0.20% (95% CI: 0.00-0.40%), 0.15% (95% CI: 0.02-0.27%), 0.18% (95% CI: 0.02-0.35%) and 0.35% (95% CI: – 0.04 to 0.79%), respectively. When NO(2) or SO(2) was added into the model, the effect estimates of PM(10) were mostly attenuated, while in those models with PM(2.5) added, the effect estimates of PM(10) were mostly increased. Stratified analysis indicated that PM(10) had a greater effect on males and the elderly.
BACKGROUND: Particulate matter (PM) pollution is a well-known risk factor of stroke. However, little is known about the association between PM(1) (aerodynamic diameter ≤ 1.0 μm) and stroke. We estimated the associations of short-term exposure to PM(1) with hospital admission and recurrence of stoke in China. METHODS: Stroke data were derived from the Chinese Stroke Center Alliance (CASA) program conducted in 1458 hospitals in 292 Chinese cities from 2015 to 2019. Daily air pollution and meteorological data were collected in the cities where studied hospitals were located. Daily PM(1) concentration was estimated by a generalized additive model (GAM) using PM(2.5) and meteorological variables. A time-stratified case-crossover design was applied to estimate the associations of short-term exposure to PM(1) with hospital admission of stroke. A GAM model was used to estimate the association between average PM(1) exposure during hospitalization and the recurrence of stroke. RESULTS: A total of 989,591 stroke cases were included in the study. Each 10 μg/m(3) increase in PM(1) (lag06-day) was associated with a 0.53% (95%CI, 0.39%, 0.67%) increment in hospital admission for stroke. The adverse effects of PM(1) on ischemic stroke was stronger than on intracerebral hemorrhage. We found the associations were significant in Northeast (0.94%, 95%CI, 0.51%, 1.38%), North (0.47%, 95%CI, 0.20%, 0.75%), Central (0.57%, 95%CI, 0.30%, 0.85%), and East China (0.63%, 95%CI, 0.27%, 0.99%). Of all stroke cases, 62,988 (6.4%) had recurrent stoke attack during their hospitalization. Each 10 μg/m(3) increase in PM(1) was associated with a 1.64% (95%CI, 1.28%, 2.01%) increment in recurrence of stroke during hospitalization. CONCLUSIONS: Short-term exposure to PM(1) may increase the risk of incidence and recurrence of stroke in China, and the effects varied across different types of stroke and regions. Geographically targeted strategies and measures are needed to control air pollution for reducing the burden of stroke from PM(1).
BACKGROUND: Nationwide studies that examine climatic modification effects on the association between air pollution and health outcome are limited in developing countries. Moreover, few studies focus on PM1 pollution despite its greater health effect. OBJECTIVES: This study aims to determine the modification effects of climatic factors on the associations between PM1 and the incidence rates of lung cancer for males and females in China. METHODS: We conducted a nationwide analysis in 345 Chinese counties (districts) from 2014 to 2015. Mean air temperature and relative humidity over the study period were used as the proxies of climatic conditions. In terms of the multivariable linear regression model, we examined climatic modification effects in the stratified and combined datasets according to the three-category and binary divisions of climatic factors. Moreover, we performed three sensitivity analyses to test the robustness of climatic modification effects. RESULTS: We found a stronger association between PM1 and the incidence rate of male lung cancer in counties with high levels of air temperature or relative humidity. If there is a 10 μg/m(3) shift in PM1, then the change in male incidence rate relative to its mean was higher by 4.39% (95% CI: 2.19, 6.58%) and 8.37% (95% CI: 5.18, 11.56%) in the middle and high temperature groups than in the low temperature group, respectively. The findings of climatic modification effects were robust in the three sensitivity analyses. No significant modification effect was discovered for female incidence rate. CONCLUSIONS: Male residents in high temperature or humidity counties suffer from a larger effect of PM1 on the incidence rate of lung cancer in China. Future research on air pollution-related health impact assessment should consider the differential air pollution effects across different climatic conditions.
RATIONALE & OBJECTIVE: Increasing evidence has linked ambient fine particulate matter (ie, particulate matter no larger than 2.5 μm [PM(2.5)]) to chronic kidney disease (CKD), but their association has not been fully elucidated, especially in regions with high levels of PM(2.5) pollution. This study aimed to investigate the long-term association of high PM(2.5) exposure with incident CKD in mainland China. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 72,425 participants (age ≥18 years) without CKD were recruited from 121 counties in Hunan Province, China. EXPOSURE: Annual mean PM(2.5) concentration at the residence of each participant derived from a long-term, full-coverage, high-resolution (1 × 1 km(2)), high-quality dataset of ground-level air pollutants in China. OUTCOMES: Incident CKD during the interval between the baseline examination of each participant (2005-2017) and the end of follow-up through 2018. ANALYTICAL APPROACH: Cox proportional hazards models were used to estimate the independent association of PM(2.5) with incident CKD and the joint association of PM(2.5) with temperature or humidity on the development of PM(2.5)-related CKD. Restricted cubic splines were used to model exposure-response relationships. RESULTS: Over a median follow-up of 3.79 (IQR, 2.03-5.48) years, a total of 2,188 participants with incident CKD were identified. PM(2.5) exposure was associated with incident CKD with an adjusted hazard ratio of 1.71 (95% CI, 1.58-1.85) per 10-μg/m(3) greater long-term exposure. Multiplicative interactions between PM(2.5) and humidity or temperature on incident CKD were detected (all P < 0.001 for interaction), whereas an additive interaction was detected only for humidity (relative risk due to interaction, 3.59 [95% CI, 0.97-6.21]). LIMITATIONS: Lack of information on participants' activity patterns such as time spent outdoors. CONCLUSIONS: Greater long-term ambient PM(2.5) pollution is associated with incident CKD in environments with high PM(2.5) exposure. Ambient humidity has a potentially synergetic effect on the association of PM(2.5) with the development of CKD. PLAIN-LANGUAGE SUMMARY: Exposure to a form of air pollution known as fine particulate matter (ie, particulate matter ≤2.5 μm [PM(2.5)]) has been linked to an increased risk of chronic kidney disease (CKD), but little is known about how PM(2.5) affects CKD in regions with extremely high levels of PM(2.5) pollution. This longitudinal cohort study in China investigates the effect of PM(2.5) on the incidence of CKD and whether temperature or humidity interact with PM(2.5). Our findings suggest that long-term exposure to high levels of ambient PM(2.5) significantly increased the risk of CKD in mainland China, especially in terms of cumulative average PM(2.5). The associations of PM(2.5) and incident CKD were greater in high-humidity environments. These findings support the recommendation that reducing PM(2.5) pollution should be a priority to decrease the burden of associated health risks, including CKD.
Facing the dual challenges of air pollution and climate change, China has set ambitious goals and made decisive efforts to reduce its carbon emission and win the ‘Battle for Blue Sky’. However, how the low-carbon transition and air quality targets could be simultaneously achieved at the sub-national levels remains unclear. The questions arise whether province-level climate change mitigation strategies could help ease the air pollution and close the air quality gap, and how these co-benefits can be compared with the cost of the green transition. Here, using an integrated modeling framework, we combined with local air pollutant emission inventories and issued policy documents to quantitatively evaluated the current situation and targets of the air quality and health co-benefits of deep carbon mitigation in Sichuan, a fast-developing inland province in China. We found that by 2035, without system-wide energy transformation induced by carbon mitigation policies, the improvement in air quality in Sichuan Province might be limited, even under stringent end-of-pipe emission control measures. On the contrary, the co-benefits of low-carbon policies would be significant. On top of stringent end-of-pipe controls, the implementation of carbon mitigation policy in line with China’s enhanced climate target could further reduce the average PM2.5 concentration in Sichuan by as much as 2.8 mu g m(-3), or the population-weighted PM2.5 concentration by 5.9 mu g m(-3) in 2035. The monetized health co-benefits in Sichuan Province would amount to 23 billion USD under the stringent carbon mitigation scenario, exceeding 1.7 billion USD of the mitigation cost by 2035. The results indicate that significant air quality and health benefits could both be achieved from carbon mitigation at the provincial level. Both air-pollution or carbon-reduction oriented policies would be important for improving environmental quality and public health.
INTRODUCTION: PM(2.5) and climate change are two major public health concerns, with majority of the research on their interaction focused on the synergistic effect, particularly for extreme events such as hot or cold temperatures. The climate sustainability index (CLS) was introduced to comprehensively explore the impact of climate change and the interactive effect on human health with air pollution. METHODS: In this study, a county-level panel data in China was collected and used. The generalized additive model (GAM) and geographically and temporally weighted regression (GTWR) was used to explore the interactive and spatial effect on mortality between CLS and PM(2.5). RESULTS AND DISCUSSIONS: Individually, when CLS is higher than 150 or lower than 50, the mortality is higher. Moreover, when PM(2.5) is more than 35 μg/m(3), the influence on mortality is significantly increased as PM(2.5) concentration rises; when PM(2.5) is above 70 μg/m(3), the trend is sharp. A nonlinear antagonistic effect between CLS and PM(2.5) was found in this study, proving that the combined adverse health effects of climate change and air pollution, especially when CLS was lower (below 100) and PM(2.5) was higher (above 35 μg/m(3)), the antagonistic effect was much stronger. From a spatial perspective, the impact of CLS and PM(2.5) on mortality varies in different geographical regions. A negative and positive influence of CLS and PM(2.5) was found in east China, especially in the northeastern and northern regions, -which were heavily polluted. This study illustrated that climate sustainability, at certain level, could mitigate the adverse health influence of air pollution, and provided a new perspective on health risk mitigation from pollution reduction and climate adaptation.
In China, the rapid development of the economy and implementation of multiple emission control policies in recent decades have been accompanied by dramatic changes in air quality. In this study, PM(2.5) concentrations estimated by using MERRA-2 reanalysis data were integrated into the Global Exposure Mortality Model (GEMM) to explore the spatiotemporal variation of nationwide PM(2.5)-related premature mortality from 1990 to 2019, and the driving factors behind decadal changes were evaluated. Since 2000, as a result of PM(2.5) pollution, air quality in China has deteriorated substantially, especially in the fast-developing eastern and southern parts. In 2009, the nationwide population-weighted (PW) PM(2.5) concentration peaked at 41.4 μg/m(3) (95% confidence interval [CI], 36.7-46.2). Simultaneously, the GEMM results revealed that nationwide PM(2.5)-related deaths increased remarkably from 1089 (95% CI, 965-1210) thousand in 1990 to 1795 (1597-1986) thousand in 2009. The implementation of the toughest-ever Air Pollution Prevention and Control Action Plan (APPCAP) in 2013 effectively controlled PM(2.5) pollution in China. By 2018, the nationwide PW PM(2.5) concentration had decreased to 34.0 (29.2-38.9) μg/m(3). Dynamic trend prediction revealed that, although the APPCAP achieved substantial health benefits, the policy did not result in further remarkable reductions in PM(2.5)-related deaths; in 2019, deaths peaked at 1932 (1716-2140) thousand. PM(2.5)-related deaths in 2030 were projected for each of four emission control scenarios. The results of the driving factor analysis and the future projections indicated that the health benefits from improving air quality are likely to be counterbalanced by changes in the population age structure. Because population ageing is becoming more and more rapid in China and the challenge of climate change is increasing, the results of this study imply that policymakers need to implement more stringent measures and set more ambitious emission control targets to reduce nationwide PM(2.5)-related premature mortality in the future.
Exposure to fine particulate matter (PM(2.5)) has become a major global health concern. Although modeling exposure to PM(2.5) has been examined in China, accurate long-term assessment of PM(2.5) exposure with high spatiotemporal resolution at the national scale is still challenging. We aimed to establish a hybrid spatiotemporal modeling framework for PM(2.5) in China that incorporated extensive predictor variables (satellite, chemical transport model, geographic, and meteorological data) and advanced machine learning methods to support long-term and short-term health studies. The modeling framework included three stages: (1) filling satellite aerosol optical depth (AOD) missing values; (2) modeling 1 km × 1 km daily PM(2.5) concentrations at a national scale using extensive covariates; and (3) downscaling daily PM(2.5) predictions to 100-m resolution at a city scale. We achieved good model performances with spatial cross-validation (CV) R(2) of 0.92 and temporal CV R(2) of 0.85 at the air quality sites across the country. We then estimated daily PM(2.5) concentrations in China from 2013 to 2019 at 1 km × 1 km grid cells. The downscaled predictions at 100 m resolution greatly improved the spatial variation of PM(2.5) concentrations at the city scale. The framework and data set generated in this study could be useful to PM(2.5) exposure assessment and epidemiological studies.
Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM2.5 to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM2.5 between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM2.5 climate change penalty of 1.43 mu g m(-3) in Eastern China, leading to an additional 35,000 PM2.5-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM2.5 climate change penalty weakens to 0.24 mu g m(-3) with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM2.5-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM2.5 decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM2.5 decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM2.5 and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions are key to attaining air quality targets and protecting human health in the context of future global climate change. (C) 2020 Elsevier B.V. All rights reserved.
OBJECTIVES: Evidence of childhood asthma hospitalizations associated with temperature variability (TV) and the attributable risk are limited in China. We aim to use a comprehensive index that reflected both intra- and inter-day TV to assess the TV-childhood asthma relationship and disease burden, further to identify seasonality vulnerable populations, and to explore the effect modification of PM(2.5). METHODS: A quasi-distributed lagged nonlinear model (DLNM) combined with a linear threshold function was applied to estimate the association between TV and childhood asthma hospitalizations during 2013-2016 in Hefei, China. Subgroup analysis was conducted by age and sex. Disease burden is reflected by the attributable fraction and attributable number. Besides, modifications of PM(2.5) were tested by introducing the cross-basis of TV and binary PM(2.5) as an interaction term. RESULTS: The risk estimates peaked at TV(0-3) and TV(0-4) in the cool and the warm season separately, with RR of 1.051 (95%CI: 1.021-1.081) and 1.072 (95%CI: 1.008-1.125), and the effects lasted longer in the cool season. The school-age children in the warm season and all subgroups except pre-school children in the cool season were vulnerable to TV. It is estimated that the disease burden related to TV account for 6.2% (95% CI: 2.7%-9.4%) and 4% (95% CI: 0.6%-7.1%) during the cool and warm seasons in TV(0-3). In addition, the risks of TV were higher under the high PM(2.5) level compared with the low PM(2.5) level in the cool season, although no significant differences between them. CONCLUSIONS: TV exposure significantly increases the risk and disease burden of childhood asthma hospitalizations, especially in the cool season. More medical resources should be allocated to school-age children. Giving priority to pay attention to TV in the cool season in practice could obtain the greatest public health benefits and those days with high TV and high PM(2.5) need more attention.
Australia is home to one of the highest rates of allergic rhinitis worldwide. Commonly known as ‘hay fever’, this chronic condition affects up to 30% of the population and is characterised by sensitisation to pollen and fungal spores. Exposure to these aeroallergens has been strongly associated with causing allergic reactions and worsening asthma symptoms. Over the last few decades, incidences of respiratory admissions have risen due to the increased atmospheric concentration of airborne allergens. The fragmentation and dispersion of these allergens is aided by environmental factors like rainfall, temperature and interactions with atmospheric aerosols. Extreme weather parameters, which continue to become more frequent due to the impacts of climate change, have greatly fluctuated allergen concentrations and led to epidemic thunderstorm asthma (ETSA) events that have left hundreds, if not thousands, struggling to breathe. While a link exists between airborne allergens, weather and respiratory admissions, the underlying factors that influence these epidemics remain unknown. It is important we understand the potential threat these events pose on our susceptible populations and ensure our health infrastructure is prepared for the next epidemic.
Global warming increases the probability of extreme events and heat waves triggering severe impacts on human health, especially the elderly. Taiwan is an aged society, so residential buildings, which cannot withstand extreme temperature events, increase the risk of harm for the elderly. Furthermore, Taiwanese prefer to open the windows to reduce indoor high temperatures, which causes high levels of outdoor PM2.5 to flow indoors, leading to health risks. Therefore, this research proposes a strategy to create a house with a low temperature and a low PM2.5 health risk for the elderly based on building envelope renovation and windows user behavior patterns. The risk day is demonstrated as an index to evaluate the indoor environment quality, which is based on the number of days that exceed the health risk threshold. The results show that the performance improvement of the building envelope and control of the window opening timing can effectively reduce the risk days by 48.5%. This means that passive strategies cannot fully control health risks, and the use of equipment is necessary. Finally, if the current situation is maintained without any adjustment or strategy improvement, an additional 41.3% energy consumption must be paid every year to control health risks.
Mental health conditions have the potential to be worsened by air pollution or other climate-sensitive factors. Few studies have empirically examined those associations when we faced to co-exposures, as well as interaction effects. There would be an urgent need to use deep learning to handle complex co-exposures that might interact in multiple ways, and the model performance reinforced by SHapely Additive exPlanations (SHAP) enabled our predictions interpretable and hence actionable. Here, to evaluate the mixed effect of short-term co-exposure, we conducted a time-series analysis using approximately 1.47 million hospital outpatient visits of mental disorders (i.e., depressive disorder-DD, Schizophrenia-SP, Anxiety Disorder-AD, Bipolar Disorder-BD, Attention Deficit and Hyperactivity Disorder-ADHD, Autism Spectrum Disorder-ASD), with matched meteorological observations from 2015 through 2019 in Nanjing, China. The global insights of gated recurrent unit model revealed that most of input features with similar effect size caused the illness risk of SP and ASD increase, and most markedly, 73% of relative humidity, 44.6 µg/m(3) of NO(2), and 14.1 µg/m(3) of SO(2) at 5-year average level associated with 2.27, 1.14, and 1.29 visits increase for DD, SP, and AD, respectively. Both synergic and antagonistic effect among informative paired-features were distinguished from local feature dependence. Interestingly, variation tendencies of excessive visits of bipolar disorder when atmospheric pressure, PM(2.5), and O(3) interacted with one another were inconsistent. Our results provided added qualitative and quantitative support for the conclusion that short-term co-exposure to ambient air pollutants and meteorological conditions posed threats to human mental health.
To examine Beijing residents’ risk perception of contracting smog-related diseases, we proposed a model in which air-pollution knowledge is a theoretical mechanism accounting for the influence on risk perception of exposure to environmental news and exposure to Under the Dome, an environmental documentary about smog in China, which has been censored. Data (N = 523) were collected from Beijing residents from February to March in 2017. We analyzed the data using Hayes’ PROCESS macro. Findings revealed that environmental-news exposure is positively associated with both air-pollution knowledge and risk perception. Exposure to environmental news has an indirect effect on risk perception through air-pollution knowledge. Exposure to Under the Dome is positively related to risk perception but is not related to air-pollution knowledge. We contributed to the literature by empirically testing the impact of Under the Dome, which has been largely studied via the critical theory approach. Implications included that Under the Dome is a successful risk communication model and that its impact goes beyond increasing public risk perception of smog.
The coupling effects of sandstorm and dust from coal bases themselves can have a major impact on the atmospheric environment as well as on human health. The typical coal resource city of Wuhai in Inner Mongolia was selected in order to study these impacts during a severe sandstorm event in March 2021. Particulate matter (PM1, PM2.5 and PM10) and total suspended particulate matter (TSP) samples were collected during the sandstorm event of 15-19 March 2021 and non-sandstorm weather (11-13 March 2021) and analyzed for their chemical composition. The concentrations of PM1, PM2.5, PM10 and TSP in Wuhai city during the sandstorm were 2.2, 2.6, 4.8 and 6.0 times higher than during non-sandstorm days, respectively. Trace metals concentrations in particles of different sizes generally increased during the sandstorm, while water-soluble ions decreased. Positive matrix fraction (PMF) results showed that the main sources of particles during both sandstorm and non-sandstorm days were industrial emissions, traffic emissions, combustion sources and dust. The proportion of industrial emissions and combustion sources increased compared with non-sandstorm days, while traffic emissions and dust decreased. The backward trajectory analysis results showed that airflows were mainly transported over short distances during non-sandstorm days, and high concentration contribution source areas were from southern Ningxia, southeast Gansu and western Shaanxi. The airflow was mainly transported over long distances during the sandstorm event, and high concentration contribution source areas were from northwestern Inner Mongolia, southern Russia, northern and southwestern Mongolia, and northern Xinjiang. A health risk analysis showed that the risk to human health during sandstorm days related to the chemical composition of particles was generally 1.2-13.1 times higher than during non-sandstorm days. Children were more susceptible to health risks, about 2-6.3 times more vulnerable than adults to the risks from heavy metals in the particles under both weather conditions.
BACKGROUND: Fine particulate matter (PM(2.5)) pollution is one of the most critical environmental and public health problems in China and has caused an enormous disease burden, especially long-term PM(2.5) exposure. Global climate change represents another environmental challenge in the coming decades and is also an essential factor affecting PM(2.5) pollution. Moreover, China has an aging population with a changing population size and falling age-standardized mortality rates. However, little evidence exists evaluating the potential impacts from climate change and population aging on the long-term PM(2.5) exposure-related disease burden. This study quantifies the impacts of climate and population changes on changes in the disease burden attributed to long-term PM(2.5) exposure from 2015 to 2030 in mainland China, which could add evidence for the revision of relevant environmental standards and health policies. METHODS: This modeling study investigated long-term PM(2.5) exposure-related mortality across China based on PM(2.5) projections under Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) and population scenarios from shared socioeconomic pathways (SSPs). PM(2.5) concentrations were simulated by the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) modeling systems. In addition, three types of population projections in 2030 relative to 2015 were set up as follows: (i) the population remained the same as that in 2015; (ii) the population size changed under SSPs, but the age structure remained the same; (iii) both the population size and age structure changed under SSPs. The global exposure mortality model (GEMM) was adopted to estimate PM(2.5)-related premature deaths. RESULTS: Ambient PM(2.5) concentrations decreased from 2015 to 2030 under the two climate and emission scenarios. Estimates of related premature mortality in 2030 declined compared with that in 2015 due to lower PM(2.5) concentrations (RCP4.5: -16.8%; RCP8.5: -16.4%). If the age structure of the population remained unchanged and the population size changed under SSPs, the nonaccidental premature mortality also showed a decrease ranging from -18.6% to -14.9%. When both population size and age structure changed under SSPs, the population in China would become older. Nonaccidental premature mortality would sharply increase by 35.7-52.3% (with a net increase of 666-977 thousand) in 2030. CONCLUSION: The PM(2.5) pollution in 2030 under both RCP4.5 and RCP8.5 would slightly improve. The population sizes in 2030 projected by SSPs are relatively stable compared with that in 2015. However, the modest decrease due to air pollution improvement and stable population size would be offset by population aging.
This study examines the impact of air pollution from straw burning on human cognitive health in China by linking household health surveys with PM2.5 emissions derived from remote sensing data on fire activity. The identification strategy leverages the spatial dispersion of air pollutants due to exogenous wind directions. The results indicate that PM2.5 emissions from upwind straw burning have a negative impact on cognitive functions of respondents aged 55 and above, but PM2.5 emissions from downwind fires do not. The impact is transitory and caused by contemporaneous PM2.5 emissions on the day of cognitive testing. Our findings demonstrate a link from air pollution to cognitive declines and suggest that through this link, climate change could result in additional health costs by increasing the risk of wildfires.
Hypertension (HTN) was a major preventable cause of cardiovascular disease (CVD), contributing to a huge disease burden. Ambient temperature, air pollution and green space were important influencing factors of HTN, and few studies have assessed the effects and interactions of ambient temperature, air pollution and green space on HTN in rural areas. In this study, we selected 8400 individuals randomly in rural areas of Anhui Province by a multi-stage stratified cluster sampling. A total of 8383 individuals were included in the final analysis. We collected particulate pollutants and meteorological data from the local air quality monitoring stations and National Center for Meteorological Science from January 1 to December 31, 2020, respectively. The normalized differential vegetation index (NDVI) of Anhui Province in 2020 was produced and processed by remote sensing inversion on the basis of medium resolution satellite images. The average annual mean exposure concentrations of air pollution, meteorological factors, and NDVI were calculated for each individual based on the geocoded residential address. HTN was defined according the Chinese Guidelines for Prevention and Treatment of HTN. The effects and interactions of ambient temperature, air pollution and green space on HTN were evaluated by generalized linear model and interaction model, respectively. In this study, the prevalence of HTN was 24.14%. The adjusted odd ratio of HTN for each 1 μg/m(3) increasing in PM(2.5) and PM(10), 1 °C of ambient temperature, and 0.1 of NDVI were:1.276 (1.013, 1.043), 1.012 (1.006, 1.018), 0.862 (0.862, 0.981) and 0.669 (0.611, 0.733), respectively. The results showed that air pollutants were positively correlated with HTN, while ambient temperature and green space were negatively correlated with HTN. Meanwhile, the negative associations of green space on HTN could decrease with the increasing concentrations of air pollution, but increase with the rising of ambient temperature.
BACKGROUND: While temperature changes have been confirmed as one of the contributory factors affecting human health, the association between high-frequency temperature variability (HFTV, i.e., temperature variation at short time scales such as 1, 2, and 5 days) and the hospitalization of chronic obstructive pulmonary disease (COPD) was rarely reported. OBJECTIVES: To evaluate the associations between high-frequency temperature variabilities (i.e., at 1, 2, and 5-day scales) and daily COPD hospitalization. METHODS: We collected daily records of COPD hospitalization and meteorological variables from 2013 to 2017 in 21 cities of Guangdong Province, South China. A quasi-Poisson regression with a distributed lag nonlinear model was first employed to quantify the effects of two HFTV measures, i.e., the day-to-day (DTD) temperature change and the intraday-interday temperature variability (IITV), on COPD morbidity for each city. Second, we used multivariate meta-analysis to pool the city-specific estimates, and stratified analyses were performed by age and sex to identify vulnerable groups. Then, the meta-regression with city-level characteristics was employed to detect the potential sources of the differences among 21 cities. RESULTS: A monotonic increasing curve of the overall exposure-response association was observed, suggesting that positive HFTV (i.e., increased DTD and IITV) will significantly increase the risk of COPD admission. Negative DTD was associated with reduced COPD morbidity while positive DTD elevated the COPD risk. An interquartile range (IQR) increase in DTD was associated with a 24% (95% CI: 12-38%) increase in COPD admissions. An IQR increase in IITV(0-1) was associated with 18% (95% CI: 7-27%) increase in COPD admissions. Males and people aged 0-64 years appeared to be more vulnerable to the DTD effect than others. Potential sources of the disparity among different cities include urbanization level, sex structure, industry structure, gross domestic product (GDP), health care services, and air quality. CONCLUSIONS: The increases of DTD and IITV have significant adverse impacts on COPD hospitalization. As climate change intensifies, precautions need to be taken to mitigate the impacts of high-frequency temperature changes.
OBJECTIVE: Most evidence comes from studies show that ambient ozone(O(3)) pollution has become a big issue in China. Few studies have investigated the impact of ozone spatiotemporal patterns on respiratory mortality and cardiovascular mortality in Nanchang city. Thus, this study aimed to explore the health effect of ozone exposure on respiratory mortality and cardiovascular mortality in Nanchang, Jiangxi Province. METHODS: Using the daily mortality data, atmospheric routine monitoring data and meteorological data in Nanchang from 2014 to 2020, we performed a generalized additive model (GAM) based on the poisson distribution in which time-series analysis to calculate the risk correlation between respiratory mortality and cardiovascular mortality and ozone exposure level (8h average ozone concentration, O(3)-8h). Besides, analyses were also stratified by season, age and sex. RESULTS: In the single-pollutant model, for every 10 μg/m(3) increase in ozone, respiratory mortality increased 1.04% with 95% confidence interval (CI) between 0.04 and 1.68%, and cardiovascular mortality increased 1.26% (95%CI: 0.68 ~ 1.83%). In the multi-day moving average lag model, the mortality of respiratory diseases and cardiovascular diseases reached a relative risk peak on the cumulative lag5 (1.77%,95%CI: 0.99 ~ 2.57%) and the cumulative lag3 (1.68%,95%CI: 0.93 ~ 2.45%), respectively. The differences were statistically significant (P < 0.05). Results of the stratified analyses showed the effect value of respiratory mortality in people aged ≥65 years was higher than aged <65 years, whereas the greatest effect of cardiovascular mortality in people aged <65 years than aged ≥65 years. Ozone had a more profound impact on females than males in respiratory diseases and cardiovascular diseases. In winter and spring, ozone had a obvious impact on respiratory mortality, and effects of ozone pollution on cardiovascular mortality were stronger in summer and winter. There was a statistically significant difference of respiratory mortality in winter and spring and of cardiovascular mortality in summer and winter (P < 0.05). CONCLUSIONS: In the long run, the more extreme the pollution of ozone exposure, the higher the health risk of residents' respiratory mortality and cardiovascular mortality. Therefore, the government should play an important role in the prevention and control ways of decreasing and eliminating the ozone pollution to protect the resident's health. The findings provide valuable data for further scientific research and improving environmental policies in Nanchang city.
Ambient ozone (O(3)) has emerged as an important public health issue worldwide. Previous studies found an association between O(3) and cardiorespiratory mortality. However, evidence was limited regarding the risk of O(3) on mortality from other diseases. In this study, we aimed to estimate the association between O(3) and mortality from a broad spectrum of diseases in Guangzhou, China, which has experienced a rapid increase in O(3) concentration over the past decades. Daily data were obtained on cause-specific mortality, air pollutant concentrations and weather conditions during 2013-2018. A generalized additive model with quasi-Poisson regression was applied to examine the association between O(3) and mortality from 10 broad causes and 26 refined subcategories, with adjustment of long-term and seasonal trends, weather conditions, public holidays and days of the week. We found that the threshold concentrations of O(3) were 40 μg/m(3) for all-cause, non-accidental, cardiovascular and respiratory mortality. Mortality risk increased monotonically with O(3) concentrations above the threshold. Per 10 μg/m(3) increase of O(3) at lag 0-3 days was associated with 0.54% (95%CI: 0.34-0.74%), 0.56% (95%CI: 0.36-0.76%), 0.59% (95%CI: 0.30-0.88%), 0.78% (95%CI: 0.33-1.24%) and 0.52% (95%CI: 0.21-0.83%) elevated risk of death from all causes, non-accidental causes, cardiovascular diseases, respiratory diseases and neoplasms, respectively. Among the subcategories, the largest effect estimate was observed in people with chronic obstructive pulmonary disease. The elderly suffered from a higher mortality risk from O(3). Stringent emission control strategies and multi-sectoral collaborations are needed to reduce the detrimental impact of O(3) on vulnerable populations.
Facing the dual challenges of climate change and air pollution, China has made great efforts to explore the co-control strategies for the both. We assessed the benefits of carbon and pollution control policies on air quality and human health, with an integrated framework combining an energy-economic model, an air quality model and a concentration-response model. With a base year 2015, seven combined scenarios were developed for 2030 based on three energy scenarios and three end-of-pipe control ones. Policy-specific benefits were then evaluated, indicated by the reduced emissions, surface concentrations of major pollutants, and premature deaths between scenarios. Compared to the 2030 baseline scenario, the nationwide PM(2.5)- and O(3)-related mortality was expected to decline 23% or 289 (95% confidence interval: 220-360) thousand in the most stringent scenario, and three quarters of the avoided deaths were attributed to the end-of-pipe control measures. Provinces in heavily polluted and densely populated regions would benefit more from carbon and pollution control strategies. The population fractions with PM(2.5) exposure under the national air quality standard (35 μg/m(3)) and WHO guideline (10 μg/m(3)) would be doubled from 2015 to 2030 (the most stringent scenario), while still very few people would live in areas with the WHO guideline achieved for O(3) (100 μg/m(3)). Increased health impact of O(3) suggested a great significance of joint control of PM(2.5) and O(3) in future policy-making.
Background This study investigated risks of mortality from and morbidity (emergency room visits (ERVs) and outpatient visits) of asthma and chronic obstructive pulmonary disease (COPD) associated with extreme temperatures, fine particulate matter (PM2.5), and ozone (O3) by sex, and age, from 2005 to 2016 in 6 metropolitan cities in Taiwan. Methods The distributed lag non-linear model was employed to assess age (0–18, 19–39, 40–64, and 65 years and above), sex-cause-specific deaths, ERVs, and outpatient visits associated with extreme high (99th percentile) and low (5th percentile) temperatures and PM2.5 and O3 concentrations at 90th percentile. Random-effects meta-analysis was adopted to investigate cause-specific pooled relative risk (RR) and 95% confidence intervals (CI) for the whole
studied areas. Results Only the mortality risk of COPD in the elderly men was significantly associated with the extreme low temperatures. Exposure to the 90th percentile PM2.5 was associated with outpatient visits for asthma in 0–18 years old boys [RR = 1.15 (95% CI: 1.09–1.22)]. Meanwhile, significant elevation of ERVs of asthma for females aged 40–64 years was associated with exposure to ozone, with the highest RR of 1.21 (95% CI: 1.05–1.39). Conclusions This study identified vulnerable subpopulations who were at risk to extreme events associated with ambient environments deserving further evaluation for adaptation.
BACKGROUND: The health effect of particulate matter pollution on stroke has been widely examined; however, the effect among patients with comorbid type 2 diabetes (T2D) in developing countries has remained largely unknown. METHODS: A time-series study was conducted to investigate the short-term effect of fine particulate matter (PM(2.5)) and inhalable particulate matter (PM(10)) on hospital admissions for stroke among patients with T2D in Beijing, China, from 2014 to 2018. An over-dispersed Poisson generalized additive model was employed to adjust for important covariates, such as weather conditions and long-term and seasonal trends. RESULTS: A total of 159,298 hospital admissions for stroke comorbid with T2D were reported. Approximately linear exposure-response curves were observed for PM(2.5) and PM(10) in relation to stroke admissions among T2D patients. A 10 μg/m(3) increase in the four-day moving average of PM(2.5) and PM(10) was associated with 0.14% (95% confidence interval [CI]: 0.05-0.23%) and 0.14% (95% CI: 0.06-0.22%) incremental increases in stroke admissions among T2D patients, respectively. A 10 μg/m(3) increase in PM(2.5) in the two-day moving average corresponded to a 0.72% (95% CI: 0.02-1.42%) incremental increase in hemorrhagic stroke, and a 10 μg/m(3) increase in PM(10) in the four-day moving average corresponded to a 0.14% (95% CI: 0.06-0.22%) incremental increase in ischemic stroke. CONCLUSIONS: High particulate matter might be a risk factor for stroke among patients with T2D. PM(2.5) and PM(10) have a linear exposure-response relationship with stroke among T2D patients. The study provided evidence of the risk of stroke due to particulate matter pollution among patients with comorbid T2D.
OBJECTIVE: To explore the relationship between ambient PM(2.5) level and outpatient visits of children with respiratory diseases in a megacity, Zhengzhou, in central China. METHODS: We collected daily outpatient visit data, air pollutant data, and meteorological data at the monitoring points of Zhengzhou from the time period 2018 to 2020 and used Spearman’s rank correlation to analyze the correlation between children’s respiratory outpatient visits and air pollutants and meteorological factors. Generalized additive models were used to analyze the association between PM(2.5) exposures and children’s respiratory outpatient visits. A stratified analysis was further carried out for the seasons. RESULTS: From 2018 to 2020, the total number of outpatients with children’s respiratory diseases was 79,1107, and the annual average concentrations of PM(2.5), PM(10), SO(2), NO(2), CO, and O(3)-8h in Zhengzhou were respectively 59.48 μg/m(3), 111.12 μg/m(3), 11.10 μg/m(3), 47.77 μg/m(3), 0.90 mg/m(3) and 108.81 μg/m(3). The single-pollutant model showed that the risk of outpatient visits for children with respiratory disease increased by 0.341% (95%CI: 0.274-0.407%), 0.532% (95%CI: 0.455-0.609%) and 0.233% (95%CI: 0.177-0.289%) for every 10 μg/m(3) increase in PM(2.5) with a 3-day lag, 1-day lag, and 1-day lag respectively for the whole year, heating period, and non-heating period. The multi-pollutant model showed that the risk of PM(2.5) on children’s respiratory disease visits was robust. The excess risk of PM(2.5) on children’s respiratory disease visits increased by 0.220% (95%CI: 0.147-0.294%) when SO(2) was adjusted. However, the PM(2.5) effects were stronger during the heating period than during the non-heating period. CONCLUSION: The short-term exposure to PM(2.5) was significantly associated with outpatient visits for children’s respiratory diseases. It is therefore necessary to strengthen the control of air pollution so as to protect children’s health.
Atmospheric coarse particulate matter (PM(10)) enriched with heavy metal(loid)s could pose potentially significant health risk to humans, while accurate health risk assessment calls for characterization of their bioaccessibility, besides the total contents. The health risk of major toxic heavy metal(loid)s in the PM(10) from four large cities in northern China via inhalation was investigated based on their total contents and bioaccessibility. The annual mean concentrations of PM-bound Zn, As, Pb, and Mn in the atmosphere of the four cities were 650, 305, 227, and 177 ng⋅m(-3), respectively. The levels of heavy metal(loid)s in the PM(10) were generally higher in winter but lower in summer in all four cities, which resulted primarily from the emissions associated with coal combustion for district and household heating and the unfavorable meteorological conditions in winter. The bioaccessibility of heavy metal(loid)s in the PM(10) ranged from 0.9 to 48.7%, following the general order of Mn > Co > Ni > Cd > Cu > As > Cr > Zn > Pb. Based on their total contents in the PM(10), most heavy metal(loid)s posed significant public health risk via inhalation exposure in the four cities. However, after accounting for the bioaccessibility of metal(loid)s, the non-carcinogenic risk of most metal(loid)s was negligible, except for As in the PM(10) of Jinzhong, while only the carcinogenic risk posed by Cr and As in the PM(10) exceeded the acceptable level. These findings demonstrate the importance of characterizing the bioaccessibility of airborne PM-bound heavy metal(loid)s in health risk assessment and could guide the on-going efforts on reducing the public health risk of PM(10) in northern China.
Air pollution has a serious fallout on human health, and the influences of the different urban morphological characteristics on air pollutants cannot be ignored. In this study, the relationship between urban morphology and air quality (wind speed, CO, and PM(2.5)) in residential neighborhoods at the meso-microscale was investigated. The changes in the microclimate and pollutant diffusion distribution in the neighborhood under diverse weather conditions were simulated by Computational Fluid Dynamics (CFD). This study identified five key urban morphological parameters (Building Density, Average Building Height, Standard Deviation of Building Height, Mean Building Volume, and Degree of Enclosure) which significantly impacted the diffusion and distribution of pollutants in the neighborhood. The findings of this study suggested that three specific strategies (e.g. volume of a single building should be reduced, DE should be increased) and one comprehensive strategy (the width and height of the single building should be reduced while the number of single buildings should be increased) could be illustrated as an optimized approach of urban planning to relief the air pollution. The result of the combined effects could provide a reference for mitigating air pollution in sustainable urban environments.
Evidence is still limited for the role of long-term PM(2.5) exposure in cerebrovascular diseases among residents in high pollution regions. The study is aimed to investigate the long-term effects of PM(2.5) exposure on stroke mortality, and further explore the effect modification of temperature variation on the PM(2.5)-mortality association in northern China. Based on a cohort data with an average follow-up of 9.8 years among 38,435 urban adults, high-resolution estimates of PM(2.5) derived from a satellite-based model were assigned to each participant. A Cox regression model with time-varying exposures and strata of geographic regions was employed to assess the risks of stroke mortality associated with PM(2.5), after adjusting for individual risk factors. The cross-product term of PM(2.5) exposure and annual temperature range was further added into the regression model to test whether the long-term temperature variation would modify the association of PM(2.5) with stroke mortality. Among the study participants, the annual mean level of PM(2.5) concentration was 66.3 μg/m(3) ranging from 39.0 μg/m(3) to 100.6 μg/m(3). For each 10 μg/m(3) increment in PM(2.5), the hazard ratio (HR) was 1.31 (95% CI: 1.04-1.65) for stroke mortality after multivariable adjustment. In addition, the HRs of PM(2.5) decreased gradually as the increase of annual temperature range with the HRs of 1.95 (95% CI: 1.36-2.81), 1.53 (95% CI: 1.06-2.22), and 1.11 (95% CI: 0.75-1.63) in the low, middle, and high group of annual temperature range, respectively. The findings provided further evidence of long-term PM(2.5) exposure on stroke mortality in high-exposure settings such as northern China, and also highlighted the view that assessing the adverse health effects of air pollution might not ignore the role of temperature variations in the context of climate change.
Ozone (O(3)) is a reactive oxidant exerting both inflammatory and oxidative damages to the respiratory system. With the ground-level O(3) progressively increasing in the past decade, the reevaluation of the pneumonia hospitalization risk from exposure to O(3) is of public health interest. We conducted an ecological time-series study to examine the city-specific association between short-term O(3) exposure and pneumonia hospitalizations in Hong Kong and Taipei, respectively. We linked the daily pneumonia hospitalization count to air pollution concentrations and weather conditions according to the date of admission during 2010-2017. We applied a generalized additive distributed lag model to examine the association while adjusting for time-varying covariates. Stratified analysis by age group and the potential harvesting effect of O(3) were evaluated. We observed the harvesting effects of O(3) on pneumonia hospitalizations in children in both cities and adults in Taipei. The short-term effect of O(3) lasted for around one week. An interquartile range (IQR) increment of daytime 8-hour mean concentration of O(3) distributed over 0-6 lag days in Hong Kong (42.4 μg/m(3)) was associated with a 7.04% (95% CI: 5.35-8.76%) increase in hospital admissions for elderly pneumonia, while the corresponding cumulative excess risk per IQR increment of O(3) in Taipei (38.7 μg/m(3)) was 3.41% (95% CI: 1.63-5.22%). Different O(3) metrics, varying degrees of freedom for filtering the temporal trend, and three-pollutant models supported the robustness of the associations. We concluded that short-term O(3) exposure was associated with pneumonia hospitalizations in the elderly population. Understanding the pneumonia hospitalization risk of O(3) will help to inform public health policies in the planning of ozone control strategies and intervention measures to prevent ozone-related pneumonia in vulnerable elderly populations.
Background: Health effects associated with extreme temperature and elevated air pollutants have been concerns. The present study examined mortality from and morbidity of chronic kidney disease (CKD) associated with extreme temperature and exposure to fine particulate matter (PM2.5) and ozone (O-3) by sex and age in 2005-2016 in metropolitans of Taiwan. Methods: The distributed lag non-linear model was applied to analyze roles of extreme high (99th percentile) and low (5th percentile) temperatures, and 90th percentile PM2.5 and ozone (O3) in association with CKD risks of deaths, emergency room visits (ERVs), and outpatient visits by age (40-64 and 65 years and above) and sex. Pooled relative risk (RR) and 95% confidence intervals (CI) for all studied areas were estimated using random -effects meta-analysis. Results: Cold spells (< 14 C) showed a higher risk on mortality from CKD for the elderly. Middle-aged population was more vulnerable to high temperature (31.3 C) with the highest risk for women admitted to outpatient visits [RR = 1.25; (95% CI; 1.17-1.34)]. Women aged 65 years and above had the highest risk after exposing to higher levels of PM2.5 (55 mu g/m(3)) [RR = 1.07; (95% CI; 1.03-1.12)] and O-3 (43 ppb) [RR = 1.07; (95% CI; 1.00-1.15)]. Conclusions: The elderly CKD patients were more prone to the adverse effect of low temperature and high levels of PM2.5 and O-3. Middle aged groups were more prone to health risks related to the high temperature. Men are more susceptible to the high temperature, meanwhile women are sensitive to higher levels of PM2.5 and O-3.
How to mitigate greenhouse gas emission and achieve human development remain major sustainability issues, particularly in China. Empirical research on the effects of climate warming and social change on human health and wellbeing is quite fragmented. This study examines the impact of environmental issues and social changes on health and human wellbeing using a time series data of China from 1991 to 2020. Findings show that environmental issues have a negative impact on health and human wellbeing in long run. While the internet is a form of social change that tends to improve health and human wellbeing in the long run. FDI exerts a positive effect on human health, but it does not improve wellbeing in the long run. In contrast, financial development does not improve human health but it has a significant positive impact on wellbeing in the long run. Our empirical insights have important implications for achieving human wellbeing through the pursuit of environmental sustainability and social change.
As the most common mental disorder, anxiety heavily damages human mental health and leads to heavy health burdens. However, evidence concerning the impact of NO2 on anxiety is limited. In this study, we aimed to further explore the association between short-term NO2 exposure and anxiety outpatient visits in Xi’an, a city located in Northwest China with relatively heavy air pollution. Daily data of anxiety outpatient visits, air pollutants (PM2.5, PM10, SO2, NO2, CO, and O-3), and meteorological conditions (daily mean temperature and relative humidity) from 2013 to 2019 were gathered. Then generalized additive models (GAM) was adopted to investigate the relationship between short-term NO2 exposure and the number of anxiety outpatient visits after controlling for long-term effects, holiday effects, day of the week, and weather conditions. The results showed that NO2 exposure was positively correlated with the number of daily anxiety outpatient visits: A 10 mu g/m(3) increase of NO2 concentration corresponded to 1.94% (95%CI: 1.19%, 2.68%) and 3.72% (95%CI: 2.35%, 5.08%) increase in anxiety outpatient visits at lag 1 and lag 07, respectively. Such a relationship showed gender differences (more obvious in females) but no age differences. More interestingly, the association between NO2 and anxiety outpatient visits showed to be more obvious during cool seasons than during warm seasons. In summary, short-term ambient NO2 exposure, especially during cool seasons, may be related to a higher risk of anxiety outpatient visits.
A reduction in the energy-related emissions of air pollutants would not only mitigate climate change but would also improve local air quality and public health. This paper aimed to analyze the trends of air quality index (AQI) and greenhouse gas (GHG) emissions in Taiwan by using the latest official statistics. In addition, this study also summarized regulatory measures for controlling air pollution from the energy sector with relevance to sustainable development goals (SDGs). With the joint efforts by the public and private sectors, the change in the total GHG emissions did not vary much with the exception of 2009, ranging from 250 to 272 million metric tons of CO2 equivalent from 2005 through 2019. Based on the data on AQI, the percentage of AQI by station-day with AQI > 100 has decreased from 18.1% in 2017 to 10.1% in 2020, indicating a decreasing trend for all criteria air pollutants. On the other hand, the coronavirus disease (COVID-19) lockdown, in 2019, has positively impacted Taiwan’s urban air quality, which was consistent with those observed in other countries. This consistent situation could be attributed to the climate change mitigation policies and promotional actions under the revised Air Pollution Control Act and the Greenhouse Gas Reduction and Management Act of 2015. In response to the SDGs launched by the Taiwan government in 2018, achieving the relevant targets by 2030 can be prospective.
The purpose of this paper is to evaluate the monetary GHG reduction benefits and health co-benefits for the industrial sector under the imposition of a carbon charge in Taiwan. The evaluation proceeds from 2023-2030 for different rates of carbon charge for the GHGs by a model of “Taiwan Economic Input Output Life Cycle Assessment and Environmental Value” constructed in this study. It is innovative in the literature to simulate the benefits of GHG reductions and health co-benefits of air pollutions for the industrial sector under the imposition of a carbon charge comprehensively. The results consistently show benefits whether the charge is imposed on the scope 1 and scope 2 GHG emissions or on the scope 1 emissions only. The health co-benefits are on average about 5 times those of GHG reductions benefits in 2023-2030. The average total benefits with the summation of GHG reduction benefits and health co-benefits are 821.9 million US dollars and 975.1 US million US dollars per year, respectively. However, both the GHG reduction benefits and health co-benefits are consistently increasing at a decreasing rate in 2023-2030. The increased multiple for the rate of the carbon charge is higher than the increased multiple of the total benefits and this result shows that the increase of the carbon charge becomes less effective.
Previous observational studies have shown that exposure to ambient temperature and air pollution were associated with the incidence of gestational diabetes mellitus (GDM). However, the susceptible time window of non-optimal temperature on GDM is still unknown, and the interaction with air pollution has not been examined. We conducted a prospective cohort study in Guangzhou, China to investigate the windows of susceptibility of temperature extremes and variability on the risk of GDM and to explore any interaction effect with air pollution. Daily maximum (T(max)), minimum temperature (T(min)) and diurnal temperature range (DTR) were obtained from Guangdong Meteorological Service. Distributed lag non-linear models with a logistic regression were applied to assess the effect of temperature extremes and DTR in different weeks of gestation on GDM. To examine the interaction effect, relative excess risk due to interaction index, attributable proportion and synergy index were calculated. There were 5,165 pregnant women enrolled, of which 604 were diagnosed with GDM (11.7%). Compared with a reference temperature (50th percentile of T(max)), we found that extreme high temperature (99th percentile of T(max)) exposure during 21st and 22nd gestational weeks was associated with an increased risk of GDM. Extreme low temperature (1st percentile of T(max)) exposure during 14th to 17th weeks increased the risk of GDM. We observed that per 1 °C increment of DTR during 21st to 24th weeks was associated with an elevated GDM risk. No interaction effect of temperature extremes or variability with air pollution on GDM were observed. Our results suggested that non-optimal temperature is an independent risk factor of GDM. The time window of susceptibility for extreme temperatures and DTR exposure on the risk of GDM generally occurred in second trimester of pregnancy. In the context of climate change, our study has important implications for reproductive health and justifies more research in different climate zones.
The independent associations of extreme temperature and ambient air pollutant with the admission to hospital and mortality of ischemic stroke have been widely investigated. However, knowledge about the modification effects of variation in season and temperature on the association between exposure to nitrogen dioxide (NO(2)) and ischemic stroke onset is still limited. This study purposed to explore the effect of NO(2) on daily ischemic stroke onset modified by season and ambient temperature, and identify the potential population that susceptible to ischemic stroke onset connected with NO(2) and ambient temperature. Data on daily ischemic stroke counts, weather conditions, and ambient air pollutant concentrations in Shenzhen were collected between January 1, 2008, and December 31, 2014. The seasonal effect on the NO(2)-associated onset was measured by a distributed-lag linear model. Furthermore, a generalized additive model that incorporated with stratification analyses was used to calculate the interactive effects between NO(2) and ambient temperature. During the winter, the average percentage increase in daily ischemic stroke onset for each 10 μg/m(3) increment in NO(2) concentration on lagged 2 days was 3.05% (95% CI: 1.31-4.82%), while there was no statistically significant effect of NO(2) during summer. And the low-temperature days ([Formula: see text] mean temperature), with a 2.23% increase in incidence (95% CI: 1.18-3.29%) for the same concentration increase in NO(2), were significant higher than high temperature days ([Formula: see text] mean temperature). The modification effects of temperature on the study association were more pronounced in individuals aged 65 years or more and in males. The adverse health effects of NO(2) on ischemic stroke are more pronounced during winter or low temperature periods. Elderly adults or males presented higher risks with these exposures.
BACKGROUND: The relationship between air pollution and meteorological factors on diseases has become a research hotspot recently. Nevertheless, few studies have touched the inferences of nitrogen dioxide (NO(2)) and atmospheric pressure (AP) on hospitalization risk for chronic obstructive pulmonary disease (COPD). OBJECTIVES: To investigate the short-term impact of particulate air pollutants and meteorology factors on hospitalizations for COPD and quantify the corresponding risk burden of hospital admission. METHODS: In our study, COPD cases were collected from Guangzhou Panyu Central Hospital (n = 11,979) from Dec of 2013 to Jun 2019. The 24-h average temperature, relative humidity (RH), wind speed (V), AP and other meteorological data were obtained from Guangzhou Meteorological Bureau. Air pollution data were collected from Guangzhou Air Monitoring Station. The influence of different NO(2) and AP values on COPD risk was quantified by a distributed lag nonlinear model (DLNM) combined with Poisson Regression and Time Series analysis. RESULTS: We found that NO(2) had a non-linear relationship with the incidence of COPD, with an approximate “M” type, appearing at the peaks of 126 μg/m³ (RR = 1.32, 95%CI, 1.07 to 1.64) and 168 μg/m³ (RR = 1.21, 95%CI, 0.94 to 1.55), respectively. And the association between AP and COPD incidence exhibited an approximate J-shape with a peak occurring at 1035 hPa (RR = 1.16, 95% CI, 1.02 to 1.31). CONCLUSIONS: The nonlinear relationship of NO(2) and AP on COPD admission risk in different periods of lag can be used to establish an early warning system for diseases and reduce the possible outbreaks and burdens of COPD in a sensitive population.
There are increasing concerns with regard to spontaneous abortion (SAB), the loss of pregnancy without external intervention before 20 weeks of gestation, among reproductive-aged women. To date, limited evidence is available concerning the association between SAB and air pollutants, especially in developing countries. Daily baseline outpatient data for SAB from January 1, 2014, to December 31, 2018 (1826 days) were obtained in Chongqing, a metropolis of southwest China. The over-dispersed Poisson generalized additive model with control of meteorological conditions and day of week was used to estimate the short-term effects of ambient air pollution on the daily number of SAB outpatients. A total of 42,334 SAB outpatient visits for SAB were recorded. No statistically significant association was observed between SAB and CO, PM(2.5), PM(10), O(3), and SO(2). The positive association only appeared for NO(2): positive associations between SAB and NO(2) were observed in both single-day models (lag 0, lag 1, lag 3, and lag 4) and cumulative exposure models (lag 01, lag 03, and lag 05) and the most significant effects were observed at lag 05 (3.289%; 95% CI: 1.568%, 5.011%). Moreover, the women with higher ages (30-39 and > 39) were more sensitive than those with lower ages (18-29), and the effect estimates were more evident in cool seasons. Collectively, our results suggested that short-term NO(2) exposure was associated with higher risk of SAB, especially in elder women and cool seasons, which may contribute to further understand the role of air pollution on SAB and other adverse obstetric outcomes.
Energy is considered a vital factor of economic growth that contributes to improve quality of life and health status. However, global warming, climate change, and environmental degradation are due primarily because of energy emissions, whereas environmental degradation is detrimental to health. Since one-fifth of the population lives in South Asia, it is necessary to analyze the impact of energy and environmental degradation on health status in this region. For this purpose, health status in South Asia is proxy with health expenditure, life expectancy, and infant mortality, and this study investigates the effect of energy intensity, income, and carbon emissions on health status, whereas urbanization is considered a control variable. The cointegration test indicates South Asia’s long-term health status factors are energy intensity, income, carbon emissions, and urbanization. Long-run results suggest that energy intensity and income improve health status as these factors reduce health expenditure, improve life expectancy, and decrease infant mortality. Environmental degradation not only increases health expenditure but also hinders life expectancy and increases mortality. Moreover, an increase in income diminishes health expenditure and is responsible for high life expectancy and low mortality in South Asia.
International trade’s impact on the pollution reduction, especially varied reduction effects dealing with global or local pollutants has not been thoroughly researched empirically. We explored effects of international trade participation on both the carbon dioxide emission intensity and sulfur dioxide emission intensity with a panel data of 179 major countries during 20 years when globalization thrived. Carbon dioxide causing climate change is a global concern. While sulfur dioxide is one major air pollutant causing local health problems. Empirically, international trade participation mainly reduces carbon dioxide emission intensity but not sulfur dioxide emission intensity. Also, trade in goods form is more effective than in service form. However, international trade participation does little to improving a country’s overall technology level, implying that regulation enhancement under international norm is the main mechanism. Compared with developed countries, developing countries can reduce both kinds of pollutant emission intensities more effectively by participating into international trade. A case study of China’s entering into World Trade Organization (WTO)’s impact on pollutant reduction can provide more evidence. Also, developing countries with higher industrialization level experiences a bigger improvement in cleaner production. And developing countries with higher democratization level pay more attention to reduce local environmental concerns.
Polycyclic aromatic hydrocarbons (PAHs) are hazardous compounds associated with respiratory disease and lung cancer. Increasing fossil fuel consumption, which causes climate change, has accelerated the emissions of PAHs. However, potential risks by PAHs have not been predicted for Korea, and appropriate PAH regulations under climate change have yet to be developed. This study assesses the potential risks posed by PAHs using climate change scenarios based on deep learning, and a multimedia fugacity model was employed to describe the future fate of PAHs. The multimedia fugacity model describes the dynamics of sixteen PAHs by reflecting inter-regional meteorological transportation. A deep neural network predicts future environmental and economic conditions, and the potential risks posed by PAHs, in the year 2050, using a prediction model and climate change scenarios. The assessment indicates that cancer risks would increase by more than 50%, exceeding the lower risk threshold in the southern and western regions. A mix of strategies for developing PAH regulatory policies highlighted the necessity of increasing PAHs monitoring stations and controlling fossil fuel usage based on the domestic and global conditions under climate change scenarios.
Exposure to polycyclic aromatic hydrocarbons (PAHs) are a cause of chronic cough occurrence in adult patients. In order to clear the relationship between transboundary transport of PAH and health effects, this study investigates the relationship between atmospheric particulate PAHs (p-PAHs), cough occurrence by epidemiological research, and meteorological conditions using a chemical transport model. Source receptor relationship (SRR) analysis revealed that a higher cough occurrence was caused by exposure to high p-PAH levels in air masses transported from central China (CCHN, 30-40 degrees N) under westerly conditions. The p-PAHs transported from northern China (NCHN, >40 degrees N) and the eastern part of Russia (ERUS) under north-westerly conditions also contributed to cough occurrence. The low equivalent potential temperature (ePT) and geopotential height anomaly suggested that the p-PAHs emitted near the surface were suppressed to upward transport under the colder air mass but were instead transported horizontally near the surface in the boundary layer, resulting in high p-PAH concentrations arriving in Kanazawa. Our study’s findings suggest that the air mass transport pattern associated with meteorology strongly influences the high p-PAH concentrations causing adult chronic cough occurrence.
BACKGROUND: Climate change models predict that atmospheric carbon dioxide [CO2] levels will be between 700 and 900 ppm within the next 80 y. Despite this, the direct physiological effects of exposure to slightly elevated atmospheric CO2 (as compared with ∼ 410 ppm experienced today), especially when exposures extend from preconception to adulthood, have not been thoroughly studied. OBJECTIVES: In this study we aimed to assess the respiratory structure and function effects of long-term exposure to 890 ppm CO2 from preconception to adulthood using a mouse model. METHODS: We exposed mice to CO2 ( ∼ 890 ppm) from prepregnancy, through the in utero and early life periods, until 3 months of age, at which point we assessed respiratory function using the forced oscillation technique, and lung structure. RESULTS: CO2 exposure resulted in a range of respiratory impairments, particularly in female mice, including higher tissue elastance, longer chord length, and lower lung compliance. Importantly, we also assessed the lung function of the dams that gave birth to our experimental subjects. Even though these mice had been exposed to the same level of increased CO2 for a similar amount of time ( ∼ 8 wk), we measured no impairments in lung function. This suggests that the early life period, when lungs are undergoing rapid growth and development, is particularly sensitive to CO2. DISCUSSION: To the best of our knowledge, this study, for the first time, shows that long-term exposure to environmentally relevant levels of CO2 can impact respiratory function in the mouse. https://doi.org/10.1289/EHP7305.
Severe volatile organic compound (VOC) pollution has become an urgent problem during the heating season in the North China Plain (NCP), as exposure to hazardous VOCs can lead to chronic or acute diseases. A campaign with online VOC measurements was conducted at a rural site in Wangdu, NCP during the 2018 heating season to characterize the compositions and associated sources of VOCs and to assess their potential health risks. The total concentration of VOCs with 94 identified species was 77.21 +/- 54.39 ppb. Seven source factors were identified by non-negative matrix factorization, including coal combustion (36.1%), LPG usage (21.1%), solvent usage (13.9%), biomass burning and secondary formation (142%), background (7.0%), industrial emissions (4.5%), and vehicle emissions (3.3%). The point estimate approach and Monte Carlo simulation were used to estimate the carcinogenic and non-carcinogenic risks of harzadous VOCs. The results showed that the cumulative health risk of VOCs was above the safety level. Acrolein, 1.2-dichlorprothane, 12-dichloropropane, chloroform, 1,3-butadiene, and benzene were identified as the key hazardous VOCs in Wangdu. Benzene had the highest average carcinogenic risk. Solvent usage and secondary formation were the dominant sources of adverse health effects. During the Spring Festival, most sources were sharply reduced; and VOC concentration declined by 49%. However, coal and biomass consumptions remained relatively large, probably due to heating demand. This study provides important references for the control strategies of VOCs during the heating season in heavily polluted rural areas in the NCP. (C) 2021 Elsevier B.V. All rights reserved.
Airborne pollens cause pollinosis and have the potential to affect microphysics in clouds; however, the number of monitored species has been very limited due to technical difficulties for the morphotype identification. In this study, we applied an eDNA approach to the airborne pollen communities in the suburbs of the Tokyo metropolitan area in Japan, within a mixed urban, rural, and mountain landscape, revealing pollen seasonality of various taxa (a total of 78 families across the period) in the spring season (February to May). Those taxa distinctly shifted in the season, especially in the beginning of February and the middle of April. Air temperature shift was an obvious key factor to affect the airborne pollen community, while the influence of other meteorological factors, such as wind speed, humidity, and precipitation, was not clear. Taxonomic classification of major Amplicon Sequence Variants (ASVs) indicates multiple pollen sources, including natural forest, planted forest, roadside, park lands, and horticultural activities. Most major ASV belongs to Japanese cedar (Cryptomeria japonica), which is the most notable allergen that causes pollinosis in Japan, peaking in mid-February to March. Backward trajectory analysis of air masses suggests that the Japanese cedar and other Cupressaceae plantation forests in the western mountains were a significant source of airborne pollen communities detected at our sampling site. Other major plant pollen sources, including Japanese zelkova (Zelkova serrata) and ginkgo (Ginkgo biloba), emanated from the nearby parks or roadside regions. This study’s approach enables us to visualize the phenology of multiple pollen, including timing and duration. Long-term monitoring of this type would provide additional insight into understanding the role of climate change on pollen transmission and links to flowering events.
In Japan, the representative allergenic airborne pollen-related allergic diseases include Cupressaceae in early spring, the birch family and grass in spring and mugwort in autumn. As a result of a long- term survey the past 27 to 33 years, an increasing in the amount of conifer airborne pollen and an earlier start dispersal were observed, related climate change. In addition, an increase in the number of patients with Japanese cedar pollinosis and the severity has been observed. Provision of medical pollen information, medication and sublingual immunotherapy have all been enhanced. Recently, pollen-food allergic syndrome has become of increased interest.
INTRODUCTION: Children with allergies are at greater risk of becoming sensitized to allergenic pollens in response to environmental changes. This study investigated the relationship between changes in pollination associated with meteorologic changes and the sensitization rates of children to tree pollen allergens in the metropolitan area of Seoul, Korea. METHODS: The study population consisted of 8,295 children who visited the pediatric allergy clinics at Hanyang University Seoul and Guri Hospital for allergy symptoms between January 1, 1998, and December 31, 2019. Pollen was collected at the two hospitals during the study using a Burkard 7-day sampler. Meteorologic data were obtained from the National Weather Service. RESULTS: Among the major tree pollens, the largest increase in allergic sensitization was to oak, hazel, and alder pollens (0.28% annually). The pollen-sensitization rates increased annually within younger age groups. The duration of the pollen season was 98 days in 1998 and 140 days in 2019. Positive correlations were determined between the duration of the pollen season and the rates of sensitization to tree pollens, as well as between the pollen-sensitization rates and increasing temperature. CONCLUSIONS: This study demonstrated the correlation between weather changes and the resulting changes in the pollen season with sensitization rates to allergenic pollens in children living in the Seoul metropolitan area. An annual increase in sensitization rates in younger children was determined. This pattern is expected to continue due to continuing climate change.
Airborne pollen causes various types of allergies in humans, and the extent of allergic infection is related to the presence of different types of sporo-pollen and existing meteorological conditions in a certain area. Therefore, an aeropalynological study of 72 airborne samples with a hydrofluoric acid (HF) treatment was conducted in the Haizhu district of Guangzhou, China, in 2016, to identify the temporal variations in airborne sporo-pollen and the relationship between airborne sporo-pollen concentrations and different meteorological variables in Guangzhou, China. Forty-five types of airborne pollen, seven types of airborne spores, and some undetermined sporo-pollen taxa were identified with two separate plant habitats occurring during this period (from January to December 2016): arboreal pollen (tree-based) and non-arboreal pollen (herb, shrub, aquatic, liane, etc.). Furthermore, the daily records of four key meteorological variables (temperature, precipitation, relative humidity, and wind speed) were acquired to distinguish the pollen seasons and correlated with Spearman’s rho test to establish a pollen-weather data book with the seasonal variations. The two leading seasons were identified based on pollen abundance: spring and autumn. Among them, the primary dominant sporo-pollen families during the spring season were Poaceae, Pinaceae, Euphorbiaceae, Moraceae, Microlepia sp., and Polypodiaceae. Conversely, Artemisia sp., Asteraceae, Cyperaceae, Poaceae, Alnus sp., Corylus sp., Myrtaceae, and Rosaceae were the dominant pollen species during autumn. However, few pollen grains were identified in January, May-July, and December. The statistical analysis revealed that temperature had both positive and negative correlations with sporo-pollen concentrations. However, precipitation and relative humidity had a strong impact on the sporo-pollen dispersion and exhibited a negative correlation with the sporo-pollen concentrations. The wind speed had a positive but strong correlation with the sporo-pollen concentration during the study period. Some inconsistent results were found due to environmental variations, vegetation type, and climate change around the study area. This study will facilitate the identification of pollen seasons to prevent the occurrence of pollen-related allergies in the Guangzhou city area.
INTRODUCTION: Aeropollen can induce detrimental effects, particularly in respiratory airways. Monitoring local aeropollen is essential for the management of pollen allergic patients in each area. However, without resources for constant monitoring, pollen counts are subjected to biases imposed by the choices of sampling season, time of collection, and location. Therefore, the effects of these factors must be better understood. This study investigated the dynamics of aeropollen types through seasonal variation, diurnal cycle and different heights from the ground in Bangkok, Thailand. METHODS: Aeropollen samples were collected for 12 months at the Faculty of Science, Mahidol University in Bangkok, using a RotoRod Sampler(®). For the investigation of diurnal effect, pollen was collected at 7 a.m., 10 a.m., 1 p.m., 4 p.m., and 7 p.m. For the study of height effect, data were collected at 2, 10, and 18 meters above ground. RESULTS AND DISCUSSION: This is the first study of the effects of diurnal cycle and height variation on airborne pollen count in Southeast Asia. The results showed the highest concentration of aeropollen was observed in November, which was at the beginning of the northeast monsoon season in Bangkok, whereas the lowest concentration was recorded in July (rainy season). Interestingly, the lowest airborne pollen concentration recorded in July was greater than the high level of most standards. Grass pollen was found as the major aeropollen. The highest total pollen concentration was detected at 1 p.m. The maximum pollen quantity was detected at 10 meters from the ground. However, the total aeropollen concentration was extremely high (>130 grains/m(3)) at all elevated heights compared to other studies that mostly found at lower height (approximately 1-2 m above ground). The result suggested that pollen concentrations of most pollen types increased as height increased. This study also illustrated the correlation between aeropollen quantity and local meteorological factors. CONCLUSION: This aeropollen survey reported that pollen concentration and diversity were affected by seasonal variation, diurnal cycle, and height from the ground. Understanding these relationships can help with predictions of aeropollen type and quantity.
Sandstorms and/or duststorms that are affecting the Korean peninsula occur most frequently in the spring season in the arid and semi-arid area of sand deserts including Badainjaran, Tengger, Mu Us, Hunsandakue and Keoeolchin, Gobi region and Loess Plateau in the Asian continent. The area of Asian dust source regions cover most of northern China and Mongolia. Warning is issued when the hourly averaged dust(PM10) concentration is expected to exceed 800 ㎛/㎥ for over 2hours.
Speciated ground-level aerosol concentrations are required to understand and mitigate health impacts from dust storms, wildfires, and other aerosol emissions. Globally, surface monitoring is limited due to cost and infrastructure demands. While remote sensing can help estimate respirable (i.e. ground level) concentrations, current observations are restricted by inadequate spatiotemporal resolution, uncertainty in aerosol type, particle size, and vertical profile. One key issue with current remote sensing datasets is that they are derived from reflectances observed by polar-orbiting imagers, which means that aerosol is only derived during the daytime and only once or twice per day. Newer quantification methods using geostationary infrared (IR) data have focussed on detecting the presence, or absence, of an event. The determination of aerosol composition or particle size using IR exclusively has received little attention. This manuscript summarizes four scientific papers, published as part of a larger study, and identifies requirements for (a) using infrared radiance observations to obtain continual (i.e. day and night) concentration estimates; (b) increasing temporal resolution by using geostationary satellites; (c) utilizing all infrared channels to maximize spectral differences due to compositional changes; and (d) applying a high-pass filter (brightness temperature differences) to identify compositional variability. Additionally, (e) a preliminary calibration methodology was tested against three severe air quality case study incidents, namely, a dust storm, smoke from prescribed burns, and an ozone smog incident, near Sydney in eastern Australia which highlighted the ability of the method to determine atmospheric stability, clouds, and particle size. Geostationary remote sensing provides near-continuous data at a temporal resolution comparable to monitoring equipment. The spatial resolution (~?4 km(2) at NADIR) is adequate for large sources but coarse for localized sources. The spectral sensitivity of aerosol is limited and appears to be dominated by humidity changes rather than concentration or compositional changes. Geostationary remote sensing can be used to determine the timing, duration, and spatial extent of an air quality event. Brightness temperature differences can assist in qualifying composition with an order of magnitude estimate of concentration.
Climate change and HIV/AIDS represent two of the greatest threats to human health in the 21st century. However, limitations in understanding the complex relationship between these syndemics continue to constrain advancements in the prevention and management of HIV/AIDS in the context of a rapidly changing climate. Here, we present a conceptual framework that identifies four pathways linking climate change with HIV/AIDS transmission and health outcomes: increased food insecurity, increased prevalence of other infectious diseases, increased human migration, and erosion of public health infrastructure. This framework is based on an in-depth literature review in PubMed and Google Scholar from June 6 to June 27, 2019. The pathways linking climate change with HIV transmission and health outcomes are complex with multiple interacting factors. Food insecurity emerged as a particularly important mediator by driving sexual risk-taking behaviours and migration, as well as by increasing susceptibility to infections that are common among people living with HIV (PLWHIV). Future interventions should focus on decreasing carbon dioxide emissions globally and increasing education and investment in adaptation strategies, particularly in those areas of sub-Saharan Africa and southeast Asia heavily impacted by both HIV and climate change. Environmentally sustainable interventions such as urban gardening and investing in sustainable agriculture technologies also have significant health co-benefits that may help PLWHIV adapt to the environmental consequences of climate change.
The increasing distribution and prevalence of fasciolosis in both human and livestock are concerning. Here, we examine the various types of factors influencing fasciolosis transmission and burden and the interrelations that may exist between them. We present the arsenal of molecules, ‘adjusting’ capabilities and parasitic strategies of Fasciola to infect. Such features define the high adaptability of Fasciola species for parasitism that facilitate their transmission. We discuss current environmental perturbations (increase of livestock and land use, climate change, introduction of alien species and biodiversity loss) in relation to fasciolosis dynamics. As Fasciola infection is directly and ultimately linked to livestock management, living conditions and cultural habits, which are also changing under the pressure of globalization and climate change, the social component of transmission is also discussed. Lastly, we examine the implication of increasing scientific and political awareness in highlighting the current circulation of fasciolosis and boosting epidemiological surveys and novel diagnostic techniques. From a joint perspective, it becomes clear that factors weight differently at each place and moment, depending on the biological, environmental, social and political interrelating contexts. Therefore, the analyses of a disease as complex as fasciolosis should be as integrative as possible to dissect the realities featuring each epidemiological scenario. Such a comprehensive appraisal is presented in this review and constitutes its main asset to serve as a fresh integrative understanding of fasciolosis.
Disaster-induced displacement is associated with an increased risk of physical and mental health disorders. We aim to understand (1) the magnitude and pattern of natural disasters, affected-population, and deaths by analyzing the surveillance data by the Emergency Events Database and (2) health outcomes by a systematic review of previous studies (1975-2017), which reported physical or mental health outcomes and epidemiological measure of association among population displaced by natural disasters in Southeast Asia. A total of 674 disasters, mainly floods, storms, and earthquakes, occurred between 2004 and 2017. From the systematic review, among 6 studies met inclusion criteria, which focused on mental health (n = 5) and physical health (n = 1). All studies describing mental health resulted from the 2004 tsunami in Ache, Indonesia. We found over 7 times more publications for the disasters in Far East Asia. Selected studies revealed significantly worse mental health outcomes and poor physical health among displaced population compared with nondisplaced population. Despite the alarmingly large population displaced by natural disasters in Southeast Asia, very few studies investigate physical and mental health outcomes of such crisis. Following the Sendai Framework for Disaster Risk Reduction 2015-2030, researcher and policy-makers have to present more resources toward preventing and mitigating health outcomes.
Global health threats including epidemics and climate change, know no political borders and require regional collaboration if they are to be dealt with effectively. This paper starts with a review of the COVID-19 outbreak in Israel, Palestine and Jordan, in the context of the regional health systems, demography and politics. We suggest that Israel and Palestine function as one epidemiological unit, due to extensive border crossing of inhabitants and tourists, resulting in cross-border infections and potential for outbreaks’ transmission. Indeed, there is a correlation between the numbers of confirmed cases with a 2-3 weeks lag. In contrast, Jordan has the ability to seal its borders and better contain the spread of the virus. We then discuss comparative public health aspects in relation to the management of COVID-19 and long term adaptation to climate change. We suggest that lessons from the current crisis can inform regional adaptation to climate change. There is an urgent need for better health surveillance, data sharing across borders, and more resilient health systems that are prepared and equipped for emergencies. Another essential and currently missing prerequisite is close cooperation within and across countries amidst political conflict, in order to protect the public health of all inhabitants of the region.
A recent multidisciplinary compilation of studies on changes in the Siberian environment details how climate is changing faster than most places on Earth with exceptional warming in the north and increased aridity in the south. Impacts of these changes are rapid permafrost thaw and melt of glaciers, increased flooding, extreme weather events leading to sudden changes in biodiversity, increased forest fires, more insect pest outbreaks, and increased emissions of CO(2) and methane. These trends interact with sociological changes leading to land-use change, globalisation of diets, impaired health of Arctic Peoples, and challenges for transport. Local mitigation and adaptation measures are likely to be limited by a range of public perceptions of climate change that vary according to personal background. However, Siberia has the possibility through land surface feedbacks to amplify or suppress climate change impacts at potentially global levels. Based on the diverse studies presented in this Ambio Special Issue, we suggest ways forward for more sustainable environmental research and management.
Global food insecurity concerns due to climate change, emphasizes the need to focus on the sensitivity of sorghum to climate change and potential crop improvement strategies available, which is discussed in the current review to promote climate-smart agriculture. Climate change effects immensely disturb the global agricultural systems by reducing crop production. Changes in extreme weather and climate events such as high-temperature episodes and extreme rainfalls events, droughts, flooding adversely affect the production of staple food crops, posing threat to ecosystem resilience. The resulting crop losses lead to food insecurity and poverty and question the sustainable livelihoods of small farmer communities, particularly in developing countries. In view of this, it is essential to focus and adapt climate-resilient food crops which need lower inputs and produce sustainable yields through various biotic and abiotic stress-tolerant traits. Sorghum, “the camel of cereals”, is one such climate-resilient food crop that is less sensitive to climate change vulnerabilities and also an important staple food in many parts of Asia and Africa. It is a rainfed crop and provides many essential nutrients. Understanding sorghum’s sensitivity to climate change provides scope for improvement of the crop both in terms of quantity and quality and alleviates food and feed security in future climate change scenarios. Thus, the current review focused on understanding the sensitivity of sorghum crop to various stress events due to climate change and throws light on different crop improvement strategies available to pave the way for climate-smart agriculture.
Lymphatic filariasis (LF) is an important neglected parasitic disease according to the World Health Organization. In this study, we aimed to determine the prevalence of human LF in Asia using a systematic review and meta-analysis approach. Records from 1990 to 2018 in reputable databases including PubMed, Science Direct, Embase, and Cochrane Library were searched using a panel of related keywords. All 48 countries of Asia were searched one by one in combination with the keywords. In all, 41,742 cases identified in this study were included in the analysis. According to our findings, the pooled prevalence of LF in Asia was estimated at 3% (95% CI: [1.7, 5.2]). There was no major trend in the cumulative prevalence of LF over time. Some countries in Asia including China, Japan, Vietnam, and South Korea succeeded in eliminating LF as a public health problem, but others still need to monitor the disease. Based on the initiative of the WHO starting in 2000, some countries in Asia succeeded in eliminating LF as a public health problem. Other countries have taken steps to eliminate the disease with variable degrees of success. These efforts might be affected by issues such as climate change.
Climatic change will have an impact on production and release of pollen, with consequences for the duration and magnitude of aeroallergen seasonal exposure and allergic diseases. Evaluations of pollen aerobiology in the southern hemisphere have been limited by resourcing and the density of monitoring sites. This review emphasizes inconsistencies in pollen monitoring methods and metrics used globally. Research should consider unique southern hemisphere biodiversity, climate, plant distributions, standardization of pollen aerobiology, automation, and environmental integration. For both hemispheres, there is a clear need for better understanding of likely influences of climate change and comprehending their impact on pollen-related health outcomes.
Increasingly severe extreme weather events (EWEs) threaten population health in Asia-Pacific. Resilient health systems can minimize health risks by improving EWE preparedness, response, and recovery. However, how health systems demonstrate resilience is less understood in the emerging resilience literature. The objective of this scoping review was to describe how peer-reviewed and grey literature has operationalized health system resilience to EWEs in Asia-Pacific. Included sources were available in English, published from 2000 to 2019, and focused on health system activity in Asia-Pacific for EWE risk management. The World Health Organization’s climate-resilient health system framework and building block model guided analysis of 49 sources. Health system activity was categorized by system building blocks. Assets and/or gaps to resilience were identified based on whether building blocks facilitated or impeded EWE risk management. Sources mostly focused on the Philippines (29%), India (16%) and Thailand (14%), with lower income economies and Pacific Island countries underrepresented. Floods (47%), typhoons (27%), and cyclones (16%) were frequently discussed while no sources mentioned droughts. Financing was the least mentioned building block (27%) and often described as a gap to resilience (24%). Overall, this review highlights opportunities for future research to develop EWE resilient health systems in Asia-Pacific and beyond.
ISSUE ADDRESSED: Climate change is one of the greatest challenges to public health and well-being. Steps taken by governments now will have a significant effect on public health outcomes, including the food system and food security. METHOD: This study reviewed municipal public health and well-being plans from 79 local government areas (LGAs) in Victoria, Australia. Documents were included if they explicitly mentioned climate change and food insecurity. Of the 79 LGAs, 13 met the selection criteria and a content and framing analysis was conducted to identify the level of recognition of climate change on food security and proposed mitigation actions and strategies. RESULTS: Of the 13 LGAs, the documents of six were identified as having a high level of responsiveness to climate change and food insecurity, five were assessed as medium and two low. Framing analysis identified council acknowledgment of how climate change effects food access through availability and price, and growing food locally and sustainably is seen as a common action to improve food security. CONCLUSION: The findings of this study suggest that planning for climate change and food insecurity is not a high priority for Victorian LGAs. Given the current political climate in Australia, where many in federal government continue to deny the existence of climate change or are reluctant to implement mitigation strategies, it is now and will be increasingly important into the future that local governments plan for the impact of climate change on food insecurity. SO WHAT?: Climate change will impact how people access food and what foods are available to them. Unless all levels of government start to address and plan for climate change, the impact on communities will continue to intensify and grow more costly and damaging.
The cold and arid mountains and plateaus of High Asia, inhabited by a relatively sparse human population, a high density of livestock, and wildlife such as the iconic snow leopard Panthera uncia, are usually considered low risk for disease outbreaks. However, based on current knowledge about drivers of disease emergence, we show that High Asia is rapidly developing conditions that favor increased emergence of infectious diseases and zoonoses. This is because of the existing prevalence of potentially serious pathogens in the system; intensifying environmental degradation; rapid changes in local ecological, socio-ecological, and socio-economic factors; and global risk intensifiers such as climate change and globalization. To better understand and manage the risks posed by diseases to humans, livestock, and wildlife, there is an urgent need for establishing a disease surveillance system and improving human and animal health care. Public health must be integrated with conservation programs, more ecologically sustainable development efforts and long-term disease surveillance.
Water is indispensable for human survival. Freshwater scarcity and unsustainable water are the main growing concerns in the world. It is estimated that about 800 million people worldwide do not have basic access to drinking water and about 2.2 billion people do not have access to safe water supply. Southeast Asia is most likely to experience water scarcity and water demand as a result of climate change. Climate change and the increasing water demand that eventually contribute to water scarcity are focused upon here. For Southeast Asia to adapt to the adverse consequences of global climate change and the growing concern of environmental water demand, fog water harvesting is considered as the most promising method to overcome water scarcity or drought. Fog water collection technique is a passive, low maintenance, and sustainable option that can supply fresh drinking water to communities where fog is a common phenomenon. Fog water harvesting system involves the use of mesh nets to collect water as fog passes through them. Only minimal cost is required for the operation and maintenance. In conclusion, fog water harvesting seems to be a promising method that can be implemented to overcome water scarcity and water demand in Southeast Asia.
Pollen, a major causal agent of respiratory allergy, is mainly affected by weather conditions. In Korea, pollen and weather data are collected by the national observation network. Forecast models and operational services are developed and provided based on the national pollen data base. Using the pollen risk forecast information will help patients with respiratory allergy to improve their lives. Changes in temperature and CO(2) concentration by climate change affect the growth of plants and their capacity of producing more allergenic pollens, which should be considered in making the future strategy on treating allergy patients.
Climate change is one of the major global health threats to the world’s population. It is brought on by global warming due in large part to increasing levels of greenhouse gases resulting from human activity, including burning fossil fuels (carbon dioxide), animal husbandry (methane from manure), industry emissions (ozone, nitrogen oxides, sulfur dioxide), vehicle/factory exhaust, and chlorofluorocarbon aerosols that trap extra heat in the earth’s atmosphere. Resulting extremes of weather give rise to wildfires, air pollution, changes in ecology, and floods. These in turn result in displacement of populations, family disruption, violence, and major impacts on water quality and availability, food security, public health and economic infrastructures, and limited abilities for civil society to maintain citizen safety. Climate change also has direct impacts on human health and well-being. Particularly vulnerable populations are affected, including women, pregnant women, children, the disabled, and the elderly, who comprise the majority of the poor globally. Additionally, the effects of climate change disproportionally affect disadvantaged communities, including low income and communities of color, and lower-income countries that are at highest risk of adverse impacts when disasters occur due to inequitable distribution of resources and their socioeconomic status. The climate crisis is tilting the risk balance unfavorably for women’s sexual and reproductive health and rights as well as newborn and child health. Obstetrician/gynecologists have the unique opportunity to raise awareness, educate, and advocate for mitigation strategies to reverse climate change affecting our patients and their families. This article puts climate change in the context of women’s reproductive health as a public health issue, a social justice issue, a human rights issue, an economic issue, a political issue, and a gender issue that needs our attention now for the health and well-being of this and future generations. FIGO joins a broad coalition of international researchers and the medical community in stating that the current climate crisis presents an imminent health risk to pregnant people, developing fetuses, and reproductive health, and recognizing that we need society-wide solutions, government policies, and global cooperation to address and reduce contributors, including fossil fuel production, to climate change.
Dust activity not only influences human health through dust storms but also affects climate at local and regional scales through the direct effects of dust aerosols on both solar and longwave radiative heating. In this study, based on dust simulations from seven Coupled Model Intercomparison Project Phase 5 (CMIP5) models, the spatial and temporal changes in dust activity over East Asia under a Representative Concentration Pathway 8.5 global warming scenario were examined for the periods of 2016-2035 (P1), 2046-2065 (P2) and 2080-2099 (P3). The results show that the multimodel ensemble mean (MME) of the CMIP5 models largely captures the spatial distribution of dust emissions and dust optical depth (DOD) over East Asia during 1986-2005 (P0). The MME reproduces the increasing trend in dust emissions and DOD over dust sources in East Asia during P0. Accompanying emission reductions during P1 to P3, the DOD simultaneously decreases, and the evident DOD decline can also be found over downwind areas in eastern China and the Korean Peninsula. Simulations project increases in precipitation and the LAI (leaf area index). Simultaneously, the weakened East Asian trough leads to anomalous southerly winds and lower wind speeds at the surface. All these results indicate unfavorable conditions for dust emissions over the sources regions, resulting in a decreased DOD over East Asia during P1 to P3.
Several climate change-related predictions and observations have been documented for the Australian continent. Extreme weather events such as cycles of severe drought and damaging flooding are occurring with greater frequency and have a severe impact on human health. Two specific aspects of climate change affecting allergic and other respiratory disorders are outlined: firstly, the consequences of extreme weather events and secondly, the change in distribution of airborne allergens that results from various climate change factors.
Observed weather and projected climate change suggest an increase in the transmission of vector-borne diseases (VBDs) in the Hindu Kush Himalayan (HKH) region. In this study, we systematically explore the literature for empiric associations between the climate variables and specific VBDs and their vectors in the HKH region. We conducted a systematic synthesis of the published literature on climate variables, VBDs and vectors in the HKH region until the 8th of December 2020. The majority of studies show significant positive associations of VBDs with climatic factors, such as temperature, precipitation, relative humidity, etc. This systematic review allowed us to identify the most significant variables to be considered for evidence-based trend estimates of the effects of climate change on VBDs and their vectors in the HKH region. This evidence-based trend was set into the context of climate change as well as the observed expansion of VBDs and disease vectors in the HKH region. The geographic range of VBDs expanded into previously considered non-endemic areas of highlands (mountains) in the HKH region. Based on scarce, but clear evidence of a positive relationship of most climate variables and VBDs and the observed climatic changes, we strongly recommend an expansion of vector control and surveillance programmes in areas of the HKH region that were previously considered to be non-endemic.
Society could sustain the impact of climate change by adapting to the change and mitigating risks from adverse effects of increasing changes, so that it can continue maintaining its prospect and improving wellbeing. Nevertheless, climate change is more or less affecting society’s functions at different scales, including both individuals and communities. In this review, we discuss the relationship between society and climate change in China from the aspects of the needs at different socioeconomic developing stages. The relationship as well as the current spatial pattern and future risks of the climate change impacts on societies are summarized. The complexity of social and climatic systems leads to the spatial heterogeneity of climate impacts and risks in China. To more effectively leverage increasing knowledge about the past, we advocate greater cross-disciplinary collaboration between climate adaption, poverty alleviation and Nature-based Solutions (Nbs). That could provide decision makers with more comprehensive train of thoughts for climate policy making.
BACKGROUND: South Asia is highly vulnerable to climate change and is projected to experience some of the highest increases in average annual temperatures throughout the century. Although the adverse impacts of ambient temperature on human health have been extensively documented in the literature, only a limited number of studies have focused on populations in this region. OBJECTIVES: Our aim was to systematically review the current state and quality of available evidence on the direct relationship between ambient temperature and heat waves and all-cause mortality in South Asia. METHODS: The databases Pubmed, Web of Science, Scopus and Embase were searched from 1990 to 2020 for relevant observational quantitative studies. We applied the Navigation Guide methodology to assess the strength of the evidence and performed a meta-analysis based on a novel approach that allows for combining nonlinear exposure-response associations without access to data from individual studies. RESULTS: From the 6,759 screened papers, 27 were included in the qualitative synthesis and five in a meta-analysis. Studies reported an association of all-cause mortality with heat wave episodes and both high and low daily temperatures. The meta-analysis showed a U-shaped pattern, with increasing mortality for both high and low temperatures, but a statistically significant association was found only at higher temperatures – above 31° C for lag 0-1 days and above 34° C for lag 0-13 days. Effects were found to vary with cause of death, age, sex, location (urban vs. rural), level of education and socio-economic status, but the profile of vulnerabilities was somewhat inconsistent and based on a limited number of studies. Overall, the strength of the evidence for ambient temperature as a risk factor for all-cause mortality was judged as limited and for heat wave episodes as inadequate. CONCLUSIONS: The evidence base on temperature impacts on mortality in South Asia is limited due to the small number of studies, their skewed geographical distribution and methodological weaknesses. Understanding the main determinants of the temperature-mortality association as well as how these may evolve in the future in a dynamic region such as South Asia will be an important area for future research. Studies on viable adaptation options to high temperatures for a region that is a hotspot for climate vulnerability, urbanisation and population growth are also needed.
The association between floods and the risk of dysentery remain controversial. Therefore, we performed a meta-analysis to clarify this relationship. A literature search was performed in PubMed, Web of science, and Embase for relevant articles published up to November 2019. Random-effects model was used to pool relative risks with 95% confidence intervals. The sensitivity analysis was carried out to evaluate the stability of the results. Publication bias was estimated using Egger’s test. Eleven studies from 10 articles evaluated the association between floods and the risk of dysentery in China. The pooled RR (95% CI) of dysentery for the flooded time versus non-flooded period was 1.48 (95% CI: 1.14-1.91). Significant association was found in subgroup analysis stratified by dysentery styles [dysentery: 1.61 (95% CI: 1.34-1.93) and bacillary dysentery: 1.46 (95% CI: 1.06-2.01)]. The pooled RR (95%CI) of sensitivity analysis for dysentery was 1.26 (95% CI: 1.05-1.52). No significant publication bias was found in our meta-analysis. This meta-analysis confirms that floods have significantly increased the risk of dysentery in China. Our findings will provide more evidence to reduce negative health outcomes of floods in China.
CHAPTER 1: HOW AUSTRALIA IMPROVED HEALTH EQUITY THROUGH ACTION ON THE SOCIAL DETERMINANTS OF HEALTH: Do not think that the social determinants of health equity are old hat. In reality, Australia is very far away from addressing the societal level drivers of health inequity. There is little progressive policy that touches on the conditions of daily life that matter for health, and action to redress inequities in power, money and resources is almost non-existent. In this chapter we ask you to pause this reality and come on a fantastic journey where we envisage how COVID-19 was a great disruptor and accelerator of positive progressive action. We offer glimmers of what life could be like if there was committed and real policy action on the social determinants of health equity. It is vital that the health sector assists in convening the multisectoral stakeholders necessary to turn this fantasy into reality. CHAPTER 2: ABORIGINAL AND TORRES STRAIT ISLANDER CONNECTION TO CULTURE: BUILDING STRONGER INDIVIDUAL AND COLLECTIVE WELLBEING: Aboriginal and Torres Strait Islander peoples have long maintained that culture (ie, practising, maintaining and reclaiming it) is vital to good health and wellbeing. However, this knowledge and understanding has been dismissed or described as anecdotal or intangible by Western research methods and science. As a result, Aboriginal and Torres Strait Islander culture is a poorly acknowledged determinant of health and wellbeing, despite its significant role in shaping individuals, communities and societies. By extension, the cultural determinants of health have been poorly defined until recently. However, an increasing amount of scientific evidence supports what Aboriginal and Torres Strait Islander people have always said – that strong culture plays a significant and positive role in improved health and wellbeing. Owing to known gaps in knowledge, we aim to define the cultural determinants of health and describe their relationship with the social determinants of health, to provide a full understanding of Aboriginal and Torres Strait Islander wellbeing. We provide examples of evidence on cultural determinants of health and links to improved Aboriginal and Torres Strait Islander health and wellbeing. We also discuss future research directions that will enable a deeper understanding of the cultural determinants of health for Aboriginal and Torres Strait Islander people. CHAPTER 3: PHYSICAL DETERMINANTS OF HEALTH: HEALTHY, LIVEABLE AND SUSTAINABLE COMMUNITIES: Good city planning is essential for protecting and improving human and planetary health. Until recently, however, collaboration between city planners and the public health sector has languished. We review the evidence on the health benefits of good city planning and propose an agenda for public health advocacy relating to health-promoting city planning for all by 2030. Over the next 10 years, there is an urgent need for public health leaders to collaborate with city planners – to advocate for evidence-informed policy, and to evaluate the health effects of city planning efforts. Importantly, we need integrated planning across and between all levels of government and sectors, to create healthy, liveable and sustainable cities for all. CHAPTER 4: HEALTH PROMOTION IN THE ANTHROPOCENE: THE ECOLOGICAL DETERMINANTS OF HEALTH: Human health is inextricably linked to the health of the natural environment. In this chapter, we focus on ecological determinants of health, including the urgent and critical threats to the natural environment, and opportunities for health promotion arising from the human health co-benefits of actions to protect the health of the planet. We characterise ecological determinants in the Anthropocene and provide a sobering snapshot of planetary health science, particularly the momentous climate change health impacts in Australia. We highlight Australia’s position as a major fossil fuel producer and exporter, and a country lacking cohesive and
As a developing country, Vietnam is facing many problems such as environmental pollution caused by industrialization, urbanization and the ethnic minority gap. Besides, Vietnam is one of the 10 countries most vulnerable to the effects of climate change and natural disasters. Vietnam has more than 26.3 million children under 16 years of age, with the ratio being 114 boys/100 girls. Children are especially vulnerable to environmental risks. This review includes much data collected during 2010-2018 on children’s environmental health in Vietnam.
A large-ensemble climate simulation database, which is known as the database for policy decision-making for future climate changes (d4PDF), was designed for climate change risk assessments. Since the completion of the first set of climate simulations in 2015, the database has been growing continuously. It contains the results of ensemble simulations conducted over a total of thousands years respectively for past and future climates using high-resolution global (60 km horizontal mesh) and regional (20 km mesh) atmospheric models. Several sets of future climate simulations are available, in which global mean surface air temperatures are forced to be higher by 4 K, 2 K, and 1.5 K relative to preindustrial levels. Nonwarming past climate simulations are incorporated in d4PDF along with the past climate simulations. The total data volume is approximately 2 petabytes. The atmospheric models satisfactorily simulate the past climate in terms of climatology, natural variations, and extreme events such as heavy precipitation and tropical cyclones. In addition, data users can obtain statistically significant changes in mean states or weather and climate extremes of interest between the past and future climates via a simple arithmetic computation without any statistical assumptions. The database is helpful in understanding future changes in climate states and in attributing past climate events to global warming. Impact assessment studies for climate changes have concurrently been performed in various research areas such as natural hazard, hydrology, civil engineering, agriculture, health, and insurance. The database has now become essential for promoting climate and risk assessment studies and for devising climate adaptation policies. Moreover, it has helped in establishing an interdisciplinary research community on global warming across Japan.
The world has experienced perceptible climate change for the past 100 years. Global warming enhances the rapid spread of mosquito-borne diseases resulting in unknown consequences in the future. The global economic development, increased urbanization, and climate change have significantly increased the mosquito-borne disease transmission pattern and dynamics. In India, mosquito-borne diseases have been a core public issue for decades. Hence, mosquito control is primordial for preventing the transmission of malaria, lymphatic filariasis, dengue fever, Yellow fever, Zika virus infection, West Nile fever, and chikungunya virus infection in the human population. The mosquito control strategies based on ecology have received much more attention during the 1960s, as chemical pesticides induce negative impacts on human health and the ecosystem. Most of the current approaches in mosquito control have several limitations related to the development of insecticide resistance, lack of long-term sustainability, and negative impacts on the ecosystem and the environment. This review offers invaluable insights into severe mosquito-borne diseases, various vector control strategies, and the influence of climate change in mosquito-borne disease transmission.
While the East Asia Pacific (EAP) region has experienced tremendous economic growth and development, the resulting public health gains from reductions in its neglected tropical diseases (NTDs) have been less than expected due to opposing forces of urbanization, political instability, food insecurity, and climate change, together with co-morbidities with non-communicable diseases, including diabetes and hypertension. To be sure there’s been progress towards the elimination of lymphatic filariasis and trachoma through mass drug administration, and there are opportunities to extend MDA to yaws and scabies, but for most of the other NTDs we’ll require new biotechnologies. So far, EAP’s major technology hubs in China, Japan, Malaysia, Singapore, South Korea, and Taiwan have mostly failed to shift their attention towards new innovations for the NTDs, including new drugs, diagnostics, and vaccines, and vector control. Unless this situation changes the EAP could be facing a new grim reality of unhealthy megacities beset by emerging arbovirus infections, widespread antimicrobial resistance, and urban helminth infections.
Cities in Australia are experiencing unprecedented levels of urban overheating, which has caused a significant impact on the country’s socioeconomic environment. This article provides a comprehensive review on urban overheating, its impact on health, energy, economy, and the heat mitigation potential of a series of strategies in Australia. Existing studies show that the average urban heat island (UHI) intensity ranges from 1.0 degrees C to 13.0 degrees C. The magnitude of urban overheating phenomenon in Australia is determined by a combination of UHI effects and dualistic atmospheric circulation systems (cool sea breeze and hot desert winds). The strong relation between multiple characteristics contribute to dramatic fluctuations and high spatiotemporal variabilities in urban overheating. In addition, urban overheating contributes to serious impacts on human health, energy costs, thermal comfort, labour productivity, and social behaviour. Evidence suggest that cool materials, green roofs, vertical gardens, urban greenery, and water-based technologies can significantly alleviate the UHI effect, cool the ambient air, and create thermally balanced cities. Urban greenery, especially trees, has a high potential for mitigation. Trees and hedges can reduce the average maximum UHI by 1.0 degrees C. The average maximum mitigation performance values of green roofs and green walls are 0.2 degrees C and 0.1 degrees C, respectively. Reflective roofs and pavements can reduce the average maximum UHI by 0.3 degrees C. In dry areas, water has a high cooling potential. The average maximum cooling potential using only one technology is 0.4 degrees C. When two or more technologies are used at the same time, the average maximum UHI drop is 1.5 degrees C. The mitigation strategies identified in this article can help the governments and other stakeholders manage urban heating in the natural and built environment, and save health, energy, and economic costs.
The health risks of a changing climate are immediate and multifaceted. Policies, plans, and programs to reduce climate-related health impacts exist, but multiple barriers hinder the uptake of these strategies, and information remains limited on the factors affecting implementation. Implementation science-a discipline focused on systematically examining the gap between knowledge and action-can address questions related to implementation and help the health sector scale up successful adaptation measures in response to climate change. Implementation science, in the context of a changing climate, can guide decision makers in introducing and prioritizing potential health adaptation and disaster risk management solutions, advancing sustainability initiatives, and evaluating and improving intervention strategies. In this article we highlight examples from Pacific Island countries and outline approaches based on implementation science to enhance the capacity of health systems to anticipate, prepare for, respond to, and recover from climate-related exposures.
Population growth, socio-cultural and economic changes as well as technological progress have an immediate impact on the environment and human health in particular. Our steadily rising needs of resources increase the pressure on the environment and narrow down untainted habitats for plants and wild animals. Balance and resilience of ecosystems are further threatened by climate change, as temperature and seasonal shifts increase the pressure for all species to find successful survival strategies. Arctic and subarctic regions are especially vulnerable to climate change, as thawing of permafrost significantly transforms soil structures, vegetation and habitats. With rising temperature, the risk of zoonotic diseases in the Republic of Sakha (Yakutia) has also increased. As vegetation periods prolong and habitats broaden, zoonotic pathogens and their vectors find more favourable living conditions. Moreover, permafrost degradation may expose historic burial grounds and allow for reviving the vectors of deadly infections from the past. To assess the current state of knowledge and emerging risks in the light of the “One Health” concept, a German-Russian Symposium took place on 13 August 2018 in Yakutsk, Russian Federation. This symposium report presents the main findings generated from presentations and discussions.
Thailand is the home of 66.4 million people of which 17.21% are children aged 0-14 years. The total population of children has decreased from 20.23% in 2009 to 17.21% in 2018. The mortality ratio of infants and children under 5 years of age has also steadily decreased between 2008 and 2017. Urbanization, globalization, and industrialization appear to be the main contributors to the transition from infectious to chronic non-communicable diseases. The main types of environmental exposure to children are water, sanitation and hygiene, air pollution from traffic in inner cities, chemical hazards from pesticides which result from agricultural activities in countryside areas, heavy metal contaminants such as lead and arsenic from anthropogenic activities, e.g. from industrial zones, mining, electronic appliance waste, and ongoing climate change. It is concluded that economic development and rapid urbanization in Thailand have resulted in environmental degradation and pose a risk to children’s health. Future development and implementation of measures to improve children’s environmental health (CEH) in the country are needed. Some examples include research specific to environmental threats to children’s health; international environmental health networks to share experience and expertise; and solutions to solve the problems.
Many studies have been conducted to assess the health effects of climate change in Korea. However, there has been a lack of consideration regarding how the results of these studies can be applied to relevant policies. The current study aims to examine research trends at the agenda-setting stage and to review future ways in which health-related adaptation to climate change can be addressed within national public health policy. A systematic review of previous studies of the health effects of climate change in Korea was conducted. Many studies have evaluated the effect of ambient temperature on health. A large number of studies have examined the effects on deaths and cardio-cerebrovascular diseases, but a limitation of these studies is that it is difficult to apply their findings to climate change adaptation policy in the health sector. Many infectious disease studies were also identified, but these mainly focused on malaria. Regarding climate change-related factors other than ambient temperature, studies of the health effects of these factors (with the exception of air pollution) are limited. In Korea, it can be concluded that studies conducted as part of the agenda-setting stage are insufficient, both because studies on the health effects of climate change have not ventured beyond defining the problem and because health adaptation to climate change has not been set as an important agenda item. In the future, the sharing and development of relevant databases is necessary. In addition, the priority of agenda items should be determined as part of a government initiative.
Climate change and non-communicable diseases (NCDs) are two of the most important global health challenges of this century. Pacific island countries and territories (PICTs) are particularly vulnerable to the adverse impacts of climate change and face an increasingly high burden of NCDs. This review synthesizes the evidence for the links between climate change, food and nutrition security (FNS) and NCDs in the Pacific region and outlines the possible implications of these relationships. A comprehensive search was performed on global databases including PubMed, SCOPUS and ScienceDirect, the grey literature and reference lists. Four dominant pathways between climate change, FNS and NCDs emerged from the literature: the impact of climate change on agriculture, fisheries, migration and humanitarian food assistance. These pathways, if not addressed, are likely to lead to impaired FNS and an increased burden of NCDs in PICTs. There is little doubt that Pacific nations will experience adverse impacts of climate change exacerbating existing health risks and other socio-cultural, political and economic drivers of food and nutrition insecurity and NCDs. Further research is needed to strengthen the evidence and develop integrated, context-specific solutions. It is, however, imperative to take action to address these issues via a cross-sectoral, no-regrets, health-in-all-policies approach.
Over the last century, nutrition research and public health in New Zealand have been inspired by Dr Muriel Bell, the first and only state nutritionist. Some of her nutritional concerns remain pertinent today. However, the nutritional landscape is transforming with extraordinary changes in the production and consumption of food, increasing demand for sustainable and healthy food to meet the requirements of the growing global population and unprecedented increases in the prevalence of both malnutrition and noncommunicable diseases. New Zealand’s economy is heavily dependent on agrifoods, but there is a need to integrate interactions between nutrition and food-related disciplines to promote national food and nutrition security and to enhance health and well-being. The lack of integration between food product development and health is evident in the lack of investigation into possible pathological effects of food additives. A national coherent food strategy would ensure all components of the food system are optimised and that strategies to address the global syndemic of malnutrition and climate change are prioritised. A state nutritionist or independent national nutrition advocacy organisation would provide the channel to communicate nutrition science and compete with social media, lead education priorities and policy development, engage with the food industry, facilitate collaboration between the extraordinary range of disciplines associated with food production and optimal health and lead development of a national food strategy.
Oncomelania hupensis quadrasi is the snail intermediate host of Schistosoma japonicum in the Philippines. It was discovered by Dr. Marcos Tubangui in 1932 more than two decades after the discovery of the disease in the country in 1906. This review, the first for O. h. quadrasi, presents past and present works on the taxonomy, biology, ecology, control, possible paleogeographic origin of the snail intermediate host and future in research, control and surveillance of the snail. Extensive references are made of other subspecies of O. hupensis such as the subspecies in China for which majority of the advances has been accomplished. Contrasting views on whether the snail is to be considered an independent species of Oncomelania or as one of several subspecies of Oncomelania hupensis are presented. Snail control methods such as chemical methods using synthetic and botanical molluscicides, environmental manipulation and biological control are reviewed. Use of technologies such as Remote Sensing, Geographical Information System and landscape genetics is stressed for snail surveillance. Control and prevention efforts in the Philippines have consistently focused on mass drug administration which has proved inadequate in elimination of the disease. An integrated approach that includes snail control, environmental sanitation and health education has been proposed. Population movement such as migration for employment and economic opportunities and ecotourism and global climate change resulting in heavy rains and flooding challenge the gains of control and elimination efforts. Concern for possible migration of snails to non-endemic areas is expressed given the various changes both natural and mostly man-made favoring habitat expansion.
Changes to Australia’s climate and land-use patterns could result in expanded spatial and temporal distributions of endemic mosquito vectors including Aedes and Culex species that transmit medically important arboviruses. Climate and land-use changes greatly influence the suitability of habitats for mosquitoes and their behaviors such as mating, feeding and oviposition. Changes in these behaviors in turn determine future species-specific mosquito diversity, distribution and abundance. In this review, we discuss climate and land-use change factors that influence shifts in mosquito distribution ranges. We also discuss the predictive and epidemiological merits of incorporating these factors into a novel integrated statistical (SSDM) and mechanistic species distribution modelling (MSDM) framework. One potentially significant merit of integrated modelling is an improvement in the future surveillance and control of medically relevant endemic mosquito vectors such as Aedes vigilax and Culex annulirostris, implicated in the transmission of many arboviruses such as Ross River virus and Barmah Forest virus, and exotic mosquito vectors such as Aedes aegypti and Aedes albopictus. We conducted a focused literature search to explore the merits of integrating SSDMs and MSDMs with biotic and environmental variables to better predict the future range of endemic mosquito vectors. We show that an integrated framework utilising both SSDMs and MSDMs can improve future mosquito-vector species distribution projections in Australia. We recommend consideration of climate and environmental change projections in the process of developing land-use plans as this directly impacts mosquito-vector distribution and larvae abundance. We also urge laboratory, field-based researchers and modellers to combine these modelling approaches. Having many different variations of integrated (SDM) modelling frameworks could help to enhance the management of endemic mosquitoes in Australia. Enhanced mosquito management measures could in turn lead to lower arbovirus spread and disease notification rates.
India is urbanizing at an alarming rate and the impact of climate change is becoming more visible each passing day. The rapid urbanization and climate change have severe direct and indirect consequences, such as increasing poverty, inequality, massive displacement, public health concerns, and challenges of urban governance, among others. This paper identifies some of the most pressing issues faced by urban India in the context of climate change. It also details the interventions undertaken at the local, national, and international levels to counter the effect of the climate change. In addition, it critically evaluates the role of government organizations, especially in terms of undertaking regulatory and planning functions. The paper argues that the implementation of institutional reforms would enable the government to reach out to the private sector to improve urban service delivery. It also provides examples of best practices from India and the world in combating climate change through adaptation and mitigation approaches.
Mesquite (Prosopis juliflora (Sw.) DC), is an medium-sized tree (family Fabaceae, subfamily Mimosoideae), that has been intorcuded around the world. It is a noxious invasive species in Africa, Asia, and the Arabian Peninsula and a source of highly allergenic pollen in. The present article reviews the adverse allergenic effects of P. juliflora pollen on human and animal health. Several studies have diagnosed that allergenic pollens from Prosopis spp. can provoke respiratory problems. Prosopis pollen extracts have 16 allergenic components of which nine proteins were recognized as major allergens with some of them showing cross-reactivity. Clinically, understanding Prosopis pollen production, flowering seasonality, pollen load, and dispersal in the atmosphere are important to avoid allergic consequences for local inhabitants. Climate change and other pollution can also help to further facilitate allergenic issues. Furthermore, we document other human and animal health problems caused by invasive Prosopis trees. This includes flesh injuries, dental and gastric problems, and the facilitation of malaria. This review summarizes and enhances the existing knowledge about Prosopis flowering phenology, aeroallergen, and other human and animal health risks associated with this noxious plant.
This article explores the development of public health infrastructure in George Town, Penang, before the 1930s. It argues that the extreme weather of the tropical climate led to a unique set of health challenges for George Town’s administrators, as the town grew from a small British base to a multi-cultural and thriving port. Weather and public health were (and still are) integrally connected, although the framing of this relationship has undergone significant shifts in thinking and appearance over time. One lens into this association is the situation and expression of these elements within municipal structures. During the nineteenth century, government departments were fewer and shared roles and responsibilities. The Medical Department, for example, observed the weather. making connections between rain. drought and the incidence of disease. Engineers asked critical questions about mortality rates from disease after floods. As ideas about climate and health developed and changed, the shift became evident in the style, concerns and proliferation of governmental departments. This article thus considers the different ways in which weather, public health, and town planning were understood, managed and enacted by the Straits Settlements’ administration until the 1930s. It will start by exploring the situation facing the settlement’s inhabitants, in terms of specific climate and health challenges. It will then consider how these challenges were understood and addressed, why and by whom, and how these elements were repositioned over the period in question.
The purpose of this article was to explore the impacts of climate change on human health in Australia in general, and the state of Queensland in particular. We evaluated healthrelated services and adaptation challenges in the health sector and indicate possible remedies. The scientific consensus on the evidence for anthropogenic climate change is convincing. Climate change will have potentially devastating human health effects including increased morbidity, mortality and injury in the near future. Its impacts will be unevenly distributed among geographical regions and population groups. The elderly, children and people who are chronically ill and economically disadvantaged will be more vulnerable than others. Adaptation is a valuable tool for minimizing the effects of climate change on human health, but the mechanisms involve various societal, cultural, economic, political, environmental, information and technological challenges that need to be addressed rigorously and cautiously. Developing and designing appropriate healthcare systems to meet the challenges involved with adaptation is equally important in reducing the health effects of climate variability. There is an increased need for information about climatic impacts on human health and a need to increase institutional capacity, social and human capital, leadership, communication and partnerships as well as promoting stakeholders’ engagement in the adaptation processes in order to ensure success.
The Mediterranean Basin is undergoing a warming trend with longer and warmer summers, an increase in the frequency and the severity of heat waves, changes in precipitation patterns and a reduction in rainfall amounts. In this unique populated region, which is characterized by significant gaps in the socio-economic levels particularly between the North (Europe) and South (Africa), parallel with population growth and migration, increased water demand and forest fires risk – the vulnerability of the Mediterranean population to human health risks increases significantly. Indeed, climatic changes impact the health of the Mediterranean population directly through extreme heat, drought or storms, or indirectly by changes in water availability, food provision and quality, air pollution and other stressors. The main health effects are related to extreme weather events (including extreme temperatures and floods), changes in the distribution of climate-sensitive diseases and changes in environmental and social conditions. The poorer countries, particularly in North Africa and the Levant, are at highest risk. Climate change affects the vulnerable sectors of the region, including an increasingly older population, with a larger percentage of those with chronic diseases, as well as poor people, which are therefore more susceptible to the effects of extreme temperatures. For those populations, a better surveillance and control systems are especially needed. In view of the climatic projections and the vulnerability of Mediterranean countries, climate change mitigation and adaptation become ever more imperative. It is important that prevention Health Action Plans will be implemented, particularly in those countries that currently have no prevention plans. Most adaptation measures are “win-win situation” from a health perspective, including reducing air pollution or providing shading solutions. Additionally, Mediterranean countries need to enhance cross-border collaboration, as adaptation to many of the health risks requires collaboration across borders and also across the different parts of the basin.
The primary needs for climate services in China, in the form of climate information for decision-making, are to better prepare for and manage meteorological-related disasters, adaptation to climate change, and sustainable development. In this paper, the vision, structure, content, and governance of the China Framework for Climate Services, which is designed to respond to these primary needs, is described. This paper reflects on practice, lessons, and experience developing and delivering climate services in China for disaster risk reduction, agriculture, water, energy, urbanization, and major engineering projects. Four key aspects of successful climate services are highlighted: the transition of climate research to operational climate services; delivering relevant, tailored, and usable climate information; effective engagement between users and providers of climate services; and building interdisciplinary professional teams. Key challenges and opportunities for climate services are recognized in this paper: a growing gap between climate science and services capability and societal need, a lack of awareness in user communities of the climate service value for their activities, and the important need for closer and more meaningful interactions between users and providers of climate services. The delivery and uptake of high-quality, relevant, usable, and effective climate services will facilitate climate-smart decisions that will reduce climate risks and improve Chinese societal resilience.
Children’s bodies are in dynamic stages of development that make them more susceptible to harm from exposure to environmental agents. Children’s physical, physiological and behavioral traits can lead to increased exposure to toxic chemicals or pathogens. In addition, the social determinants of health interact with this exposure and create an increasing risk for further disparities among children. In Indonesia, the fourth most populated country in the world, children are under threat of exposure to contaminated water, air, food and soil, which can cause gastrointestinal and respiratory diseases, birth defects and neurodevelopmental disorders. A safe and balanced nutrition is still an unmet need for too many children. At the same time, the prevalence of obesity and the risk of later development of metabolic diseases, including diabetes and cardiovascular diseases, are increasing as a consequence of both unhealthy diets and inadequate physical activity. The risks of potential long-term toxicity, including carcinogenic, neurotoxic, immunotoxic, genotoxic, endocrine-disrupting and allergenic effects of many chemicals, are also close to their lives. This paper provides an overview of common disease risks in Indonesian children, including: acute hepatitis A, diarrheal diseases, dengue and malaria due to lack of water supply and sanitation, vectors, and parasites; asthma, bronchopneumonia, chronic obstructive pulmonary disease (COPD) and acute respiratory infections (ARIs) due to air pollution and climate change; some chronic diseases caused by toxic and hazardous waste; and direct or indirect consequences due to the occurrence of disasters and health emergencies.
Throughout history, humans have experienced epidemics. The balance of living in nature encircled by microorganisms is delicate. More than 70% of today’s emerging infections are zoonotic, i.e., those in which microorganisms transmitted from animals infect humans. Species are on the move at speeds never previously recorded, among ongoing climate change which is especially rapid at high latitudes. This calls for intensified international surveillance of Northern infectious diseases. Russia holds the largest area of thawing permafrost among Northern nations, a process which threatens to rapidly disrupt the balance of nature. In this paper, we provide details regarding Russian health infrastructure in order to take the first steps toward a collaborative international survey of Northern infections and international harmonization of the procured data.
BACKGROUND: Viral hemorrhagic fevers (VHF) refers to a group of febrile illnesses caused by different viruses that result in high mortality in animals and humans. Many risk factors like increased human-animal interactions, climate change, increased mobility of people and limited diagnostic facility have contributed to the rapid spread of VHF. MATERIALS: The history of VHFs in the Saudi Arabian Peninsula has been documented since the 19(th) century, in which many outbreaks have been reported from the southwestern region of Saudi Arabia. Despite presence of regional network of experts and technical organizations, which expedite support and respond during outbreaks, there are some more challenges that need to be addressed immediately. Gaps in funding, exhaustive and inclusive response plans and improved surveillance systems are some areas of concern in the region which can be dealt productively. This review primarily focusses on the hemorrhagic fevers that are caused by three most common viruses namely, the Alkhurma hemorrhagic fever virus, Rift valley fever virus, and Dengue fever virus. CONCLUSION: In summary, effective vector control, health education, possible use of vaccine and concerted synchronized efforts between different government organizations and private research institutions will help in planning effective outbreak-prevention and response strategies in future.
In this literature review, we analyze existing research on climate change and its impact on mental health and well-being, primarily among Pacific Islanders. To compensate for a lack of research in this area, we also address some of the projected mental health implications resulting from disasters linked to climate change, such as flooding, hurricanes, and cyclones. This broader scope enables the identification of areas where more research into mental health concerns related to climate change in the Pacific is needed. In closing, we provide recommendations for further research into the mental health and well-being of Pacific peoples and suggest ways to develop resilience to the effects of climate change.
Objectives: Mental and social health is among the notable domains affected by natural disasters, with nearly one-quarter of the people living in an area affected by natural disasters expressing the symptoms of depression, anxiety, post-traumatic stress disorder, bipolar disorder, or schizophrenia. Bringing harmony among these affected individuals is an important clinical priority. The effect of yoga, which is reported to reduce mental disorders to a great extent in many conditions, has not been studied in the setting of natural disaster recovery. Methods: Thirty-two participants [Mean age 37.8(SD +/- 8.9)] from a flood-affected state of India exhibiting mental and social impacts from the natural disaster were enrolled for 15 days of yoga interventions after obtaining written consent. Breathing exercises and guided relaxation techniques were provided as intervention after obtaining a self-rated visual analog scale (VAS) for fear, sadness, anxiety, and lack of sleep. Results: All participants completed the study. Statistically significant changes were observed (P < 0.05) in all the VAS dependent scale variables such as fear, sadness, anxiety, and lack of sleep. No adverse events were reported. Conclusion: Fifteen days of yoga interventions in victims of the flood-affected region might offer resilience to the people affected by natural disasters. Results of this study are encouraging and yoga can be introduced for addressing mental health issues in such emergencies and can be a valuable tool. However, more studies with robust designs and focused tools to determine the effects are warranted. (C) 2021 Elsevier Ltd. All rights reserved.
BACKGROUND: Both the World Health Organization and the Intergovernmental Panel on Climate Change project that malnutrition will be the greatest contributor to climate change-associated morbidity and mortality. Although there have been several studies that have examined the potential effects of climate change on human health broadly, the effects on malnutrition are still not well understood. We conducted a systematic review investigating the role of three climate change proxies (droughts, floods, and climate variability) on malnutrition in children and adults. METHODS AND FINDINGS: We identified 22 studies examining the effects of droughts, floods, and climate variability on at least one malnutrition metric. We found that 17 out of 22 studies reported a significant relationship between climate change proxies and at least one malnutrition metric. In meta-analysis, drought conditions were significantly associated with both wasting (Odds Ratio [OR] 1.46, 95% Confidence Interval [CI] 1.05-2.04) and underweight prevalence (OR 1.46, 95% CI 1.01-2.11). CONCLUSIONS: Given the long-term consequences of malnutrition on individuals and society, adoption of climate change adaptation strategies such as sustainable agriculture and water irrigation practices, as well as improving nutritional interventions aimed at children aged 1-2 years and older adults, should be prioritised on global policy agendas in the coming years.
Climate change and its impact on population health have been well explored in China in recent years, especially health risk assessments such as studying its impact on the transmission and development of climate-sensitive infectious diseases and non-communicable diseases. However, knowledge gaps including using morbidity as health indicators (e.g. hospitalisations, ED visits, and ambulance call-outs), identifying disease attributable contributions to climate variability and burden of diseases due to climate change, calculating related healthcare costs, and developing climate change adaptation and mitigation strategies need to be addressed. Future research directions could focus on both mitigation and health adaptation studies, such as exploring active transportation and green hospitals, studying health co-benefits, identifying vulnerable populations, prioritizing resource allocation, building healthcare capacity and capability, evaluating intervention effect, developing tailored risk communication strategies and community health education packages for vulnerable communities in the context of climate change.
A city’s climate is affected both by global warming and the local factors such as built form and the landscape. The temperature related impacts of climate change make urban areas more vulnerable particularly due to higher population concentration as well as heat island effect. Cities in India are already experiencing enhanced temperature and precipitation related impacts of climate change and extreme events, e.g., >2 degrees C warming in some places. This study describes a case of Ahmedabad a city of around 5 million people (Census, 2011) and currently almost 7.8 million, located in the hot and humid western part of India to understand the current temperature-related mortality impacts and the role of land use. Satellite images (MODIS from NASA), temperature data from India Meteorological Department (IMD) and daily all-cause mortality from Ahmedabad Municipal Corporation between 2001 and 2015 have been used to create a distributed lag non-linear model. Using land surface temperature for mortality risk assessment gives significantly different results as compared to using air temperature for mortality risk assessment. This indicates impacts of localized temperature variations on mortality risks. Thus, the microclimate in a city as represented by land surface temperatures is a better indicator for estimating relative risk of temperature related mortality as compared to air temperature. The study also infers that with increase in built-up spaces by 1% in the land use mix, the relative risk of heat related mortality increases by 0.59 points at 40 degrees C and by 0.78 points at 45 degrees C.
Climate change and urbanization are converging to challenge the flood control in the Pearl River Delta (PRD) due to their adverse impacts on precipitation extremes and the urban areas environment. Previous studies have investigated temporal changes in flood risk with various single factor, few have considered the joint effects of climate change, urbanization and socio-economic development. Here, based on the representative concentration pathway (RCP) scenarios, we conducted a comprehensive assessment of future (2030-2050) flood risk over the PRD combined with a thorough investigation of climate change, urbanization and socio-economic development. Precipitation extremes were projected using the regional climate model RegCM4.6, and urbanization growth was projected based on the CA-Markov model. The economic and population development was estimated by the shared socio-economic pathways (SSPs). Flood risk mapping with different RCPs-urbanization-SSPs scenarios was developed for the PRD based on the set pair analyze theory. The results show that climate change and urbanization are expected to exacerbate flood risk in most parts of the PRD during the next few decades, concurrently with more intense extreme precipitation events. The high flood risk areas are projected mainly in the urban regions with unfavorable terrain and dense population. The highest flood risk areas are expected to increase by 8.72% and 19.80% under RCP4.5 and RCP8.5 scenarios, respectively. Reducing greenhouse gas emissions may effectively mitigate the flood risk over the PRD. This study highlight the links between flood risk and changing environment, suggesting that flood risk management and preventative actions should be included in regional adaptation strategies.
Objective To explore the views of those in later life on the usability of a smartphone application (app) which could assist in negotiating the external environment, particularly during extreme weather and local environmental changes. Methods Seven adults aged over 55 years (four women, three men) living in Sydney, Australia, participated in focus groups. Responses were analysed thematically. Results The findings demonstrate older adults would use a reliable and relevant app to assist in accessing their external environment if it could provide assistance with accurate, up-to-date transport options, road closures, community events and weather. Conclusion If relevant, in real time and locally focussed adults aged over 55 could find value in a mobile app to assist them to navigate their external environment. These results suggest an age-friendly, specifically designed app will have an impact on accessibility to the local environment with the potential to lead to increased walking and social engagement.
BACKGROUND: Ross River virus (RRV) disease is Australia’s most widespread vector-borne disease causing significant public health concern. The aim of this study was to identify the ecological covariates of RRV risk and to develop epidemic forecasting models in a disease hotspot region of South Australia. METHODS: Seasonal autoregressive integrated moving average models were used to predict the incidence of RRV disease in the Riverland region of South Australia, an area known to have a high incidence of the disease. The model was developed using data from January 2000 to December 2012 then validated using disease notification data on reported cases for the following year. RESULTS: Monthly numbers of the mosquito Culex annulirostris (?=0.033, p<0.001) and total rainfall (?=0.263, p=0.002) were significant predictors of RRV transmission in the study region. The forecasted RRV incidence in the predictive model was generally consistent with the actual number of cases in the study area. CONCLUSIONS: A predictive model has been shown to be useful in forecasting the occurrence of RRV disease, with increased vector populations and rainfall being important factors associated with transmission. This approach may be useful in a public health context by providing early warning of vector-borne diseases in other settings.
The present study describes the development of a web-based flood risk information system ‘WebFRIS’ for Jagatsinghpur district, a severely flood-prone region in Eastern India. The WebFRIS is designed by using various readily available open-source web tools and packages such as Google Map, PHP, MySQL, and JSON. Special emphasis is directed towards designing the layout and architecture, to be easily accessible by any end-user irrespective of any technical know-how. The WebFRIS illustrates spatial maps of flood hazard, socio-economic vulnerability, and flood risk at the village level for two-time scenarios. While analyzing a set of graphical statistics depicting the changes in flood risk components, a significant increase in high and very-high categories of both flood hazard (~140%) and socio-economically vulnerable villages (~68%) is noticed during Scenario-I. The number of villages facing compound risk (contributed equally by flood hazard and socio-economic vulnerability) nearly doubled in Scenario-I. A spatial analysis of diametric changes in flood risk shows that a large proportion of villages in Balikuda, Ersama, and Tirtol tehsils have undergone radical changes. Following these observations, a set of possible engineering, social, and policy measures are proposed, whose implementation in the near future is expected to reinforce flood management in the study area. The WebFRIS architecture is flexible, easy-to-use; it is expected to provide crucial lessons to the local bodies, town-planners, water professionals, flood experts, and also the citizens, a precious knowledge on flood risk management. The WebFRIS may be considered as a precious cartographic product for environmental management. The proposed web platform is generic, as it can be applied to study other inter-related systems such as environmental protection, land-use planning, coastal habitat restoration, and community resilience building.
BACKGROUNDS: Studies on the association between ambient temperature and human mortality have been widely reported, focusing on common diseases such as cardiopulmonary diseases. However, multi-city studies on the association between both high and low temperatures and mortality of nervous system diseases were scarce, especially on the evidence of vulnerable populations. METHODS: Weekly meteorological data, air pollution data and mortality data of nervous system were collected in 5 cities in China. A quasi-Poisson regression with distributed lag non-linear model (DLNM) was applied to quantify the association between extreme temperatures and mortality of nervous system diseases. Multivariate meta-analysis was applied to estimate the pooled effects at the overall levels. The attributable fractions (AFs) were calculated to assess the mortality burden attributable to both high and low temperatures. Stratified analyses were also performed by gender and age-groups through the above steps. RESULTS: A total of 12,132 deaths of nervous system diseases were collected in our study. The overall minimum mortality temperature was 23.9 °C (61.9th), the cumulative relative risks of extreme heat and cold for nervous system diseases were 1.33(95%CI: 1.10, 1.61) and 1.47(95%CI: 1.27, 1.71). The mortality burden attributed to non-optimal temperatures accounted for 29.54% (95%eCI: 13.45%, 40.52%), of which the mortality burden caused by low temperature and high temperature accounted for 25.89% (95%eCI: 13.03%, 34.36%) and 3.65% (95%eCI: 0.42%, 6.17%), respectively. The mortality burden attributable to ambient temperature was higher in both males and the elderly (>74 years old), with the AF of 31.85% (95%eCI: 20.68%, 39.88%) and 31.14% (95%eCI: -6.83%, 49.51%), respectively. CONCLUSIONS: The non-optimal temperature can increase the mortality of nervous system diseases and the males and the elderly over 74 years have the highest attributable burden. The findings add the evidence of vulnerable populations of nervous system diseases against ambient temperatures.
(1) Background: The health effect of temperature has become a rising public health topic. The objective of this study is to assess the association between apparent temperature and non-accidental deaths, and the mortality burden attributed to cold and heat temperature; (2) Methods: The daily data on temperature and deaths were collected from 10 cities in Thailand, Korea and China. We fitted a time-series regression with a distributed lag nonlinear model (DLNM) to derive the health risk of temperature for each city and then pooled them to get the overall cumulative risk by multivariate meta-analysis. Additionally, we calculated the attributable fraction of deaths for heat and cold, which was defined as temperatures above and below minimum-mortality temperature (MMT); (3) Results: There are regional heterogeneities in the minimum mortality percentiles (MMP) and attributable fractions for different countries. The MMP varied from about the 5-10th percentile in Thailand to 63-93rd percentile in China and Korea. The attributable fractions of the total deaths due to short-term exposure to temperature in Asia is 7.62%, of which the cold effect (6.44%) is much higher than the heat effect (1.18%); (4) Conclusions: Our study suggested that apparent temperature was associated with an increase in non-accidental mortality. Most of the temperature-related mortality burden was attributable to cold, except for Thailand.
The association between meteorological factors and infectious diarrhea has been widely studied in many countries. However, investigation among children under 5 years old in Jiangsu, China remains quite limited. Data including infectious diarrhea cases among children under five years old and daily meteorological indexes in Jiangsu, China from 2015 to 2019 were collected. The lag-effects up to 21 days of daily maximum temperature (Tmax) on infectious diarrhea were explored using a quasi-Poisson regression with a distributed lag non-linear model (DLNM) approach. The cases number of infectious diarrhea was significantly associated with seasonal variation of meteorological factors, and the burden of disease mainly occurred among children aged 0-2 years old. Moreover, when the reference value was set at 16.7°C, Tmax had a significant lag-effect on cases of infectious diarrhea among children under 5 years old in Jiangsu Province, which was increased remarkably in cold weather with the highest risk at 8°C. The results of DLNM analysis implicated that the lag-effect of Tmax varied among the 13 cities in Jiangsu and had significant differences in 8 cities. The highest risk of Tmax was presented at 5 lag days in Huaian with a maximum RR of 1.18 (95% CI: 1.09, 1.29). Suzhou which had the highest number of diarrhea cases (15830 cases), had a maximum RR of 1.04 (95% CI:1.03, 1.05) on lag 15 days. Tmax is a considerable indicator to predict the epidemic of infectious diarrhea among 13 cities in Jiangsu, which reminds us that in cold seasons, more preventive strategies and measures should be done to prevent infectious diarrhea.
Small-scale flash flood events are climate-related disasters which can put multiple aspects of the system at risk. The consequences of flash floods in densely populated cities are increasingly becoming problematic around the globe. However, they are largely ignored in disaster impact assessment studies, especially in assessing socioeconomic loss and damage, which can provide a significant insight for disaster risk reduction measures. Using a structured questionnaire survey, this study applied a statistical approach and developed a structural equation model (SEM) for assessing several socioeconomic dimensions including physical impacts, mobility disruption, lifeline facilities, health and income-related impacts. The study reveals that respondents have experienced a stronger impact on direct tangible elements such as household contents and buildings as well as direct intangible elements with ? coefficients 0.703, 0.576 and 0.635, respectively, at p?
OBJECTIVES: Despite the well-established benefits of exercise, pregnant women are discouraged from physical activity in hot/humid conditions to avoid hyperthermia (core temperature (T(core))???39.0 °C). Recent epidemiological evidence also demonstrates greater risk of negative birth outcomes following heat exposure during pregnancy, possibly due to thermoregulatory impairments. We aimed to determine (1) the risk of pregnant women exceeding a T(core) of 39.0 °C during moderate-intensity exercise in the heat; and (2) if any thermoregulatory impairments are evident in pregnant (P) versus non-pregnant (NP) women. METHODS: Thirty participants (15 pregnant in their second trimester or third trimester) completed two separate exercise-heat exposures in a climate chamber (32 °C, 45%RH). On separate occasions, each participant cycled on a semi-recumbent cycle ergometer for 45 min at a workload representative of a moderate-intensity (1) non-weight-bearing (NON-WB), or (2) weight-bearing (WB) activity. Thermoregulatory responses were monitored throughout. RESULTS: The highest rectal temperature observed in a pregnant individual was 37.93 °C. Mean end-exercise rectal temperature did not differ between groups (P:37.53?±?0.22 °C, NP:37.52?±?0.34 °C, P?=?0.954) in the WB trial, but was lower in the P group (P:37.48?±?0.25 °C, vs NP:37.73?±?0.38 °C, P?=?0.041) in the NON-WB trial. Whole-body sweat loss was unaltered by pregnancy during WB (P:266?±?62 g, NP:264?±?77 g; P?=?0.953) and NON-WB P:265?±?51 g, NP:300?±?75 g; P?=?0.145) exercise. Pregnant participants reported higher ratings of thermal sensation (felt hotter) than their non-pregnant counterparts in the WB trial (P?=?0.002) but not in the NON-WB trial, (P?=?0.079). CONCLUSION: Pregnant women can perform 45 min of moderate-intensity exercise at 32 °C, 45%RH with very low apparent risk of excessive maternal hyperthermia. No thermoregulatory impairments with pregnancy were observed.
Risk to health from extreme heat is gaining attention in scholarship and policy. Demographic and socio-economic factors affect the extent to which a person is at risk from extreme heat, whilst empirical research of social vulnerability to heat outside a ‘Western’ context is relatively limited. Many countries still rely on expert judgements to draw locally specific context for heat vulnerability assessment. Yet, their view might not be evidence-informed and the result is influenced by who are involved. This paper reflects this point by eliciting expert views of social heat vulnerability in Taiwan through an expert questionnaire survey using the Analytic Hierarchy Process method, and the result was compared to existing empirical research. Our study finds that experts consider factors related to adaptive capacity, especially societal support, as the most important; but rate gender and ethnicity as the least important. Although experts point to the importance of adaptive capacity, there are relatively few empirical studies to date in societal support, and the low priority given to gender and ethnicity also contradicts prior empirical research. For heat risk assessment, our findings show that whilst systematic elicitation of expert judgement may help to fill gaps in empirical evidence specific to the local context, caution should be paid to the significant divergence with existing empirical data and expert opinions depending on who are selected to involve.
Understanding and improving the public risk perception have become an important element in the management of flood risk. In China, the risk government is of so-called nationwide catastrophe response mode which is different from the widely adopted “bottom up” risk governance mode in the Western countries. Such a particular mode may make Chinese people perceive risk in a different way from people in other countries. Hence, a further discussion of risk perception is of great value in China. ?This paper presents a case study on the public perception of flood hazard and flood risk in a city prone to floods. The relationship between risk perception and exposure was examined by spatial analysis. Meanwhile, inferential testing with chi-squared tests was undertaken regarding experience, social trust, and protective behaviors. Our results suggest that (1) the relationship between exposure and risk perception of people in Nanjing is positive and statistically significant, (2) flood experience was strongly related to risk perception, (3) trust showed a significant relationship to risk perception, and (4) people who have perceived the probability of floods and associated loss of life have a higher willingness to take more protective measures. These findings will help local government to develop effective flood risk communication strategies for improving public awareness creation, emergency response and preparedness.
Increasing urban heat island and global warming have aroused serious thermal environmental problems and even harm people’s thermal health. Because of the importance in people’s daily life, a commercial pedestrianized block represents a symbol of a city or metropolis; therefore, focusing the attention on the thermal environment in such regions is very necessary. Most of the researches on the urban thermal environment are calculated by remote sensing data; limited by the low spatial resolution of remote sensing image, it may not obviously reflect the true thermal environment of the research site, especially in some microscale regions. Based on this, the new software ENVI-met is developed to research the thermal environment and forecast people’s thermal sensation in a microscale region. Therefore, the objective of this study aims at conducting field measurement and numerical simulation to assess the thermal environment of a typical commercial pedestrianized space in southern China and assess the different urban design parameters in ameliorating the urban heat island effect. Our final results demonstrate a quantitative evidence for establishing a comprehensive standard for improving the thermal environment in a microscale region, and this study also can be a supplementary in the research field about improving thermal health.
OBJECTIVE: The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures. METHODS: Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7?days’ lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined. RESULTS: The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH(4), and NO. Six air pollutants, namely CH(4), NO, CO, NO(2), PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R(2)?=?0.422). CONCLUSION: The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases.
Epidemiological studies have suggested an association between particulate air pollution, increased temperatures, and morbidity related to pregnancy outcomes. However, the roles of desert dust storms and climatological factors have not been fully addressed. The objectives of the present study were to investigate the association between desert dust storms, particulate matter with a diameter ?10 ?m (PM(10)), daily temperatures, and toxemia of pregnancy and spontaneous abortion in Gaziantep, South East Turkey. The study was conducted retrospectively at emergency department of two hospitals in Gaziantep city. Data from January 1, 2009, to March 31, 2014, were collected. Patients, who were diagnosed with toxemia of pregnancy and spontaneous abortion by radiological imaging modalities, were included in the study. Daily temperature ranges, mean temperature values, humidity, pressure, wind speed, daily PM10 levels, and records of dust storms were collected. A generalized additive regression model was designed to assess variable effects on toxemia of pregnancy and spontaneous abortion, while adjusting for possible confounding factors. Our findings demonstrated that presence of dust storms was positively associated with the toxemia of pregnancy both in outpatient admissions (OR=1.543 95% CI=1.186-2.009) and inpatient hospitalizations (OR=1.534; 95% CI=1.162-2.027). However, neither PM(10) nor maximum temperature showed a marked association with spontaneous abortion or toxemia of pregnancy in our study population. Our findings suggest that desert dust storms may have an impact on the risk for adverse pregnancy outcomes such as toxemia of pregnancy. Health authorities should take necessary measures to protect pregnant women against detrimental effects of these storms.
This study evaluated the effect of extreme temperatures on events requiring emergency room visits (ERVs) for hypertensive disease, ischemic heart disease (IHD), cerebrovascular disease, and chronic kidney disease (CKD) for population stratified by sex and age living in Taiwan’s metropolitan city from 2000 to 2014. The distributed lag non-linear model was adopted to examine the association between ambient temperature and area-age-sex-disease-specific ERVs for a population aged 40 years and above. The reference temperature was defined by a percentile value to describe the temperature in each city. Area-age-sex-disease-specific relative risk (RR) and 95% confidence intervals (CI) were estimated in association with extreme high (99th percentile) and low (5th percentile) temperatures. Temperature-related ERV risks varied by area, age, sex, and disease. Patients with CKD tend to have comorbidities with hypertensive disease. All study populations with hypertensive disease have significant risk associations with extreme low temperatures with the highest RR of 2.64 (95% CI: 2.08, 3.36) appearing in New Taipei City. The risk of IHD was significantly associated with extreme high temperature for male subpopulation aged 40-64 years. A less significant association was observed between the risks of cerebrovascular disease with extreme temperature. The risk of CKD was most significantly associated with extreme high temperature especially for a subpopulation aged 40-64 years. All study subpopulations with hypertensive disease have significant risk associations with extreme low temperature. Male subpopulations were more vulnerable to extreme temperatures, especially for those aged 40-64 years.
This study evaluated the effect of extreme temperatures on events requiring emergency room visits (ERVs) for hypertensive disease, ischemic heart disease (IHD), cerebrovascular disease, and chronic kidney disease (CKD) for population stratified by sex and age living in Taiwan’s metropolitan city from 2000 to 2014. The distributed lag non-linear model was adopted to examine the association between ambient temperature and area-age-sex-disease-specific ERVs for a population aged 40 years and above. The reference temperature was defined by a percentile value to describe the temperature in each city. Area-age-sex-disease-specific relative risk (RR) and 95% confidence intervals (CI) were estimated in association with extreme high (99th percentile) and low (5th percentile) temperatures. Temperature-related ERV risks varied by area, age, sex, and disease. Patients with CKD tend to have comorbidities with hypertensive disease. All study populations with hypertensive disease have significant risk associations with extreme low temperatures with the highest RR of 2.64 (95% CI: 2.08, 3.36) appearing in New Taipei City. The risk of IHD was significantly associated with extreme high temperature for male subpopulation aged 40-64 years. A less significant association was observed between the risks of cerebrovascular disease with extreme temperature. The risk of CKD was most significantly associated with extreme high temperature especially for a subpopulation aged 40-64 years. All study subpopulations with hypertensive disease have significant risk associations with extreme low temperature. Male subpopulations were more vulnerable to extreme temperatures, especially for those aged 40-64 years.
The Paris Agreement has prompted much interest in the societal and health impacts of limiting global warming to 1.5 degrees C and 2 degrees C. Previous assessments of differential impacts of two targets indicate that 1.5 degrees C warming target would substantially reduce the impact on human health compared to 2 degrees C, but they mainly focused on the magnitude of temperature changes under future climate change scenarios without any consideration of greater frequency of cumulative heat exposures within a day. Here we quantified the health risks of compound daytime and night-time hot extremes using morbidity data in a megacity of China, and also identified the time-period of heat exposure with higher risks. Then we projected future morbidity burden attributable to compound hot extremes due to the half-degree warming. We estimated that the 2 degrees C warming scenario by 2100 as opposed to 1.5 degrees C would increase annual heat-related ambulance dispatches by 31% in Shenzhen city. Substantial additional impacts were associated with occurrence of consecutive hot days and nights, with ambulance dispatches increased by 82%. Our results suggested that compound hot extremes should be considered in assessment of heat-related health impacts, particularly in the context of climate change. Minimizing the warming of climate in a more ambitious target can significantly reduce the health damage.
Cold spells have been associated with mortality from a few broad categories of diseases or specific diseases. However, there is a lack of data about the health effects of cold spells on mortality from a wide spectrum of plausible diseases which can reveal a more comprehensive contour of the mortality burden of cold spells. We collected daily mortality data in Guangzhou during 2010-2018 from the Guangzhou Center for Disease Control and Prevention. The quasi-Poisson generalized linear regression model mixed with the distributed lag non-linear model (DLNM) was conducted to examine the health impacts of cold spells for 11 broad causes of death groupings and from 35 subcategories in Guangzhou. Then, we examined the effect modification by age group (0-64 and 65+ years) and sex. Effects of cold spells on mortality generally delayed for 3-5 d and persisted up to 27 d. Cold spells were significantly responsible for increased mortality risk for most categories of deaths, with cumulative relative risk (RR) over 0-27 lagged days of 1.57 [95% confidence interval (CI): 1.48-1.67], 1.95 (1.49-2.55), 1.58 (1.39-1.79), 1.54 (1.26-1.88), 1.92 (1.15-3.22), 1.75, (1.14-2.68), 2.02 (0.78-5.22), 1.92 (1.49-2.48), 1.48 (1.18-1.85), and 1.18 (1.06-1.30) for non-accidental causes, cardiovascular diseases, respiratory diseases, digestive diseases, nervous system diseases, genitourinary diseases, mental diseases, endocrine diseases, external cause and neoplasms, respectively. The magnitudes of the effects of cold spells on mortality varied remarkably among the 35 subcategories, with the largest cumulative RR of 2.87 (1.72-4.79) estimated for pulmonary heart diseases. The elderly and females were at a higher risk of mortality for most diseases after being exposed to cold spells. Increased mortality from a wide range of diseases was significantly linked with cold spells. Our findings may have important implications for formulating effective preventive strategies and early warning response plans that mitigate the health burden of cold spells.
The aim of the study was to examine the relationship between ambient temperature, ultraviolet radiation, and the development of herpes zoster in Taiwan. An ecological study was conducted to analyse the database of the Taiwan National Health Insurance Programme. Participants aged ?20 years with newly diagnosed herpes zoster between 2003 and 2012 were selected for analysis. The monthly incidence rate of herpes zoster was measured between 2003 and 2012. Monthly average ambient temperature in Celsius (°C) between 2003 and 2012 was measured according to the official database of the Central Weather Bureau in Taiwan. Monthly accumulated ultraviolet radiation (MJ m(-2) ) between 2003 and 2012 was measured according to the official database of the Environmental Protection Administration in Taiwan. The overall incidence rates of herpes zoster ranged from 2.54 to 5.67 per 10 000 persons per month from 2003 to 2012.The monthly average ambient temperature was higher and the monthly accumulated ultraviolet radiation was stronger from May to October. The incidence rates of herpes zoster seemed to be high during the period of high ambient temperature and strong ultraviolet radiation (from May to October).Whenever ambient temperature increased 1°C per month, the incidence rate of herpes zoster increased by 0.072 per 10,000 persons per month. Whenever ultraviolet radiation increased 1 MJ m(-2) per month, the incidence rate of herpes zoster increased by 0.313 per 10 000 persons per month. There is a significant association between ambient temperature, ultraviolet radiation, and the development of herpes zoster in Taiwan. The incidence rate of herpes zoster is high during the period of high ambient temperature and strong ultraviolet radiation. Low ambient temperature and weak ultraviolet radiation might be beneficial for the prevention of herpes zoster.
Some studies have demonstrated that precipitation is an important risk factor of dengue epidemics. However, current studies mostly focused on a single precipitation variable, and few studies focused on the impact of precipitation patterns on dengue epidemics. This study aims to explore optimal precipitation patterns for dengue epidemics. Weekly dengue case counts and meteorological data from 2006 to 2018 in Guangzhou of China were collected. A generalized additive model with Poisson distribution was used to investigate the association between precipitation patterns and dengue. Precipitation patterns were defined as the combinations of three weekly precipitation variables: accumulative precipitation (Pre_A), the number of days with light or moderate precipitation (Pre_LMD), and the coefficient of precipitation variation (Pre_CV). We explored to identify optimal precipitation patterns for dengue epidemics. With a lead time of 10 weeks, minimum temperature, relative humidity, Pre_A, and Pre_LMD were positively associated with dengue, while Pre_CV was negatively associated with dengue. A precipitation pattern with Pre_A of 20.67-55.50 mm per week, Pre_LMD of 3-4 days per week, and Pre_CV less than 1.41 per week might be an optimal precipitation pattern for dengue epidemics in Guangzhou. The finding may be used for climate-smart early warning and decision-making of dengue prevention and control.
BACKGROUND: Climate change is leading to an increased number of natural disasters. Children from low- and middle-income countries are disproportionately affected. The impacts of exposure to multiple natural disasters on the development of children are not well understood. The Philippines had 6.5 million people affected by natural disasters in 2018 and is therefore an ideal country in which to study the cumulative effects of natural disasters on human development. METHODS: We used wave 1 (2016-17) of the Longitudinal Cohort Study on the Filipino Child, a nationally representative cohort study of 4952 10-year-old children, to examine the impact of natural disasters. For caregivers, we examined mental health, family violence, and food insecurity. For children, we examined exposure to violence and stunting. We used random effects models to estimate the associations between natural disasters and children’s development outcomes and caregivers’ outcomes, after adjusting for neighbourhood, demographic, and geographic variables. Disaster exposure was measured using caregiver-reported measures of cumulative exposure and cumulative impact of disasters, average neighbourhood reports and data linked from the International Disaster Database (EM-DAT), an independent measure of community exposure to disaster. FINDINGS: We found that experiencing natural disasters, as measured by neighbourhood reports, was associated with higher levels of family violence in the previous 12 months, parenting stress, children witnessing physical violence, physical abuse of children, stunting in children, and greater food insecurity. Associations with individual self-reported exposure showed was similar. Associations with natural disasters measured using EM-DAT data showed a similar pattern: exposure to greater numbers of natural disasters was associated with higher levels of family violence, physical abuse of children, stunting in children, and food insecurity. Impacts of disasters was associated with higher levels of family violence, depression and food insecurity. INTERPRETATION: This is the first national study to document that cumulative measures of natural disasters had small, but wide-ranging, impacts on children and their caregivers. Further research is needed to identify factors that will protect populations who are at risk of high levels of natural disasters to ensure the optimal development of children. FUNDING: The Philippines Project, The Australian National University.
Aim. To examine the temporal variations of the association between ambient temperature and mortality for cardiovascular diseases in Queensland, Australia between 1997 and 2013. Methods. We obtained 147 238 cardiovascular deaths data from Queensland Health between 1 January 1997 and 31 December 2013. Time-stratified case-crossover design was fitted via the conditional quasi-Poisson regression with time-varying distributed lag non-linear model to estimate the associations between temperature and cardiovascular mortality. Stratified analyses were performed by age, sex, climate zone, and socioeconomic status. Results. We found a substantial decrease in the cold effect, while there was no significant change in the heat effect. Results of subgroup analyses showed an increasing trend for heat effects in men, people 84 years old, those living in low and middle socioeconomic areas and those living in hot climate areas. There was a decreasing trend for the magnitude of associations between temperature (both cold and hot temperatures) and cardiovascular mortality in people 85 years old and in areas of high socioeconomic status. Conclusions. The associations between cold temperature and cardiovascular mortality decreased in Queensland, Australia between 1997 and 2013, but no declines were observed for hot temperatures. Men, people 84 years old, people living in low and middle socioeconomic score areas and people living in hot climate areas demonstrated increased susceptibility to hot temperatures. Our findings suggest a need for heat awareness health promotion campaigns to enhance adaptation to a warming climate among vulnerable population.
Along with climate change, unstable weather patterns are becoming more frequent. However, the temporal trend associated with the effect of temperature variation on schizophrenia (SCZ) is not clear. Daily time-series data on SCZ and meteorological factors for 15-year between January 1, 2005 and December 31, 2019 were collected. And we used the Poisson regression model combined with the time-varying distribution lag nonlinear model (DLNM) to explore the temporal trend of the association between three temperature variation indicators (diurnal temperature range, DTR; temperature variability, TV; temperature change between neighboring days, TCN) and SCZ hospitalizations, respectively. Meanwhile, we also explore the temporal trend of the interaction between temperature and temperature variation. Stratified analyses were performed in different gender, age, and season. Across the whole population, we found a decreasing trend in the risk of SCZ hospitalizations associated with high DTR (from 1.721 to 1.029), TCN (from 1.642 to 1.066), and TV (TV0-1, from 1.034 to 0.994; TV0-2, from 1.041 to 0.994, TV0-3, from 1.044 to 0.992, TV0-4, from 1.049 to 0.992, TV0-5, from 1.055 to 0.993, TV0-6, from 1.059 to 0.991, TV0-7, from 1.059 to 0.990), but an increasing trend in low DTR (from 0.589 to 0.752). Subgroup analysis results further revealed different susceptible groups. Besides, the interactive effect suggests that temperature variation may cause greater harm under low-temperature conditions. There was a synergy between TCN and temperature on the addition and multiplication scales, which were 1.068 (1.007, 1.133) and 0.067 (0.009, 0.122), respectively. Our findings highlight public health interventions to mitigate temperature variation effects needed to focus not only on high temperature variations but also moderately low temperature variations. Future hospitalizations for SCZ associated with temperature variation may be more severely affected by temperature variability from low temperature environments. The temporal trend is associated with the effect of temperature variation on schizophrenia (SCZ).
Culex mosquitoes are important vectors of West Nile Virus (WNV), St. Louis Encephalitis Virus (SLEV) and Japanese Encephalitis Virus (JEV). Climate change is expected to alter their ability to spread diseases in human populations. Studies examining the influence of climate variability on Culex mosquitoes in South East Asia are scarce. We examined the influence of climate variability on reported Culex mosquito larval habitats from 2009 to 2018 in Singapore. We analysed the non-linear immediate and lagged weather dependence of Culex habitats over 5 weeks in negative binomial regression models using nationally representative data. We adjusted for the effects of long-term trend, seasonality, public holidays and autocorrelation. There were 41,170 reported Culex larval habitats over the study period. Non-residential premises were associated with more reports of habitats compared to residential premises [Rate Ratio (RR): 113.9, 95% CI: 110.9, 116.9]. Larvae in more than 90% of these habitats were entomologically identified as Culex quinquefasciatus. In residences, every 10 mm increase in rainfall above a 90 mm threshold was associated with a 10.1% [Incidence Rate Ratio (IRR): 0.899, 95% CI: 0.836, 0.968] cumulative decline in larval habitats. Public holidays were not significantly included in the model analysing larval habitats in residences. In non-residences, a 1 °C increase in the ambient air temperature with respect to the mean was associated with a 36.0% (IRR: 1.360, 95% CI: 1.057, 1.749) cumulative increase in Culex larval habitats. Public holidays were associated with a decline in Culex larval habitats in the same week. Our study provides evidence of how ambient air temperature and rainfall variability influences the abundance of Culex mosquito larval habitats. Our findings support the utility of using weather data in predictive models to inform the timing of vector control measures aimed at reducing the risk of WNV and other Culex-borne flavivirus transmission in urban areas.
The effects of daily mean temperature on health outcomes have been discussed in many previous studies, but few have considered the adverse impacts on upper respiratory tract infection (URTI) due to variance of temperature in one day. Diurnal temperature range (DTR) was a novel indicator calculated as maximum temperature minus minimum temperature on the same day. In this study, generalized additive model (GAM) with quasi-Poisson distribution was used to investigate the association between DTR and the number of daily outpatient visits for URTI among college students. Data about meteorological factors and air pollutants were provided by Hubei Meteorological Bureau and Wuhan Environmental Protection Bureau, respectively. Outpatient visits data were collected from the Hospital of Wuhan University from January 1, 2016, to December 31, 2018. Short-term exposure to DTR was associated with the increased risk of outpatient for URTI among all college students. Per 1 °C increased in DTR was associated with 0.73% (95%CI: 0.24, 1.21) increased in outpatient visits of all college students for URTI at lag 0 day. The greatest effect values were observed in males [1.35% (95%CI: 0.33,2.39)] at lag 0-6 days, and in females [0.86% (95%CI: 0.24, 1.49)] at lag 0-1 days. DTR had more adverse health impact in autumn and winter. Public health departments should consider the negative effect of DTR to formulate more effective prevention and control measures for protecting vulnerable people.
Drought is a devastating natural hazard that significantly affects human health and social and economic activities. This study aims to explore the short-term association between drought and outpatient visits for respiratory diseases (RDs) in four northwest cities, China. In this study, we obtained daily outpatient visits for RDs, meteorological factors, and air pollutant data in four cities (Lanzhou from 2014 to 2016, Wuwei from 2016 to 2018, Tianshui and Zhangye from 2015 to 2018) of northwest China. We used the daily Standardized Precipitation Index (SPI) as an indicator of drought and estimated the effects of drought on outpatient visits with RDs by using a generalized additive model (GAM) in each city, controlling for daily temperature, time trends, and other confounding factors. The city-specific estimates were pooled by random-effects meta-analysis. There were 1,134,577 RDs cases in the hospitals across the four cities. We found that a 1-unit decrease in daily exposure to SPI-1 was positively associated with daily outpatient visits for RDs, with estimated RR of 1.0230 (95% CIs: 1.0096, 1.0366). Compared to non-drought periods, the RR of daily outpatient visits for RDs for exposure to all drought conditions was 1.0431 (95% CIs: 1.0309, 1.0555). In subgroup analysis, the estimated effects of drought on outpatient visits for RDs appeared larger for males than females though not statistically different, and the estimated effects in children and adolescents were the greatest among different age groups. Drought likely increases the risk of respiratory diseases, particularly among children and adolescents. We highlight that public health adaptations to drought such as drought monitoring, mitigation measures, and adaptation strategies are necessary.
This study aims to examine the relationship between daily temperature and mortality in the Klang Valley, Malaysia, over the period 2006-2015. A quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM) was used to estimate the association between the mean temperature and mortality categories (natural n=69,542, cardiovascular n= 15,581, and respiratory disease n=10,119). Particulate matter with an aerodynamic diameter below 10 ?m (PM(10)) and surface ozone (O(3)) was adjusted as a potential confounding factor. The relative risk (RR) of natural mortality associated with extreme cold temperature (1st percentile of temperature, 25.2 °C) over lags 0-28 days was 1.26 (95% confidence interval (CI): 1.00, 1.60), compared with the minimum mortality temperature (28.2 °C). The relative risk associated with extremely hot temperature (99th percentile of temperature, 30.2 °C) over lags 0-3 days was 1.09 (95% CI: 1.02, 1.17). Heat effects were immediate whereas cold effects were delayed and lasted longer. People with respiratory diseases, the elderly, and women were the most vulnerable groups when it came to the effects of extremely high temperatures. Extreme temperatures did not dramatically change the temperature-mortality risk estimates made before and after adjustments for air pollutant (PM(10) and O(3)) levels.
INTRODUCTION: Extremely preterm births (EPT), require complex decision making and significant medical interventions. While environmental factors such as ambient temperature extremes have been associated with preterm births, little is known of the environmental associations with EPT births. The objective of this study is to explore whether ambient temperature is associated with increased risk of EPT birth. METHODS: Birth records for 315,226 infants born in Queensland Australia (2007-2015) were matched to average maximum and minimum temperature for the last month of pregnancy. Odds ratios and 95% confidence intervals were calculated using a generalised linear model. Population attributable risk was calculated for a 5% reduction in maximum temperature. RESULTS: Each one degree increase in maximum [aOR 1.03 (95% CI 1.01, 1.05)] and minimum temperature [aOR 1.02 (95% CI 1.01, 1.04)] was associated with an increase in odds for EPT birth. Increased odds for EPT births was found for maternal smoking [aOR 1.46 (95% CI 1.23, 1.72)], increasing plurality [OR 6.38 (95% CI 5.48, 7.42)] and stillbirth [aOR 342.99 (95% CI 295.53, 398.06)]. When stratified by birth status, the association was only found for live births. DISCUSSION: Higher temperatures are associated with small increases in the odds of delivering an infant in the EPT period. The risk may be enhanced for women who smoke during pregnancy. Women at an increased risk of preterm births should be counselled around methods to reduce their exposure to excessive heat.
Influenza is an acute respiratory disease that seriously threatens public health. The occurrence of influenza has been proved to be related to a variety of meteorological factors. However, less attention has been paid to the effect of relative humidity (RH) on different types of influenza, especially in subtropical regions. Daily data on laboratory-confirmed influenza cases, weather variables, and air pollutants in Hefei covering the 2014-2019 period were collected. The seasonality and trend of daily influenza cases were explored by the time series seasonal decomposition method. Generalized linear model was fitted in conjunction with distributed lag nonlinear model to quantify the associations of RH with influenza A and influenza B. Subgroup analyses were conducted by sex, age (0-4, 5-17, and ?18 years), and season (cold and warm seasons). A total of 5238 influenza cases including 2847 influenza A cases and 2391 influenza B cases were recorded. The epidemic of influenza presented a distinct seasonal pattern, and the number of daily influenza cases increased steadily since 2016. High RH was related to an increased risk of influenza A (maximum RR = 1.683, 95%CI: 1.365-2.076), especially among males, females, and school-age children. Low RH was associated with an increased risk of influenza B (maximum RR = 1.252, 95%CI: 1.169-1.340). The contrasting relationships of RH with influenza A and B remained significant in cold seasons. High RH and low RH were significantly associated with the increased risk of influenza A and B, respectively. The findings of our study may provide clues for proposing new effective interventions.
Previous studies found non-linear mutual interactions among hydrometeorological factors on diarrheal disease. However, the complex interactions of the hydrometeorological, topographical and human activity factors need to be further explored. This study aimed to reveal how hydrological and other factors jointly influence bacillary dysentery in different geographical regions. Using Anhui Province in China, consisted of Huaibei plain, Jianghuai hilly and Wannan mountainous regions, we integrated multi-source data (6 meteorological, 3 hydrological, 2 topographic, and 9 socioeconomic variables) to explore the direct and interactive relationship between hydrological factors (quick flow, baseflow and local recharge) and other factors by combining the ecosystem model InVEST with spatial statistical analysis. The results showed hydrological factors had significant impact powers (q = 0.444 (Huaibei plain) for local recharge, 0.412 (Jianghuai hilly region) and 0.891 (Wannan mountainous region) for quick flow, respectively) on bacillary dysentery in different regions, but lost powers at provincial level. Land use and soil properties have created significant interactions with hydrological factors across Anhui province. Particularly, percentage of farmland in Anhui province can influence quick flow across Jianghuai, Wannan regions and the whole province, and it also has significant interactions with the baseflow and local recharge across the plain as well as the whole province. Percentage of urban areas had interactions with baseflow and local recharge in Jianghuai and Wannan regions. Additionally, baseflow and local recharge could be interacted with meteorological factors (e.g. temperature and wind speed), while these interactions varied in different regions. In conclusion, it was evident that hydrological factors had significant impacts on bacillary dysentery, and also interacted significantly with meteorological and socioeconomic factors. This study applying ecosystem model and spatial analysis help reveal the complex and nonlinear transmission of bacillary dysentery in different geographical regions, supporting the development of precise public health interventions with consideration of hydrological factors.
PURPOSE: Diurnal temperature range (DTR) is a meteorological indicator closely associated with global climate change. Thus, we aim to explore the effects of DTR on the outpatient and emergency room (O&ER) admissions for cardiovascular diseases (CVDs), and related predictive research. METHODS: The O&ER admissions data for CVDs from three general hospitals in Jinchang of Gansu Province were collected from 2013 to 2016. A generalized additive model (GAM) with Poisson regression was employed to analyze the effect of DTR on the O&ER admissions for all cardiovascular diseases, hypertension, ischemic heart disease (IHD) and stoke. GAM was also used to preform predictive research of the effect of DTR on the O&ER admissions for CVDs. RESULTS: There were similar positive linear relationships between DTR and the O&ER visits with the four cardiovascular diseases. And the cumulative lag effects were higher than the single lag effects. A 1 °C increase in DTR corresponded to a 1.30% (0.99-1.62%) increase in O&ER admissions for all cardiovascular diseases. Males and elderly were more sensitivity to DTR. The estimates in non-heating season were higher than in heating season. The trial prediction accuracy rate of CVDs based on DTR was between 59.32 and 74.40%. CONCLUSIONS: DTR has significantly positive association with O&ER admissions for CVDs, which can be used as a prediction index of the admissions of O&ER with CVDs.
Seasonal changes in temperature, humidity, and rainfall affect vector survival and emergence of mosquitoes and thus impact the dynamics of vector-borne disease outbreaks. Recent studies of deterministic and stochastic epidemic models with periodic environments have shown that the average basic reproduction number is not sufficient to predict an outbreak. We extend these studies to time-nonhomogeneous stochastic dengue models with demographic variability wherein the adult vectors emerge from the larval stage vary periodically. The combined effects of variability and periodicity provide a better understanding of the risk of dengue outbreaks. A multitype branching process approximation of the stochastic dengue model near the disease-free periodic solution is used to calculate the probability of a disease outbreak. The approximation follows from the solution of a system of differential equations derived from the backward Kolmogorov differential equation. This approximation shows that the risk of a disease outbreak is also periodic and depends on the particular time and the number of the initial infected individuals. Numerical examples are explored to demonstrate that the estimates of the probability of an outbreak from that of branching process approximations agree well with that of the continuous-time Markov chain. In addition, we propose a simple stochastic model to account for the effects of environmental variability on the emergence of adult vectors from the larval stage.
Few evidences are available about the impact of temperature variation on childhood asthma in different seasons. This study aimed to assess the influence of temperature changes between neighboring days (TCN) on the exacerbation of asthma among children. Daily outpatient visits for childhood asthma (DOVCA) were collected from 17 main hospitals in Shanghai, China, from 2016 to 2018. A quasi-Poisson regression combined with distributed lagged nonlinear models was employed to estimate the association between TCN and asthma visits in cool or warm seasons, after controlling for short- and long-term trends, day of week, holidays, daily mean temperature, daily mean relative humidity, and air pollutants. The TCN varied from -?9.6 to 6.7 °C. The relationship between TCN and DOVCA greatly varied by season. In warm seasons, positive TCN (temperature rise) was associated with higher risks of asthma outpatient visits and negative TCN (temperature drop) was associated with lower risks; the associations were present on lag 1 day and lasted for 2 weeks; the cumulative relative risk of childhood asthma over 0 to 14 days was 1.98 (95% confidence interval: 1.42, 2.76) and 0.31 (95% confidence intervals: 0.21, 0.44) comparing a TCN of 2.5 °C (5th percentile) and -?3.2 °C (95th percentile) with 0 °C, respectively. In cool seasons, neither negative nor positive TCN showed significant risks. In conclusion, temperature rise might increase the risk of childhood asthma exacerbation and temperature drop might decrease the risks in warm seasons. There were no statistically significant influences in cool seasons.
In recent years, disasters have caused extensive water damage in various parts of Japan. Flooded evacuation routes and ineffective hazard maps commonly constrain evacuees’ behavior, which results in casualties. In this study, storm surge flooding analysis was carried out using OpenFOAM, which is a computational fluid dynamics software that monitors flooding state as a function of time, and evacuation simulations using a multi-agent system that considers evacuation behavior knowing the flooding state established by the flooding analysis. In some of the scenarios, many residents were caught in the flooding and could not be evacuated. Additional evacuation simulations revealed that evacuation behavior is more effective if residents have advance knowledge of the area expected to flood. Identifying these flood hazard areas and recognizing these areas in advance as impassable enables evacuees to avoid flood hazard areas; consequently, there is a decrease in the number of evacuees who get caught in the flooding. Anticipating the area expected to be flooded suggests the best evacuation locations and routes. Using these simulation results with useful hazard maps and disaster education, residents will correctly recognize the risk of a storm surge disaster and prepare for it, which will assist recovery. Finally, our analytical and simulation approach to disaster management is amenable to long-term planning for disaster-resistant cities.
Concurrent meteorological droughts and consecutive cold events can significantly impact local ecosystems, socio-economies, and human health. The respective characteristics of droughts and cold extremes have been extensively studied, however, their concurrent extremes have received very little attention. In this study, we used the Huai River Basin as a case to build a magnitude index of concurrent meteorological droughts and consecutive cold events (CDCMI) based on daily minimum temperature data and a 1-month standardized precipitation evapotranspiration index (SPEI) from 1961 to 2018. Results show that the magnitude of meteorological droughts increased over the observation period, while consecutive cold events significantly decreased. CDCMI showed a significant downward trend at a rate of -0.14 per decade. Large differences were observed between 1990-2018 and 1961-1989-especially in the southern parts of the basin (around -50%). The frequency of mild and moderate concurrent meteorological droughts and consecutive cold events showed no significant upward or downward trends, but severe and extreme concurrent events showed pronounced decreasing trends at rates of -0.03 events/decade and – 0.036 events/decade, respectively. Under the same return period, high CDCMI values are present in the southeastern part of the basin, indicating that the concurrent events in this region are more serious. When CDCMI = 1.79 (extreme grade), the return period in the southeastern part of the basin (5-10 years) is much lower than that in the northwestern part of the basin (>100 years), indicating that this part is harmed to a greater extent by the concurrent extremes than elsewhere in the basin. The spatial pattern of maximum CDCMI again indicates that the southeastern part of the basin is at a high risk for concurrent events. The proposed magnitude index may be a useful tool for analysing concurrent (compound) droughts and cold events as well as their potential impacts.
We herein report a 56-year-old woman who developed allergic bronchopulmonary aspergillosis (ABPA) possibly due to fungal exposure after disastrous heavy rainfall in Western Japan in 2018. She was diagnosed with ABPA complicated with asthma, increased peripheral blood eosinophil count, elevation of specific immunoglobulin E for Aspergillus fumigatus, positive Aspergillus fumigatus precipitation antibody reaction test results, and notable chest computed tomography findings. After treatment with benralizumab, her symptoms, peripheral blood eosinophil count, radiological findings, and respiratory function dramatically improved. The administration of benralizumab appears to be an effective treatment strategy for ABPA.
Natural air ventilation in the hot-dry regions plays a key role to decrease indoor air temperature in hot season, also to improve thermal comfort during the cold season. One of the most common ways to take advantage of natural ventilation is using wind catcher with an underground tunnel. In this method, the tower catches the airflow and directs it to the underground tunnel to decrease the air temperature by transferring heat to the ground, which is cooler in the summer and warmer in the winter. Earth-to-air heat exchanger (EAHE) is a modern form of wind catcher with underground tunnel. In this method, air after passing through buried pipes exchanges heat with the ground, and its temperature increases in the winter and decreases during the summer. This study analyzes the energy performance and cost-effectiveness of earth-to-air heat exchanger to be utilized in a residential building in climate condition of the province of Kermanin Iran. In this regard, 9 different configurations of the EAHE are investigated to find the optimized EAHE. The system performance and cost-effectiveness are studied in 3 different depths including 1, 2, and 3 m with 3 different pipe lengths including 25, 50, and 75 m. The results show that the EAHE is capable of reducing the inlet air temperature by 0.5-9.9celcius in the summer and increasing it by 0.9-11.2celcius in the winter. Furthermore, by integrating the EAHEs in a building design, one can reduce the total annual cooling load by 1.25%-3.97% and for heating by 1.34%-3.96%. The payback period of the system with a pipe length of 25 m is 16 years, but for the systems with pipe lengths of 50 and 75 m, this period reduces to almost 3 years.
Temperature has been studied in relation to many health outcomes. However, few studies have explored its effect on the risk of hospital admission for rheumatoid arthritis (RA). A distributed lag non-linear model (DLNM) was used to analyze associations between mean temperature, diurnal temperature range (DTR), temperature change between neighboring days (TCN), and daily admissions for RA from 2015 to 2019 in Anqing, China. Subgroup analyses based on age, gender, rheumatoid factors, and admission route were performed. In total, 1456 patients with RA were hospitalized. Regarding the cumulative-lag effects of extreme cold temperature (5th percentile?=?3?), the risks of admissions for RA were increased and highest at lag 0-11 (RR?=?2.68, 95% CI: 1.23-5.86). Exposing to low (5th percentile?=?1.9?) and high (95th percentile?=?14.2?) DTRs both had increased risks of RA admission, with highest RRs of 1.40 (95% CI: 1.03-1.91) and 1.24 (95% CI: 1.0-1.53) at lag 0 day, respectively. As for TCN, the marginal risk of admission in RA patients was found when exposed to high TCN (95th percentile?=?2.9?) with the largest single-day effect at lag 10 (RR?=?1.11, 95% CI: 1.01-1.23). In subgroup analyses, females were more susceptible to extreme cold temperature, low and high DTRs, and high TCN. In regard to extreme cold temperature, significant risk of hospital admission in females only appeared at lag 2 (RR?=?1.48, 95% CI: 1.02-2.15) and lag 0-2 (RR?=?2.35, 95% CI: 1.11-4.95). It is clear that RA patients exposed to changing temperature may increase risks of admission.
Current development of temperature-related health early warning systems mainly arises from knowledge of temperature-related mortality or hospital-based morbidity. However, due to the delay in data reporting and limits in hospital capacity, these indicators cannot be used in health risk assessments timely. In this study, we examine temperature impacts on emergency ambulance and discuss the benefits of using this near real-time indicator for risk assessment and early warning. We collected ambulance dispatch data recording individual characteristics and preliminary diagnoses between 2015 and 2016 in Shenzhen, China. Distributed lag nonlinear model was used to examine the effects of high and low temperatures on ambulance dispatches during warm and cold seasons. Lag effects were also assessed to evaluate the sensitivity of ambulance dispatches in reflecting immediate health reactions. Stratified analyses by gender, age, and a wide range of diagnoses were performed to identify vulnerable subgroups. Disease-specific numbers of ambulance dispatches attributable to non-optimal temperature were calculated to determine the related medical burdens. Effects of temperature on ambulance dispatches appeared to be acute on the current day. Males, people aged 18-44 years, were more susceptible to non-optimal temperatures. Highest RR during heat exposure by far was for urinary disease, alcohol intoxication, and traumatic injury, while alcohol intoxication and cardiovascular disease were especially sensitive to cold exposure, causing the main part of health burden. The development of local health surveillance systems by utilizing ambulance dispatch data are important for temperature impact assessments and medical resource reallocation.
To date, research evidence suggests that extreme ambient temperatures may lead to preterm birth. Since the results of studies in subtropical humid monsoon climate are inconclusive, we investigated the association between extreme ambient temperatures and the risk of preterm birth in Xuzhou, China. We analyzed the association between the birth data of 103,876 singleton deliveries (from July 1, 2016 to June 30, 2019) and ambient temperature. We used a quasi-Poisson model with distributed lag nonlinear models (DLNM) to investigate the delay and nonlinear effects of temperature, taking into account the effects of air pollutants and relative humidity. During the study period, the number of hospitalizations for preterm birth was 4623. Taking the median temperature (16.8 °C) as a reference, the highest risk estimate at extreme cold temperature (- 2.8 °C, 1st percentile) was found at lag 0-1 days. Exposure to extreme cold (- 2.8 °C, 1st percentile), or moderate cold (6.8 °C, 25th percentile) were associated with 1.659 (95% confidence interval [CI] 1.177-2.338) and 1.456 (95% CI 1.183-1.790) increased risks of preterm birth, respectively. In the further stratified analysis of the age of pregnant women, we found that there were significant associations between cold temperatures and preterm birth in both groups (older group ? 35; younger group < 35). In a subtropical humid monsoon climate, low ambient temperatures may lead to preterm birth, suggesting that women should stay away from low temperatures during pregnancy.
Social inequalities lead to flood resilience inequalities across social groups, a topic that requires improved documentation and understanding. The objective of this paper is to attend to these differences by investigating self-stated flood recovery across genders in Vietnam as a conceptual replication of earlier results from Germany. This study employs a regression-based analysis of 1,010 respondents divided between a rural coastal and an urban community in Thua Thien-Hue province. The results highlight an important set of recovery process-related variables. The set of relevant variables is similar across genders in terms of inclusion and influence, and includes age, social capital, internal and external support after a flood, perceived severity of previous flood impacts, and the perception of stress-resilience. However, women were affected more heavily by flooding in terms of longer recovery times, which should be accounted for in risk management. Overall, the studied variables perform similarly in Vietnam and Germany. This study, therefore, conceptually replicates previous results suggesting that women display slightly slower recovery levels as well as that psychological variables influence recovery rates more than adverse flood impacts. This provides an indication of the results’ potentially robust nature due to the different socio-environmental contexts in Germany and Vietnam.
Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233-1.606), 1.470 (95% CI: 1.220-1.771) and 1.741 (95% CI: 1.157-2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384-1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change.
Considering the increasing rate of hospitalization due to the symptoms intensification, and the increasing trend of air pollution, this study aimed to determine the relationship between the amount of air pollutants and the incidence of cardiovascular disease leading to hospitalization. This case-crossover study was carried out on the data of admitted patients with cardiovascular disease such as hypertension, ischemic heart disease, and cerebrovascular disease in Urmia during 2011-2016. Weather data about air pollutants (NO2, PM10, SO2, and CO) were obtained from the meteorological department of Urmia. The data were coded for each patient and matched with the meteorological data for statistical modeling. The data were analyzed through STATA version 14. Conditional logistic regression was used to estimate the effects of air pollutants on cardiovascular disease adjusted to air temperature, relative humidity, and air pollutants. The final analysis was performed on 43,424 patients with cardiovascular disease using code I10-I99 including ischemic heart disease, hypertension, and cerebrovascular disease adjusted to air temperature and relative humidity. Of all pollutants, CO with each increase 10 ?g/m(3) had a meaningful relationship with the incidence of cardiovascular hospitalization. By selecting the window of exposure, 1, 2, and 6 days before admission, lag 6 (6 days) was the best estimation for exposure time in the patients with cardiovascular patients (OR 1.0056, CI 1.0041-1.007), and in the patients with ischemic heart disease (OR 1.000055, CI 1.000036-1.000075) and in the patients with hypertension (OR 1.000076, CI 1.00002-1.000132). Regarding cerebrovascular disease, no statistically significant association was observed. The results showed that only CO was associated with an increased risk of admission in patients with cardiovascular disease, ischemic heart disease, and hypertension, and there was no clear evidence for pollution effects on cerebrovascular diseases.
OBJECTIVES/HYPOTHESIS: This study investigated the impacts of air pollution and meteorological factors on the occurrence of epiglottitis. STUDY DESIGN: A nested case-control study. METHODS: Participants ?40?years old in the Korean National Health Insurance Service-Health Screening Cohort were analyzed. A total of 2,615 epiglottitis patients and 10,460 matched control participants were analyzed. The odds ratios (ORs) for epiglottitis associated with meteorological and air pollution factors, including sulfur dioxide (SO(2) , ppb), nitrogen dioxide (NO(2) , ppb), ozone (O(3) , ppb), and carbon monoxide (CO, ppm), after 3, 7, 15, and 30?days of exposure were analyzed using conditional logistic regression adjusted for total cholesterol, blood pressure, fasting blood glucose, obesity, smoking, alcohol consumption, prior upper respiratory infection, tonsillectomy, immunocompromise, autoimmune disease, and the Charlson comorbidity index. RESULTS: The daily temperature range and NO(2) exposure after 3?days were associated with increased rates of epiglottitis (OR = 1.03, 95% confidence interval [CI] = 1.02-1.05 for temperature range and OR = 1.78, 95% CI = 1.14-2.77 for NO(2) , respectively). These results were generally consistent at 7, 15, and 30?days. CONCLUSIONS: The temperature range and NO(2) exposure for 3, 7, 15, and 30?days were positively related to the occurrence of adult epiglottitis. LEVEL OF EVIDENCE: 3 Laryngoscope, 131:2483-2489, 2021.
Objective: Numerous epidemiological studies have reported relevance of morbidity and mortality from cardiovascular diseases with short-term exposure to environmental temperature. In this study, we examined the hypothesis between temperature indices and hospital admission because of cardiovascular diseases. Methods: The daily number of CVDs was obtained from all hospitals of the Sabzevar city. A semi-parametric generalized additive model (GAM) following a quasi-Poisson distribution with distributed lag non-linear model (dlnm) was selected as a modeling framework for time-series analysis. Results: The overall CVD risk comparing the 1st percentile and the 99th percentile relative to the mean temperature (at lag 0) was 1.33 (95% CI, 1.11: 1.61), and 1.34 (95% CI, 1.10: 1.64), respectively. For all indicators, the extremely cold effects persisted for the initial 7 days. Conclusions: Our results suggest that extremely cold and extremely hot temperatures increase the relative risk of cardiovascular diseases.
This study aims to describe the effectiveness of social capital in the management of flood disasters in Bengawan Solo Riverbank area in Plumpang, Tuban and the problems faced in managing the flood. The flood occurs every year during the rainy season from October to April due to the rising water level that overtops the riverbank. Though occurs annually, the timing cannot be predicted precisely. The impacts of the flooding are: a) submersion of farm lands and houses; b) damage of public facilities (schools, village roads, places of worship, village offices, etc.); and c) disruption of social and economic activities of the villagers. Dealing with the flood and its impacts would have to be a collaborative endeavor of multiple stakeholders. One of the important strategies for managing flood is strengthening social capital. For this reason, a qualitative study was conducted from January to July 2019 in a village of which the river runs through and is severely affected by the flood. The research data were collected through observation, interviews, focused group discussions, and a review of documents related to the problem of flooding. The study finds that social capital in flood disaster management includes a) social capital for preventing flood impacts; b) moment of flooding, and c) recovery from the impacts of the flood. Social capital in each stage of flood disaster management involves several stakeholders, including the villagers, people from outside the village, government, and private sector. Social capital for managing flood is necessary to strengthen the collaboration between stakeholders and researchers on flood management evaluation.
Social vulnerability indicators are a valuable tool for understanding which population groups are more vulnerable to experiencing negative impacts from disasters, and where these groups live, to inform disaster risk management activities. While many approaches have been used to measure social vulnerability to natural hazards, there is no single method or universally agreed approach. This paper proposes a novel approach to developing social vulnerability indicators, using the example of flooding in Aotearoa New Zealand. A conceptual framework was developed to guide selection of the social vulnerability indicators, based on previous frameworks (including the MOVE framework), consideration of climate change, and a holistic view of health and wellbeing. Using this framework, ten dimensions relating to social vulnerability were identified: exposure; children; older adults; health and disability status; money to cope with crises/losses; social connectedness; knowledge, skills and awareness of natural hazards; safe, secure and healthy housing; food and water to cope with shortage; and decision making and participation. For each dimension, key indicators were identified and implemented, mostly using national Census population data. After development, the indicators were assessed by end users using a case study of Porirua City, New Zealand, then implemented for the whole of New Zealand. These indicators will provide useful data about social vulnerability to floods in New Zealand, and these methods could potentially be adapted for other jurisdictions and other natural hazards, including those relating to climate change.
This study attempts to measure the spatial correlation length (SCL) of summer extreme heat stress in any location by using a characterized scale identification method. Daily datasets of multiple meteorological variables from 2,134 observation stations over eastern China during 1961-2010 were used. Three types of heat indexes (a total of seven indexes) were applied to characterize the heat stress. The first type used a single variable, that is, daily maximum temperature (T-max) or daily minimum temperature (T-min), while the second used mean temperature (T) and relative humidity, and the third used T, vapour pressure, and 10-m wind speed. A 90th percentile of the climatology of local heat stress was applied to identify hot days. The SCLs of heat stress were analysed in three regions: North China (NC), the Yangtze River Valley (YRV), and South China (SC). Results showed that the trend changes in heat stress had obvious temporal and geographical characteristics, especially in NC and YRV. Generally, the SCLs of heat stress in NC were the largest, reaching more than 440 km for T-max, with YRV second, about 350 km, and SC the smallest, only about 185 km. This phenomenon could be found for almost all indexes. Moreover, the SCLs of the first two types of heat indexes (except T-min) for the three regions were greater than that of the third one, particularly in NC and YRV, which was related to inconsistent changes in the variables used and the primary role of which one characterized the heat stress. The spatial distributions of high SCLs for all indexes were in line with that of the major urban agglomeration in eastern China. The SCL of heat stress for a location was related not only to the changes themselves, but also to the surroundings, involving the number and spatial distribution of hot days.
Flood relief and rescue form an important basis of disaster management, and the assessment of flood damage is a critical component of flood risk management. In its recent history, Kashmir Valley witnessed the floods in 2014, 2015, 2017, 2019, 2020, and 2021, but the worst flood in the living memory of the people was witnessed in the year 2014, which created widespread loss in economic and societal aspects. The present study discusses the spatial dimension of impact, relief, and rescue of the flood of 2014 in the Kashmir Valley. It analyses the distribution of relief and politics of relief and rescue and highlights the role of the communitarianism and the heroics of the community members in dealing with floods. The study provides the data of relief distribution under different government schemes and reveals that the relief was not distributed equally in various districts of the valley. The study relies on primary and secondary sources of data. Ethnographic approach was used for acquiring primary data because it provides the complex narratives of disasters and the political and social rupture experienced during the disasters. The data have been analysed with the help of Geographic Information System.
Previous studies indicate that the incidence of bacillary dysentery is closely related to meteorological factors. However, the impact of temperature and the spatial heterogeneity of the disease in regions of unbalanced socioeconomic development remains unclear. Therefore, this research collected data for 29,639 daily bacillary dysentery cases in children under 5 years of age, as well as the meteorological variables from China’s Beijing-Tianjin-Hebei region, to analyze the spatial pattern of bacillary dysentery and reveal its nonlinear association with temperature. The SatScan method was employed first, to detect the spatial heterogeneity of the disease risk, and then the distributed lag nonlinear model (DLNM) was used to analyze the relationships between the daily minimum, mean, and maximum temperatures and bacillary dysentery in the stratified heterogeneous regions. The results indicated that bacillary dysentery incidence presented statistically significant spatial heterogeneity. The area of highest risk was found to be Beijing and its neighboring regions, which have high population densities. There was also a positive association between bacillary dysentery and temperature. Hotter temperatures were accompanied by higher relative risks. In the most likely spatial cluster region, the excess risk (ER) values for a 1°C rise in minimum, mean, and maximum temperatures above the median were 4.65%, 11.30%, and 19.21%, respectively. The effect of temperature on bacillary dysentery peaked at a lag of 3 to 4 days. The findings of this study will aid risk assessments and early warning systems for bacillary dysentery.
Floods are common natural disasters in Asia. Flood datasets from 48 countries in Asia were collected to investigate the spatiotemporal distribution and influencing factors, using the Mann-Kendall trend test and the Spearman’s rank correlation. These results show that flood occurrences and damages increased significantly in Asia, with the mortality rates and deaths decreasing. Southern and Eastern Asia are flood vulnerable regions, with Central Asia being the least flood-occurrence region, and China and India are also flood-prone countries with a largest population and land area in Asia. Least flood disasters occurred in Bahrain, Cyprus, Brunei Darussalam and Singapore, with a smaller population and land area. The spatial disparities of flood disasters were positively influenced by population and land area, and negatively influenced by urbanization rate and per capita GDP. The largest proportion of flood disasters were discovered in riverine floods, followed by flash floods, with coastal floods being the least. The highest and second-highest mortality rates were observed in flash floods and coastal floods, which showed decreasing trends, and the mortality rate of riverine floods was the lowest, with an increasing trend. The rain was the main triggering origin of floods, and tropical cyclone contributed to the second, followed by snowmelt, convective storms, and dam-break flows. This analysis can help to provide a useful insight into the formulation of flood risk maps, disaster mitigation measures and emergency management.
Ischemic stroke is one of the most common causes of death worldwide, and uncomfortable meteorological and built environments may increase its risk. Residents in different built environments are exposed to different risks of ischemic stroke in cold and hot weather. By using the data from 3547 patients hospitalized, a distributed lag non-linear model was established to compare the differences in the risk of ischemic stroke in urban areas with respect to different Building Height, Building Density, Normalized Differential Vegetation Index, and Distance to Water under the meteorological condition. The results showed that lower Building Height is related to the negative cold effects in winter, and higher Building Height is related to increased risks at high temperatures. Built environments with Building Heights of 10-15 m in hot weather and above 15 m in cold weather have low risks. Higher Building Density was found to be associated with reduced negative cold effects; however, the negative hot effects increased in summer. Built environments with a Building Density of more than 0.3 showed low risks, regardless of the weather conditions. Increasing NDVI seemed to mitigate negative effects in uncomfortable weather, and built environments with higher NDVI were found to be associated with lower risks of ischemic stroke. Built environments with shorter Distance to Water seemed to pose higher risks in summer, and longer Distance to Water was correlated with higher risks in winter. Built environments with Distance to Water in the range of 0.65-2.30 km showed low risks. The research results could have some implications for urban planners to form reasonable built environments under certain meteorological factors which can be beneficial for the mitigation of incidence of ischemic stroke. (C) 2020 Elsevier B.V. All rights reserved.
Following a devastating flood, some survivors adapt well, showing a growth trajectory and resilience, while others do not. This qualitative study aims to explore the precursors of resilience among survivors of the 2018 Kerala flood in India. Twenty-one survivors were interviewed with seven semi-structured questions aimed at unpacking their lived experiences. Responses were thematically analyzed, and three themes emerged: dispositional, cognitive, and situational attributes. Dispositional attributes incorporate adaptive processes to meet emerging challenges and include self-efficacy, hope, optimism, striving, and grit. Cognitive attributes include cognitive reframing and flexibility, which facilitate survivors’ ability to analyze situations and formulate adaptable solutions. Situational attributes incorporate social support, community embeddedness, and collective efficacy, which create an avenue for overcoming situational demands. These attributes contribute to survivors’ resilience in countering the adverse consequences of the flood.
Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM(2.5) to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM(2.5) between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM(2.5) climate change penalty of 1.43 ?g m(-3) in Eastern China, leading to an additional 35,000 PM(2.5)-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM(2.5) climate change penalty weakens to 0.24 ?g m(-3) with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM(2.5)-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM(2.5) decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM(2.5) decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM(2.5) and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions are key to attaining air quality targets and protecting human health in the context of future global climate change.
Purpose Quantitative and spatial-explicit flood risk information is of great importance for strengthening climate change adaptation and flood resilience. Shanghai is a coastal megacity at large estuary delta with rising flood risks. This study aims to quantify the overall economic-societal risks of storm flooding and their spatial patterns in Shanghai. Design/methodology/approach Based on multiple storm flood scenarios at different return periods, as well as fine-scale data sets including gridded GDP, gridded population and vector land-use, a probabilistic risk model incorporating geographic information system is used to assess the economic-societal risks of flooding and their spatial distributions. Findings Our results show that, from 1/200 to 1/5,000-year floods, the exposed assets will increase from USD 85.4bn to USD 657.6bn, and the direct economic losses will increase from USD 3.06bn to USD 52bn. The expected annual damage (EAD) of assets is around USD 84.36m. Hotpots of EAD are mainly distributed in the city center, the depressions along the upper Huangpu River in the southwest, the north coast of Hangzhou Bay, and the confluence of the Huangpu River and Yangtze River in the northeast. From 1/200 to 1/5,000-year floods, the exposed population will rise from 280 thousand to 2,420 thousand, and the estimated casualties will rise from 299 to 1,045. The expected annual casualties (EAC) are around 2.28. Hotspots of casualties are generally consistent with those of EAD. Originality/value In contrast to previous studies that focus on a single flood scenario or a particular type of flood exposure/risk in Shanghai, the findings contribute to an understanding of overall flood risks and their spatial patterns, which have significant implications for cost-benefit analysis of flood resilience strategies.
PURPOSE: To investigate whether previously reported seasonal variation and winter-dominant prevalence of acute massive submacular hemorrhages (SMHs) caused by age-related macular degeneration (AMD) disappeared, and those caused by retinal microaneurysms (RMAs) emerged. METHOD: The medical charts of 95 patients (95 eyes) with SMH caused by AMD and 76 patients (76 eyes) with SMH caused by RMAs in 2012-2019 were retrospectively reviewed. For each subject, the month of onset, the mean ambient temperature of that month were recorded. RESULTS: The monthly numbers of cases of SMHs caused by AMD from January to December were 6, 8, 4, 9, 7, 10, 9, 11, 7, 11, 3, and 10. No significant seasonal variation in the monthly incidence was identified (Roger’s R?=?1.89, p?=?0.39). The monthly numbers of SMHs caused by RMAs from January to December were 3, 11, 11, 8, 7, 8, 5, 5, 2, 4, 7, and 5. There was significant seasonal variation in the monthly incidence (Roger’s R?=?7.67, p?=?0.02). There was no significant correlation between the monthly incidence of SMHs caused by RMAs and mean ambient temperature. CONCLUSION: Our previous study conducted for cases obtained in 1998-2005 showed seasonal cyclic trend in the number of SMHs caused by AMD, with the peak in winter. However, that significant seasonal variation disappeared in 2012-2019 in the present study. Common usage of OCT devices and anti-VEGF drugs might be the reason for the lack of seasonal variation in the cases of SMH caused by AMD.
BACKGROUND: Ambient temperature may contribute to seasonality of mortality; in particular, a warming climate is likely to influence the seasonality of mortality. However, few studies have investigated seasonality of mortality under a warming climate. METHODS: Daily mean temperature, daily counts for all-cause, circulatory, and respiratory mortality, and annual data on prefecture-specific characteristics were collected for 47 prefectures in Japan between 1972 and 2015. A quasi-Poisson regression model was used to assess the seasonal variation of mortality with a focus on its amplitude, which was quantified as the ratio of mortality estimates between the peak and trough days (peak-to-trough ratio (PTR)). We quantified the contribution of temperature to seasonality by comparing PTR before and after temperature adjustment. Associations between annual mean temperature and annual estimates of the temperature-unadjusted PTR were examined using multilevel multivariate meta-regression models controlling for prefecture-specific characteristics. RESULTS: The temperature-unadjusted PTRs for all-cause, circulatory, and respiratory mortality were 1.28 (95% confidence interval (CI): 1.27-1.30), 1.53 (95% CI: 1.50-1.55), and 1.46 (95% CI: 1.44-1.48), respectively; adjusting for temperature reduced these PTRs to 1.08 (95% CI: 1.08-1.10), 1.10 (95% CI: 1.08-1.11), and 1.35 (95% CI: 1.32-1.39), respectively. During the period of rising temperature (1.3?°C on average), decreases in the temperature-unadjusted PTRs were observed for all mortality causes except circulatory mortality. For each 1?°C increase in annual mean temperature, the temperature-unadjusted PTR for all-cause, circulatory, and respiratory mortality decreased by 0.98% (95% CI: 0.54-1.42), 1.39% (95% CI: 0.82-1.97), and 0.13% (95% CI: – 1.24 to 1.48), respectively. CONCLUSION: Seasonality of mortality is driven partly by temperature, and its amplitude may be decreasing under a warming climate.
INTRODUCTION: Patients with knee osteoarthritis (KOA) often complain about clinical symptoms affected by weather-related factors. The purpose of the present study was to use cross-sectional analysis to determine whether weather sensitivity was associated with clinical symptoms, as well as structure abnormalities, in KOA patients. METHODS: Data from 80 participants were obtained from the Feng Hans Shi Effects on OA (FHS) study, an OA cohort study initiated in China in 2015. The weather sensitivity of each participant was determined by a self-reported questionnaire. The following measurements were used to assess clinical outcomes: Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) for symptoms, and semi-quantitative Whole-Organ Magnetic Resonance Imaging Score (WORMS) for cartilage defects and marrow abnormalities of magnetic resonance imaging (MRI). Chi-square with Cochran-Armitage test for trend and regression analysis were used to evaluate the associations between weather sensitivity and WOMAC and WORMS of KOA patients. RESULTS: Most of the KOA participants (57.5%) perceived the weather as affecting their knee-joint clinical symptoms. After adjusting for age, gender, and body mass index (BMI), weather sensitivity was not only associated with knee pain [OR?=?3.3 (95% CI 1.1, 9.9), P?=?0.032], dysfunction [OR?=?5.5 (95% CI 1.8, 16.8), P?=?0.003], and overall clinical symptoms [OR?=?3.3 (95% CI 1.1, 10.2), P?=?0.034], but also associated with cartilage defect [OR?=?3.1 (95% CI 1.1, 8.5), P?=?0.027] and marrow abnormality [OR?=?3.0 (95% CI 1.1, 8.1), P?=?0.029]. CONCLUSIONS: In KOA patients, weather sensitivity was associated with clinical symptoms and structural abnormalities. Future longitudinal study is warranted for the causal relationship. INFOGRAPHIC.
Recent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2-3.3%) in the 2010s to 2.4% (0.4-4.1%) in the 2030?s and 5.5% (0.5-9.9%) in the 2090?s under RCP8.5, with corresponding relative changes of 0.5% (0.0-1.2%) and 3.6% (-0.5-7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.
Background: Extreme temperature events have been observed to appear more frequently and with greater intensity in Taiwan in recent decades due to climate change, following the global trend. Projections of temperature extremes across different climate zones and their impacts on related mortality and adaptation have not been well studied. Methods: We projected site-specific future temperature extremes by statistical downscaling of 8 global climate models followed by Bayesian model averaging from 2021 to 2060 across Taiwan under the representative concentration pathway (RCP) scenarios RCP2.6, RCP4.5, and RCP8.5. We then calculated the attributable mortality (AM) in 6 municipalities and in the eastern area by multiplying the city/county- and degree-specific relative risk of mortality according to the future population projections. We estimated the degree of adaptation to heat by slope reduction of the projected AM to be comparable with that in 2018. Results: The annual number of hot dayswithmean temperatures over 30 degrees C was predicted to have a substantial 2-to 5-fold increase throughout the residential areas of Taiwan by the end of 2060 under RCP8.5, whereas the decrease in cold days was less substantial. The decrease in cold-related mortality below 15 degrees C was projected to outweigh heat-related mortality for the next two decades, and then heat-related mortality was predicted to drastically increase and cross over cold-related mortality, surpassing it from 2045 to 2055. Adjusting for future population size, the percentage increase in heat-related deaths per 100,000 people could increase by more than 10-fold under the worst scenario (RCP8.5), especially for those over 65 years old. The heat-related impacts will be most severe in southern Taiwan, which has a tropical climate. There is a very high demand for heat-adaptation prior to 2050 under all RCP scenarios. Conclusions: Spatiotemporal variations in AM in cities in different climate zones are projected in Taiwan and are expected to have a net negative effect in the near future before shifting to a net positive effect from 2045 to 2055. However, there is an overall positive and increasing trend of net effect for elderly individuals under all the emission scenarios. Active adaptation plans need to bewell developed to face future challenges due to climate change, especially for the elderly population in central and southern Taiwan. (C) 2020 Elsevier B.V. All rights reserved.
INTRODUCTION: A decline in semen quality caused by global warming and torrid working conditions is a major cause of human male infertility, and heat stress-induced decreases in male reproductive ability results in economic losses in livestock husbandry. Increasing evidence suggests that melatonin exerts protective effects on stress-induced DNA damage and apoptosis in germ cells. However, few studies have assessed the effects of melatonin on testicular recovery during post-heat stress and the underlying mechanisms. METHODS AND RESULTS: In vivo studies using 8-week-old male CD-1 mice revealed that melatonin pretreatment (50 mg/kg for 5 days) did not alleviate heat stress-induced germ cell loss and disrupted testicular histomorphology, however, long-term melatonin administration after heat stress accelerated germ cell apoptosis, spermatogenic cell regeneration, and testicular weight recovery. In vitro studies demonstrated that melatonin enhanced RAC1 activity, resulting in increased phagocytosis of apoptotic germ cells by Sertoli cells. In addition, melatonin restored gap junctions and tight junctions after heat stress, thereby promoting hollow seminiferous tubule filling. DISCUSSION: Long-term melatonin administration accelerated testicular recovery after heat stress by enhancing the phagocytotic activity of Sertoli cells and the regeneration of spermatogenic cells. This finding suggests that melatonin is a potential therapeutic for heat stress-induced male infertility.
OBJECTIVES: The primary objective was to evaluate the association between weather variables and joint pain in patients with chronic rheumatic diseases (CRD: rheumatoid arthritis (RA), osteoarthritis (OA), and spondyloarthritis (SpA)). A secondary objective was to study the impact of air pollution indicators on CRD pain. METHOD: The study is prospective, correlational, with time-series analysis. Patients with CRD, living in a predefined catchment area, filled their level of pain daily using a 0-10 numerical scale (NS), for 1 year. Weather (temperature, relative humidity (H), atmospheric pressure (P)) and air pollution indicators (particulate matters (PM(10), PM(2.5)), nitrogen dioxide (NO(2)), and ozone (O(3))) were recorded daily using monitoring systems positioned in the same area. Association between pain and weather and air pollution indicators was studied using Pearson’s correlation. Time-series analysis methodology was applied to determine the temporal relationship between pain and indicators. RESULTS: The study included 94 patients, 82% reported they were weather-sensitive. Pain variation was similar across diseases over a year. Pain was associated negatively with temperature, H, and O(3,) and positively with P and NO(2). However, the strength of correlation was moderate; temperature explained 22% of pain variance. A drop of 10°C in temperature corresponded to an increase of 0.5 points in pain NS. Also, there was a significant interaction among environmental factors. In time-series analysis, temperature and NO(2) remained independently associated with pain. CONCLUSIONS: The perception of joint pain in patients with CRD was correlated with weather and air pollution. The strength of association was moderate and independent of underlying disease. Key Points •Weather variation was moderately correlated with joint pain in chronic rheumatic diseases, with an inverse association with temperature, humidity, and O(3). • Air pollution indicators, mainly nitrogen dioxide and ozone, were correlated with joint pain; particulate matters were also correlated but to a lesser extent. • The influence of these environmental factors was independent of the type of rheumatic disease, thus raising the hypothesis of their impact on pain perception mechanisms.
BACKGROUND: Accurate and timely forecasts of bacillary dysentery (BD) incidence can be used to inform public health decision-making and response preparedness. However, our ability to detect BD dynamics and outbreaks remains limited in China. OBJECTIVES: This study aims to explore the impacts of meteorological factors on BD transmission in four representative regions in China and to forecast weekly number of BD cases and outbreaks. METHODS: Weekly BD and meteorological data from 2014 to 2016 were collected for Beijing (Northern China), Shenyang (Northeast China), Chongqing (Southwest China) and Shenzhen (Southern China). A boosted regression tree (BRT) model was conducted to assess the impacts of meteorological factors on BD transmission. Then a real-time forecast and early warning model based on BRT was developed to track the dynamics of BD and detect the outbreaks. The forecasting methodology was compared with generalized additive model (GAM) and seasonal autoregressive integrated moving average model (SARIMA) that have been used to model the BD case data previously. RESULTS: Ambient temperature was the most important meteorological factor contributing to the transmission of BD (80.81%-92.60%). A positive effect of temperature was observed when weekly mean temperature exceeded 4 °C, -3 °C, 9 °C and 16 °C in Beijing (Northern China), Shenyang (Northeast China), Chongqing (Southwest China) and Shenzhen (Southern China), respectively. BD incidence (Beijing and Shenyang) in temperate cities was more sensitive to high temperature than that in subtropical cities (Chongqing and Shenzhen). The dynamics and outbreaks of BD can be accurately forecasted and detected by the BRT model. Compared to GAM and SARIMA, BRT model showed more accurate forecasting for 1-, 2-, 3-weeks ahead forecasts in Beijing, Shenyang and Shenzhen. CONCLUSIONS: Temperature plays the most important role in weather-attributable BD transmission. The BRT model achieved a better performance in comparison with GAM and SARIMA in most study cities, which could be used as a more accurate tool for forecasting and outbreak alert of BD in China.
BACKGROUND: Severe hand-foot-and-mouth disease (HFMD) is a life-threatening contagious disease among young children and infants. Although enterovirus A71 has been well acknowledged to be the dominant cause of severe HFMD, there still remain other unidentified risk factors for severe HFMD. Previous studies mainly focused on identifying the individual-level risk factors from a clinical perspective, while rare studies aimed to clarify the association between regional-level risk factors and severe HFMD, which may be more important from a public health perspective. METHODS: We retrieved the clinical HFMD counts between 2008 and 2014 from the Chinese Center for Disease Control and Prevention, which were used to calculated the case-severity rate in 143 prefectural-level cities in mainland China. For each of those 143 cities, we further obtained city-specific characteristics from the China City Statistical Yearbook (social and economic variables) and the national meteorological monitoring system (meteorological variables). A Poisson regression model was then used to estimate the associations between city-specific characteristics (reduced by the principal component analysis to avoid multicollinearity) and the case-severity rate of HFMD. The above analysis was further stratified by age and gender to examine potential modifying effects and vulnerable sub-populations. RESULTS: We found that the case-severity rate of HFMD varied dramatically between cities, ranging from 0 to 8.09%. Cities with high case-severity rates were mainly clustered in Central China. By relating the case-severity rate to city-specific characteristics, we found that both the principal component characterized by a high level of social and economic development (RR = 0.823, 95%CI 0.739, 0.916) and another that characterized by warm and humid climate (RR = 0.771, 95%CI 0.619, 0.960) were negatively associated with the case-severity rate of HFMD. These estimations were consistent across age and gender sub-populations. CONCLUSION: Except for the type of infected pathogen, the case-severity rate of HFMD was closely related to city development and meteorological factor. These findings suggest that social and environmental factors may also play an important role in the progress of severe HFMD.
Exposure to air pollution has been suggested to be associated with an increased risk of women’s health disorders. However, it remains unknown to what extent changes in ambient air pollution affect gynecological cancer. In our case-control study, the logistic regression model was combined with the restricted cubic spline to examine the association of short-term exposure to air pollution with gynecological cancer events using the clinical data of 35,989 women in Beijing from December 2008 to December 2017. We assessed the women’s exposure to air pollutants using the monitor located nearest to each woman’s residence and working places, adjusting for age, occupation, ambient temperature, and ambient humidity. The adjusted odds ratios (ORs) were examined to evaluate gynecologic cancer risk in six time windows (Phase 1-Phase 6) of women’s exposure to air pollutants (PM(2.5), CO, O(3), and SO(2)) and the highest ORs were found in Phase 4 (240 days). Then, the higher adjusted ORs were found associated with the increased concentrations of each pollutant (PM(2.5), CO, O(3), and SO(2)) in Phase 4. For instance, the adjusted OR of gynecological cancer risk for a 1.0-mg m(-3) increase in CO exposures was 1.010 (95% CI: 0.881-1.139) below 0.8 mg m(-3), 1.032 (95% CI: 0.871-1.194) at 0.8-1.0 mg m(-3), 1.059 (95% CI: 0.973-1.145) at 1.0-1.4 mg m(-3), and 1.120 (95% CI: 0.993-1.246) above 1.4 mg m(-3). The ORs calculated in different air pollution levels accessed us to identify the nonlinear association between women’s exposure to air pollutants (PM(2.5), CO, O(3), and SO(2)) and the gynecological cancer risk. This study supports that the gynecologic risks associated with air pollution should be considered in improved public health preventive measures and policymaking to minimize the dangerous effects of air pollution.
Extreme heat is an increasing climate threat, most pronounced in urban areas where poor populations are at particular risk. We analyzed heat impacts and vulnerabilities of 1027 outdoor workers who participated in a KAP survey in Hanoi, Vietnam in 2018, and the influence of their mitigation actions, their knowledge of heat-risks, and access to early warnings. We grouped respondents by their main income (vendors, builders, shippers, others, multiple jobs, and non-working) and analyzed their reported heat-health impacts, taking into consideration socioeconomics, knowledge of heat impacts and preventive measures, actions taken, access to air-conditioning, drinking amounts and use of weather forecasts. We applied linear and logistic regression analyses using R. Construction workers were younger and had less knowledge of heat-health impacts, but also reported fewer symptoms. Older females were more likely to report symptoms and visit a doctor. Access to air-conditioning in the bedroom depended on age and house ownership, but did not influence heat impacts as cooling was too expensive. Respondents who knew more heat exhaustion symptoms were more likely to report impacts (p < 0.01) or consult a doctor (p < 0.05). Similarly, those who checked weather updates were more likely to report heat impacts (p < 0.01) and experienced about 0.6 more symptoms (p < 0.01). Even though occupation type did not explain heat illness, builders knew considerably less (40%; p < 0.05) about heat than other groups but were twice as likely to consult a doctor than street vendors (p < 0.01). Knowledge of preventive actions and taking these actions both correlated positively with reporting of heat-health symptoms, while drinking water did not reduce these symptoms (p < 0.01). Child carers and homeowners experienced income losses in heatwaves (p < 0.01). The differences support directed actions, such as dissemination of educational materials and weather forecasts for construction workers. The Red Cross assisted all groups with cooling tents, provision of drinks and health advice.
Flood prediction has gained prominence world over due to the calamitous socio-economic impacts this hazard has and the anticipated increase of its incidence in the near future. Artificial intelligence (AI) models have contributed significantly over the last few decades by providing improved accuracy and economical solutions to simulate physical flood processes. This study explores the potential of the AI computing paradigm to model the stream flow. Artificial neural network (ANN), fuzzy logic, and adaptive neuro-fuzzy inference system (ANFIS) algorithms are used to develop nine different flood prediction models using all the available training algorithms. The performance of the developed models is evaluated using multiple statistical performance evaluators. The predictability and robustness of the models are tested through the simulation of a major flood event in the study area. A total of 12 inputs were used in the development of the models. Five training algorithms were used to develop the ANN models (Bayesian regularization, Levenberg Marquardt, conjugate gradient, scaled conjugate gradient, and resilient backpropagation), two fuzzy inference systems to develop fuzzy models (Mamdani and Sugeno), and two training algorithms to develop the ANFIS models (hybrid and backpropagation). The ANFIS model developed using hybrid training algorithm gave the best performance metrics with Nash-Sutcliffe Model Efficiency (NSE) of 0.968, coefficient of correlation (R(2)) of 97.066%, mean square error (MSE) of 0.00034, root mean square error (RMSE) of 0.018, mean absolute error (MAE) of 0.0073, and combined accuracy (CA) of 0.018, implying the potential of using the developed models for flood forecasting. The significance of this research lies in the fact that a combination of multiple inputs and AI algorithms has been used to develop the flood models. In summary, this research revealed the potential of AI algorithm-based models in predicting floods and also developed some useful techniques that can be used by the Flood Control Departments of various states/regions/countries for flood prognosis.
Because of climate change and rapid urbanization, urban impervious underlying surfaces have expanded, causing Chinese cities to become strongly affected by flood disasters. Therefore, research on urban flood risks has greatly increased over the past decade, with studies focusing on reducing the risk of flood disaster. From 2012 to 2020, the impervious underlying surface has increased, and the permeable underlying surface has decreased annually in Kunming City. This study was conducted to investigate the impact of continuous changes in the urban underlying surface on flood disasters in the Runcheng area south of Kunming City from 2012 to 2020. We constructed a two-dimensional flood model to conduct flood simulations and flood risk analysis for this area. The relationship between the permeability of the underlying surface and urban flood risk was simulated and analyzed by varying the urban underlying surface permeability (0-60%). The simulation results show that the model can accurately simulate urban waterlogging, and the increase in urban waterlogging risk is related to the underlying surface permeability. Urban flood risk decreases with the increase in permeable underlying surface. The increase rate of flood risk in the part with permeability of 0-35% is greater than that the part with permeability of 35-60%, that is, when the permeability of underlying surface is lower than 35%, the flood risk rate will be higher. We demonstrated the impact of the urban underlying surface permeability on the risk of urban flood disasters, which is useful for urban planning decisions and urban flooding risk controls.
The United Nations Sustainable Development Goals, New Urban Agenda and Paris Agreement on Climate Change are blueprints for health promotion action that mandate human health is linked inextricably to the health of the environment. In the Anthropocene, new indicators are required to promote community engagement with, and measurement of, healthy and sustainable wellbeing for people and planet. This study explored the need for a metric such as the Happy Planet Index that explicitly links human health to health of the environment for a local level scale in Australia. The project arose from an international coalition of health promoters advocating for ‘planetary health’ approaches. Qualitative description methods guided the study design involving key informant interviews (n?=?17) and four focus groups (n?=?27 participants) with health and/or sustainability academics, practitioners and policy-makers. Document analysis of health and environment indices and policy mandates augmented the analysis. Qualitative content analysis techniques were used to analyse the findings. There was strong interest for a local level composite indicator, such as a rescaled Happy Planet Index (life expectancy?×?life satisfaction?×?equity adjustment/ecological footprint) for use at a local level. The value of a composite index was: its ability to promote community engagement with planetary health thinking; an advocacy tool for joint health and sustainability policy; to justify programs on health and environmental co-benefits; and to provide a mechanism for correlative comparisons between local governments and national comparisons. However, disciplinary silos currently limit partnerships for health promotion and planetary health and a local composite index could help bridge these divides.
Both droughts and hot extremes may exert critical impacts on human society, and their concurrence is no exception. Global warming is expected to increase the frequency and intensity of compound dry and hot events widely, the impacts of which will be particularly severe for sensitive and vulnerable sectors. However, projected risk and impact of compound dry and hot events in China are less assessed, especially in the context of the goals specified by the Paris Agreement in 2015. Here, we show an overall increased risk of compound dry and hot events on human health in China, particularly in eastern regions, for the two warming levels (1.5 and 2 degrees C) based on Coupled Model Intercomparison Project Phase 5 climate models. The population exposure to extreme compound dry and hot events is projected to increase by about 165.46% for the 1.5 degrees C warming and about 200.49% for the 2 degrees C warming compared with the exposure in the present period 1986-2005. These potential variations are driven by climate change and population change with climate effect being the dominantly positive contributor. These findings highlight the urgent need for more efforts to limit warming within 1.5 degrees C to reduce the risk of compound dry and hot events and associated impacts on human society.
Changes in the preconception ambient temperature (PAT) can affect the gametogenesis, disturbing the development of the embryo, but the health risks of PAT on the developing fetus are still unclear. Here, based on the National Free Preconception Health Examination Project in the rural areas of Henan Province, we evaluate the effects of PAT on preterm birth (PTB). Data of 1,231,715 records from self-reported interviews, preconception physical examination, early gestation follow-up, and postpartum follow-up were collected from 1 January 2013 to 31 December 2016. Generalized additive models were used to assess the cumulative and lag effects of PAT upon PTB. The significant cumulative effects of mean temperature within 2 weeks and 3 weeks on the risk of PTB, especially upon late PTB (34-36 weeks) (P < 0.05), were observed. Exposure to extreme heat (> 90th percentile) within 2 weeks (RR = 1.470) and 3 weeks (RR = 1.375) before conception could increase the risk of PTB. After stratifying PTB, exposure to extreme heat within 2 weeks before conception can increase the risks of early (< 34 weeks) and late PTB (P < 0.05). Besides, exposure to extreme cold (< 10th percentile) within 3 weeks or longer before conception can elevate the risk of PTB, especially late PTB. The significant lag effects of temperature changes on the risk of early PTB (lag-8 days or earlier) were observed. In conclusion, the risk of PTB was susceptible to PAT changes within 2 weeks or longer before conception. Our findings provide (i) guidance for rural couples to make pregnancy plans and (ii) scientific evidence for the government to formulate policies to prevent PTB.
Newly emerging or re-emerging infections are posing continuous threat to both public health system and clinical care globally. The emergence of infections especially caused by arboviruses can be linked to several mechanisms which include geographical expansion linked to human development and transportation, global warming, enhanced transmission in peridomestic area and close proximity of human habitations to domestic as well as wild animals. The co-circulation of Dengue, Chikungunya and Zika is a matter of public health priority due to the fact that they are transmitted by the same vector as well as increase in the number of reported cases of severe dengue, post-chikungunya chronic joint disease and microcephaly related to Zika virus disease. The study was designed to estimate the prevalence of these arboviral infections in Odisha. About 5198 cases presenting with common clinical symptoms of fever, arthralgia, headache, myalgia and malaise were screened during 2016-2019. A total of 42.2% patients tested positive for dengue NS1 antigen (n?=?4154), 30.2% for dengue IgM (n?=?2161) and 14.3% for chikungunya IgM (n?=?1816). A total of 1684 samples were subjected to Zika RT-PCR and none was tested positive. Peak in the numbers of dengue/ chikungunya cases was evident in the post-monsoon months of July – October. Circulation of all four serotypes of dengue i.e. DEN 1, 2, 3, and 4 was noticed in the state. Molecular investigation of suspected Chik cases in early phases showed circulation of Eastern Central Southern African genotype (E1:226A). There is dearth of knowledge about disease severity during arbovirus co-infections and importance of adequate management of patients at an early stage residing in risk areas. It is the first study in Odisha to study the pattern and status of these three arboviral diseases Dengue, Chikungunya and Zika. The outcome of this study will help in focusing and improvement of existing surveillance systems and vector control tools, as well as on the development of suitable antiviral agents and formulating candidate vaccine.
Individuals around the world believe global climate change is a major threat, with media attention and polling suggesting young adults may decide to go childfree as a result. Yet, there is limited research on the link between environmental concern and reproductive attitudes. The purpose of this research was to explore how climate change-related concerns affect reproductive attitudes and motivations to remain childfree. Two studies were conducted: study 1 consisted of a content analysis of reader comments on articles discussing going childfree in response to climate change, and study 2 featured semi-structured interviews conducted in New Zealand and the USA. The impact of future children on the planet, in the context of overpopulation and overconsumption, was a major theme in both studies. Perspectives of doom and hope emerged simultaneously, indicating how climate anxiety influences reproductive attitudes. Study findings point at implications for public policy makers regarding this largely neglected perspective on climate change adaptation and mitigation and potential psychological and societal effects.
Although vaccination is available, mumps remains a public health concern in many countries including China. Previous studies have indicated the impact of meteorological factors and mumps, but findings vary across different regions with limited evidence to inform local public health responses. We aim to examine the impacts of meteorological variables on mumps in Jinan, a temperate city of China, and explore the interactions of temperature with humidity or wind speed. Weekly meteorological data and notified cases of mumps in Jinan were collected for 2014-2018. Regression analyses using the generalized additive model were performed with considerations of multicollinearity, lag effects, school holidays, long-term trend, and seasonality. A stratification model was applied to investigate the interaction. We found a non-linear relationship between weekly mean temperature and the number of cases. Between 1.2 and 24.5 °C, the excess risk (ER) of mumps for a 1 °C increase in weekly mean temperature was 3.08% (95% CI 1.32 to 4.87%) at 0-week lag. The lagged effects could last for 3 weeks. There were interactions between mean temperature and relative humidity or wind speed. The effect of mean temperature was enhanced in days with low relative humidity or high wind speed. This study suggests that temperature is positively associated with mumps cases with thresholds in the temperate city of China, and the effect can be modified by relative humidity and wind speed and is independent of vaccine coverage. Findings could be integrated into current early warning systems of mumps in order to protect people’s health from the risk of changing climate.
Under the dual effects of climate change and urban heat islands (UHI), non-optimum temperature-related mortality burdens are complex and uncertain, and are rarely discussed in China. In this study, by applying city-specific exposure-response functions to multiple temperature and population projections under different climate and urbanization scenarios, we comprehensively assessed the non-optimum temperature-related mortality burdens in China from 2000 to 2050. Our results showed that temperature-related deaths will decrease from 1.19 million in 2010 to 1.08-1.17 million in 2050, with the exception of the most populous scenario. Excess deaths attributable to non-optimal temperatures under representative concentration pathway 8.5 (RCP8.5) were 2.35% greater than those under RCP4.5. This indicates that the surge in heat-related deaths caused by climate change will be offset by the reduction in cold-related deaths. As the climate changes, high-risk areas will be confronted with more severe health challenges, which requires health protection resource relocation strategies. Simultaneously, the net effects of UHIs are beneficial in the historical periods, preventing 3493 (95% CI: 22-6964) deaths in 2000. But UHIs will cause an additional 6951 (95% CI: -17,637-31,539, SSP4-RCP4.5) to 17,041 (95% CI: -10,516-44,598, SSP5-RCP8.5) deaths in 2050. The heavier health burden in RCP8.5 than RCP4.5 indicates that a warmer climate aggravates the negative effects of UHIs. Considering the synergistic behavior of climate change and UHIs, UHI mitigation strategies should not be developed without considering climate change. Moreover, the mortality burden exhibited strong spatial variations, with heavy burdens concentrated in the hotspots including Beijing-Tianjin Metropolitan Region, Yangtze River Delta, Chengdu-Chongqing City Group, Guangzhou, Wuhan, Xi’an, Shandong, and Henan. These hotspots should be priority areas for the allocation of the national medical resources to provide effective public health interventions.
Early adolescence (12-13 years old) is a critical but under-researched demographic for the formation of attitudes related to climate change. We address this important area by exploring adolescent views about climate change. This paper presents opinions collected from surveys of?463 1st-year secondary school students (12-13 years old) in public secondary schools in inner-urban centres in Austria and Australia on whether climate change is (1) something about which to worry, (2) caused by humans and (3) happening now. Eligible respondents in both countries showed similar levels of agreement that climate change was probably or definitely something we should (1) worry about (84.6% Austria, 89.1% Australia), which is significantly higher than either country’s adult population. Eligible respondents agreed that climate change probably or definitely is (2) caused by humans (75.6% Austria, 83.6% Australia) and that climate change is probably or definitely something that is (3) happening now (73.1% Austria, 87.5% Australia). Their response differed from the respective adult populations, but in opposite directions. Our results suggest that socio-cultural worldview may not have as much influence on this age group as it does on the respective adult populations and suggests that this age group would be receptive and ready for climate science education and engagement initiatives.
Schizophrenia (SCZ) hospital re-admissions constitute a serious disease burden worldwide. Some studies have reported an association between air pollutants and hospital admissions for SCZ. However, evidence is scarce regarding the effects of ambient particulate matter (PM) on SCZ hospital re-admissions, especially in coastal cities in China. The purpose of this study was to examine whether PM affects the risk of SCZ hospital re-admission in the coastal Chinese city of Qingdao. Daily SCZ hospital re-admissions, daily air pollutants, and meteorological factors from 2015 to 2019 were collected. A quasi-Poisson generalized linear regression model combined with distributed lag non-linear model (DLNM) was applied to model the exposure-lag-response relationship between PM and SCZ hospital re-admissions. The relative risks (RRs) were estimated for an inter-quartile range (IQR) increase in PM concentrations. Subgroup analyses by age and gender were conducted to identify the vulnerable subgroups. There were 6220 SCZ hospital re-admissions during 2015-2019. The results revealed that PM, including PM(10) (particles with an aerodynamic diameter ?10 ?m), PM(c) (particles >2.5 ?m but <10 ?m), and PM(2.5) (particles ?2.5 ?m), was positively correlated with SCZ hospital re-admissions. The strongest single-day effects all occurred on lag3 day, and the corresponding RRs were 1.07 (95% CI: 1.02-1.11) for PM(10), 1.03 (95% CI: 1.00-1.07) for PM(c), and 1.05 (95% CI: 1.01-1.09) for PM(2.5) per IQR increase. Stronger associations were observed in males and younger individuals (<45 years). Our findings suggest that PM exposure is associated with increased risk of SCZ hospital re-admission. Active intervention measures against PM exposure should be taken to reduce the risk of SCZ hospital re-admission, especially for males and younger individuals.
Using interviews and surveys of 212 households in villages situated at different elevations in the Everest National Nature Preserve (ENNP), correlations and comparative analyses were employed to reveal the residents’ perceptions and understanding of climate change and its effects on the ENNP. Results showed that: (1) nearly all residents thought that climate warming and ice-snow landscape decrease were very significant, but there was an obvious difference between the residents’ cognition and observations to the change of runoff; (2) higher altitude is, more obvious warming is, and stronger residents’ perception of climate change and its impacts is in the ENNP, for which educational level and age were the main factors affecting their degree of perception; (3) especially, higher altitude is, more frequent the tourism participation of residents is and higher their income is; and (4) because the centralized pollutant treatment facilities have a low efficiency, and because the area receives a large number of tourists whose activities are spatially scattered, the potential risk of environmental pollution has been increasing in recent years. At present there is an urgent need for policy suggestions at the strategic level of national ecological security and interregional equity principles concerning the adaptation to climate and environmental changes in the ENNP.
Statistical models for measuring the impact of adverse weather conditions on pedestrian injuries are of great importance for enhancing road safety measures. The development of these models in the presence of high collinearity among the weather conditions poses a real challenge in practice. The collinearity among these conditions may result in underestimation of the regression coefficients of the regression model, and hence inconsistency regarding the impact of the weather conditions on the pedestrian injuries counts. This paper presents a methodology through which the penalization-based regression is applied to model the impact of weather conditions on pedestrian injury in the presence of a high level of collinearity among these conditions. More specifically, the methodology integrates both the least absolute shrinkage squared operator (Lasso) with the cross-validation approach. The statistical performance of the proposed methodology is assessed through an analytical comparison involving the standard Poisson regression, Poisson generalized linear model (Poisson-GzLM), and Ridge penalized regression model. The mean squared error (MSE) was used as a criterion of comparison. In terms of the MSE, the Lasso-based Poisson generalized linear model (Lasso-GzLM) revealed an advantage over the other regression models. Moreover, the study revealed that weather conditions involved in this study are of insignificant impact on pedestrian injury counts.
Several studies have investigated the associations between diurnal temperature rage (DTR) and mortality, but little evidence has been available regarding the association of DTR with years of life lost (YLL). The aim of this study was to examine the association of DTR with YLL rate, and quantify life loss per death caused by DTR in China. Daily meteorological and death data were collected from 364 locations in China during 2006-2017. First, we calculated daily YLL rate. Then, the distributed lag nonlinear model was applied to estimate the associations of DTR with YLL rate in each location, and multivariable meta-analysis was conducted to pool the location-specific estimates. Finally, we calculated the attributable fractions of DTR on YLL rate and average life loss per death to estimate the mortality burden caused by DTR. Subgroups analyses were conducted by region, age, sex and cause of death. A J-shaped association of DTR with YLL rate was identified in China. The minimum YLL-rate DTR (MYDTR) was 3.7 degrees C nationwide. The overall AF of DTR in China was 6.40% [95% confidence interval (CI) 3.95-8.86%], and AFs caused by DTR were higher in females, the elderly and south China. An average of 0.96 years (95%CI 0.57-1.35) life loss per death was attributable to DTR nationwide, and life losses per death attributed to DTR were higher in female, young population, and south China. AF and life loss per death caused by DTR were much higher in cold season than that in warm season. Both high DTR and low DTR increased YLL rate in China. Mortality burdens of DTR were much higher in cold season than warm season. The effects of DTR were modified by region, demography and cause of death. Our findings suggest that vulnerable population should be protected when daily temperature change rapidly, especially in cold season.
Coastal floods are the most prominent natural disaster causing severe damages to the local communities regarding food security, economy and shelter. Risks can be defined by physiographical sensitivity and vulnerability associated with socio-economic, demographic and infrastructure aspects of the region. Population with poor socio-economic status and high dependence on natural resources for livelihood in coastal dwellings of rural India are extremely vulnerable to flood hazards. Policy formulation to reduce coastal flood risks necessitates quantifying hazard vulnerability at an administrative scale. In this context, we propose a method for evaluating the coastal flood risk of an island located in the habited part of Sundarbans, West Bengal. Extending up to 282 sq. km, Sagar Island has been a keystone in harbouring and supporting both local and migrant population since the 1880s. Land-use classification of the island indicates an increase of 1.7% to 3.6% in the built-up class, almost double in the past eight years (2012-2020). A considerable rise in area under the water bodies is also seen from 6.6 to 8.6%, signifying fair evidence of a coastal breach. Flood risk assessment of Sagar Island was carried out using high spatial resolution data from Indian remote sensing satellites and census data. This assessment was performed by modifying the established MCDA technique considering the data limitations and accounting accessibility to infrastructure as a novel variable to a multi-dimensional framework. The framework maps spatial vulnerability of the region using sub-factors such as socio-demographic, economic, infrastructure and accessibility. The exposure profile of the area is drawn with the help of topographic factors and classified land-use results. Literature evidence was used to develop classification rules for data standardization from very high to very low based on their flood sensitivity. Further, the factors and sub-factors were ranked using AHP by a panel of experts belonging to diverse fields such as disaster management, regional planning, environment, hydrology and social science. The weighted sum technique was used to quantify total vulnerability and exposure parameters, respectively. The total risk map generated is the product of the hazard and vulnerability map of the region. The findings reveal the dominance of economic and accessibility parameters in defining the vulnerability of the regional population towards coastal flood risks. Proximity to coastline and tidal creeks enhances disaster sensitivity due to frequent inundation, erosion, saltwater intrusion and complete submergence of land area. Water bodies engulfing the coastline emerge as a serious threat to sustenance given the present rate of submergence of about 6 m/year. The research highlights the pressing need for grassroots development through social and economic upliftment. It also advocates the undeniable need for proactive adaptation such as flood resilient housing and coastline protection by stabilizing sandbars and planting/nurturing/maintaining native species (mangroves).
Currently, the correlation between ambient temperature and systemic lupus erythematosus (SLE) hospital admissions remains not determined. The aim of this study was to explore the correlation between ambient temperature and SLE hospital admissions in Hefei City, China. An ecological study design was adopted. Daily data on SLE hospital admissions in Hefei City, from January 1, 2007, to December 31, 2017, were obtained from the two largest tertiary hospitals in Hefei, and the daily meteorological data at the same period were retrieved from China Meteorological Data Network. The generalized additive model (GAM) combined with distributed lag nonlinear model (DLNM) with Poisson link was applied to evaluate the influence of ambient temperature on SLE hospital admissions after controlling for potential confounding factors, including seasonality, relative humidity, day of week, and long-term trend. There were 1658 SLE hospital admissions from 2007 to 2017, including 370 first admissions and 1192 re-admissions (there were 96 admissions with admission status not stated). No correlation was observed between ambient temperature and SLE first admissions, but a correlation was found between low ambient temperature and SLE re-admissions (RR: 2.53, 95% CI: 1.11, 5.77) (3.5 °C vs 21 °C). The effect of ambient temperature on SLE re-admissions remained for 2 weeks but disappeared in 3 weeks. Exposure to low ambient temperature may increase hospital re-admissions for SLE, and thus it is important for SLE patients to maintain a warm living environment and avoid exposure to lower ambient temperature.
Heat waves (HWs) and urban heat islands (UHIs) can potentially interact. The mechanisms behind their synergy are not fully disclosed. Starting from the localized UHI phenomenon, this study aims i) to reveal their associated impacts on human thermal comfort through three different definitions of HW events, based on air temperature (airT), wet-bulb globe temperature (WBGT) and human-perceived temperature (AppT) respectively, and ii) to understand the role of air moisture and wind. The analysis was conducted in four districts (NH, JD, MH and XJH) with different urban development patterns and geographic conditions, in the megacity of Shanghai with a subtropical humid climate. Results evidenced the localized interplay between HWs and UHIs. The results indicate that less urbanized districts were generally more sensitive to the synergies. JD district recorded the highest urban heat island intensity (UHII) amplification, regardless of the specific HW definition. Notably, during AppT-HWs, the increment was observed in terms of maximum (1.3 °C), daily average (0.8 °C), diurnal (0.4 °C) and nocturnal UHII (1.0 °C). Nevertheless, localized synergies between HWs and UHIs at different stations also exhibited some commonalities. Under airT-HW, the UHII was amplified throughout the day at all stations. Under WBGT-HW, diurnal UHII (especially at 11:00-17:00 LST) was consistently amplified at all stations. Under AppT-HW conditions, the nocturnal UHII was slightly amplified at all stations. Air moisture and wind alleviated the synergistic heat exacerbation to the benefit of thermal comfort. The extent depended on geographic condition, diurnal and nocturnal scenarios, temperature type and HW/normal conditions. Stronger HW-UHI synergies indicate the necessity to develop specific urban heat emergency response plans, able to capture and intervene on the underlying mechanisms. This study paves to way to their identification.
The short-term effects of ambient temperature on mortality have been widely investigated. However, the epidemiological evidence on the long-term effects of temperature on mortality is rare. In present study, we conducted a nationwide quasi-experimental design, which based on a variant of difference-in-differences (DID) approach, to examine the association between long-term exposure to ambient temperature and mortality risk in China, and to analyze the effect modification of population characteristics and socioeconomic status. Data on mortality were collected from 364 communities across China during 2006-2017, and environmental data were obtained for the same period. We estimated a 2.93 % (95 % CI: 2.68 %, 3.18 %) increase in mortality risk per 1 °C decreases in annual temperature, the greater effects were observed on respiratory diseases (5.16 %, 95 % CI: 4.53 %, 5.79 %) than cardiovascular diseases (3.43 %, 95 % CI: 3.06 %, 3.80 %), and on younger people (4.21 %, 95 % CI: 3.73 %, 4.68 %) than the elderly (2.36 %, 95 % CI: 2.06 %, 2.65 %). In seasonal analysis, per 1 °C decreases in average temperature was associated with 1.55 % (95 % CI: 1.23 %, 1.87 %), -0.53 % (95 % CI: -0.89 %, -0.16 %), 2.88 % (95 % CI: 2.45 %, 3.31 %) and 4.21 % (95 % CI: 3.98 %, 4.43 %) mortality change in spring, summer, autumn and winter, respectively. The effects of long-term temperature on total mortality were more pronounced among the communities with low urbanization, low education attainment, and low GDP per capita. In total, the decrease of average temperature in summer decreased mortality risk, while increased mortality risk in other seasons, and the associations were modified by demographic characteristics and socioeconomic status. Our findings suggest that populations with disadvantaged characteristics and socioeconomic status are vulnerable to long-term exposure of temperature, and targeted policies should be formulated to strengthen the response to the health threats of temperature exposure.
In the context of global climate change, far less is known about the impact of long-term temperature variability (TV), especially in developing countries. The current study aimed to estimate the effect of long-term TV on the incidence of cardiovascular disease (CVD) in China. A total of 23,721 individuals with a mean age of 56.15 years were enrolled at baseline from 2012 to 2016 and followed up during 2017-2019. TV was defined as the standard deviation of daily temperatures during survey years and was categorized into tertiles (lowest? 8.78 °C, middle = 8.78-10.07 °C, highest ? 10.07 °C). The Cox proportional hazards regression was used to estimate the multivariable-adjusted hazard ratio (HR) between TV and CVD. During the median follow-up of 4.65 years, we ascertained 836 cases of incident CVD. For per 1 °C increase in TV, there was a 6% increase of CVD (HR = 1.06 [95% confidence interval (CI): 1.01-1.11]). A significant positive trend was observed between CVD risk and increasing levels of TV compared to the lowest tertile [HR = 1.34 (95% CI: 1.13-1.59) for the medium tertile, HR = 1.72 (95% CI: 1.35-2.19) for the highest tertile, P(trend) < 0.001]. Exposure to high TV would lose 2.11 disease-free years for the population aged 35-65 years and 66 CVD cases (or 7.95% cases) could been attributable to TV higher than 8.11 °C in the current study. The current findings suggested that long-term TV was associated with a higher risk of CVD incidence, it is needed to reduce the TV-related adverse health effect.
Natural disasters have negative health impacts on patients who need dialysis in affected areas. Severely affected areas are usually rural, with limited basic infrastructure and a population without optimal dialysis-specific care after a disaster. A population-based longitudinal case-cohort study enrolled 715,244 adults from the National Health Insurance Registry who lived in areas affected by a major natural disaster, Typhoon Morakot, in 2009. The observation period was from 2008 to 2011. A total of 13,268 patients (1.85%) had a history of end-stage renal disease (ESRD). Of the ESRD patients, 1264 patients (9.5%) received regular dialysis. Only eight patients missed dialysis sessions in the first month after the disaster. Compared to the moderately affected areas, the incidences of acute cerebrovascular and cardiovascular diseases were higher in patients in severely affected areas. Male dialysis patients aged 45-75 years had a higher mortality rate than that of the general population. Among the affected adults receiving regular dialysis, patients with diabetes (adjusted hazard ratio (aHR): 1.58, 95% confidence interval (CI): 1.20-2.08) or a history of cerebrovascular disease (aHR: 1.58, 95% CI: 1.12-2.21), chronic obstructive pulmonary disease (COPD) or asthma (aHR: 1.99, 95% CI: 1.24-3.17) in moderately affected areas had significantly elevated mortality rates. Additionally, among dialysis patients living in severely affected areas, those with a history of cerebrovascular disease (aHR: 4.52 95% CI: 2.28-8.79) had an elevated mortality rate. Early evacuation plans and high-quality, accessible care for cardiovascular and cerebrovascular diseases are essential to support affected populations before and after disasters to improve dialysis patients’ health outcomes.
The rising temperature makes the weather becoming more extreme. Understanding how extreme hot temperature-heat wave events (HWEs)-are likely to alter individual heat exposure and sensitivity is crucial for developing climate change mitigation and adaptation strategies. Despite the importance, little is known about the real-time impacts of HWEs on individual daily life in developing nations, like China. To fill this gap, we adopt over 1544 thousand Weibo (Chinese Twitter) social media data, coupled with meteorological conditions people face when posting, to assess the heat exposure and people’s sensitivity to HWEs across 31 mega-cities in China. The results show the hotspot of Weibo heat is coincident with the extremely hot temperature, with a correlation of 0.7 (p < 0.05). The intensities, frequencies, and durations of HWEs in both geographical and social media space have high spatial heterogeneity. Its spatial variation can be explained by the type of climate zone and the unique geographical environment. The cities with extreme hot weather are more likely to adapt to the heatwave and less sensitivity to HWEs. The proposed framework, which integrates the real-time social media semantic analysis, statistical method, and spatial techniques, provides a new paradigm to assess the HWEs exposure and sensitivity analysis in China.
This paper uses a holistic approach within a catchment scale, through the application of both climatic and non-climatic parameters, to analyze the impacts of river floods on the human security needs of rural riverine communities in the Waimanu Catchment situated in Nausori, Fiji. Consideration of both climatic and non-climatic factors is required since non-climatic factors could be controlled to build resilience against floods. The indicator-based flood vulnerability index methodology is applicable worldwide, but the indicators used in this study were specifically related to the Pacific Island context. In the context of fluvial flood vulnerability, effects of land management and climate change are not mutually exclusive of each other. Consequently, vulnerability assessments should consider the connection between people’s actions and ecosystems for the entire catchment area since upstream land use practices influence flood vulnerabilities downstream. In our research, a community-based flood vulnerability index system in conjunction with rainfall variability and land use assessments was used to quantitatively and qualitatively analyze the flood vulnerability, and it was found that increased rainfall, poor agricultural practices, gravel extraction, and improper waste management predominantly increased the exposure and sensitivity of midstream and downstream communities to river floods by modifying river morphology. Midstream communities in the Waimanu Catchment were most vulnerable to river floods due to their very low adaptive capacity in terms of poor ecosystem health and lack of natural resources to cope with the subsequent impacts of floods, being most sensitive to changes in land use and land cover.
Foodborne diseases (FBDs) remain a global public health concern. Climatic factors such as wind-chill temperature, rainfall, and relative humidity affect the incidence of several FBDs. This study was performed to analyze how the various factors of the climate influence the incidence and severity of FBDs. This study retrospectively analyzed the results of multiplex polymerase chain reaction (mPCR) tests for diarrhea-causing bacteria performed on 2300 fecal samples obtained from patients at Dankook University Hospital, Cheonan, from June 2010 to December 2019. The Clostridioides difficile toxin B infection rate positively correlated with the intensity of sunshine, and the content of particulate matter. The Campylobacter spp. infection rate positively correlated with wind-chill temperature and the content of particulate matter. The Escherichia coli O157:H7 infection rate positively correlated with relative humidity. These findings may explain the dynamics and risks of Clostridioides difficile toxin B, Clostridium perfringens, Campylobacter spp., and Escherichia coli O157:H7 infection. They may help predict interrelationships among climatic factors and standardize national environmental health policies. However, in-depth research with large-scale data, molecular biology, and epidemiology would be required going forward. Future research would also require objective indicators of the changes in the prevalence of FBD-causing microbial pathogens for the effective prevention and management of these bacterial infections.
BACKGROUND: Short-term exposure to PM(2.5) has been widely associated with human morbidity and mortality. However, most up-to-date research was conducted at a daily timescale, neglecting the intra-day variations in both exposure and outcome. As an important fraction in PM(2.5), PM(1) has not been investigated about the very acute effects within a few hours. METHODS: Hourly data for size-specific PMs (i.e., PM(1), PM(2.5), and PM(10)), all-cause emergency department (ED) visits and meteorological factors were collected from Guangzhou, China, 2015-2016. A time-stratified case-crossover design with conditional logistic regression analysis was performed to evaluate the hourly association between size-specific PMs and ED visits, adjusting for hourly mean temperature and relative humidity. Subgroup analyses stratified by age, sex and season were conducted to identify potential effect modifiers. RESULTS: A total of 292,743 cases of ED visits were included. The effects of size-specific PMs exhibited highly similar lag patterns, wherein estimated odds ratio (OR) experienced a slight rise from lag 0-3 to 4-6 h and subsequently attenuated to null along with the extension of lag periods. In comparison with PM(2.5) and PM(10), PM(1) induced slightly larger effects on ED visits. At lag 0-3 h, for instance, ED visits increased by 1.49% (95% confidence interval: 1.18-1.79%), 1.39% (1.12-1.66%) and 1.18% (0.97-1.40%) associated with a 10-?g/m(3) rise, respectively, in PM(1), PM(2.5) and PM(10). We have detected a significant effect modification by season, with larger PM(1)-associated OR during the cold months (1.017, 1.013 to 1.021) compared with the warm months (1.010, 1.005 to 1.015). CONCLUSIONS: Our study provided brand-new evidence regarding the adverse impact of PM(1) exposure on human health within several hours. PM-associated effects were significantly more potent during the cold months. These findings may aid health policy-makers in establishing hourly air quality standards and optimizing the allocation of emergency medical resources.
Urban heat island (UHI) and cool island (UCI) effects are well-known and prevalent in cities worldwide. An increasing trend of extreme heat events has been observed over the last few decades and is expected to continue in the foreseeable future. In this study, warm periods (May to September) of 2000-2018 were examined to acquire a comprehensive understanding of the UHI and UCI characteristics for the case study of Hong Kong, China. Twenty-two weather stations in Hong Kong were classified into four categories, namely urban, urban oasis, suburban, and rural, with reference to the local climate zone (LCZ) scheme, to analyze UHI and UCI phenomena during extreme heat and non-extreme heat situations. One representative type of extreme heat events was considered in this study: three consecutive hot nights with two very hot days in between (2D3N). Results show that both the UHI and UCI effects are exacerbated during extreme heat events. Using the concept of the UHI degree hours (UHIdh) and UCI degree hours (UCIdh), their spatial patterns in Hong Kong during extreme heat and non-extreme heat situations were mapped based on multiple linear regression models. It is found that the predictor variable – windward/leeward index is a significant influential factor of both UHIdh and UCIdh during extreme heat events. The resulting UHIdh and UCIdh maps not only enhance our understanding on the spatial pattern and characteristics of the UHI and UCI during extreme heat events, but could also serve as a useful reference in climate change adaptation, heat-health risk detection, cooling-energy estimation and policy making.
BACKGROUND: Dengue is linked with climate change in tropical and sub-tropical countries including the Lao People’s Democratic Republic (Laos) and Thailand. Knowledge about these issues and preventive measures can affect the incidence and outbreak risk of dengue. Therefore, the present study was conducted to determine the knowledge, attitudes, and practices (KAP) among urban and rural communities and government officials about climate change and dengue in Laos and Thailand. METHODS: A cross-sectional KAP survey about climate change and dengue were conducted in 360 households in Laos (180 urban and 180 rural), 359 households in Thailand (179 urban and 180 rural), and 20 government officials (10 in each country) using structured questionnaires. Data analysis was undertaken using descriptive methods, principal component analysis (PCA), Chi-square test or Fisher’s exact test (as appropriate), and logistic regression. RESULTS: Significant differences among the selected communities in both countries were found in terms of household participant’s age, level of education, socioeconomic status, attitude level of climate change and KAP level of dengue (P < 0.05; 95% CI). Overall, participants’ KAP about climate change and dengue were low except the attitude level for dengue in both countries. The level of awareness among government officials regarding the climatic relationship with dengue was also low. In Lao households, participants’ knowledge about climate change and dengue was significantly associated with the level of education and socioeconomic status (SES) (P < 0.01). Their attitudes towards climate change and dengue were associated with educational level and internet use (P < 0.05). Householders’ climate change related practices were associated with SES (P < 0.01) and dengue related practices were associated with educational level, SES, previous dengue experience and internet use (P < 0.01). In Thailand, participants’ knowledge about climate change was associated with the level of education and SES (P < 0.01). Their attitudes towards climate change were associated with residence status (urban/rural) and internet use (P < 0.05); climate change related practices were associated with educational level and SES (P < 0.05). Dengue related knowledge of participants was associated with SES and previous dengue experience (P < 0.05); participants’ dengue related attitudes and practices were associated with educational level (P < 0.01). CONCLUSION: The findings call for urgently needed integrated awareness programs to increase KAP levels regarding climate change adaptation, mitigation and dengue prevention to improve the health and welfare of people in these two countries, and similar dengue-endemic countries.
Increasing resilience to natural hazards and climate change is critical for achieving many Sustainable Development Goals (SDGs). In recent decades, China has experienced rapid economic development and became the second-largest economy in the world. This rapid economic expansion has led to large-scale changes in terrestrial (e.g., land use and land cover changes), aquatic (e.g., construction of reservoirs and artificial wetlands) and marine (e.g., land reclamation) environments across the country. Together with climate change, these changes may significantly influence flood risk and, in turn, compromise SDG achievements. The Luanhe River Basin (LRB) is one of the most afforested basins in North China and has undergone significant urbanisation and land use change since the 1950s. However, basin-wide flood risk assessment under different development scenarios has not been considered, although this is critically important to inform policy-making to manage the synergies and trade-offs between the SDGs and support long-term sustainable development. Using mainly open data, this paper introduces a new framework for systematically assessing flood risk under different social and economic development scenarios. A series of model simulations are performed to investigate the flood risk under different land use change scenarios projected to 2030 to reflect different development strategies. The results are systematically analysed and compared with the baseline simulation based on the current land use and climate conditions. Further investigations are also provided to consider the impact of climate change and the construction of dams and reservoirs. The results potentially provide important guidance to inform future development strategies to maximise the synergies and minimise the trade-offs between various SDGs in LRB.
Medical statistics collected by WHO indicates that dengue fever is still ravaging developing regions with climates befitting mosquito breeding amidst moderate-to-weak health systems. This work initiates a study over 2009-2017 panel data of dengue incidences and meteorological factors in Jakarta, Indonesia to bear particular understanding. Using a panel random-effect model joined by the pooled estimator, we show positively significant relationships between the incidence level and meteorological factors. We ideate a clustering strategy to decompose the meteorological datasets into several more datasets such that more explanatory variables are present and the zero-inflated problem from the incidence data can be handled properly. The resulting new model gives good agreement with the incidence data accompanied by a high coefficient of determination and normal zero-mean error in the prediction window. A risk measure is characterized from a one-step vector autoregression model relying solely on the incidence data and a threshold incidence level separating the low-risk and high-risk regime. Its magnitude greater than unity and the weak stochastic convergence to the endemic equilibrium mark a persistent cyclicality of the disease in all the five districts in Jakarta. Moreover, all districts are shown to co-vary profoundly positively in terms of epidemics occurrence, both generally and timely. We also show that the peak of incidences propagates almost periodically every year on the districts with the most to the least recurrence: Central, South, West, East, and North Jakarta.
Many studies have linked temperature with respiratory deaths, but epidemiological evidence of temperature-attributable years of life lost (YLL) from respiratory diseases is limited. Daily respiratory YLL rates were calculated using mortality data from 364 locations of China during 2006-2017, and meteorological data were collected for the same period. First, the distributed lag non-linear model (DLNM) was applied to estimate specific temperature-respiratory YLL rate associations in each location. Then multivariable meta-analysis was conducted to pool the location-specific estimates. Finally, we calculated the average life loss per death (LLD) to quantify the respiratory mortality burden of non-optimal temperature. Subgroup analyses were conducted by gender, age, region and cause of death. Inversely J-shaped association was observed between non-optimal temperature and respiratory YLL rate in China. The minimum YLL-rate temperature was 26.9 degrees C nationwide. An average of 1.37 years (95% CI: 1.06-1.65) LLD was attributable to non-optimal temperatures with 2.06 years (95% CI: 1.57-2.60) for pneumonia, 2.03 years (95% CI: 1.76-2.31) for chronic lower respiratory infections (LRTI), 0.88 years (95% CI: 0.65-1.09) for chronic obstructive pulmonary disease (COPD), most of which was attributed to moderate cold (0.73 years, 95% CI: 0.65-0.80). LLD caused by non-optimal temperature was higher in males, the young, and north China. Exposure to non-optimal temperature increases respiratory YLL rate in China, most of which were attributed to moderate cold. People with respiratory diseases including pneumonia, chronic LRTI and COPD are vulnerable to non-optimal temperature exposure. The result of this study provides useful information to reduce temperature-related respiratory disease burden.
Many deltas worldwide have increasingly faced extreme drought and salinity intrusion, which have adversely affected millions of coastal inhabitants in terms of lives and property. The Vietnamese Mekong Delta (VMD) is considered one of the world?s most vulnerable regions to drought and saline water intrusion, especially in the context of climate change. This study aims to assess livelihood vulnerability and adaptation of the coastal people of the VMD under the impacts of drought and saltwater intrusion. A multi-disciplinary approach was applied, including desktop literature reviews, field surveys, interviews, and focus group discussions with 120 farmers and 30 local officials in two representative hamlets of Soc Trang, a coastal province of the VMD. A vulnerability assessment tool in combination with a sustainable livelihood framework was used to evaluate livelihood vulnerability using the five capital resources to indicate the largest effects of drought and salinity intrusion on the migration of local young people to large cities for adaptation. Livelihood Vulnerability Indexes revealed higher vulnerability in terms of the five capitals of coastal communities living in Nam Chanh hamlet compared to Soc Leo. Results of interviews with officials indicated an optimized mechanism between social organizations and local communities before, at the time, and after being impacted by the drought and salinity intrusion. Our findings contribute evidence-based knowledge to decision-makers to enable coastal communities in the VMD and other deltas worldwide to effectively adapt to the impacts of drought and salinity intrusion.
Livelihoods of ethnic minority populations living in the mountains of Northern Vietnam are highly vulnerable to climate-induced natural hazards. Therefore, the livelihoods of vulnerable ethnic minority populations in these areas could be improved through climate change adaptation measures. This study pursues an enhancement of three different aggregate indices such as Livelihood Vulnerability Index (LVI), Livelihood Vulnerability Index framed within the IPCC vulnerability framework (LVI-IPCC), and Livelihood Effect Index (LEI) to find out components contributing to the livelihood vulnerability of major ethnic minority populations in a case study of Mo Vang mountain (Yen Bai, Vietnam). A total of 120 Dzao and Hmong respondents from 11 villages are surveyed based on a combination of informal interviews, a questionnaire survey, and Focused Group Discussions (FGD). Twenty-nine sub-components belonging to 10 major components (socio-demographic profile, livelihood strategies, social networks, revenue, health, food, water, housing, land, and natural hazards and climate variability) are conducted to calculate LVI, LVI-IPCC, and LEI. The results show that the livelihood of Hmong populations is more vulnerable to climate change for natural conditions such as natural hazards and climate variability, housing, land, water, food, and health. However, the livelihood of Dzao populations is more vulnerable because of socio-economic conditions such as socio-demographic profile, livelihood strategies, revenue, and social networks. The results provide a scientific basis for both residents, local officials, and policy-makers prioritizing solutions to enhance livelihood capitals as well as to improve adaptive capacity to climate change in the mountains of Northern Vietnam.
BACKGROUND/PURPOSE: Typhoon Morakot in August 2009 caused significant damages and health and socio-economic impacts in Taiwan. Therefore, we evaluated the mental health status of adult and patients who lived in the affected area after the disaster. METHODS: An observational, prospective population-based study was conducted. Adults living in the affected area were selected as the affected population in the National Health Insurance Database from January 2008 to December 2011. Prevalence and incidence of stress-associated illnesses, such as insomnia, anxiety, depressive, adjustment and mood disorders, post-traumatic stress disorder (PTSD) in the psychiatry department were analysed after the disaster. RESULTS: A total of 897,689 adult patients were studied. Of the affected population without pre-existing chronic mental health illness, the monthly visits for stress-associated illnesses, such as insomnia, anxiety, depressive disorders and PTSD increased about twice after the disaster in elderly and non-elderly groups. Comparing to the non-elderly group, the elderly group has more increased in the incidence of insomnia (356% vs. 318% increase) and depressive disorders (308% vs. 245%) but was affected to a lesser extent increase in the anxiety (269% vs. 307%), PTSD, episodic mood disorders (82% vs. 158%), and adjustment reaction (160% vs. 202%). CONCLUSION: The mental health statuses of patients who experienced a major natural disaster deteriorated in the elderly population after the disaster. However, we still need pay more attentions on the elderly of the affected population to decrease the risk for insomnia and depressive disorders after the disaster.
Health risks from climate change are increasing and becoming a critical global concern. Implementation of health adaptation policies is vital, particularly in settings with high socioeconomic vulnerability and physical exposure to climate-risks, such as the Philippines. We identified from the literature a set of reference principles and categories of barriers to the implementation of national health adaptation policy. These were then used to assess the extent to which these policy principles and barriers are evident in Philippine national health adaptation. This assessment was undertaken based on data and information from policy analysis, key informant interviews, and an expert workshop. The results suggest that the Philippines have made notable progress on health adaptation by establishing a strong policy framework. However, implementation remains challenging and requires continued commitment. The health adaptation policy principles identified in the Philippines are policy congruence, mainstreaming, multi-sectoral approach, multiscale approach, adaptive management, and evidence-based decision-making. The most important implementation barriers are uncertain leadership, appropriateness and longevity of the governance structures within the Department of Health, and data and evidence. The value of considering policy principles alongside implementation barriers is twofold. First, this enables understanding of how implementation barriers relate directly to policy principles. Second, it facilitates identification of future implementation barriers that may arise in relation to current policy principles. Multi-sectoral governance and the integration of evidence in decision-making arose as potential future challenges in the Philippines. These areas may require special consideration in future policy design and planning.
From 21 to 22 July 2012, Beijing and its surrounding areas suffered from an extreme precipitation event that was unprecedented relative to the past 61 years, and the event caused 79 deaths and reported direct economic losses of 11.64 billion Yuan. However, current models have difficulty to simulate the spatial and temporal distribution characteristics of such events. Therefore, improved simulations of these extreme precipitation processes are needed. In this study, nudging methods, including grid nudging (GN) and spectral nudging (SN), and more accurate surface type data retrieved from remote sensing were used in the Weather Research and Forecasting (WRF) model to simulate this extreme precipitation case. When the default city underlay surface of the WRF model was replaced by a more accurate urban surface (NU), the precipitation intensity could be better simulated, but the peak moment of precipitation seriously lagged. Although the peak precipitation intensity simulated by the GN experiment was weak, the simulated precipitation time was basically consistent with the observations. Using GN in only the outside domain could better simulate precipitation peaks, while using GN in both the inside and outside domains could better simulate the spatial distribution characteristics of precipitation. Additionally, the precipitation from GN could be better simulated than that from SN. Overall, the two nudging methods could contribute to better simulations of this case because the nudging methods could improve the simulations of 500-hPa geopotential height, 850-hPa water vapor transport, and low-level weather systems, which are the key factors in adjusting the spatial and temporal distributions of precipitation. This study is the basis for the investigation of the mechanism and attribution of extreme precipitation processes, and the results are of great significance for promoting understanding of and mitigating disasters caused by extreme precipitation.
Urban resilience is a major indicator of a city’s sustainability. Climate change increases the frequency and intensity of extreme weather events, thereby increasing uncertainty and disaster risk. A city’s capacity to cope with climatic risks can be improved by developing resilience. In China, heavy rainfall is the most frequent and costly extreme weather event. We conducted a comparative case study on Beijing’s extraordinary 7.21 rainstorm disaster in 2012 and the 7.20 rainstorm in 2016. Taken generic resilience and specific resilience as the analytical framework, we found that generic resilience is mainly determined by the socio-economic development level and geography of each district; while the combination of engineering and non-engineering adaptive measures after 2012 disaster has improved the specific resilience to rainstorm disaster, which contributed a good performance in the 2016 rainstorm. As a megacity in China, Beijing is a representative case that provides guidance for other cities to improve their urban resilience to rainstorm disasters.
Hydro-meteorological risks are a growing issue for societies, economies and environments around the world. An effective, sustainable response to such risks and their future uncertainty requires a paradigm shift in our research and practical efforts. In this respect, Nature-Based Solutions (NBSs) offer the potential to achieve a more effective and flexible response to hydro-meteorological risks while also enhancing human well-being and biodiversity. The present paper describes a new methodology that incorporates stakeholders’ preferences into a multi-criteria analysis framework, as part of a tool for selecting risk mitigation measures. The methodology has been applied to Tamnava river basin in Serbia and Nangang river basin in Taiwan within the EC-funded RECONECT project. The results highlight the importance of involving stakeholders in the early stages of projects in order to achieve successful implementation of NBSs. The methodology can assist decision-makers in formulating desirable benefits and co-benefits and can enable a systematic and transparent NBSs planning process.
Most studies focused on the temporal trend of mortality risk associated with temperature exposure. The relative role of heat, cold, and temperature variation (TV) on morbidity and its temporal trends are explored insufficiently. This study aims to investigate the temporal trends of emergency ambulance dispatch (EAD) risk and the attributable burden of heat, cold, and hourly temperature variation (HTV). We collected time-series data of daily EAD and ambient temperature in Shenzhen from 2010 to 2017. HTV was calculated as the standard deviation of the hourly temperatures between 2 consecutive days. Quasi-Poisson generalized additive models (GAM) with a time-varying distributed lag nonlinear model (DLNM) were applied to examine temporal trends of the HTV-, heat-, and cold-EAD association. The temporal variation of the attributable fraction (AF%) and attributable number (AN) for different temperature exposures was also calculated. The largest RR was observed in extreme cold [1.30 (95% CI: 1.18, 1.43)] and moderate cold [1.25 (95% CI: 1.17, 1.34)]. Significant increasing trends in HTV-related effects and burden were observed, especially for the extreme HTV effects (P for interaction < 0.05). Decreasing trends were observed in the heat-related effect and burden, though it showed no significance (P for interaction = 0.46). There was no clear change pattern of cold-related effects and burdens. Overall, the three temperature exposure caused 13.7% of EAD, of which 4.1%, 4.3%, and 5.3% were attributed to HTV, heat, and cold, respectively. All the temperature indexes in this study, especially the cold effect, are responsible for the increased risk of EAD. People have become more susceptible to HTV over the recent decade. However, there is no clear evidence to support the temporal change of the population's susceptibility to heat and cold. Thus, in addition to heat and cold, the emergency ambulance service department should pay more attention to HTV under climate change.
With the increasing awareness of the risks and impacts of climate change, scholars tend to pay more attention to the applications of indicators, which access the effectiveness of climate change adaptation. This study aims to evaluate the overall progress of climate change adaptation in China during 2010-2018 in a quantitative manner. The Index for Climate Change Adaptation in China (ICCAC) has been thus developed by adopting the analytic hierarchy process weighting and expert scoring method. Namely, ICCAC is composed of national climate change impacts, adaptation actions in key sectors, adaptation progress in key sectors, and the national adaptation policy framework. Overall, the ICCAC and its four sub-indexes increased significantly from 2010 to 2018, on a yearly-basis. Each sub-index implied that the socio-economic impacts caused by climate change in China have been alleviated gradually; specifically, the mainstream endeavor of key sectors has witnessed remarkable progress, however, it is worth noting that the gap between individual adaptation actions and policies still exists; the implementation effect of policies in key sectors is not as affluent as that of actions; the current adaptation endeavor in key areas is still closely related to the mainstream business of corresponding competent ministries rather than adaptation-aimed actions; the national adaptation policy framework has been primarily formed, but there are still some deficiencies. As a result, the gap in China’s adaptation process could be mainly manifested in the following five aspects: i) adaptation effectiveness assessment in forestry and urban infrastructure is urgently needed; ii) policies in marine and water resources sectors need structural reforms; iii) evaluation criteria for national adaptation are not necessarily sufficient; iv) the improvement of adaptive management efficiency has stagnated recently; and v) the adaptation works of relevant Ministries should be coordinated and put forward the corresponding strategies. Finally, this study presents four proposals: conducting an evaluation of adaptation actions in all key sectors, integrating climate change impacts into sectoral planning decisions, launching concrete action plans for adaptation, establishing a complete policy framework on adaptation.
Particulate matter (PM) has been occurring regularly during the dry season in the upper north of Thailand including Lamphun Province that might be influenced by various factors including climatologic and other pollutants. This paper aims to investigate the climatologic and gaseous factors influencing the occurrence of PM(10) concentration using Pollution Control Department (PCD) data. The secondary data of 2009 to 2017 obtained from the PCD was used for analysis. We used descriptive statistics, Pearson’s correlation coefficient, multiple regression and graphic presentation using R program (R packages of ‘open air’ and ‘ncdf4’) and Microsoft Excel Spreadsheet®. In addition, the periodic measurement of PM(2.5) and PM(10) were investigated to determine the ratio of PM(2.5)/PM(10). The results indicated that haze episodes (daily PM(10) concentration always over the PCD standard) normally occur during the dry season from February to April. The maximum concentration was always found in March. The PM(10) concentration was negatively associated with relative humidity and temperature while the PM(10) concentration showed a strongly positive association with CO and NO(2) concentration with correlation values of 0.70 and 0.57, respectively. Furthermore, we found CO and PM(10) concentration was associated with ozone concentration. This finding will benefit local communities and the public health sector to provide a warning system for preparation and response plans to react to PM(10) episodes in their responsible areas.
Achieving environmental sustainability by improving the urban microclimate is a key principle in mitigating the urban heat island (UHI) effect. This study aimed to (a) investigate the outdoor thermal comfort by establishing Heat Index (HI) values to identify thermal hot spots and (b) model green infrastructure possibilities to alleviate UHI in Colombo urban metropolitan in Sri Lanka using ENVImet climate model. Daytime temperature and humidity values of 14 urban locations were collected to determine HI to recognize thermal urban hotspots in Colombo area. A pretested comprehensive random-stratified questionnaire survey has been conducted to appraise the thermal discernment of the general public. ENVImet microclimate model was accompanied to test the temperature reduction levels in different bioclimatic green infrastructure scenarios [Two belts (R-1), three belts (R-2), four belts (R-3), five belts (R-4)] in the selected study site. Five sites (Borella, Colombo Fort, Maradana, Wellawaththa, Liberty junction) were identified as thermal hotspots in Colombo metropolitan. HI values were fluctuated within 33.82-40.35 degrees C range and the highest average day time HI value was observed at Maradana (40.35 degrees C) and the lowest HI was observed at Thummulla (33.82 degrees C). Survey results revealed that 89.3% people are affected with thermal uncomfortability and 5% were affected with heat-related skin diseases. Inserting trees into curbsides (R-4) reduced temperature remarkably by 2.07 degrees C in the urban metropolitan. Therefore, the proposed green infrastructure scenario has proved to be the most suitable way to improve the thermal comfort conditions of urban environment, as it can reduce the UHI effects.
Over recent decades, substantial funding from a variety of sources has been directed towards climate change adaptation projects in Pacific Island countries. There remains, however, considerable uncertainty about which factors influence adaptation project completion, as a pre-cursor to effective adaptation. In this study, we empirically establish the links between project attributes (duration, funding, cash co-financing, in-kind contributions, location, and adaptation approach) and whether a project is likely to complete or be terminated. We examine this issue by developing a logistic regression model to predict the probability of completion for small-scale climate change adaptation projects using a new dataset of 190 projects in the South Pacific (with end dates ranging from November 1995 to May 2016) that were financed through the Global Environment Facility Small Grants Programme. Empirical results suggest that all else equal, such a project was more likely to complete if it was shorter, received more co-financing cash input and in-kind support from other donors and project partners, was explicitly targeted towards climate change adaptation, focused on a single adaptation approach, and was undertaken in Micronesia or Fiji. Our results can be used to help funders and project proponents design projects to mitigate the risks of non-completion, particularly in high-risk settings. These findings should not be misinterpreted to undermine the importance of continued investment in adaptation projects across the whole of South Pacific region.
In the context of global climate change, research efforts were focused on the association of ambient temperatures on maternal and neonatal health condition, but few have examined associations with low Apgar scores. From January 1, 2017, to December 31, 2018, all singleton deliveries of Ningxia Hui Autonomous Region were extracted from the Hospital Information System (N = 182,322). Daily temperature data were obtained from the official website of China Meteorological Administration. Low Apgar scores were defined as Apgar score ? 3 at 5 min in the present study. Logistic regression models were used to estimate the adjusted association between prenatal temperature exposure and low Apgar scores. Restricted cubic spline models were used to explore the dose-response relationship between temperature and low Apgar scores. The study population included 182,322 live singleton births, with 1575 (0.86%) cases of low Apgar scores. The elevated ambient temperature in different exposure timing windows in late pregnancy was associated with increased risk of low Apgar scores. As compared to moderate (10th-90th) temperature exposure, prenatal exposure to extreme hot (>90th) was associated with 13.9-47.0% increased risk of low Apgar scores, while non-significant relationship was found between extreme cold (<10th) exposure and low Apgar scores. The restricted cubic spline models showed a U-shaped relationship between prenatal temperature exposure and low Apgar scores (P for non-linearity < 0.05). Exposure to high ambient temperature during late pregnancy is associated with an increased risk of low Apgar scores in northwest China.
Cardiovascular disease (CVD) has been a major threat to global public health. The association between temperature and CVD has been widely studied and reported in cities in developed countries. However, information from developing countries, especially from suburbs and countryside, is quite limited. In this study, the daily time series data on CVD hospital admissions in farmers in the suburbs of Tianshui, China, and the meteorological data from 2012 to 2015, were collected; besides, a quasi-Poisson regression with a distributed-lag non-linear model (DLNM) was used to explore the impact of local daily mean temperature on CVD hospital admissions in suburban farmers. This study found that, first, from 2011 to 2015, a total of 30,611 person-times of CVD hospital admissions in farmers were recorded; second, there was a “J-shaped” relation between temperature and CVD hospital admissions, and both low and high temperature increased the risk of hospital admission, but the impact of high temperature was greater; third, compared with the minimum hospitalization temperature (MHT) at 0.3 °C, during 0 to 21 lag days, the cumulative relative risk (RR) for extreme cold and heat (1st and 99th percentile of temperature, respectively) was 1.117 (95% CI 0.941-1.325) and 1.740 (95% CI 1.302-2.327), respectively, and that of moderate cold and heat (5st and 95th percentile of temperature, respectively) was 1.029 (95% CI 0.958-1.106) and 1.572 (95% CI 1.210-2.042), respectively; fourth, compared with male and ? 65 years groups, the risk for low temperature was greater for female and < 65 years groups, the risk for high temperature was just the opposite; last, about 21.04% of CVD hospital admissions burden were attributed to the ambient temperature, and most of (about 19.26%) were caused by moderate heat. In Tianshui, alongside with extreme temperature, the moderate temperature might be an important risk factor for CVD hospital admissions in suburban farmers.
BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disease that affects 20% of children worldwide. Environmental factors including weather and air pollutants have been shown to be associated with AD symptoms. However, the time-dependent nature of such a relationship has not been adequately investigated. This paper aims to assess whether real-time data on weather and air pollutants can make short-term prediction of AD severity scores. METHODS: Using longitudinal data from a published panel study of 177 paediatric patients followed up daily for 17 months, we developed a statistical machine learning model to predict daily AD severity scores for individual study participants. Exposures consisted of daily meteorological variables and concentrations of air pollutants, and outcomes were daily recordings of scores for six AD signs. We developed a mixed-effect autoregressive ordinal logistic regression model, validated it in a forward-chaining setting and evaluated the effects of the environmental factors on the predictive performance. RESULTS: Our model successfully made daily prediction of the AD severity scores, and the predictive performance was not improved by the addition of measured environmental factors. Potential short-term influence of environmental exposures on daily AD severity scores was outweighed by the underlying persistence of preceding scores. CONCLUSIONS: Our data does not offer enough evidence to support a claim that weather or air pollutants can make short-term prediction of AD signs. Inferences about the magnitude of the effect of environmental factors on AD severity scores require consideration of their time-dependent dynamic nature.
Background: The health impacts of heatwaves are a growing public health concern with the frequency, intensity, and duration of heatwaves increasing with global climate change. However, little is known about the healthcare costs and the attributable morbidity associated with heatwaves Objective This study aims to examine the relationship between heatwaves and costs of emergency department (ED) presentations, and to quantify heat-attributable burden during the warm seasons of 2014-2017, in Adelaide, South Australia. Methods: Daily data on ED presentations and associated costs for the period 2014-2017 were obtained from the South Australian Department of Health and Wellbeing. Heatwave intensity was determined using the excess heat factor (EHF) index, obtained from the Australian Bureau of Meteorology. A distributed lag non-linear model (DLNM) was used to quantify the cumulative risk of heatwave-intensity over a lag of 0-7 days on ED presentations and costs. Effects of heatwaves were estimated relative to no heatwave. The number of ED presentations and costs attributable to heatwaves was calculated separately for two EHF severity categories (low-intensity and severe/extreme heatwaves). Subgroup analyses by disease-diagnosis groups and age categories were performed. Results: For most disease diagnosis and age categories, low-intensity and severe heatwaves were associated with higher rates of ED presentations and costs. We estimated a total of 1161 (95% empirical confidence interval (eCI): 342, 1944) heatwave-attributable all-cause ED presentations and associated healthcare costs (thousands) of AU $1020.3 (95% eCI: 224.9, 1804.7) during the warm seasons of 2014-2017. The heat-related illness was the disease category contributing most to ED presentations and costs. Age groups 0-14 and >= 65 years were most susceptible to heat. Conclusions: Heatwaves produced a statistically significant case-load and cost burden to the ED. Developing tailored interventions for the most vulnerable populations may help reduce the health impacts of heatwaves and to minimise the cost burden to the healthcare system. (C) 2021 Elsevier B.V. All rights reserved.
Tropospheric ozone is known to have adverse effects on human health. Ozone pollution events are often associated with specific atmospheric circulation conditions. Therefore, studying the relationship between atmospheric circulation and ozone is particularly important for early warning and forecasting of ozone pollution events. Focusing on the Yangtze River Delta region, particularly in four important large industrial cities (Xuzhou, Nanjing, Shanghai, and Hangzhou) in the Yangtze River Delta, the T-mode objective classification method was applied to classify the weather circulation that mainly affects the Yangtze River Delta region into nine types. Local wind fields for the four industrial cities were classified according to their propensity for ventilation, stagnation, and recirculation based on the Allwine and Whiteman method. Based on the analysis of large-scale atmospheric circulation, we concluded that certain circulation patterns correspond to excessive ozone concentrations, while other circulation patterns correspond to good air quality. Moreover, ozone pollution was not closely related to local regional transmission. The importance of high temperatures in potentiating ozone pollution was also identified in the study area, whereas the effect of relative humidity was negligible. Finally, the importance of the different scale atmospheric motions was analyzed by studying two specific ozone pollution events in Xuzhou area (March, 2019) and Nanjing area (July-August, 2017). This analysis was complemented by HYSPLIT model’s outputs to simulate the pollutant diffusion path. Regarding the first episode, ozone concentration is often closely related to the slowly approaching thermal high-pressure system. In the second episode, local transmission had little effect on the generation and spread of ozone pollution. Furthermore, and comparing the circulation conditions with local meteorological factors, it was found that the increase in ozone concentration was often accompanied by higher temperature, and the response to humidity was not clear.
Changes in ambient temperature have been reported as an important risk factor for respiratory diseases among pre-school children. However, there have been few studies so far on the effects of temperature on children respiratory health in developing countries including Vietnam. This study examined the impact of short-term changes in ambient temperature on hospital admissions for acute lower respiratory infection (ALRI) among children aged less than 5 years old in Ho Chi Minh City (HCMC), Vietnam. Data on daily hospital admissions from 2013 to 2017 were collected from two large paediatric hospitals of the city. Daily meteorological data of the same period were also collected. Time series analysis was performed to evaluate the association between risk of hospitalisations and temperatures categorised by seasons, age, and causes. We found that a 1 °C increase in maximum temperature was associated with 4.2 and 3.4% increase in hospital admission for ALRI among children 3-5 years old during the dry season and the rainy season, respectively. Surprisingly, in the rainy season, a rise of 1°C diurnal temperature range (DTR) was significantly associated with a decrease from 2.0 to 2.5% risk of hospitalisation for ALRI among children <3 years old. These findings suggested that although high temperature is a risk factor for hospital admissions among children in general, other modifiable factors such as age, exposure time, air conditioning usage, wearing protective clothing, socioeconomic status, and behaviour may influence the overall effect of high temperature on hospital admissions of children <5 years old in HCMC. The findings of this study have provided evidence for building public health policies aimed at preventing and minimizing the adverse health effects of temperature on children in HCMC.
The health of smallholder farmers is crucial for ensuring food and nutritional security for two billion people. However, their health is in jeopardy for several reasons including challenges from climate change impacts. Using a narrative literature review supported by field observations and informal interviews with key informants in India, Bangladesh and Malawi, this paper identifies and discusses the health impacts of climate change under four categories: (i) communicable diseases, (ii) non-communicable diseases, (iii) mental health, and (iv) occupational health, safety and other health issues. The health impacts of climate change on smallholder farmers will hamper the realization of many of the United Nations’ Sustainable Development Goals, and a series of recommendations are made to regional and country governments to address the increasing health impacts of accelerating climate change among smallholder farmers.
Heat-related illnesses (HRIs), mainly heat exhaustion (HE) and heat stroke (HS), are characterized by an elevation of core body temperature. In this study, we aimed to explore the HRIs’ types and patient characteristics among a sample taken from various representative in-field points in the Hajj season. A cross-sectional study was conducted in 2018 at 80 data collection points distributed in the field. Data related to demographics, features and risk factors were collected and analyzed from all encountered cases with suspected HRIs. Moreover, we developed a diagnostic tree for HRIs by using the XGBoost model. Out of the 1200 persons encountered during the study period, 231 fulfilled the criteria of HRIs spectrum and were included in this study. Around 6% had HS and 20% had HE. All HS cases (100%) were from outside of Saudi Arabia as compared with 72.5% diagnosed with HE (27.5% were from Saudi Arabia). In addition, 16% were considered as heat-induced muscle spasms, and 7% had limb heat edema. Additionally, most of HRIs cases were reported between 11 am and 1 pm. The HRIs diagnostic tree model gave a diagnostic accuracy of 93.6%. This study highlights the magnitude of HRIs among pilgrims in Hajj and provides a diagnostic tree that can aid in the risk stratification and diagnosis of these patients. We advise the implementation of more educational campaigns to pilgrims regarding preventable measures especially for the vulnerable groups (e.g. from outside Saudi Arabia, those with comorbidities and light-skinned people).
Hendra virus (HeV) continues to pose a serious public health concern as spillover events occur sporadically. Terminally ill horses can exhibit a range of clinical signs including frothy nasal discharge, ataxia or forebrain signs. Early signs, if detected, can include depression, inappetence, colic or mild respiratory signs. All unvaccinated ill horses in areas where flying foxes exist, may potentially be infected with HeV, posing a significant risk to the veterinary community. Equivac® HeV vaccine has been fully registered in Australia since 2015 (and under an Australian Pesticides and Veterinary Medicines Authority special permit since 2012) for immunization of horses against HeV and is the most effective and direct solution to prevent disease transmission to horses and protect humans. No HeV vaccinated horse has tested positive for HeV infection. There is no registered vaccine to prevent, or therapeutics to treat, HeV infection in humans. Previous equine HeV outbreaks tended to cluster in winter overlapping with the foaling season (August to December), when veterinarians and horse owners have frequent close contact with horses and their bodily fluids, increasing the chance of zoonotic disease transmission. The most southerly case was detected in 2019 in the Upper Hunter region in New South Wales, which is Australia’s Thoroughbred horse breeding capital. Future spillover events are predicted to move further south and inland in Queensland and New South Wales, aligning with the moving distribution of the main reservoir hosts. Here we (1) review HeV epidemiology and climate change predicted infection dynamics, (2) present a biosecurity protocol for veterinary clinics and hospitals to adopt, and (3) describe diagnostic tests currently available and those under development. Major knowledge and research gaps have been identified, including evaluation of vaccine efficacy in foals to assess current vaccination protocol recommendations.
In this study, 30 subjects were exposed to different combinations of air temperature (T(a) : 24, 27, and 30°C) and CO(2) level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T(a) = 24°C, exposure to 30°C at all CO(2) levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T(a) on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO(2) from 8000 to 12 000 ppm at all T(a) caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T(a) and CO(2) concentration on human responses was identified.
Difficulties in controlling the effects of outdoor thermal environment on the human body are attracting considerable research attention. This study investigated the outdoor thermal comfort of urban pedestrians by assessing their perceptions of the tropical, micrometeorological, and physical conditions via a questionnaire survey. Evaluation of the outdoor thermal comfort involved pedestrians performing various physical activities (sitting, walking, and standing) in outdoor and semi-outdoor spaces where the data collection of air temperature, globe temperature, relative humidity, wind speed, solar radiation, metabolic activity, and clothing insulation data was done simultaneously. A total of 1011 participants were interviewed, and the micrometeorological data were recorded under outdoor and semi-outdoor conditions at two Malaysian university campuses. The neutral temperatures obtained which were 28.1 °C and 30.8 °C were within the biothermal acceptable ranges of 24-34 °C and 26-33 °C of the PET thermal sensation ranges for the outdoor and semi-outdoor conditions, respectively. Additionally, the participants’ thermal sensation and preference votes were highly correlated with the PET and strongly related to air and mean radiant temperatures. The findings demonstrated the influence of individuals’ thermal adaptation on the outdoor thermal comfort levels. This knowledge could be useful in the planning and designing of outdoor environments in hot and humid regions to create better thermal environments.
Under climate change, compound flooding has resulted in severe disasters in coastal areas around the world. In this study, an integrated framework is proposed to determine the range of compound flood risk without the requirement of joint probability analysis between storm surge and rainfall. In the framework, the flood risks are analyzed under four extreme scenarios with/without the compound effect of storm surge and rainfall in the past and the future. From the end of the 20th century to the middle of the 21st century, the worst scenario shows that the flood area significantly increases by 92% for the low-lying coastal areas in southwest Taiwan under the compound effect of storm surge and rainfall if they are fully correlated. In the most optimistic scenario, the flood area slightly increases by 15% without compound effect (only storm surge is considered). To coastal flooding, the synchronization of storm surge and rainfall contributes much more than the climate-induced amplification of individual factors. When storm surge and rainfall happen at the same time, the extent and duration of flooding increase simultaneously under the influence of pluvial and surge-induced flooding. Risk analysis shows an obvious increase of risk level for villages originally at low risks, which require integrated countermeasures against the consequence brought by compound flooding in the future. The framework can be applied in other low-lying coastal areas to quantify the potential impacts on human and environment caused by compound flooding under climate change.
Floods are one of the most devastating natural catastrophes, always associated with massive disruption to humans, land, and the economy. The current research focusses on the identification of Flood Vulnerable Zones (FVZ) of Kanyakumari district with the integration of Remote Sensing (RS) and Geographic Information System (GIS), and the Multi-criteria Decision-Making Analysis (MCDM)-based Analytical Hierarchy Process (AHP) model in the geospatial environment. The weights derived from 10 x 10 decision matrix of AHP model for the flood inducing factors are reflecting their varied priorities from high to low priority as rainfall (0.22), slope (0.124), drainage density (0.154), Land Use Land Cover (LULC) (0.153), Digital Elevation Model (DEM) (0.109), Soil (0.068), geology (0.052), geomorphology (0.048), Surface Runoff (0.042) and Topographic Wetness Index (TWI) (0.03), respectively. Consistency Ratio (CR) value obtained in this case is equal to 0.093 (< 0.1) signifies the acceptance of the derived weights. The more is the weightage given to the parameters, more significance is of the factor towards the occurrence of the flood hazard. The outcomes of the research found that the very high and highly vulnerable zones are spreading over a vast expanse of the district, which are situated in the south, south-east, south-west, and in some pockets of middle and north-east. The use of such a decision-making model-based approach is helpful in the identification and prediction of the susceptible sites, further helps the policymakers in hazard mitigation and decision-making planning.
The South Asian region is predicted to be among the most severely affected by the health impacts of climate change and warrants regional health policy leadership to tackle the same. Model World Health Organization (WHO) simulations offer the academic opportunity to build this leadership. This study describes the conceptualization and conduct of the ‘Manipal Model World Health Organization’ 2018 debate simulation, where a multi-professional group of students at an Indian university deliberated approaches to address the regional health impacts of climate change in South Asia. We contextualized the Model WHO debate model for a multi-professional classroom. Multi-sectoral stakeholders were engaged to draw participants from health and non-health disciplines. Participants were trained in health research literacy, policy politics, bloc politics, writing and public speaking for Model WHO. Mock sessions provided training in navigating parliamentary procedures. The debate event consisted of 22 participants and a four-member panel from diverse academic disciplines who independently assessed the deliberations. All delegations demonstrated competent written and verbal contributions. Content analysis of resolutions reaffirmed international agreements and addressed the Climate Change Health Risk Framework, and objectives of the WHO Secretariat Action Plan. Besides presenting a stratified typology of academic health policy debate simulations in global, regional, and subnational contexts, we also propose a ‘theory of change’, illustrating how academic policy discourse platforms can nurture critical thinking, research/policy literacy and leadership skills. Such initiatives help build the health policy leadership required for addressing global health challenges such as climate change.
Longevity research is a hot topic in the health field. Considerable research focuses on longevity phenomenon in Bama Yao Autonomous County, which has a typical karst landform and is located in Southwest China. This study aims to illustrate the spatial feature of longevity indicators in other Yao areas, to analyze the correlation between climatic factors and longevity indicators, and to provide new clues and targets for further longevity studies. We collect and integrate population, climate, and terrain data into a spatial database. The main analysis methods include spatial autocorrelation, high/low clustering, and multiscale geographically weighted regression (MGWR). Two longevity clusters are identified in Guijiang River Basin (longevity index (LI%): 2.49?±?0.63) and Liujiang River Basin (LI%: 2.13?±?0.60). The spatial distribution of longevity indicators is autocorrelative (Moran’s I?=?0.652, p?
INTRODUCTION/AIMS: Exertional rhabdomyolysis (ER) often occurs during prolonged intense exercise in hot environments, posing a threat to the health of military personnel. In this study we aimed to investigate possible risk factors for ER and provide further empirical data for prevention and clinical treatment strategies. METHODS: A retrospective investigation of 116 concurrent ER cases was conducted. Conditional logistic regression analyses were performed to assess the association between each potential risk (or protective) factor and ER. The clinical characteristics of the 71 hospitalized patients were analyzed descriptively. RESULTS: After screening, the following variables significantly increased the risk of ER: shorter length of service (recruits; odds ratios [OR], 7.49; 95% confidence interval [CI], 2.58-21.75); higher body mass index (BMI; OR, 1.14, 95% CI, 1.03-1.26); lack of physical exercise in the last half year (less than once per month; OR, 3.20; 95% CI, 1.08-9.44); and previous heat injury (OR, 2.94; 95% CI, 1.26-6.89). Frequent fruit consumption (OR, 0.57; 95% CI, 0.33-0.99), active hydration habit (OR, 0.37; 95% CI, 0.20-0.67), water replenishment of more than 2 L on the training day (OR, 0.15; 95% CI, 0.05-0.45), and water replenishment of at least 500?mL within 1 hour before training (OR, 0.33; 95% CI, 0.12-0.88) significantly decreased the risk of ER. Of the 71 hospitalized patients, 41 (57.7%) were diagnosed with hypokalemia on admission. DISCUSSION: In military training, emphasis should be placed on incremental adaptation training before more intense training, and close attention should be given to overweight and previously sedentary recruits. Fluid replenishment before exercise, increased fruit intake, and proper potassium supplementation may help prevent ER.
Scholars argue that personal experience with climate change related impacts can increase public engagement, with mixed empirical evidence. Previous studies have almost exclusively focussed on individuals’ experience with extreme weather events, even as scientific research on health impacts of climate change is burgeoning. This article extends previous research in the domain of public perceptions about climate-related public health impacts. Results from a nationally representative sample survey in New Zealand indicates that subjective attribution of infectious disease outbreaks to climate change and to human impact on the environment is positively associated with mitigation behavioural intentions and climate-focussed COVID-19 economic recovery policies. In contrast, knowledge about COVID-19 and self-reported economic impact due to COVID-19 is not associated with policy support. Moreover, significant interaction between political affiliation and subjective attribution to climate change on policy support indicate that learning about the links between health and climate change will particularly help increase mitigation engagement among right-leaning individuals. Subjective attribution may be the key to help translate personal experience to personal engagement.
ISSUE ADDRESSED: Health promotion has adopted the planetary health perspective to address the threats posed by climate change, environmental degradation and environmental deprivation. Nature is a setting for health promotion that can produce co-benefits for human health and the protection of the environment. This paper presents the findings of a New South Wales (NSW) study of peoples’ motivations for, and co-benefits of, environmental volunteering. METHODS: This paper combines the findings of a literature review and qualitative data from a larger mixed-methods study of environmental volunteering (eg administration and co-ordination, bush regeneration, advocacy, tour guiding) in NSW. A review of international literature from 2005 yielded 100 documents for analysis. Maximum variation and stratified purposeful sampling strategies were applied to engage 12 environmental volunteers and 30 employees of environmental organisations in a series of focus groups (n = 2) and interviews (n = 22). Qualitative thematic analysis techniques were applied and data triangulated. RESULTS: Motivations for environmental volunteering include the following: personal, for example, new skills or knowledge, environmental, for example, improve the environment and social/community, for example, forming connections. Environmental volunteering offers a range of benefits for individuals, environmental organisations and the natural environment. These include enhanced mental and social health, and connection to place and learning about the environment. CONCLUSIONS: Environmental volunteering has the potential to address key determinants of health – social inclusion, employment and education. From a planetary health perspective, there are multiple co-benefits of human-environmental interaction arising from environmental volunteering. Environmental volunteering is a planetary health strategy that could be incorporated into community-based health promotion. SO WHAT?: Health promotion has a mandate to act on ecological determinants of health. Environmental volunteering is an untapped resource for community-based health promotion and for achieving planetary health goals.
Introduction: As the global climate is undergoing significant changes, the incidence of natural disasters of various characters and intensity is on the rise. Many direct and indirect mental health impacts have been observed as an aftermath of these disasters. The study attempts to assess the psychiatric symptoms prevalent among disaster-affected individuals, 4-6 months after the impact. Methods: A community based cross-sectional survey was conducted 4-6 months after a flood in Kodagu (Coorg) district of Karnataka state. 171 randomly selected samples were assessed. Demographic details and disaster experiences were collected and symptoms psychiatric disorders were evaluated. The data were entered into Microsoft Excel and analyzed using SPSS version 23 software. The descriptive data were presented in percentages and bar charts appropriately. Categorical data were presented in tables tests for significance were done appropriately. Results: The prevalence of psychiatric symptoms among residents of flood-affected areas was 66.7%. The major symptoms detected were that of Depression, Anxiety, Somatic disorders, Sleep problems and Substance abuse. Leaving the house during the disaster and damage to the house were found as the most important factors influencing the development of these symptoms. Conclusion: The Prevalence of psychiatric symptoms in the district, was high and hence more community-based activities should be designed by the health department to address this problem. The symptoms were significantly higher among people who stayed in flood relief camps and faced partial or complete damage to their house. These people should be identified to prevent further development of illness.
INTRODUCTION: Patients with primary Sjögren’s syndrome (pSS) reportedly believe that their symptoms worsen on extreme weather days due to variations in environmental conditions. However, few studies have assessed the acute effects of environmental exposure on the onset of pSS. This study aimed to evaluate the exposure-response relationship between extreme environmental conditions and pSS outpatient visits. METHOD: We obtained data on pSS outpatient visits from two provincial general hospitals in Hefei, China, during 2014-2019. A distributed lag non-linear model was used to estimate the exposure-lag-response relationship between environmental variables and pSS. RESULTS: We detected significant and non-linear associations between extreme environments and pSS. The estimated relative risk (RR) for a lag of 3 days was 1.11 (95% CI: 1.03 to 1.19) for extreme cold and for a lag of 21 days was 1.07 (95% CI: 1.01 to 1.12) for extreme dampness. Long sunshine duration was positively correlated with pSS (lag 11, 1.05, 95% CI: 1.01 to 1.08). Moreover, female patients were more susceptible to these effects. Patients older than 65 years old were more vulnerable to frigid environments (lag 3, RR?=?1.30, 95% CI: 1.09 to 1.54), while younger patients were more vulnerable to extreme dampness (lag 21, RR?=?1.10, 95% CI: 1.03 to 1.16). Extreme cold and high humidity were negatively correlated with the same-day outpatient visits. CONCLUSIONS: Our findings suggest a potential relationship between exposure to extreme environmental conditions and increased risk of pSS outpatient visits. We therefore suggest that policymakers and doctors aim to further our understanding of environmental effects on pSS and adopt adequate measures to alleviate pSS symptoms. Key Points • Extreme cold, extreme dampness, and long sunshine duration increased the risk of pSS outpatient visits, especially for females. • Young pSS patients are more susceptible to a rise in humidity. • Elderly pSS patients are more sensitive to extreme cold weather.
The effects of meteorological factors on health outcomes have gained popularity due to climate change, resulting in a general rise in temperature and abnormal climatic extremes. Instead of the conventional cross-sectional analysis that focuses on the association between a predictor and the single dependent variable, the distributed lag non-linear model (DLNM) has been widely adopted to examine the effect of multiple lag environmental factors health outcome. We propose several novel strategies to model mortality with the effects of distributed lag temperature measures and the delayed effect of mortality. Several attempts are derived by various statistical concepts, such as summation, autoregressive, principal component analysis, baseline adjustment, and modeling the offset in the DLNM. Five strategies are evaluated by simulation studies based on permutation techniques. The longitudinal climate and daily mortality data in Taipei, Taiwan, from 2012 to 2016 were implemented to generate the null distribution. According to simulation results, only one strategy, named MV(DLNM), could yield valid type I errors, while the other four strategies demonstrated much more inflated type I errors. With a real-life application, the MV(DLNM) that incorporates both the current and lag mortalities revealed a more significant association than the conventional model that only fits the current mortality. The results suggest that, in public health or environmental research, not only the exposure may post a delayed effect but also the outcome of interest could provide the lag association signals. The joint modeling of the lag exposure and the delayed outcome enhances the power to discover such a complex association structure. The new approach MV(DLNM) models lag outcomes within 10 days and lag exposures up to 1 month and provide valid results.
Extreme fine particulate matter (PM2.5) events heavily impact residents, incurring high social and medical costs. As such, it is important to understand the characteristics of extreme PM2.5 events. This study used hourly PM2.5 and meteorological data to elucidate the effects, and predict the occurrence of these extreme weather events in Taiwan. The results show that synoptic conditions are unique for extreme PM2.5 events. During the maximum mean PM2.5 concentrations, weather conditions in Taiwan were dominated by synoptic weather patterns and the north-easterly monsoon. The maximum mean surface air pressure indicator had also occurred at this time. The azimuth of the resultant surface air pressure was 36.8 degrees + 7.6 degrees, while 96.2% of winds were in the north-north-easterly and north-easterly direction. The back trajectories suggest that the cold continental high air pressure system introduced dry and cold air masses with PM2.5. The SImax (mu g/m(3)/h)(,) relative humidity (%), global solar radiation (MJ/m(2)), visibility (km), weather type I, and weather type II predictor variables of the multi-regression model accounted for 80.6% of the variance in the magnitude of maximum hourly PM2.5 events. Extreme PM2.5 events were related to synoptic weather characteristics including type, strength, and position. The new quantitative variables aid the development of an efficient alarm system for extreme PM2.5 events that will help protect public health.
BACKGROUND: Many people die from cardiovascular diseases each year, and extreme temperatures are regarded as a risk factor for cardiovascular deaths. However, the relationship between temperature and cardiovascular deaths varies in different regions because of population density, demographic inequality, and economic situation, and the evidence in Ganzhou, China is limited and inconclusive. OBJECTIVE: This study aimed to assess extreme temperature-related cardiovascular mortality and identify the potential vulnerable people. METHODS: After controlling other meteorological measures, air pollution, seasonality, relative humidity, day of the week, and public holidays, we examined temperature-related cardiovascular mortality along 21 lag days by Poisson in Ganzhou, China. RESULTS: A J-shaped relationship was observed between mean temperature and cardiovascular mortality. Extremely low temperatures substantially increased the relative risks (RR) of cardiovascular mortality. The effect of cold temperature was delayed by 2-6 days and persisted for 4-10 days. However, the risk of cardiovascular mortality related to extremely high temperatures was not significant (p > 0.05). Subgroup analysis indicated that extremely low temperatures had a stronger association with cardiovascular mortality in people with cerebrovascular diseases (RR: 1.282, 95% confidence interval [CI]: 1.020-1.611), males (RR: 1.492, 95% CI: 1.175-1.896), married people (RR: 1.590, 95% CI: 1.224-2.064), and people above the age of 65 years (RR: 1.641, 95% CI: 1.106-2.434) than in people with ischemic heart disease, females, unmarried people, and the elderly (?65 years old), respectively. CONCLUSIONS: The type of cardiovascular disease, sex, age, and marital status modified the effects of extremely low temperatures on the risk of cardiovascular mortality. These findings may help local governments to establish warning systems and precautionary measures to reduce temperature-related cardiovascular mortality.
Modern technology empowers human beings to cope with various extreme weather events. Using Chinese historical data, we examine the impact of extreme weather on long-term human mortality in an environment where individuals had no access to modern technology. By combining life-course data on 5000 Chinese elites with historical weather data over the period 1-1840 AD, we find a significant and robust negative impact of droughts in childhood on the longevity of elites. Quantitatively, encountering three years of droughts in childhood reduces an elite’s life span by about two years.
Dengue transmission is climate-sensitive and permissive conditions regularly cause large outbreaks in Asia-Pacific area. As climate change progresses, extreme weather events such as heatwaves and unusually high rainfall are predicted more intense and frequent, but their impacts on dengue outbreaks remain unclear so far. This paper aimed to investigate the relationship between extreme weather events (i.e., heatwaves, extremely high rainfall and extremely high humidity) and dengue outbreaks in China. We obtained daily number of locally acquired dengue cases and weather factors for Guangzhou, China, for the period 2006-2015. The definition of dengue outbreaks was based on daily number of locally acquired cases above the threshold (i.e., mean + 2SD of daily distribution of dengue cases during peaking period). Heatwave was defined as ?2 days with temperature ? 95th percentile, and extreme rainfall and humidity defined as daily values ?95th percentile during 2006-2015. A generalized additive model was used to examine the associations between extreme weather events and dengue outbreaks. Results showed that all three extreme weather events were associated with increased risk of dengue outbreaks, with a risk increase of 115-251% around 6 weeks after heatwaves, 173-258% around 6-13 weeks after extremely high rainfall, and 572-587% around 6-13 weeks after extremely high humidity. Each extreme weather event also had good capacity in predicting dengue outbreaks, with the model’s sensitivity, specificity, accuracy, and area under the receiver operating characteristics curve all exceeding 86%. This study found that heatwaves, extremely high rainfall, and extremely high humidity could act as potential drivers of dengue outbreaks.
This study’s purpose is to analyze the degree of risk and vulnerability involved in landslide and flash flood prone community areas in Thepparat sub-district, Sichon district, Nakhon Si Thammarat province, Thailand. It also aims to analyze and understand the socio-economic impacts on the community at the household level, and assess the community’s risk and vulnerability by examining its risk perception. The risk perception was done using focus group discussions and a questionnaire survey with key stakeholders. It mainly focused on how the risk of landslides and flash floods influences the community’s risk perceptions, which was tested in two parts: at the organizational and community levels by focusing on government officials and households, respectively. A correlation matrix was used to understand the relationship of the indicators selected. The Pearson correlation result has shown that the degree of risk awareness positively correlates with the income level, education level, and controllability, signifying that the risk of landslides and flash floods influences household risk perceptions. The qualitative assessment recommends community-level preparedness as being paramount to reduce the risk for a resilient community.
Severe fever with thrombocytopenia syndrome (SFTS) was firstly identified in mainland China in 2009 and the geographic distribution has expanded in recent years. In this study, we constructed ecological niche models (ENM) of SFTS with meteorological factors, environmental factor, and density of domestic animals using MaxEnt. We found four significant associated factors including altitude, yearly average temperature, yearly accumulated precipitation, and yearly average relative humidity which accounted for 94.1% percent contribution. SFTS occurrence probability was high when altitude was between -100 m and 100 m, and the probability was nearly 0 when altitude was beyond 3000 m. Response curves of SFTS to the yearly average temperature, yearly accumulated precipitation, and yearly average relative humidity were all reversed V-shape. SFTS occurrence probability was high where the yearly average temperature, yearly accumulated precipitation, and yearly relative humidity were 12.5-17.5 °C, 700-2250 mm and 63-82%, respectively. ENMs predicted that the potential high-risk areas were mainly distributed in eastern areas and central areas of China. But there were some predicted potential high-risk areas where no SFTS case was reported up to date. More researches should be done to make clear whether SFTS case had occurred in these areas.
This study focuses on Guizhou Province, a region with difficult geographical conditions and poor economic development, to examine the effect of rainfall shocks on contemporaneous infant health and long-run socioeconomic outcomes in China. The study results indicate that negative rainfall shocks are robustly correlated with higher infant mortality and lower birth weight. In the long run, early life rainfall shortages limit an individual’s income and housing conditions. The study findings indicate a significant interaction of rainfall shock with the severity of water scarcity. This result implies that drinking water safety is an essential channel through which early life rainfall shocks influence individual health endowments. However, agriculture production is not a likely channel for rainfall effects despite its association with infant mortality. Accordingly, our empirical results suggest that improving public facility coverage will reduce the vulnerability of infant health to adverse rainfall shocks in Guizhou and other developing areas.
Under the global climate warming, extreme weather events occur more and more frequently. Epidemiological studies have proved that extreme temperature is strongly correlated with respiratory diseases. We evaluated extreme-temperature effect on respiratory emergency room (ER) visits for 5 years in Lanzhou, a northwest temperate climate city of China from January 1st, 2013, to August 31st, 2017. We built a distributed lag non-linear model (DLNM) to evaluate the lag effect up to 30 days. Results showed the relative risk (RR) of respiratory disease always reached the maximum at lag 0 day and decreased to 1.0 at lag 5 days. Extremely low temperature showed the lag effect of 22 days and the maximum RR was 1.415 (95% CI 1.295-1.546) at lag 0 day. Extremely high temperature showed the lag effect of 7 days and the maximum RR was 1.091 (95% CI 1.069-1.114) at lag 0 day. The elders (age > 65 years) were at the greatest risk to extreme temperatures and the response were very acute. Children (age ? 15 years) were at the lowest risk but the lag effect lasted the longest lag days than other subgroups. Males showed longer-term lag effect and higher RR than females. Our study indicated that the extremely low temperature has a significantly greater effect on respiratory diseases than extremely high temperature.
The floods of 2018 caused havoc in the State of Kerala, situated in the extreme south-west of India, in terms of infrastructure and health. This research provides the first-ever assessment of the bacterial diversity and its antibiotic susceptibility of the inundated areas of Pampa, Periyar and Vembanad waterbodies by comparing the data collected in two different time intervals succeeding the calamitous floods that is, immediately after flood and 5 months post-flood. An elevated total coliform count was detected in the waterbodies after the flood thereby rendering it unsafe for drinking. Variation in bacterial diversity was observed in the river and lake water samples with a distinct increase in that of the river samples immediately after flood indicated by shannon diversity index (>5.5). Resistance to ampicillin and cefotaxime was observed in a major proportion of isolates from the three biotopes thus indicating the influence of antibiotic wastes accumulated from different sources of human interventions. Furthermore, operational taxonomic units clustering to Acinetobacter, Legionella, Pseudomonas and Burkholderia genera were detected by metataxonomic analysis which portray as a potential health risk in the future. The article emphasises the importance of adopting sanitation programmes for effective management of epidemic outbreaks post floods.
BACKGROUND: Tuberculosis (TB) is a serious public health problem in China. There is evidence to prove that meteorological factors and exposure to air pollutants have a certain impact on TB. But the evidence of this relationship is insufficient, and the conclusions are inconsistent. METHODS: Descriptive epidemiological methods were used to describe the distribution characteristics of TB in Shijiazhuang in the past five years. Through the generalized linear regression model (GLM) and the generalized additive model (GAM), the risk factors that affect the incidence of TB are screened. A combination of GLM and distribution lag nonlinear model (DLNM) was used to evaluate the lag effect of environmental factors on the TB. Results were tested for robustness by sensitivity analysis. RESULTS: The incidence of TB in Shijiazhuang showed a downward trend year by year, with seasonality and periodicity. Every 10 ?g/m(3) of PM(10) changes, the RR distribution is bimodal. The first peak of RR occurs on the second day of lag (RR = 1.00166, 95% CI: 1.00023, 1.00390); the second risk period starts from 13th day of lag and peaks on15th day (RR = 1.00209, 95% CI: 1.00076, 1.00341), both of which are statistically significant. The cumulative effect of increasing 10 ?g/m(3) showed a similar bimodal distribution. Time zones where the RR makes sense are days 4-6 and 13-20. RR peaked on the 18th day (RR = 1.02239, 95% CI: 1.00623, 1.03882). The RR has a linear relationship with the concentration. Under the same concentration, the RR peaks within 15-20 days. CONCLUSION: TB in Shijiazhuang City showed a downward trend year by year, with obvious seasonal fluctuations. The air pollutant PM(10) increases the risk of TB. The development of TB has a short-term lag and cumulative lag effects. We should focus on protecting susceptible people from TB in spring and autumn, and strengthen the monitoring and emission management of PM(10) in the atmosphere.
Climate change could intensify extreme weather events, such as flooding, which amplifies the public health threat of waterborne diseases. Thus, assessing health vulnerability and adaptation (V&A) could facilitate nationally effective responses to extreme climate events. However, related studies are still negligible, and the assessment urgently needs to be validated with actual health data after extreme weather events. We established health V&A indices through literature review and factor analyses. Then, we separately mapped the spatial distribution of flood exposure, social and public health sensitivity, and adaptive capacity before the 2016 flood in Anhui province and compared it with post-flood diarrhea risks by using the geographic information system method to assess health vulnerability. Finally, we validated the indices by exploring the relationship between health V&A indices and post-flood diarrhea risks by using the quantile regression model. Results revealed that health V&A can be framed and categorized as key components of exposure, sensitivity, and adaptive capacity. The remarkable differences in the spatial distribution of health vulnerability were generally consistent with the demographic sensitivity, geographic flooding exposure, and post-flood diarrhea risks in Anhui. In addition, health V&A indices exerted significant positive impacts on infectious diarrhea post-flooding at all quantiles and were significant across different percentiles. Moreover, the impacts of flood exposure on total infectious diarrhea were high and continuous, whereas the impacts of sensitivity were not obvious in the flood’s early stage (Coeff = 0.643; p < 0.001) but high in the flood's middle (Coeff = 0.997; p < 0.001) and late stages (Coeff = 0.975; p < 0.001). However, the impacts of adaptive capacity were heterogeneous and high in the flood's early stage (Coeff = 0.665; p < 0.001 at the 25th percentile) and late stage (Coeff = 1.296; p < 0.001 at the 75th percentile) but were insignificant at the 50th percentile. This study contributed validated three-layered health V&A indices with 30 indicators and identified that the impacts of the key components on post-flood waterborne-disease risks are heterogeneous. For instance, local public health sensitivity and adaptive capacity are insufficient to reduce these risks in the long run. This study could be used to project population health risks after extreme weather events and thereby contributes to local government planning of health adaptation.
OBJECTIVES: Evolutionary theorists have debated the adaptive significance of developmental plasticity in organisms with long lifespans such as humans. This debate in part stems from uncertainty regarding the timing of sensitive periods. Does sensitivity to environmental signals fluctuate across development or does it steadily decline? We investigated developmental plasticity in brown adipose tissue (BAT) among indigenous Siberians in order to explore the timing of phenotypic sensitivity to cold stress. METHODS: BAT thermogenesis was quantified using infrared thermal imaging in 78 adults (25 men; 33 women). Cold exposure during gestation, infancy, early childhood, middle childhood, and adolescence was quantified using: (1) the average ambient temperature across each period; (2) the number of times daily temperature dropped below -40°F during each period. We also assessed past cold exposure with a retrospective survey of participation in outdoor activities. RESULTS: Adult BAT thermogenesis was significantly associated with the average temperature (p = 0.021), the number of times it was below -40°F (p = 0.026), and participation in winter outdoor activities (p = 0.037) during early childhood. CONCLUSIONS: Our results suggest that early childhood represents an important stage for developmental plasticity, and that culture may play a critical role in shaping the timing of environmental signals. The findings highlight a new pathway through which the local consequences of global climate change may influence human biology, and they suggest that ambient temperature may represent an understudied component of the developmental origins of health and disease.
The present study was planned to explore the pollution characteristics, health risks, and influence of atmospheric fine particulate matter (PM(2.5)) and its components on blood routine parameters in a typical industrial city (Xinxiang City) in China. In this study, 102 effective samples 28 (April-May), 19 (July-August), 27 (September-October), 28 (December-January) of PM(2.5) were collected during different seasons from 2017 to 2018. The water-soluble ions and metal elements in PM(2.5) were analyzed via ion chromatography and inductively coupled plasma-mass spectrometry. The blood routine physical examination parameters under different polluted weather conditions from January to December 2017 and 2018, the corresponding PM(2.5) concentration, temperature, and relative humidity during the same period were collected from Second People’s Hospital of Xinxiang during 2017-2018. Risk assessment was carried out using the generalized additive time series model (GAM). It was used to analyze the influence of PM(2.5) concentration and its components on blood routine indicators of the physical examination population. The “mgcv” package in R.3.5.3 statistical software was used for modeling and analysis and used to perform nonparametric smoothing on meteorological indicators such as temperature and humidity. When Akaike’s information criterion (AIC) value is the smallest, the goodness of fit of the model is the highest. Additionally, the US EPA exposure model was used to evaluate the health risks caused by different heavy metals in PM(2.5) to the human body through the respiratory pathway, including carcinogenic risk and non-carcinogenic risk. The result showed that the air particulate matter and its chemical components in Xinxiang City were higher in winter as compared to other seasons with an overall trend of winter > spring > autumn > summer. The content of nitrate (NO(3)(-)) and sulfate (SO(4)(2)(-)) ions in the atmosphere were higher in winter, which, together with ammonium, constitute the main components of water-soluble ions in PM(2.5) in Xinxiang City. Source analysis reported that mobile pollution sources (coal combustion emissions, automobile exhaust emissions, and industrial emissions) in Xinxiang City during the winter season contributed more to atmospheric pollution as compared to fixed sources. The results of the risk assessment showed that the non-carcinogenic health risk of heavy metals in fine particulate matter is acceptable to the human body, while among the carcinogenic elements, the order of lifetime carcinogenic risk is arsenic (As) > chromium(Cr) > cadmium (Cd) > cobalt(Co) > nickel (Ni). During periods of haze pollution, the exposure concentration of PM(2.5) has a certain lag effect on blood routine parameters. On the day when haze pollution occurs, when the daily average concentration of PM(2.5) rises by 10 ?g·m(-3), hemoglobin (HGB) and platelet count (PLT) increase, respectively, by 9.923% (95% CI, 8.741-11.264) and 0.068% (95% CI, 0.067-0.069). GAM model analysis predicted the maximum effect of PM(2.5) exposure concentration on red blood cell count (RBC) and PLT was reached when the hysteresis accumulates for 1d (Lag0). The maximum effect of exposure concentration ofPM(2.5) on MONO is reached when the lag accumulation is 3d (Lag2). When the hysteresis accumulates for 6d (Lag5), the exposure concentration of PM(2.5) has the greatest effect on HGB. The maximum cumulative effect of PM(2.5) on neutrophil count (NEUT) and lymphocyte (LMY) was strongest when the lag was 2d (Lag1). During periods of moderate to severe pollution, the concentration of water-soluble ions and heavy metal elements in PM(2.5) increases significantly and has a significant correlation with some blood routine indicators.
Temperature change between neighboring days (TCN) is an important trigger for cardiovascular diseases, but the modulated effects by seasonal temperature trends have been barely taken into account. A quantified comparison between impacts of positive TCNs (temperature rise) and negative situations (temperature drop) is also needed. We evaluated the associations of TCNs with emergency room (ER) visits for coronary heart disease (CHD) and cerebral infarction (CI) in Beijing, China, from 2008 to 2012. A year was divided into two segments dominated by opposite temperature trends, quasi-Poisson regression with distributed lag nonlinear models estimating TCN-morbidity relations were employed, separately for each period. High morbidities of CHD and CI both occurred in transitional seasons accompanied by large TCNs. Under warming backgrounds, positive TCNs increased CHD risk in patients younger than 65 years, and old people showed limited sensitivity. In the cooling periods, negative TCNs induced CHD risk in females and the elderly; the highest RR showed on lag 6 d. In particular, a same diurnal temperature decrease (e.g., – 2°C) induced greater RR (RR = 1.113, 95% CIs: 1.033-1.198) on old people during warming periods than cooling counterparts (RR = 1.055, 95% CIs: 1.011-1.100). Moreover, positive TCNs elevated CI risk regardless of background temperatures, and males were particularly vulnerable. Seasonal temperature trends modify TCN-cardiovascular morbidity associations significantly, which may provide new insights into the health impact of unstable weathers.
BACKGROUND: An acute upper respiratory tract infection (URI) is the most common disease worldwide, irrespective of age or sex. This study aimed to evaluate the short-term effect of diurnal temperature range (DTR) on emergency room (ER) visits for URI in Seoul, Korea, between 2009 and 2013. METHODS: Daily ER visits for URI were selected from the National Emergency Department Information System, which is a nationwide daily reporting system for ER visits in Korea. URI cases were defined according to International Classification of Diseases, 10(th) Revision codes J00-J06. The search for DTR effects associated with URI was performed using a semi-parametric generalized additive model approach with log link. RESULTS: There were 529,527 ER visits for URI during the study period, with a daily mean of 290 visits (range, 74-1942 visits). The mean daily DTR was 8.05 °C (range, 1.1-17.6 °C). The cumulative day (lag 02) effect of DTR above 6.57 °C per 1 °C increment was associated with a 1.42% (95% confidence interval [CI] 0.04-2.82) increase in total URI. Children (? 5 years of age) were affected by DTR above 6.57 °C per 1 °C, with 1.45% (95% CI 0.32-2.60) at lag 02, adults (19-64 years) with 2.77% (95% CI 0.39-5.20) at lag 07. When the DTR (lag02) was 6.57 °C to 11.03 °C, the relative risk was significant at 6.01% (95% CI 2.45-9.69) for every 1 °C increase in youth subjects aged for 6 to 18 years. CONCLUSIONS: DTR was associated with a higher risk for ER visits for URI. In addition, the results suggested that the lag effects and relative risks of DTR on URI were quite different according to age.
BACKGROUND: Previous studies have reported that fine particulate matter (PM(2.5)) affects the incidence of premature births. In addition, recent studies have suggested that heat waves have a negative impact on birth outcomes. However, the combined effect of PM(2.5) and heat waves on the incidence of premature birth is controversial. This study investigated the independent and combined effects of PM(2.5) and heat wave exposures during the 1st and 2nd trimesters on premature birth. METHODS: The National Statistical Office of Korea provided birth data from 2010 to 2016. Preterm birth was defined as birth between 22 and 36 weeks. To assess the exposure to PM(2.5) and heat waves, we used PM(2.5) data estimated by the Community Multiscale Air Quality Modeling System (CMAQ) and heat wave warning data provided by the Korea Meteorological Administration. A multivariate logistic regression was used to investigate the risk of preterm birth according to the exposure to PM(2.5) and heat waves during the 1st and 2nd trimesters, and it was adjusted for residential area, year of birth, season of birth, parity, education level of the mother, age of the mother, and sex of the baby. RESULTS: In the 2nd trimester, compared with the 0 h of heat wave exposure (?67 percentile), 62.50-314.00 h (79-88 percentile) and>315.00 h of heat wave exposure (>88 percentile) were both significantly associated with preterm birth (OR for 79-88 percentile, 1.037, 95% CI, 1.003-1.073; OR for > 88 percentile, 1.174, 95% CI, 1.134-1.215). However, PM(2.5) exposure was not significantly associated with preterm birth. On the other hand, in the analysis to evaluate the combined effect of PM(2.5) and heat wave exposures of the 2nd trimester, compared with 0 h of heat wave exposure (?67 percentile) and<11.64 ?g/m(3) (?25 percentile) of PM(2.5), 11.64-22.74 ?g/m(3) (?25 percentile), 22.74-27.58 ?g/m(3) (26-50 percentile), and 27.57-32.39 ?g/m(3) (51-75 percentile) of PM(2.5) exposure combined with>315.00 h of heat wave exposure (>88 percentile) were all significantly associated with preterm birth. In addition, the effect size was increased with an increase of PM(2.5) exposure (OR for ? 25 percentile, 1.148, 95% CI, 1.095-1.203; OR for 26-50 percentile, 1.248, 95% CI, 1.178-1.323; OR for 51-75 percentile, 1.370, 95% CI, 1.245-1.507). CONCLUSION: Our findings suggest that the combined effect of heat wave and PM(2.5) exposure during the 2nd trimester on the risk of preterm birth was greater than that of each exposure alone. In other words, exposure to PM(2.5) increases the impact of heat waves on the risk of preterm birth. These results indicate that control of prenatal exposure to fine particular matter and extreme temperatures is important for the prevention of preterm birth.
Heatwaves and greenness have been shown to affect health, but the evidence on their joint effects is limited. We aim to assess the associations of the combined exposure to greenness and heatwaves. We utilized five waves (February 2000-October 2014) of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), a prospective cohort of older adults aged 65. We defined heatwaves as the daily maximum temperature ?92.5th percentile with duration ?3 days. We calculated the number of heatwave days in one year before death to and cumulative Normalized Difference Vegetation Index (NDVI) during follow-up to assess individual long-term exposure to heatwaves and greenness. Cox proportional hazards models were used to assess the effects of greenness, heatwaves, and their interaction on mortality, adjusted for covariates. We conducted subgroup analyses by residence, gender, and age. There were 20,758 participants in our study, totaling 67,312 person-years of follow-up. The mean NDVI was 0·41 (SD 0.13), and the mean number of heatwave days was 8.92 (2.04). In the adjusted model, the mortality hazard ratio (HR) for each 3-day increase in heatwave days was 1.04 (95% CI 1.04, 1.05), each 0.1-unit decrease in cumulative NDVI was 1.06 (1.05, 1.07). In the adjusted model with an interaction term, the HR for the interaction term was 1.01 (1.01, 1.02) with a p-value less than 0.001. In our subgroup analyses, the HR for each 3-day increase in heatwave days was higher in urban areas than in rural areas (1.06 vs. 1.03), and the HR for 0.1-unit decrease in NDVI was higher in urban areas than in rural areas (1.08 vs. 1.04). Greenness can protect against the effect of heatwaves on mortality, and heatwaves affect the health effects of greenness. Urban dwellers have a higher response to the detrimental effect of heatwaves and a higher marginal benefit from greenness exposure.
BACKGROUND/AIM: Previous studies have suggested that the short-term ambient air pollution and temperature are associated with myocardial infarction. In this study, we aimed to conduct a time-series analysis to assess the impact of fine particulate matter (PM2.5) and temperature on acute myocardial infarction (AMI) among adults over 20 years of age in Korea by using the data from the Korean National Health Information Database (KNHID). METHODS: The daily data of 192,567 AMI cases in Seoul were collected from the nationwide, population-based KNHID from 2005 to 2014. The monitoring data of ambient PM2.5 from the Seoul Research Institute of Public Health and Environment were also collected. A generalized additive model (GAM) that allowed for a quasi-Poisson distribution was used to analyze the effects of PM2.5 and temperature on the incidence of AMI. RESULTS: The models with PM2.5 lag structures of lag 0 and 2-day averages of lag 0 and 1 (lag 01) showed significant associations with AMI (Relative risk [RR]: 1.011, CI: 1.003-1.020 for lag 0, RR: 1.010, CI: 1.000-1.020 for lag 01) after adjusting the covariates. Stratification analysis conducted in the cold season (October-April) and the warm season (May-September) showed a significant lag 0 effect for AMI cases in the cold season only. CONCLUSIONS: In conclusion, acute exposure to PM2.5 was significantly associated with AMI morbidity at lag 0 in Seoul, Korea. This increased risk was also observed at low temperatures.
Malaria is a climate-sensitive infectious disease. Many ecological studies have investigated the independent impacts of ambient temperature on malaria. However, the optimal temperature measures of malaria and its interaction with other meteorological factors on malaria transmission are less understood. This study aims to investigate the effect of ambient temperature and its interactions with relative humidity and rainfall on malaria in Suzhou, a temperate climate city in Anhui Province, China. Weekly malaria and meteorological data from 2005 to 2012 were obtained for Suzhou. A distributed lag nonlinear model was conducted to quantify the effect of different temperature measures on malaria. The best measure was defined as that with the minimum quasi-Akaike information criterion. GeoDetector and Poisson regression models were employed to quantify the interactions of temperature, relative humidity, and rainfall on malaria transmission. A total of 13,382 malaria cases were notified in Suzhou from 2005 to 2012. Each 5 °C rise in average temperature over 10 °C resulted in a 22% (95% CI: 17%, 28%) increase in malaria cases at lag of 4 weeks. In terms of cumulative effects from lag 1 to 8 weeks, each 5 °C increase over 10 °C caused a 175% growth in malaria cases (95% CI: 139%, 216%). Average temperature achieved the best performance in terms of model fitting, followed by minimum temperature, most frequent temperature, and maximum temperature. Temperature had an interactive effect on malaria with relative humidity and rainfall. High temperature together with high relative humidity and high rainfall could accelerate the transmission of malaria. Meteorological factors may affect malaria transmission interactively. The research findings could be helpful in the development of weather-based malaria early warning system, especially in the context of climate change for the prevention of possible malaria resurgence.
Meteorological factors, which are periodic and regular in a long run, have an unignorable impact on human health. Accurate health risk prediction based on meteorological factors is essential for optimal allocation of resource in healthcare units. However, due to the non-stationary and non-linear nature of the original hospitalization sequence, traditional methods are less robust in predicting it. This study aims to investigate hospital admission prediction models using time series pre-processing algorithms and deep learning approach based on meteorological factors. Using the electronic medical record data from Panyu Central Hospital and meteorological data of Panyu district from 2003 to 2019, 46,089 eligible patients with lower respiratory tract infections (LRTIs) and four meteorological factors were identified to build and evaluate the prediction models. A novel hybrid model, Cascade GAM-CEEMDAN-LSTM Model (CGCLM), was established in combination with generalized additive model (GAM), complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and long-short term memory (LSTM) networks for predicting daily admissions of patients with LRTIs. The experimental results show that CGCLM multistep method proposed in this paper outperforms single LSTM model in the prediction of health risk time series at different time window sizes. Moreover, our results also indicate that CGCLM has the best prediction performance when the time window is set to 61 days (RMSE = 1.12, MAE = 0.87, R(2) = 0.93). Adequate extraction of exposure-response relationships between meteorological factors and diseases and suitable handling of sequence pre-processing have an important role in time series prediction. This hybrid climate-based model for predicting LRTIs disease can also be extended to time series prediction of other epidemic disease.
Despite the significant economic cost of falls and injuries to individuals and communities, little is known about the impact of meteorological factors on the incidence of fall-related injuries (FRIs). Therefore, a time-series study was conducted to explore the effects of meteorological factors on FRIs in Ma’anshan City, East China. Injury data from 2011 to 2017 were collected from the National Injury Monitoring Station in Ma’anshan City. A distributed lag nonlinear model was used in this study to evaluate the correlation between ambient temperature and fall injuries. The results showed a significant exposure-response relationship between temperature and FRIs in Ma’anshan City. The high temperatures increased the risk of FRIs (RR = 1.110; 95% CI, 1.005-1.225; lag 0). The lag effect appeared at lag 10 (RR = 1.032; 95% CI, 1.003-1.063), and then gradually remained stable after lag 25 (RR = 1.077; 95% CI, 1.045-1.110). The effect of ambient temperature varied with age and gender. The lag effect of high temperature appeared in the male group after lag 15 (RR = 1.042; 95% CI, 1.006-1.079). In contrast, the effect of the female group appeared for the first time at lag 0 (RR = 1.187; 95% CI, 1.042-1.352). And the ? 60 years subgroup seemed to be more sensitive in low temperature (RR = 1.017; 95% CI, 1.004-1.031; lag 0; RR = 1.003; 95% CI, 1.000-1.007; lag 25). The cumulative result is similar to the single-day effect. From the results, this study would help the establishment of fall-related injury prediction and provide evidence for the formulation and implementation of preventive strategies and measures in the future.
Rotavirus A is the most common cause of infectious diarrhea worldwide. This study aimed to retrospectively study and analyze 4009 stool samples that were tested for viruses causing diarrhea, using multiplex reverse transcription PCR at Dankook University Hospital between 2010 and 2019. Furthermore, we determined the correlation between these factors and various climatic factors, including wind-chill temperature, relative humidity, rate of sunshine, and particulate matter. Rotavirus A infections occurred frequently in February, March, and April on an annual basis. Furthermore, during the study, the detection rate was highest at 17.0% (n=61/359) in 2011. Based on an analysis of weather big data, patient age, and period-specific infection during the summer, when the wind-chill temperature and relative humidity were high, the Rotavirus A infection rate was very low. Relative humidity (p=0.020) and particulate matter (p=0.049) were associated with the average number of monthly cases of Rotavirus A infection. However, wind chill temperature (p=0.074) and rate of sunshine (p=0.993) were not associated with the average monthly distribution of Rotavirus A cases. These results indicate that Rotavirus A infection was correlated with relative humidity and particulate matter during the study period and further the current understanding of the distribution of Rotavirus A infections resulting from climatic factors and particulate matter. This could help establish climate-related health policies to reduce the incidence of diarrhea and guide the development of vaccines against Rotavirus A.
Studying relationships between meteorological conditions and respiratory virus infections may help interpret the causality of disease outbreaks and provide a better understanding of the seasonal distribution of viruses. Therefore, in this study, we analyzed the correlations between meteorological data and the trends of infection by human parainfluenza virus-1 (HPIV-1; also known as human respirovirus 1), human parainfluenza virus-2 (human orthorubulavirus 2), and human parainfluenza virus-3 (human respirovirus 3) using 9010 viral samples collected at Dankook University Hospital from January 1, 2012, to December 31, 2018. Infection frequency data were used to detect the seasonal patterns of HPIV-1, HPIV-2, and HPIV-3 infections, and these patterns were compared with local weather data over the same period. We performed descriptive statistical analysis, frequency analysis, t test, and binomial logistic regression analysis to examine the relationships of weather and particulate matter conditions with the incidence of HPIV-1, HPIV-2, and HPIV-3 infections. The highest average infection rate with one of these three viruses (88.17%) was found in children aged 1-9 years. Specifically, the infection rate of HPIV-1 was 91.9% in children aged 1-9 years, whereas that of HPIV-2 and HPIV-3 was 86.3%. HPIV infection exhibited a meaningful relationship with climatic factors, such as temperature, wind-chill temperature, and atmospheric pressure. Our results suggest that climate changes might affect the rate of infection by HPIV. These findings may help in predicting the effectiveness of preventive strategies of HPIV infection.
Growing studies have shown that high temperature is a potential risk factor of schizophrenia occurrence. Therefore, elaborate analysis of different temperature exposure patterns, such as cumulative heat exposure within a time period and transient exposure at a particular time point, is of important public health significance. This study aims to utilize hourly temperature data to better capture the effects of cumulative and transient heat exposures on schizophrenia during the warm season in Hefei, China. We included the daily mean temperature and daily schizophrenia hospitalizations into the distributed lag non-linear model (DLNM) to simulate the exposure-response curve and determine the heat threshold (19.4 °C). We calculated and applied a novel indicator-daily excess hourly heat (DEHH)-to examine the effects of cumulative heat exposure over a day on schizophrenia hospitalizations. Temperature measurements at each time point were also incorporated in the DLNM as independent exposure indicators to analyze the impact of transient heat exposure on schizophrenia. Each increment of interquartile range (IQR) in DEHH was associated with elevated risk of schizophrenia hospitalizations from lag 1 (RR = 1.036, 95% confidence interval (CI): 1.016, 1.057) to lag 4 (RR = 1.025, 95% CI: 1.005, 1.046). Men and people over 40 years old were more susceptible to DEHH. Besides, we found a greater risk of heat-related schizophrenia hospitalizations between 0 a.m. and 6 a.m. This study revealed the adverse effects of accumulated and transient heat exposures on schizophrenia hospitalizations. Our findings need to be further tested in other regions with distinct regional features.
Cardiovascular disease (CVD), reported to relate with climate change, is the leading cause of global mortality and morbidity. Since the relevant information is quite limited from suburbs and countryside in developing and underdeveloped countries, there are no studies that focused on morbidity through diurnal temperature range (DTR) for these regions. This is the first study to evaluate the short-term effect of DTR on CVD hospital admission in suburban farmers, as well as to identify vulnerable subpopulations. Daily time series data of CVD hospital admissions on suburban farmers of Qingyang, China, and meteorological data from 2011 to 2015 were collected, and a distributed lag non-linear model (DLNM) combined with a quasi-Poisson generalized additive regression model (GAM) was used to examine the exposure-response relationship and delayed effect between DTR and CVD hospital admissions. Stratified analyses by age and gender were performed and extreme DTR effects were examined. Non-linear relation between DTR and CVD hospital admissions was observed, and whether DTR lower or higher than the reference (13 °C, 50(th) percentile) had adverse effect while lower DTR have slightly higher impact. Also, both extreme low and extreme high DTR had adverse effect. Besides, adults (age < 65) and males were more vulnerable to the effects of DTR compared with the old (age ? 65) and females, respectively. This study provides evidence that not only high DTR but also low DTR had adverse effects on CVD which should be paid attention to. Adults and males were more vulnerable among suburban farmers. The results are inconsistent with the studies from urban and indicate differences between urban and suburban residents. Multiple factors such as occupations, risk awareness, and lifestyles could have a significant influence on CVD morbidity, and further study is needed to explore more evidence.
Industrialization and urbanization have aggravated the contradiction between environmental protection and economic growth, leading to health issues. While there are considerable interests in understanding the health effects of carbon emissions in the context of climate change, little is observed at regional scale and by econometric methods. Applying regression analysis on 2002-2017 Chinese provincial-level panel data, this study explores the intermediary mechanisms and regional differences of carbon emissions on residents’ health. The results indicate that: (1) Carbon emissions have a long-term adverse impact on residents’ health-a 1% rise in carbon emission adds 0.298% more outpatients and 0.162% more inpatients; (2) The rise in carbon emissions impairs residents’ health mainly by raising the temperature; (3) In areas with high levels of industrialization and urbanization, increased carbon emissions bring greater health risks; and (4) In terms of China’s unique “leading industrialization and lagging urbanization” situation, only by upgrading industrial structure, improving urbanization quality, and promoting coordinated industrialization and urbanization can the harm of carbon emissions to residents’ health be reduced. Therefore, the “one-size-fits-all” policy model is not suitable for China’s current situation. To address global “climate change” issues, China must act according to local conditions by applying mitigating (adaptive) measures in economically developed (less developed) regions. Simultaneously, the authorities must focus on the interaction and synergy between industrialization and urbanization.
Many methods have been developed to verify the correlation between meteorological conditions and air pollutants; however, all have limitations that lead to biased or incomplete conclusions. Hence, improved methods are urgently required to describe this correlation comprehensively and accurately. In this study, we demonstrated the ability of the Copula function to apply time-varying correlations between meteorological factors and atmospheric pollutants. A mixed Copula model was constructed using meteorological monitoring data for Beijing and Guangzhou from 2014 to 2019 to dynamically analyse the correlation characteristics and tail dependence between these factors. We then performed a correlation analysis for the data from the average, lower, and upper tails to obtain a more accurate and comprehensive correlation description. Dynamic analysis results demonstrated significant seasonal fluctuations between meteorological conditions and pollutants relationships. Moreover, the correlation coefficient variations differ according to their average and tail values. High humidity is more likely to be accompanied by increased NO2 compared with average summer humidity. Our proposed model represents a novel application of the Copula function for determining the factors influencing air pollution. This model emphasizes the tail dependence between meteorological conditions and air pollutant concentrations and can be used to guide more targeted prevention and control strategies.
Air pollution has been a rising concern of the 21st due to its effects to public health. Air Monitoring Stations are state-of-the-art equipment used to measure airborne pollutants concentration i.e. carbon monoxide, nitrogen oxide, sulphur dioxide, particulate matter (PM10) and ozone (O-3), as well as the meteorological parameters (i.e. ambient air temperature, relative humidity, wind speed and wind direction). Effects of climate change will affect the ambient temperature and humidity, which may induce a direct effect on air quality. In light of this, feed forward artificial neural network was employed to simulate the dynamic variations of PM10 and O-3 with relative humidity, temperature, and windspeed data being the inputs under 12 different training algorithms. Based on the results obtained, Bayesian regularization with 12 hidden neurons is the optimized network structure, with mean absolute percentage error in testing dataset of O-3 and PM10 at 51.31% and 36.49%, respectively. The models performed better in O-3 prediction as it is a photochemical reaction where ozone concentration varies according to temperature, the effect of meteorological parameters is significant. On the other hand, PM10 is not heavily dependent on meteorological parameters as the diversity of particulate matter components where most of its sources are dormant to changes in climate.
Aedes aegypti is the main vector of dengue globally. The variables that influence the abundance of dengue vectors are numerous and complex. This has generated a need to focus on areas at risk of disease transmission, the spatial-temporal distribution of vectors, and the factors that modulate vector abundance. To help guide and improve vector-control efforts, this study identified the ecological, social, and other environmental risk factors that affect the abundance of adult female and immature Ae. aegypti in households in urban and rural areas of northeastern Thailand. A one-year entomological study was conducted in four villages of northeastern Thailand between January and December 2019. Socio-demographic; self-reported prior dengue infections; housing conditions; durable asset ownership; water management; characteristics of water containers; knowledge, attitudes, and practices (KAP) regarding climate change and dengue; and climate data were collected. Household crowding index (HCI), premise condition index (PCI), socio-economic status (SES), and entomological indices (HI, CI, BI, and PI) were calculated. Negative binomial generalized linear models (GLMs) were fitted to identify the risk factors associated with the abundance of adult females and immature Ae. aegypti. Urban sites had higher entomological indices and numbers of adult Ae. aegypti mosquitoes than rural sites. Overall, participants’ KAP about climate change and dengue were low in both settings. The fitted GLM showed that a higher abundance of adult female Ae. aegypti was significantly (p < 0.05) associated with many factors, such as a low education level of household respondents, crowded households, poor premise conditions, surrounding house density, bathrooms located indoors, unscreened windows, high numbers of wet containers, a lack of adult control, prior dengue infections, poor climate change adaptation, dengue, and vector-related practices. Many of the above were also significantly associated with a high abundance of immature mosquito stages. The GLM model also showed that maximum and mean temperature with four-and one-to-two weeks of lag were significant predictors (p < 0.05) of the abundance of adult and immature mosquitoes, respectively, in northeastern Thailand. The low KAP regarding climate change and dengue highlights the engagement needs for vector-borne disease prevention in this region. The identified risk factors are important for the critical first step toward developing routine Aedes surveillance and reliable early warning systems for effective dengue and other mosquito-borne disease prevention and control strategies at the household and community levels in this region and similar settings elsewhere.
OBJECTIVE: Evidence on the relationship between ambient temperature and morbidity of different stroke subtypes in China is limited. This study aimed to assess the influence of ambient temperature on stroke risk in Shenzhen, China. METHODS: From 1 January 2003 to 31 December 2014, 114 552 stroke cases in Shenzhen were collected. A generalised additive model with quasi-Poisson regression combined with a distributed lag non-linear model was applied to evaluate the temperature effects on stroke subtypes. Furthermore, this study explored the variability of the effects across sex, age and education. RESULTS: The immediate heat effects on ischaemic stroke (IS) and the persistent effects of ambient temperature on intracerebral haemorrhage (ICH) were significant. Overall, the cold-related relative risks (RRs) of IS, ICH and subarachnoid haemorrhage (SAH) were 1.02 (0.97-1.07), 1.16 (1.04-1.30) and 1.12 (0.61-2.04), whereas the heat-related RRs were 1.00 (0.97-1.04), 0.80 (0.73-0.88) and 1.05 (0.63-1.78), respectively. For IS, a weakly beneficial cold effect was found among men while a detrimental heat effect among both men and women, the elderly and higher-educated population at lag0. However, regarding ICH, the temperature effects in men, the young and higher-educated population are stronger at lag0-4, lag0-7 as cold reveals threat and heat reveals protection. CONCLUSION: Responses of diverse stroke subtypes to ambient temperature varied. Effective measures should be taken to increase public awareness about the effects of ambient temperature on stroke attack and to educate the public about self-protection.
BACKGROUND: Many studies have explored the association between meteorological factors and infectious diarrhea (ID) transmission but with inconsistent results, in particular the roles from temperatures. We aimed to explore the effects of temperatures on the transmission of category C ID, to identify its potential heterogeneity in different climate zones of China, and to provide scientific evidence to health authorities and local communities for necessary public health actions. METHODS: Daily category C ID counts and meteorological variables were collected from 270 cities in China over the period of 2014-16. Distributed lag non-linear models (DLNMs) were applied in each city to obtain the city-specific temperature-disease associations, then a multivariate meta-analysis was implemented to pool the city-specific effects. Multivariate meta-regression was conducted to explore the potential effect modifiers. Attributable fraction was calculated for both low and high temperatures, defined as temperatures below the 5th percentile of temperature or above the 95th percentile of temperature. RESULTS: A total of 2,715,544 category C ID cases were reported during the study period. Overall, a M-shaped curve relationship was observed between temperature and category C ID, with a peak at the 81st percentile of temperatures (RR = 1.723, 95% CI: 1.579-1.881) compared to 50th percentile of temperatures. The pooled associations were generally stronger at high temperatures compared to low ambient temperatures, and the attributable fraction due to heat was higher than cold. Latitude was identified as a possible effect modifier. CONCLUSIONS: The overall positive pooled associations between temperature and category C ID in China suggest the increasing temperature could bring about more category C infectious diarrhea cases, which warrants further public health measurements.
The purpose of this study was to explore the application of serum amyloid A (SAA) in the outcome of upper respiratory tract infection in children by analyzing the correlation between the change of mean air temperature and the positive rate of SAA detection in children. Daily data on upper respiratory tract infection diseases and weather conditions were collected in 2016-2019. A quasi-Poisson regression with a distributed lag non-linear model was used to examine the association between temperature and SAA-positive rate. The positive rate of SAA had a moderate correlation with the temperature and a weak correlation with relative humidity. Low ambient temperature (7 °C, P(1)) was related to the increase in the positive rate of SAA, with the effect lag for 0-7 days (RR 1.34 (1.19~1.74)). The increase in the SAA-positive case induced by 27 °C (P(75)) could last for 0-14 days (RR 1.07 (1.01-1.08)), and high temperature (30 °C, P(99)) could reduce the positive rate of SAA. Our findings add additional evidence to the adverse effects of sub-optimal ambient temperature and provide useful information for public health programs targeting pediatric patients.
BACKGROUND: In recent years, many previous studies have examined the association between ambient temperature and mortality in different parts of the world. However, very few studies have explored the mortality burden attributable to temperature, especially those in developing countries. This study aimed to quantify the burden of mortality attributable to non-optimum temperature in Thailand and explore whether greenness, using normalized difference vegetation index (NDVI) as indicator, alleviates the mortality contributed by non-optimum ambient temperature. METHODS: Daily number of mortality (i.e., all-cause, cardiovascular and respiratory diseases) and daily meteorological data were obtained over 65 provinces in Thailand during 2010 to 2017. The two-stage statistical approach was applied to estimate the association between temperature and mortality. First, the time-stratified case-crossover analysis was performed to examine province-specific temperature-mortality association. Second, province-specific association was pooled to derive national estimates using multivariate meta-regression. Mortality burden attributable to temperature was then estimated, and the association between attributed mortality and NDVI was explored using multivariate meta-regression models. RESULTS: A total of 2,891,407 all-cause of death was included over the study period, in which 403,450 and 264,672 deaths were accounted for cardiovascular and respiratory diseases, respectively. The temperature-mortality association at cumulative lag 0-7 days was non-linear with J-shaped curve for all-cause and respiratory mortality, whereas V-shaped curve was observed for cardiovascular mortality. Using minimum mortality temperature (MMT) as optimum temperature, 3.72% (95% empirical CI: 2.18, 5.21) of all-cause, 2.92% (0.55, 5.10) of cardiovascular and 3.00% (0.27, 5.49) of respiratory mortality were attributable to non-optimum temperature (both hot and cold effects). Higher level of NDVI was associated with alleviated impacts of non-optimum temperature, especially hot temperature. CONCLUSION: Exposure to non-optimum temperature was associated with increased risks of mortality in Thailand. This finding is useful for planning the public health interventions to reduce health effects of non-optimum ambient temperature.
In this study, we examined the cognitive performance of subtropically acclimatized subjects at an extreme high indoor temperature and the effect of decreased humidity on the cognitive performance at the high temperature. Forty-eight healthy subjects experienced the three exposure conditions: 26 degrees C/relative humidity (RH) 70%, 39 degrees C/RH50%, and 39 degrees C/RH70% in a climate chamber. During 140-minute-long exposures to each thermal condition, they were required to perform cognitive tests that assess the perception, spatial orientation, concentration, memory, and thinking abilities. Meanwhile, their heart rate, core temperature, skin temperature, blood pressure, and body weight were measured and subjective responses, that is, thermal comfort, perceived air quality, and acute health symptoms were investigated. At the relative humidity of 70%, increasing indoor temperature from 26 degrees C to 39 degrees C caused a significant decrease in the accuracy of these cognitive tests. However, when the relative humidity decreased from 70% to 50% at 39 degrees C, the accuracy of the cognitive tests increased significantly. Accordingly, the physiological and subjective responses of the subjects changed significantly with the changes in indoor temperature and humidity, which provided a basis to the variation in the cognitive performance. These results indicated that decreasing indoor humidity at extreme high temperature could improve the impaired cognitive performance.
The distribution of temperature and temperature-health association varied largely across different regions in China, a region-specific definition for heatwave was therefore needed. We collected the data on daily mortality, meteorological factors and air pollution in 84 Chinese cities during 2013-2016, which was divided into seven regions. Based on the association between daily maximum temperature and mortality in each city in a threshold distributed lag non-linear model, where the threshold was defined as the temperature corresponding to the lowest mortality risk, we calculated the number of deaths that could be avoided for 1 degrees C decrease in maximum temperature under different thresholds, then a random-effect meta-analysis was used to generate regional results, in which the temperature with the highest avoidable mortality number for 1 degrees C decrease was considered as the most appropriate heatwave definition. We observed an immediate detrimental effect of high temperature within three lag days. Our analysis suggested to use 29.5 degrees C, 31.5 degrees C, 29.0 degrees C, 31.5 degrees C, 30.0 degrees C, and 28.5 degrees C as the heatwave standard for east, north, northeast, central, south, and southwest region, with the avoidable mortality number of 1.54 (95 % Confidence interval (CD: 0.88, 2.19), 0.55 (95 % CI: 0.16, 0.94), 0.59 (95 % CI: 0.32, 0.86), 1.14 (95 % CI: 0.68, 1.59), 1.22 (95 % CI: 0.54, 1.90), and 0.78 (95 % CI: 0.01, 1.55), respectively, while the estimated number 0.19 (95 % CI: -0.02, 0.40) in northwest region was not statistically significant. The concept of ‘avoidable mortality for 1 degrees C decrease’ was proposed to define the heatwave event, and varied maximum temperature between 28.5 and 31.5 degrees C was suggested for region-specific heatwave definition in China.
Food poisoning is caused by pathogenic bacteria in water and aquatic products, especially bivalves (e.g., oysters, clams), which can bioaccumulate pathogenic bacteria. Polluted water and aquatic products thus pose a serious threat to human health and safety. In this study, the types of pathogenic bacteria in water samples and shellfish collected from the Dadeng offshore area in Xiamen were examined. We also analyzed the relationships between dominant pathogens and major climate and water quality parameters. Our objective was to provide reference data that may be used to help prevent bacterial infections and to improve aquatic food hygiene in Xiamen and its surrounding areas to safe levels, thus ensuring the health of Xiamen residents. We found that the main pathogenic bacteria were Vibrio and Bacillus, with the dominant pathogen being Vibrio parahaemolyticus. Physical and chemical indexes (water temperature, salinity, pH, dissolved oxygen, and turbidity) of water bodies and the 3-day accumulated rainfall were found to be important factors affecting the occurrence and abundance of V. parahaemolyticus.
ISSUE ADDRESSED: Across Australia there are inconsistent and varying guidelines or ‘recommendations’ across a number of jurisdictions for the protection of school children from heat-related consequences, yet there is no national policy for heat protection in school settings. The aim of this study was to determine public perceptions of the efficacy of implementing a heat protection policy for Australian schools. METHODS: A sample of public perceptions was drawn upon from public comments posted on a national Australian Broadcasting Corporation (ABC) news article on the proposed heat protection policy. Public comments were analysed using a social-ecological model thematic content analysis. RESULTS: Themes that emerged to support a national heat protection policy for schools included: protection from the consequences of extreme heat, reliance of children on adult/school decisions and utilising modern knowledge/technology advancements. In contrast, criticism emerged relating to the importance of having resilient children, air conditioning costs, perceived over-regulation and heat exposure being a lifestyle choice in some contexts. CONCLUSIONS: Overall, this study provides support for the introduction of a national heat protection policy with a number of key considerations identified for implementation to benefit and protect Australian school children. SO WHAT?: As a number of the heat guidelines are developed by individual organisations with differing messages, determining the public efficacy of comprehensive heat protection strategies can help lead to the development of policy for a widespread and consistent heat protection program across Australian schools.
Constant environmental degradation and increased frequency and severity of natural disasters have been evident over the past few decades worldwide. As such, scientific tools to predict and assess risks keep being developed. Assessing disaster risk is an important task in supporting the transition to a sustainable society. However, as disasters and systems become more complex, disaster models combining diverse aspects including climatic, social, economic, and environmental factors are necessary. For this study, we set a model using the concept of risk by identifying hazards, exposure, and vulnerability. Here, the vulnerability was classified into two domains, sensitivity and adaptive capacity, and two spheres, natural/built environment and human environment. Also, we stressed that controllable geo-spatial indicators should be included in risk assessments to effectively reduce risk and implement adequate spatio-temporal actions. The approach of this study was applied to Kazakhstan and South Korea as a pilot study to develop Agricultural Drought Risk Index (ADRI) and maps. As a result, the agricultural drought risk could be analyzed for South Korea and Kazakhstan. In addition, we performed additional spatial analyses at a reasonable scale for practical use. It was concluded that prioritizing risk areas at administrative and site level could contribute in decision and policy-making for risk reduction. Furthermore, spatial data availability and quality were found to be significant in assessing disaster risk.
Air Quality assessment and forecasting are the essentials today and they attracted many researchers. Environmental organizations regularly monitor and predict the air contaminants to make the public awareness, provide a better environment, and suitable for human health. Physical factors like climate changes, Industrialization, Fires and Urbanization are some of the factors which directly affect and reduce the air quality. All these data are time-series and real-time data. The primary pollutant is PMx that affect the respiratory systems and cardiac activity of humans. The secondary pollutants are SO2, CO, NOx, and O-3. Each has allowable range of concentration levels. In this work, meteorological elements are collected in different locations in last 5 years, with time window of 24 h and mapped to the concentration level of pollutants. The Machine Learning(ML) Methods such as Non-Linear Artificial Neural Network(ANN), Statistical Multilevel Regression, Neuro- Fuzzy and Deep Learning Long-Short-Term Memory (DL-LSTM) are used; to find the current concentration level of pollutants and will be useful for Real Time Correction (RTC) to give a feedback that can be used to reduce the contaminants in air for further days. The results are compared with the parameters such as R-2, RMSE and MAPE. Using these methods, the concentration level of contaminants is predicted with the deviation of R-2 in the range of 0.71-0.89. The results proved that DL-LSTM suits well when comparing to the ANN, Neuro-fuzzy and regression algorithms.
BACKGROUND: During the period 2001 to 2016, the maximum temperatures in Thailand rose from 38-41(o)C to 42-44(o)C. The current occupational heat exposure standard of Thailand issued in 2006 is based on wet bulb globe temperature (WBGT) defined for three workload levels without a work-rest regimen. This study examined whether the present standard still protects most workers. METHODS: The sample comprised 168 heat acclimatized workers (90 in construction sites, 78 in foundries). Heart rate and auditory canal temperature were recorded continuously for 2 hours. Workplace WBGT, relative humidity, and wind velocity were monitored, and the participants’ workloads were estimated. Heat-related symptoms and signs were collected by a questionnaire. RESULTS: Only 55% of the participants worked in workplaces complying with the heat standard. Of them, 79% had auditory canal temperature ? 38.5(o)C, compared with only 58% in noncompliant workplaces. 18% and 43% of the workers in compliant and noncompliant workplaces, respectively, had symptoms from heat stress, the trend being similar across all workload levels. An increase of one degree (C) in WBGT was associated with a 1.85-fold increase (95% confidence interval: 1.44-2.48) in odds for having symptoms. CONCLUSION: Compliance with the current occupational heat standard protects 4/5 of the workers, whereas noncompliance reduces this proportion to one half. The reasons for noncompliance include the gaps and ambiguities in the law. The law should specify work/rest schedules; outdoor work should be identified as an occupational heat hazard; and the staff should include occupational personnel to manage heat stress in establishments involving heat exposure.
BACKGROUND: Dengue is one of the most rapidly spreading vector-borne diseases, which is considered to be a major health concern in tropical and sub-tropical countries. It is strongly believed that the spread and abundance of vectors are related to climate. Construction of climate-based mathematical model that integrates meteorological factors into disease infection model becomes compelling challenge since the climate is positively associated with both incidence and vector existence. METHODS: A host-vector model is constructed to simulate the dynamic of transmission. The infection rate parameter is replaced with the time-dependent coefficient obtained by optimization to approximate the daily dengue data. Further, the optimized infection rate is denoted as a function of climate variables using the Autoregressive Distributed Lag (ARDL) model. RESULTS: The infection parameter can be extended when updated daily climates are known, and it can be useful to forecast dengue incidence. This approach provides proper prediction, even when tested in increasing or decreasing prediction windows. In addition, associations between climate and dengue are presented as a reversed slide-shaped curve for dengue-humidity and a reversed U-shaped curves for dengue-temperature and dengue-precipitation. The range of optimal temperature for infection is 24.3-30.5 °C. Humidity and precipitation are positively associated with dengue upper the threshold 70% at lag 38 days and below 50 mm at lag 50 days, respectively. CONCLUSION: Identification of association between climate and dengue is potentially useful to counter the high risk of dengue and strengthen the public health system and reduce the increase of the dengue burden.
In 2016, an outbreak of anthrax killing thousands of reindeer and affecting dozens of humans occurred on the Yamal peninsula, Northwest Siberia, after 70 years of epidemiological situation without outbreaks. The trigger of the outbreak has been ascribed to the activation of spores due to permafrost thaw that was accelerated during the summer heat wave. The focus of our study is on the dynamics of local environmental factors in connection with the observed anthrax revival. We show that permafrost was thawing rapidly for already 6 years before the outbreak. During 2011-2016, relatively warm years were followed by cold years with a thick snow cover, preventing freezing of the soil. Furthermore, the spread of anthrax was likely intensified by an extremely dry summer of 2016. Concurrent with the long-term decreasing trend in the regional annual precipitation, the rainfall in July 2016 was less than 10% of its 30-year mean value. We conclude that epidemiological situation of anthrax in the previously contaminated Arctic regions requires monitoring of climatic factors such as warming and precipitation extremes.
Flooding is a major natural disaster in Thailand. Dependent older adults are at higher risk because of health conditions and limited mobility. This qualitative study described community flood experiences of family caregivers, and the collaboration of care managers and sub-district administrative officers in the process of flood preparedness for Thai dependent older adults. We conducted in-depth interviews with 15 family caregivers and a focus group with eight administrative and public health officers. We identified several themes of relevance when formulating flood preparedness plans and links between family preparedness and organizational management. A community-based approach is key to successful management of flood preparedness system and involves collaborations between families, communities, and public and private entities.
Human society has experienced, and will continue to experience, extensive loss and damage from worsening anthropogenic climate change. Despite our natural tendencies to categorise and organise, it can be unhelpful to delineate clean boundaries and linear understandings for complex and messy concepts such as loss and damage. Drawing on the perspectives of 42 local and regional Pacific Islander stakeholders, an underexplored resource for understanding loss and damage, we explore the complexity and interconnectedness of non-economic loss and damage (NELD). According to participants, Pacific Islander worldviews, knowledge systems and cosmologies often make it difficult to separate and evaluate NELD independently, challenging the nomenclature of NELD categories developed through international mechanisms. Instead, NELD understandings are often centred on the interdependencies between losses, including the cascading flow-on effects that can occur and the nature of some losses as risk multipliers (i.e. one loss creating the risk for further losses). Most notably, losses to biodiversity, ecosystem services and land are critically linked to, and have cascading effects on, livelihoods, knowledge, ways of life, wellbeing, and culture and heritage. We argue that loss and damage is not always absolute, and that there are NELD that are arguably reparable. Concerning, however, is that biodiversity loss, as a risk multiplier, was considered the least reparable by participants. We put forward that NELD understandings must consider interconnectivity, and that biodiversity and ecosystem conservation and restoration must be the focus for interventions to prevent irreparable and cascading losses from climate change in the Pacific Islands.
The Himalayan rivers are vulnerable to devastating flooding caused by landslides and outbreak of glacial lakes. On 7 February 2021, a deadly disaster occurred near the Rishi Ganga Hydropower Plant in the Rishi Ganga River, killing more than 100 people. During the event, a large volume of debris and broken glacial fragments flooded the Rishi Ganga River and washed away the Rishi Ganga Hydropower plant ongoing project. This study presents the impact of the Chamoli disaster on the water quality of Rishi Ganga River in upstream near Tapovan and Ganga River in downstream near Haridwar through remote sensing data. Five points have been used at different locations across the two study areas and three different indices were used such as Normalized difference water index (NDWI), Normalized difference turbidity Index (NDTI), and Normalized difference chlorophyll index (NDCI), to analyze changes in water quality. Spectral signatures and backscattering coefficients derived from Sentinel-2 Optical and Sentinel-1 Synthetic-aperture radar (SAR) data were also compared to study the changes in water quality. It was evident from the water quality indices and spectral signatures that the flood plains changed significantly. Using spectral signatures and different indices, the water level in the Chilla dam canal near Haridwar was found to decreased after the Chamoli disaster event as the flood gates were closed to stop the deposit of sediments in the canal. Results suggest changes in water quality parameters (turbidity, chlorophyll concentration, NDWI) at the five locations near the deadly site and far away at Haridwar along the Ganga River. This study is a preliminary qualitative analysis showing changes in river flood plain and water quality after the Chamoli disaster.
In this study we examine whether specific ‘anxiety-maintaining’ parenting behaviors (i.e., overinvolvement and/or negativity) exacerbate the effects of disaster-related prenatal maternal stress (PNMS) on school-age anxiety symptoms. Women (N?=?230), pregnant at the time of the 2011 Queensland Floods, reported on their experience of flood-related PNMS (objective hardship, cognitive appraisal, subjective distress). At 4-years, mother-child dyads were coded for maternal overinvolvement and negativity during a challenging task; at 6-years mothers reported on their children’s anxiety symptoms and their own mood, N?=?83. Results showed no associations between PNMS and 6-year anxiety, nor did parenting moderate these effects. Poorer maternal concurrent mood was associated with greater anxiety symptoms at 6 years (??=?0.52). Findings suggest maternal concurrent mood, but not exposure to disaster-related PNMS nor ‘anxiety-maintaining’ parenting behaviors at preschool age, is related to school-age anxiety symptoms.
Epidemiological studies have reported significant associations between weather situations and health. Cardiovascular disease is a serious chronic non-communicable disease which causes mortality and morbidity, bringing large economic burden to patients’ families. This study explored the relationship between cardiovascular disease (CVD) and weather conditions in Changchun, northeast China. The frequency distributions of 13 main circulation weather types (CWTs) were analyzed, and a comparison between air mass classification and hospital admissions was performed for various groups using an admission index (AI). The results indicated that women had a lower risk of CVD than men did. The risk of CVD for older people (aged???65 years) was lower than that for young people (aged?
Some epidemiological studies have confirmed the association between environmental factors and congenital heart defects (CHD). While the possibility that maternal ambient heat exposures are related to CHD has received little attention. Our study aims to investigate the association between maternal ambient extreme heat exposure early in pregnancy and the risk of CHD in offspring in China. We conducted a retrospective cohort study of 1,918,105 fetuses between 2 and 8 weeks after gestation from May to October in Guangdong, China, 2015-2019. The main heat exposure was defined as extreme heat events (EHE) by using the 90th (EHE90) or 95th (EHE95) percentile of the daily maximum temperature. For each EHE definition, we further defined four indicators: having EHE or not, frequency, duration, and cumulative days. We used the log-binomial regression models to calculate the prevalence ratios (PR) of CHD with 95% confidence intervals (CI) for the associations between CHD and EHE, adjusted for potentially confounding covariates. There are 1,918,105 infants included in the study, of which 9588 had CHD, with a prevalence rate of 499.9 per 100,000 (95% CI: 489.9, 509.8). We found that all EHE indicators were positively associated with the increased risks of overall CHD, some CHD classes (congenital malformations of cardiac septa, congenital malformations of great arteries, and congenital malformations of great arteries), and some CHD subtypes (atrial septal defect and patent ductus arteriosus). In addition, the PR yielded higher estimates when exposing to EHE95. For instance, the risk of suffering congenital malformations of great arteries was 1.548 (95% CI: 1.401, 1.712) for EHE90 exposure and 1.723 (95% CI: 1.565, 1.898) for EHE95 exposure, respectively. Our study demonstrated that EHE during 2-8 weeks postconception was associated with overall CHD in offspring, particularly atrial septal defects and patent ductus arteriosus. The associations strengthened with the extent and cumulative days of maternal exposure to EHE.
BACKGROUND: Understanding the association between floods and bacillary dysentery (BD) incidence is necessary for us to assess the health risk of extreme weather events. This study aims at exploring the association between floods and daily bacillary dysentery cases in main urban areas of Chongqing between 2005 and 2016 as well as evaluating the attributable risk from floods. METHODS: The association between floods and daily bacillary dysentery cases was evaluated by using distributed lag non-linear model, controlling for meteorological factors, long-term trend, seasonality, and day of week. The fraction and number of bacillary dysentery cases attributable to floods was calculated. Subgroup analyses were conducted to explore the association across age, gender, and occupation. RESULTS: After controlling the impact of temperature, precipitation, relative humidity, long-term trend, and seasonality, a significant lag effect of floods on bacillary dysentery cases was found at 0-day, 3-day, and 4-day lag, and the cumulative relative risk (CRR) over a 7-lag day period was 1.393 (95%CI 1.216-1.596). Male had higher risk than female. People under 5?years old and people aged 15-64?years old had significantly higher risk. Students, workers, and children had significantly higher risk. During the study period, based on 7-lag days, the attributable fraction of bacillary dysentery cases due to floods was 1.10% and the attributable number was 497 persons. CONCLUSIONS: This study confirms that floods can increase the risk of bacillary dysentery incidence in main urban areas of Chongqing within an accurate time scale, the risk of bacillary dysentery caused by floods is still serious. The key population includes male, people under 5?years old, students, workers, and children. Considering the lag effect of floods on bacillary dysentery, the government and public health emergency departments should advance to the emergency health response in order to minimize the potential risk of floods on public.
BACKGROUND: Existing evidence has suggested that heat exposure was associated with increase of low-density lipoprotein (LDL) and decrease of high-density lipoprotein (HDL). This study aimed to assess the effects of extreme temperatures (i.e., heat and cold) on hospitalizations and post-discharge deaths for stroke amongst individuals with and without pre-existing hyperlipidemia, and examine whether individual- and community-level characteristics modified the temperature-stroke relationship. METHODS: People who were hospitalized for stroke from 1(st) January 2005 to 31(st) December 2013 in Brisbane, Australia, and died from stroke within two months after discharge were included in this cohort study. The effects of extreme temperatures on hospitalizations and post-discharge deaths for stroke in patients with and without pre-existing hyperlipidemia were quantified using a time-stratified case-crossover design with conditional logistic regression. Suburb-level temperature data were used to minimize exposure measurement bias. Relative humidity, NO(2) and PM(10) were adjusted as potential confounders in the regression. Subgroup analyses were conducted to examine if age, sex, and suburb-level greenspace (measured as normalized difference vegetation index (NDVI)) and socioeconomic status (measured as Socio-Economic Indexes for Areas (SEIFA)) modified the temperature-stroke relationship in the hyperlipidemia group and the non-hyperlipidemia group. RESULTS: There were 11,469 hospitalizations for stroke during the study period, and 2270 (19.79%) of them died within two months after discharge. Significant effect of heat on hospitalizations for stroke was observed only in individuals with pre-existing hyperlipidemia (odds ratio (OR): 1.85; 95% confidence interval (CI): 1.07-3.19), and significant effect of cold on hospitalizations was found in individuals without pre-existing hyperlipidemia (OR: 1.60; 95% CI: 1.03-2.47). Males appeared to be more vulnerable to the effects of heat and cold on hospitalizations for stroke than females. People living in suburbs with low-level greenspace (OR: 4.23; 95% CI: 1.08-16.61) were more vulnerable to heat effect on stroke hospitalizations than those living in suburbs with high-level greenspace (OR: 1.41; 95% CI: 0.32-6.16). People living in suburbs with the lowest socioeconomic advantage level or the lowest economic resources level were most vulnerable the effects of heat and cold on hospitalizations for stroke. No significant effect of heat or cold on post-discharge deaths from stroke was observed. CONCLUSIONS: This study provides suggestive evidence that heat adaptation strategies aiming to reduce stroke attacks may need to target those individuals with pre-existing hyperlipidemia.
In addition to several negative environmental effects, climate change, which reduces bioclimatic comfort levels especially in urban areas, also has economic implications, especially in cities where the economic structure is tourism-oriented. Considering most of the tourism practices are based on outdoor activities in cities such as Antalya, it is of great importance to determine bioclimatic comfort level as well as the attitudes of people toward climate change who live in those conditions to be able to take proper precautions in terms of tourism and urban planning. Therefore, the purpose of this study was to reveal the bioclimatic comfort conditions of Antalya city center, and a comprehensive questionnaire was conducted with the people living in the area questioning the opinions on reasons and consequences of climate change, perceivable effects of climate change in Antalya, and suggestions to prevent or reduce the adverse effects. The areas with appropriate bioclimatic comfort conditions were determined and mapped via geographical information systems using temperature and relative humidity data of the years between 1960 and 2018. The data gathered via questionnaires were analyzed using confirmatory factor analysis, regression, correlation, and structural equation modelling via SPSS and AMOS software. According to the results, it was determined that in some parts of city center the bioclimatic comfort conditions decreased to levels that could reach harmful dimensions for human health and the analysis of the questionnaires revealed that people living in that area state that the effects of climate change are perceivable as the precipitation seasons have become irregular. According to the participants, it was determined that a 1-unit increase in environmental measures causes a decrease of 0.136 units in disasters (R(2)?=?1.1%). In comparison, 1-unit increase of Administrative Precautions will cause 0.030 units decrease in effects of climate change on vital needs (R(2)?=?1.4%). These analysis results show that the respondents expect the disaster scenarios to decrease when environmental measures are increased.
Disastrous bushfires during the last months of 2019 and January 2020 affected Australia, raising the question to what extent the risk of these fires was exacerbated by anthropogenic climate change. To answer the question for southeastern Australia, where fires were particularly severe, affecting people and ecosystems, we use a physically based index of fire weather, the Fire Weather Index; long-term observations of heat and drought; and 11 large ensembles of state-of-the-art climate models. We find large trends in the Fire Weather Index in the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis (ERA5) since 1979 and a smaller but significant increase by at least 30% in the models. Therefore, we find that climate change has induced a higher weather-induced risk of such an extreme fire season. This trend is mainly driven by the increase of temperature extremes. In agreement with previous analyses we find that heat extremes have become more likely by at least a factor of 2 due to the long-term warming trend. However, current climate models overestimate variability and tend to underestimate the long-term trend in these extremes, so the true change in the like-lihood of extreme heat could be larger, suggesting that the attribution of the increased fire weather risk is a conservative estimate. We do not find an attributable trend in either extreme annual drought or the driest month of the fire season, September-February. The observations, however, show a weak drying trend in the annual mean. For the 2019/20 season more than half of the July-December drought was driven by record excursions of the Indian Ocean Dipole and Southern Annular Mode, factors which are included in the analysis here. The study reveals the complexity of the 2019/20 bushfire event, with some but not all drivers showing an imprint of anthropogenic climate change. Finally, the study concludes with a qualitative review of various vulnerability and expo- sure factors that each play a role, along with the hazard in increasing or decreasing the overall impact of the bushfires.
Several theories exist regarding the role of memory in the development of PTSD. The metacognitive model of PTSD contends beliefs about trauma memory are pivotal in the development and maintenance of PTSD. The Beliefs About Memory Questionnaire (BAMQ) was developed to measure metacognitive beliefs about trauma memory. This study aimed to test the psychometric properties of the BAMQ and its relationship to PTSD in a community sample of 674 adults exposed to the 2010-2011 Canterbury earthquakes and Queensland floods. Participants completed a series of online, self-report questionnaires between October and December 2012, exploring thinking and memory processes related to their experience of a natural disaster. Factor analysis validated the two-factor, positive and negative structure of the BAMQ. Convergent, concurrent, and discriminant validity was established through positive relationships with relevant metacognitive beliefs, thought control variables, and risk factors related to PTSD. Logistic regression revealed scores on the BAMQ predicted clinically significant symptoms of PTSD. The psychometric properties of the BAMQ suggest the instrument is a valuable addition to the assessment of metacognitive beliefs about trauma memory, and the utility of the BAMQ in the prediction of clinically significant symptoms of PTSD.
The 2020 summer Olympic and Paralympic Games in Tokyo were postponed to July-September 2021 due to the coronavirus disease 2019 (COVID-19) pandemic. While COVID-19 has emerged as a monumental health threat for mass gathering events, heat illness must be acknowledged as a potentially large health threat for maintaining health services. We examined the number of COVID-19 admissions and the Tokyo rule for emergency medical care, in Tokyo, from March to September 2020, and investigated the weekly number of emergency transportations due to heat illness and weekly averages of the daily maximum Wet Bulb Globe Temperature (WBGT) in Tokyo in the summer (2016-2020). The peak of emergency transportations due to heat illness overlapped the resurgence of COVID-19 in 2020, and an increase of heat illness patients and WBGT has been observed. Respect for robust science is critical for the decision-making process of mass gathering events during the pandemic, and science-based countermeasures and implementations for COVID-19 will be warranted. Without urgent reconsiderations and sufficient countermeasures, the double burden of COVID-19 and heat-related illnesses in Tokyo will overwhelm the healthcare provision system, and maintaining essential health services will be challenging during the 2021 summer Olympic and Paralympic Games.
Climate change poses significant threats to wellbeing and livelihoods of people and the ecosystems in many Small Island Developing States (SIDS). Adaptation solutions must counteract these threats while also supporting development in vulnerable SIDS. Suitable options need to ensure that connections between the social, economic, and environmental dimensions of socio-economic systems are defined in a way that can support how decisions are made (and by whom) and how these can impact on other parts of these systems. This is particularly important in many Pacific SIDS, where communities practise customary natural resource management and continue to rely on local natural resources. In this study, we model the anticipated impacts of climate change and the benefits of the ecosystem-based adaptation (EbA) approaches on community wellbeing in Vanuatu. To do this, we applied participatory and expert elicitation methods to develop a Bayesian network model, which was designed to evaluate community wellbeing responses at four explicit spatial scales. The model includes both acute and chronic impacts of climate change, the impact of coral bleaching, and the potential loss of Vanuatu’s fringing coral reefs. The model predicts that all proposed EbA interventions will have a positive impact on wellbeing in all four locations to some degree, by either directly improving the integrity of Vanuatu’s ecosystems or by protecting these ecosystems as a positive spill-over of related actions. Significantly, it also predicts that if climate change exceeds 1.5 degrees C of warming, the costs of achieving the same level of wellbeing are increased.
What is already known on this topic? The health risk caused by high-temperatures depends on the interaction between high temperature exposure and the sensitivity and adaptability of the affected populations. What is added by this report? A comprehensive assessment model was established by principal component analysis using the data of 19 cities, 15 provincial-level administrative divisions and used to identify regional characteristics and major influencing factors of health vulnerability to extreme heat in China. What are the implications for public health practice? The results of the health vulnerability assessment could effectively identify the regions highly vulnerable to extreme heat in China and provide scientific evidence for the development of adaptive measures and resource allocation plans.
The present study aims to assess the recent changes and trends in the extreme climate indices in the Kashmir basin using the observational records from 1980 to 2016. The extreme climate indices were computed using the ClimPACT2 software and a total of 39 indices were selected for the analysis having particular utility to various sectors like agriculture, water resources, energy consumption, and human health. Besides adopting the station scale analysis, regional averages were computed for each index. In terms of the mean climatology, an increase has been observed in the annual mean temperature with a magnitude of 0.024 °C/year. Further, differential warming patterns have been observed in the mean maximum and minimum temperatures with mean maximum temperature revealing higher increases than mean minimum temperature. On the other hand, the annual precipitation shows a decrease over most of the region, and the decreases are more pronouncing in the higher altitudes. The trend analysis of the extreme indices reveals that in consonance with the rising temperature there has been an increase in the warm temperatures and decrease in the cold temperatures across the Kashmir basin. Furthermore, our analysis suggests a decrease in the extreme precipitation events. The drought indices viz., Standardised Precipitation Index (SPI), and Standardised Precipitation Evapotranspiration Index (SPEI) manifest decreasing trends with the tendency towards drier regimes implying the need for better water resource management in the region under changing climate.
Many studies have explored the association between temperature and atopic dermatitis (AD); however, the results are inconsistent. We used a quasi-Poisson function fitted to a distributed lag nonlinear model (DLNM) to evaluate the association between daily average temperature and AD outpatient visits from January 1, 2013, to December 31, 2019, in Lanzhou, China. We found that the exposure-response association curve was inversely “s-shaped,” low-temperature effects occurred at a lag of 11 days and then lasted for 10 days, and high-temperature effects occurred on the current day and then significantly decreased. Both low and high ambient temperatures can increase the risk of outpatient visits. Compared with median temperature (12.89°C), the cumulative relative risk (RR) of extreme high temperature and moderate-high temperature were 1.847 (95% confidence interval [CI]: 1.613, 2.114) and 1.447 (95% CI: 1.298, 1.614), respectively, at lag0-7 days, and the cumulative RRs of extremely low temperature and moderate-low temperature were 1.004 (95% CI: 0.904, 1.115) and 1.056 (95% CI: 0.925, 1.205), respectively, at lag0-21 days. Females were more sensitive to high temperatures than males, and high or low temperatures had significant effects on children ?14 years of age. Graphical abstract.
People with chronic obstructive pulmonary disease, cardiovascular disease, or hypertension have a high risk of developing severe coronavirus disease 2019 (COVID-19) and of COVID-19 mortality. However, the association between long-term exposure to air pollutants, which increases cardiopulmonary damage, and vulnerability to COVID-19 has not yet been fully established. We collected data of confirmed COVID-19 cases during the first wave of the epidemic in mainland China. We fitted a generalized linear model using city-level COVID-19 cases and severe cases as the outcome, and long-term average air pollutant levels as the exposure. Our analysis was adjusted using several variables, including a mobile phone dataset, covering human movement from Wuhan before the travel ban and movements within each city during the period of the emergency response. Other variables included smoking prevalence, climate data, socioeconomic data, education level, and number of hospital beds for 324 cities in China. After adjusting for human mobility and socioeconomic factors, we found an increase of 37.8% (95% confidence interval [CI]: 23.8%-52.0%), 32.3% (95% CI: 22.5%-42.4%), and 14.2% (7.9%-20.5%) in the number of COVID-19 cases for every 10-?g/m(3) increase in long-term exposure to NO(2), PM(2.5), and PM(10), respectively. However, when stratifying the data according to population size, the association became non-significant. The present results are derived from a large, newly compiled and geocoded repository of population and epidemiological data relevant to COVID-19. The findings suggested that air pollution may be related to population vulnerability to COVID-19 infection, although the extent to which this relationship is confounded by city population density needs further exploration.
In the present study, we aim to evaluate the delayed and cumulative effect of ozone (O(3)) exposure on mumps in a megacity with high population density and high humidity. We took Chongqing, a megacity in Southwest China, as the research area and 2013-2017 as the research period. A total of 49,258 confirmed mumps cases were collected from 122 hospitals of Chongqing. We employed the distributed lag nonlinear models with quasi-Poisson link to investigate the relationship between prevalence of mumps and O(3) exposure after adjusting for the effects of meteorological conditions. The results show that the effect of O(3) exposure on mumps was mainly manifested in the lag of 0-7 days. The ?single-day ;lag effect was the most obvious on the 4th day, with the relative risk (RR) of mumps occurs of 1.006 (95% CI: 1.003-1.007) per 10 ?g/m(3) in the O(3) exposure. The cumulative RR within 7 days was 1.025 (95% CI: 1.013-1.038). Our results suggest that O(3) exposure can increase the risk of mumps infection, which fills the gap of relevant research in mountainous areas with high population density and high humidity.
OBJECTIVE: The aim of this study was to determine whether an association existed between intussusception and air temperature. METHODS: A retrospective study was performed between March 2006 and February 2016 to determine the relationship between pediatric primary intussusception (PPI) and air temperature. Information from hospital records of 5922 cases of PPI and Mean daily temperatures of Shenyang were obtained. Pearson correlation analysis was used to examine the association between monthly PPI cases and monthly mean temperature. Factorial analysis-of-variance was used to examine differences in the numbers of seasonal PPI cases during different seasons. RESULTS: Monthly PPI cases fluctuated throughout the year, with a peak in June, and a trough in February. Pearson correlation analysis showed that monthly PPI cases was associated with the monthly mean temperature (p < 0.01). Factorial analysis-of-variance showed there was significant difference in the numbers of seasonal PPI cases during different seasons. Multiple comparison showed a significant difference in seasonal PPI cases between spring and summer, spring and winter, summer and autumn, summer and winter, autumn and winter (p < 0.01). CONCLUSIONS: Monthly PPI cases were positively associated with monthly mean temperature in Shenyang. The incidence of intussusception shows a seasonal trend, with a peak in summer (May to July).
Evidence of the impact of ambient temperatures on emergency ambulance calls (EACs) in developing countries contributes to the improvement and complete understanding of the acute health effects of temperatures. This study aimed to examine the impacts and burden of heat on EACs in China, quantify the contributions of regional modifiers, and identify the vulnerable populations. A semi-parametric generalized additive model with a Poisson distribution was used to analyze the city-specific impacts of the daily maximum temperature (T-ma(x)) on EACs in June-August in 2014-2017. Stratified analyses by sex and age were performed to identify the vulnerable sub-populations. Meta-analysis was undertaken to illustrate the pooled associations. Further subgroup analysis, stratified by climate, latitude, and per capita disposable income (PCDI), and meta-regression analysis were conducted to explore the regional heterogeneity and quantify the contributions of possible modifiers. The city- and region-specific attributable fractions of EACs attributable to heat were calculated. Strong associations were observed between the daily T-max and total EACs in all cities. A total of 11.7% (95% confidence interval (CI): 11.2%-12.3%) of EACs were attributed to high temperatures in ten Chinese cities, and the central region with a low level of PCDI had the highest attributable fraction of 17.8% (95% CI: 17.2%-18.4%). People living in the central region with lower PCDI, and those aged 18-44 and 0-6 years were more vulnerable to heat than the others. The combined effects of PCDI, temperature, and latitude contributed 88.6% of the regional heterogeneity. The results complemented the understanding of the burden of EACs attributable to heat in developing countries and the quantitative contribution of regional modifiers.
BACKGROUND: Ozone pollution keeps deteriorating in the context of climate change. Maternal ozone exposure may be associated with low birth weight (LBW), but the results are still inconsistent. The identification of the critical exposure windows, a specific period of particular susceptibility during pregnancy, remains unresolved. We aimed to evaluate whether ozone exposure was associated with term LBW and further identify the susceptible exposure windows. METHODS: A retrospective cohort study was conducted in Guangzhou, a megacity in the most populous and economically developed city clusters in China. We included 444,096 singleton live births between January 2015 and July 2017. From 11 fixed stations, we collected daily 1-h maximum and 8-h maximum moving average ozone level (O(3)-1 h and O(3)-8 h) and calculated exposures for each participant based on their district of residence during pregnancy. We used traditional Logistic regression to estimate the trimester-specific association between ozone exposure and term LBW, and further estimated monthly- and weekly association by distributed lag models (DLMs) with Logistic regression. Odds ratios (ORs) and 95% confidence intervals (CIs) of term LBW were calculated for an interquartile range (IQR) increase in ozone exposure. Stratified analyses and heterogeneity tests were conducted by maternal age and infant sex. RESULTS: The incidence of term LBW was 1.9%. During the study period, the mean O(3)-1 h and O(3)-8 h levels were 112.6 µg/m(3) and 84.5 µg/m(3), respectively. Increased O(3)-1 h (IQR: 90 µg/m(3)) and O(3)-8 h (73 µg/m(3)) exposure during the second trimester were associated with increased risk of term LBW. At a monthly level, the term LBW risk was associated with O(3)-1 h exposure during the 4th-6th month and O(3)-8 h exposure during the 6th month. By estimating the weekly-specific association, we observed that critical exposure windows were the 15th- 26th gestational weeks for O(3)-1 h, and the 20th-26th weeks for O(3)-8 h, respectively. Estimated ORs and 95% CIs ranged from 1.012 (1.000, 1.024) to 1.023 (1.007, 1.039). When examined by subgroups, the effects were present among women ? 35 years or < 25 years old and those with female babies. CONCLUSIONS: This study provides compelling evidence that exposure to O(3) was associated with increased risk of term LBW, and gestational weeks 15th- 26th was found to be particularly susceptible. These findings provide a research basis for further mechanism examination, public health interventions, and targeted environmental policy-making.
Most studies of short-term exposure to ambient air pollution and cerebrovascular diseases focused on specific stroke-related outcomes, and results were inconsistent due to data unavailability and limited sample size. It is unclear yet how ambient air pollution contributes to the total cardiovascular mortality in central China. Daily deaths from cerebrovascular diseases were obtained from the Disease Surveillance Point System (DSPs) of Wuhan Center for Disease Control and Prevention during the period from 2013 to 2019. Air pollution data were obtained from Wuhan Ecology and Environment Institute from 10 national air quality monitoring stations, including average daily PM(2.5), PM(10), SO(2), NO(2), and O(3). Average daily temperature and relative humidity were obtained from Wuhan Meteorological Bureau. We performed a Poisson regression in generalized additive models (GAM) to examine the association between ambient air pollution and cerebrovascular disease mortality. We observed a total of 84,811 deaths from cerebrovascular diseases from 1 January 2013 to 31 December 2019 in Wuhan. Short-term exposure to PM(2.5), PM(10), SO(2), and NO(2) was positively associated with daily deaths from cerebrovascular diseases, and no significant association was found for O(3). The largest effect on cerebrovascular disease mortality was found at lag0 for PM(2.5) (ERR: 0.927, 95% CI: 0.749-1.105 per 10 ?g/m3) and lag1 for PM(10) (ERR: 0.627, 95% CI: 0.493-0.761 per 10 ?g/m(3)), SO(2) (ERR: 2.518, 95% CI: 1.914, 3.122 per 10 ?g/m(3)), and NO(2) (ERR: 1.090, 95% CI: 0.822-1.358 per 10 ?g/m(3)). The trends across lags were statistically significant. The stratified analysis demonstrated that females were more susceptible to SO(2) and NO(2), while elder individuals aged above 65 years old, compared with younger people, suffered more from air pollution, especially from SO(2). Short-term exposure to PM(2.5), PM(10), SO(2), and NO(2) were significantly associated with a higher risk of cerebrovascular disease mortality, and elder females seemed to suffer more from air pollution. Further research is required to reveal the underlying mechanisms.
Little is known about the association between ambient temperature and DNA methylation, which is a potential biological process through which ambient temperature affects health. This study aimed to evaluate the association between ambient temperature and DNA methylation across human genome. We included 479 Australian women, including 132 twin pairs and 215 sisters of these twins. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on average ambient temperature during eight different exposure windows [lag0d (the blood draw day), lag0-7d (the current day and previous seven days prior to blood draw), lag0-14d, lag0-21d, lag0-28d, lag0-90d, lag0-180d, and lag0-365d)] was linked to each participant’s home address. For each cytosine-guanine dinucleotide (CpG), we evaluated the association between its methylation level and temperature using generalized estimating equations (GEE), adjusting for important covariates. We used comb-p and DMRcate to identify differentially methylated regions (DMRs). We identified 31 CpGs at which blood DNA methylation were significantly associated with ambient temperature with false discovery rate [FDR] < 0.05. There were 82 significant DMRs identified by both comb-p (Sidak p-value < 0.01) and DMRcate (FDR < 0.01). Most of these CpGs and DMRs only showed association with temperature during one specific exposure window. These CpGs and DMRs were mapped to 85 genes. These related genes have been related to many human chronic diseases or phenotypes (e.g., diabetes, arthritis, breast cancer, depression, asthma, body height) in previous studies. The signals of short-term windows (lag0d and lag0-21d) showed enrichment in biological processes related to cell adhesion. In conclusion, short-, medium-, and long-term exposures to ambient temperature were all associated with blood DNA methylation, but the target genomic loci varied by exposure window. These differential methylation signals may serve as potential biomarkers to understand the health impacts of temperature.
BACKGROUND: The health impacts of temperatures are gaining attention in Australia and worldwide. While a number of studies have investigated the association of temperatures with the risk of cardiovascular diseases, few examined out-of-hospital cardiac arrest (OHCA) and none have done so in Australia. This study examined the exposure-response relationship between temperatures, including heatwaves and OHCA in Brisbane, Australia. METHODS: A quasi-Poisson regression model coupled with a distributed lag non-linear model was employed, using OHCA and meteorological data between 1 January 2007 and 31 December 2019. Reference temperature was chosen to be the temperature of minimum risk (21.4°C). Heatwaves were defined as daily average temperatures at or above a heat threshold (90th, 95th, 98th, 99th percentile of the yearly temperature distribution) for at least two consecutive days. RESULTS: The effect of any temperature above the reference temperature was not statistically significant; whereas low temperatures (below reference temperature) increased OHCA risk. The effect of low temperatures was delayed for 1 day, sustained up to 3 days, peaking at 2 days following exposures. Heatwaves significantly increased OHCA risk across the operational definitions. When a threshold of 95th percentile of yearly temperature distribution was used to define heatwaves, OHCA risk increased 1.25 (95% CI 1.04 to 1.50) times. When the heat threshold for defining heatwaves increased to 99th percentile, the relative risk increased to 1.48 (1.11 to 1.96). CONCLUSIONS: Low temperatures and defined heatwaves increase OHCA risk. The findings of this study have important public health implications for mitigating strategies aimed at minimising temperature-related OHCA.
Climate change and mental health concerns are both defining issues of the generation of today. It has been established that the worsening climate causes many environmental disasters and physical health problems. However, its psychological impacts are still not well understood. Climate change has brought about an emerging psychological phenomenon termed ‘climate anxiety’ or ‘eco-anxiety,’ which has been described as a “chronic fear of environmental doom” (Clayton et al., 2017, p. 68) due to the impact of climate change. This predictive cross-sectional study investigated the link between climate change anxiety and mental health among 433 Filipinos. A total of 145 males and 288 females aged 18 to 26 completed the Climate Change Anxiety Scale and the Mental Health Inventory (MHI-38). Results show a significant relationship between climate change anxiety and mental health, with climate change anxiety predicting 13.5% of the overall Mental Health Index variance. Significantly, climate change anxiety was associated with the MHI-38’s global scale of Psychological Distress but not with the global scale of Psychological Well-being. The findings are discussed concerning the broader context of research on the mental health impacts of climate change.
Hot weather not only impacts upon human physical comfort and health, but also impacts the way that people access and experience active travel options such as walking and cycling. By evaluating the street thermal environment of a city alongside an assessment of those communities that are the most vulnerable to the effects of heat, we can prioritise areas in which heat mitigation interventions are most needed. In this paper, we propose a new approach for policy makers to determine where to delegate limited resources for heat mitigation with most effective outcomes for the communities. We use eye-level street panorama images and community profiles to provide a bottom-up, human-centred perspective of the city scale assessment, highlighting the situation of urban tree shade provision throughout the streets in comparison with environmental and social-economic status. The approach leverages multiple sources of spatial data including satellite thermal images, Google street view (GSV) images, land use and demographic census data. A deep learning model was developed to automate the classification of streetscape types and percentages at the street- and eye-view level. The methodology is metrics based and scalable which provides a data driven assessment of heat-related vulnerability. The findings of this study first contribute to sustainable development by developing a method to identify geographical areas or neighbourhoods that require heat mitigation; and enforce policies improving tree shade on routes, as a heat adaptation strategy, which will lead to increasing active travel and produce significant health benefits for residents. The approach can be also used to guide post COVID-19 city planning and design.
The mean radiant temperature (T(mrt)) is the most important meteorological factor influencing human thermal comfort in urban areas. Numerous methods have been implemented for estimating T(mrt) using measured radiometer or thermometer data, and exhibit different levels of accuracy. This study presents a simple technique based on the traditional method (T(mrt_TM)) to estimate T(mrt) by utilizing measured radiation data from the radiometers. The estimated T(mrt) values from the six-directional method (T(mrt_SM)) and two black globe thermometer methods (T(mrt_BG) and T(mrt_BGv)) at two stations (sky view factor 0.69 and 0.94) in Jeju, Republic of Korea, for 8 days (5 sunny days, 3 (semi-) cloudy days) in spring and summer were used to validate the T(mrt_TM). The results showed that the mean differences between T(mrt_TM) and T(mrt_SM) were within the required accuracy for comfort in ISO 7726 (±?2 ?) on sunny days and were reduced to 0.1-0.3 ? in high T(mrt) conditions such as clear summer days. The T(mrt_BG) in most sunny and semi-cloudy days and T(mrt_BGv) on all days resulted in large mean differences from the T(mrt_TM) that exceeded the required accuracy for thermal stress in ISO 7726 (±?5 ?). Therefore, both black globe thermometer methods should be used carefully when estimating T(mrt), especially during sunny days. The correlations between T(mrt_TM) and T(mrt_SM) were highly significant, 0.93 on all days (p?=?0.01). The newly developed regression equations between T(mrt_TM) and T(mrt_SM) could reduce mean differences within 0.5 ? for all days, and their r(2) values exceeded 0.87. Therefore, the simple T(mrt_TM) technique can be used for T(mrt) estimation in human thermal comfort studies.
A comprehensive risk assessment of different types of natural disasters at the county level can promote quantitative disaster risk assessment and can provide a scientific basis for the formulation of disaster prevention measures. Focusing on climate-related hazards and based on natural disaster risk assessment theories and methods, this study integrates disaster statistics, meteorological data, geographic information, and other multivariate data to quantify the hazards of various disasters and the vulnerability and exposure of hazard-bearing bodies and conducts an integrated assessment of comprehensive risks of multiple climate-related hazards in Cangnan County, Zhejiang Province. Typhoon disaster risk is high in the central and northern parts of this county and low in its surroundings, with high-risk areas mainly distributed in Lingxi Town to the north. The comprehensive risk distribution patterns of drought and flood disasters in Cangnan County are similar: low in the south and high in the north. With the method of standard deviation, the comprehensive risk of multiple climate-related hazards in Cangnan County shows a distribution pattern of being low in the south and high in the north, with high risk in the northeast and low risk in the northwest and south.
Ambient air pollutants have been linked to adverse health outcomes, but evidence is still relatively rare in college students. Upper respiratory tract infection (URTI) is a common disease of respiratory system among college students. In this study, we assess the acute effect of air pollution on clinic visits of college students for URTI in Wuhan, China. Data on clinic visits due to URTI were collected from Wuhan University Hospital, meteorological factors (including daily temperature and relative humidity) provided by Wuhan Meteorological Bureau, and air pollutants by Wuhan Environmental Protection Bureau. In the present study, generalized additive model with a quasi-Poisson distribution link function was used to examine the association between ambient air pollutants (fine particulate matter (PM(2.5)), particulate matter (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), and ozone (O(3))) and the daily number of clinic visits of college students for URTI at Wuhan University Hospital in Wuhan, China. In the meantime, the model was adjusted for the confounding effects of long-term trends, seasonality, day of the week, public holidays, vacation, and meteorological factors. The best degrees of free in model were selected based on AIC (Akaike Information Criteria). The effect modification by gender was also examined. A total of 44,499 cases with principal diagnosis of URTI were included from January 1, 2016, to December 31, 2018. In single-pollutant models, the largest increment of URTI visits were found at lag 0 day in single-day lags, and the effect values in cumulative lags were greater than those in single-day lags. PM(2.5) (0.74% (95%CI: 0.05, 1.44)) at lag 0 day, PM(10) (0.61% (95%CI: 0.12, 1.11)) and O(3) (1.01% (95%CI: 0.24, 1.79)) at lag 0-1 days, and SO(2) (9.18% (95%CI: 3.27, 15.42)) and NO(2) (3.40% (95% CI:1.64, 5.19)) at lag 0-3 days were observed to be strongly and significantly associated with clinic visits for URTI. PM(10) and NO(2) were almost still significantly associated with URTI after controlling for the other pollutants in our two-pollutant models, where the effect value of SO(2) after inclusion of O(3) appeared to be the largest and the effects of NO(2) were also obvious compared with the other pollutants. Subgroups analysis demonstrated that males were more vulnerable to PM(10) and O(3), while females seemed more vulnerable to exposure to SO(2) and NO(2). This study implied that short-term exposure to ambient air pollution was associated with increased risk of URTI among college students at Wuhan University Hospital in Wuhan, China. And gaseous pollutants had more negative health impact than solid pollutants. SO(2) and NO(2) were the major air pollutants affecting the daily number of clinic visits on URTI, to which females seemed more vulnerable than males.
Conjunctivitis is one of the most common eye-related health problems and significantly influences patients’ quality of life. Whether air pollution increased the risks of conjunctivitis is still unclear. Daily counts of outpatient visits for conjunctivitis, air pollution, and meteorological data during January 1, 2015-December 31, 2019 were collected from Tai’an, China. Generalized additive model with Poisson distribution was used to estimate the relationship between air pollution and visits for conjunctivitis, after controlling for the long-term and seasonal trends, weather variables, and day of the week. The effect of air pollution on visits for conjunctivitis was generally acute and significant at the current day and disappeared after 2 days. The relative risk of conjunctivitis visits associated with per 10 ?g/m(3) increases in PM(2.5), PM(10), SO(2), and NO(2) at lag 0-2 days was 1.006 (95% CI: 1.001-1.011), 1.003 (95% CI: 1.000-1.0107), 1.023 (95% CI: 1.009-1.037), and 1.025 (95% CI: 1.010-1.040), respectively. The impact of air pollution on visits for conjunctivitis varied greatly by individual characteristics. The impact of NO(2) was higher in males than in females, with the opposite trend for SO(2) and PM(2.5). Effect estimates of air pollutants were higher among return visits for conjunctivitis, the elderly, and white-collar workers. Our study highlights that the vulnerable subpopulations should pay more attention to protect themselves from air pollution.
The air quality and human health impacts of wildfires depend on fire, meteorology, and demography. These properties vary substantially from one region to another in China. This study compared smoke from more than a dozen wildfires in Northeast, North, and Southwest China to understand the regional differences in smoke transport and the air quality and human health impacts. Smoke was simulated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) with fire emissions obtained from the Global Fire Emission Database (GFED). Although the simulated PM2.5 concentrations reached unhealthy or more severe levels at regional scale for some largest fires in Northeast China, smoke from only one fire was transported to densely populated areas (population density greater than 100 people/km(2)). In comparison, the PM2.5 concentrations reached unhealthy level in local densely populated areas for a few fires in North and Southwest China, though they were very low at regional scale. Thus, individual fires with very large sizes in Northeast China had a large amount of emissions but with a small chance to affect air quality in densely populated areas, while those in North and Southwest China had a small amount of emissions but with a certain chance to affect local densely populated areas. The results suggest that the fire and air quality management should focus on the regional air quality and human health impacts of very large fires under southward/southeastward winds toward densely populated areas in Northeast China and local air pollution near fire sites in North and Southwest China.
To assess YLL and mortality burden attributable to non-optimum ambient temperature, we collected mortality and environmental data from June 1, 2012 to December 30, 2017 in Shenzhen. We applied distributed lag nonlinear models with 21 days of lag to examine temperature-YLL and temperature-mortality associations, and calculated the attributable fractions of YLL and deaths for non-optimum temperature, including four subranges, mild cold, mild heat, extreme cold, and extreme heat. Cold and heat were distinguished by the optimum temperature, and each was separated into extreme and mild by cutoffs at 2.5th (12.2?°C) and 97.5th (30.4?°C) temperature percentile further. The optimum temperature was defined as the temperature that had minimum effect on YLL or mortality risk. The optimum temperature for non-accidental YLL was 24.5?°C, and for mortality it was 25.4?°C. Except for the population older than 65 years, the optimum temperature was generally lower in the YLL model than the mortality model. Of the total 61,576 non-accidental deaths and 1,350,835.7 YLL within the study period, 17.28% (95% empirical CI 9.42-25.14%) of YLL and 17.27% (12.70-21.34%) of mortality were attributable to non-optimum temperature. More YLL was caused by cold (10.14%, 3.94-16.36%) than by heat (7.14%, 0.47-13.88%). Mild cold (12.2-24.5?°C) was responsible for far more YLL (8.78%, 3.00-14.61%) than extreme cold (3.5-12.2?°C). As for cardiovascular deaths, only the fractions attributable to overall and cold temperature were significant, with mild cold contributing the largest fraction to YLL (16.31%, 6.85-25.82%) and mortality (16.08%, 9.77-21.22%). Most of the temperature-related YLL and mortality was attributable to mild but non-optimum weather, especially mild cold, while the YLL model implied a more prominent heat effect on premature death. Our findings can supply additional evidence from multiperspectives for health planners to define priorities and make targeted policies for mitigating the burden of adverse temperatures.
We aimed to explore whether there were cold and heat temperature adverse effects on years of life lost (YLL) for non-accidental mortality in Yuxi, a southwest plateau region of China. From data for 89,467 non-accidental deaths over an 8-year study period, we used a general linear regression model combined with a distributed lag non-linear model to assess the burden of disease non-accidental mortality due to ambient temperature with the YLL indicator. We estimated the mean YLL change per 1 °C decrease from the 25th to 1st percentile mean temperature as the cold effect and per 1 °C increase from the 75th to 99th percentile as the heat effect. The 95% empirical confidence intervals (eCIs) were calculated by using a bootstrap simulation method. The exposure-response curve between average temperature and YLL was U-shaped. The cold effect peaked at the first day after exposure and disappeared at 2 weeks, and the heat effect only lasted for the first 3 days. A per 1 °C decrease from the 25th to 1st mean temperature percentile was associated with an increase of 15.6 (95% eCI: 2.4, 22.9) in YLL for non-accidental diseases, and the cumulative effects due to cold were stronger in contrast to that attributed by heat. Cold temperature had a significant impact on YLL among the subgroups, with higher YLL in cardiovascular disease, stroke, males, Han nationality, married, and those engaged in agriculture than their corresponding categories. An increasing death burden of non-accidental in Yuxi of China due to cold temperature was demonstrated, and the association was also modified by specific disease causes and individual features.
BACKGROUND: Extreme weather events happen more frequently along with global warming and they constitute a challenge for public health preparedness. For example, many investigations showed heavy rainfall was associated with an increased risk of acute gastroenteritis. In this study, we examined the associations between different meteorological factors and paediatric acute gastroenteritis in an affluent setting in China controlling for pollutant effects. METHODS: Aggregated total weekly number of intestinal infection-related hospital admissions, and meteorological and air pollution data during 1998-2018 in Hong Kong were collected and analysed by a combination of quasi-Poisson generalized additive model and distributed lag nonlinear model. Study population was restricted to children under 5 years of age at the time of admission. RESULTS: While heavy rainfall did not exhibit a statistically significant association with the risk of paediatric admission due to intestinal infections, low temperature and humidity extremes (both relative humidity and vapour pressure) did. Compared with the temperature at which the lowest risk was detected (i.e. 22.5 °C), the risk was 6.4% higher (95% confidence interval: 0.0% to 13.0% at 15.1 °C (i.e. the 5th percentile)). We also found the risk of paediatric admission was statistically significantly associated with an increase in the number of extreme cold days in a week over the study period. CONCLUSION: Cold condition may have greater impact on disease transmission through increased stability and infectivity of enteric viruses in affluent settings like Hong Kong and thus resulted in an increased risk for paediatric acute gastroenteritis. On the contrary, an insignificant impact from heavy rainfall and high temperature may indicate a minor effect on disease transmission through bacterial growth in contaminated food and water. With the identified impacts of weather factors, extreme weather events are likely to distort the prevalence and seasonal pattern of diarrhoeal diseases in the future.
Recognition of Individual and environmental risks is crucial to alleviate damage inflicted by disasters. In particular, an awareness of floods and their health risks in patients’ residences is important for patients and their healthcare professionals.
The purpose of this study is to analyze and compare the human suffering exacerbation processes in the coastal metropolitan areas of Nagoya, New Orleans and Metro Manila caused by 1959 Typhoon Isewan, 2005 Hurricane Katrina and 2009 Tropical Storm Ondoy, respectively, in order to understand disasters. The research method applied was firstly to create a timeline of each disaster process with disaster responses by referring to newspapers, literature, and others, then the facts were categorized with similar social conditions and government responses to establish a hypothesis. Field surveys were conducted to verify the hypothesis. The research outcome shows the human suffering exacerbation processes of these three large-scale disasters can be seen that the pattern of the process is the same; however, the duration and content of each disaster are quite different. These differences mainly depend on social backgrounds, disaster subculture, and disaster management by local and national governments. Based on the above research findings, a useful view for disaster investigation and disaster management is clarified, along with the possible contributions of disaster countermeasures’ timeline development, especially for the disaster management in metropolitan areas.
The indigenous knowledge of our ancestors provides valuable information on how to prevent negative health impacts on water hygiene in the event of drought. The present study aimed to explore the role of indigenous knowledge in maintaining water safety in drought conditions. A qualitative content analysis method using in-depth semi-structured interviews was used to collect and analyze the data. The current research was carried out from April 2017 to June 2018. A purposive sampling method was used to select 15 participants. Trustworthiness was applied with the Lincoln and Guba approach and data were analyzed using Graneheim and Lundman’s method. Two categories including drinking water storage and water collection were extracted from the data. Each category includes different strategies to deal with water. Water storage includes water quantity and water quality. Water collection consists of collection methods and rules. Indigenous knowledge is an indispensable component of community disaster resilience. It can be transferred to other communities and employed to empower affected communities. But using the knowledge without scientific considerations cannot guarantee peoples’ health throughout the drought periods.
Future climate change may worsen air quality in many regions. However, evaluations of this ‘climate penalty’ on air quality have typically not assessed the radiative effects of changes in short-lived aerosols. Additionally, China’s clean air goals will decrease pollutant emissions and aerosol loadings, with concomitant weakening of aerosol feedbacks. Here we assess how such weakened aerosol direct effects alter the estimates of air pollution and premature mortality in China attributable to mid-century climate change under Representative Concentration Pathway 4.5. We found that weakening aerosol direct effects cause boundary layer changes that facilitate diffusion. This reduces air-pollution exposure (similar to 4% in fine particulate matter) and deaths (13,800 people per year), which largely offset the additional deaths caused by greenhouse gas-dominated warming. These results highlight the benefits of reduced pollutant emissions through weakening aerosol direct effects and underline the potential of pollution control measures to mitigate climate penalties locked in by greenhouse gas emissions.
Environmental factors have been suspected to have effects on the development of Kawasaki disease. However, the associations have been conflicting. The aim of this study was to investigate the effects of air pollution, weather conditions, and epidemic infections on the risks for Kawasaki disease in Japan. The concentrations of air pollutants (nitric oxide, nitrogen dioxide, and sulfur dioxide); ambient weather conditions (temperature, atmospheric pressure, relative air humidity, precipitation, sunshine duration, and wind velocity); and the epidemic conditions of 14 infectious diseases in hospitalized patients with Kawasaki disease were monitored from 2011 to 2018 in Beppu, Japan. The overdispersed generalized additive model was used to evaluate the effects, and a combination model with a distributed lag nonlinear model was used to estimate the cumulative effects. The incidence of Kawasaki disease had positive associations with preceding hot temperature and increased concentrations of nitric oxide and sulfur dioxide and a negative association with epidemic herpangina. The cumulative relative risk of Kawasaki disease at 5 lagged days of increased temperature was 1.76 (95% confidence interval: 1.01-3.07). This city-level observational study suggested that the incidence of Kawasaki disease was associated with air pollution and increased temperature and may be indirectly influenced by epidemic herpangina.
BACKGROUND: Stroke has been found to have a seasonally varying incidence; blood pressure, one of its risk factors, is influenced by humidity and temperature. The relationship between the incidence of stroke and meteorological parameters remains controversial. OBJECTIVE: We investigated whether meteorological conditions are significant risk factors for stroke, focusing on the fluctuation of weather elements that triggers the onset of stroke. METHODS: We collected ambulance transportation data recorded by emergency personnel from Gifu Prefecture. We included cases where the cause of the transportation was stroke and excluded cases of trauma. We combined these data with meteorological data as well as data on average temperature, average air pressure, and humidity provided publicly by the Japan Meteorological Agency. Our target period was from January 2012 to December 2016. RESULTS: In the 5-year target period, there were 5,501 occurrences of ambulance transportation due to stroke. A seasonal tendency was confirmed, since ambulance transportation for stroke occurred more frequently at low temperatures (p < 0.001). Temperature (odds ratio: 0.91; p < 0.001) and humidity change (odds ratio: 1.50; p = 0.016) were identified as risk factors for ambulance transportation due to stroke. An increase in temperature incurs a lower risk than a decrease (odds ratio: 0.58; p = 0.09), although there is no statistically significant difference. CONCLUSIONS: Meteorological effects on the frequency of ambulance transportation due to stroke were studied. A lower temperature and radical humidity change were identified as risk factors for ambulance transportation due to stroke, and a decrease in temperature was also associated. We speculate on the possibilities of using meteorological data to optimize the assignment of limited medical resources in medical economics.
Mitigation and adaption measures must be designed strategically by urban planners, designers, and decision-makers to reduce urban heat island (UHI) related risks. We employed the Weather Research and Forecasting (WRF) model to assess UHI mitigation scenarios for the tropical city of Singapore during April 2016, including two heat wave periods. The local climate zones for Singapore were used as the land use/land cover data to account for the intra-urban variability. The simulations show that the canopy layer UHI intensity in Singapore can reach up to 5 degrees C in compact areas during nighttime. The results reveal that city-scale deployment of cool roofs can provide an overall reduction of 1.3 degrees C in the near-surface daytime air temperature in large lowrise areas. Increasing the thermostat set temperature to 25 degrees C from 21 degrees C in city-wide buildings can potentially reduce the air temperature due to less (similar to 20%) waste heat discharge from airconditioning units. A densification scenario considering an increase from approximately 7 841 people/km(2) (2016) to 9040-9,600 people/km(2) (2030) under the current climate leads to air temperature increase of 1.4 degrees C, which demonstrates the importance of limiting the densification of less compact areas in maintaining thermal comfort in the future.
Heat stress has been recognized as one of the consequences of climate change in urban areas. Its adverse effects on the urban population range from economy, social, environment, and human health. With the increasing urbanization and economic development in cities, heat stress is expected to worsen. This particular study aims to achieve two objectives: (1) to understand the determinants of heat stress, especially the roles of the urban environment in exacerbating the heat stress, and (2) to explore the effects of heat stress to human health using self-reported health assessment. We employed a cross-sectional study using a survey questionnaire from 505 respondents living in the urban area of Bangkok, Thailand. We found that socioeconomic conditions of the individual and urban environment were significant determinants of urban heat stress. Low-income urban populations living in high-density areas with less green open space were more likely to experience heat stress. We also found that heat stress significantly affects human health. Those who reported a higher level of heat stress were more likely to have adverse health and well-being outcomes. The findings suggest that the increased risk of heat stress represents a major problem in the Bangkok, Thailand. It is necessary to address heat stress in adaptation policy and measures at the city levels amid the continued increase of global temperature and climate change.
The scarlet fever incidence has increased drastically in recent years in China. However, the long-term relationship between climate variation and scarlet fever remains contradictory, and an early detection system is lacking. In this study, we aim to explore the potential long-term effects of variations in monthly climatic parameters on scarlet fever and to develop an early scarlet-fever detection tool. Data comprising monthly scarlet fever cases and monthly average climatic variables from 2004 to 2017 were retrieved from the Notifiable Infectious Disease Surveillance System and National Meteorological Science Center, respectively. We used a negative binomial multivariable regression to assess the long-term impacts of weather parameters on scarlet fever and then built a novel forecasting technique by integrating an autoregressive distributed lag (ARDL) method with a nonlinear autoregressive neural network (NARNN) based on the significant meteorological drivers. Scarlet fever was a seasonal disease that predominantly peaked in spring and winter. The regression results indicated that a 1 °C increment in the monthly average temperature and a 1-h increment in the monthly aggregate sunshine hours were associated with 17.578% (95% CI 7.674 to 28.393%) and 0.529% (95% CI 0.035 to 1.025%) increases in scarlet fever cases, respectively; a 1-hPa increase in the average atmospheric pressure at a 1-month lag was associated with 12.996% (95% CI 9.972 to 15.919%) decrements in scarlet fever cases. Based on the model evaluation criteria, the best-performing basic and combined approaches were ARDL(1,0,0,1) and ARDL(1,0,0,1)-NARNN(5, 22), respectively, and this hybrid approach comprised smaller performance measures in both the training and testing stages than those of the basic model. Climate variability has a significant long-term influence on scarlet fever. The ARDL-NARNN technique with the incorporation of meteorological drivers can be used to forecast the future epidemic trends of scarlet fever. These findings may be of great help for the prevention and control of scarlet fever.
Epidemiological evidence has shown an association between exposure to high temperatures and occupational injuries, an issue gaining importance with environmental change. The aim of this study was to better understand contributing risk factors and preventive actions based on personal experiences. Interviews were conducted with 21 workers from five Australian states using a critical phenomenological approach to capture the lived experiences of participants, whilst exploring contextual factors that surround these experiences. Two case studies are presented: a cerebrovascular injury and injuries among seasonal horticulture workers. Other accounts of heat-related injuries and heat stress are also presented. Risk factors were classified as individual, interpersonal and organizational. In terms of prevention, participants recommended greater awareness of heat risks and peer-support for co-workers. Adding value to current evidence, we have provided new insights into the etiology of the health consequences of workplace heat exposure with workers identifying a range of influencing factors, prevention measures and adaptation strategies. Underpinning the importance of these are future climate change scenarios, suggesting that extended hot seasons will lead to increasing numbers of workers at risk of heat-stress and associated occupational injuries.
Recently, the ceaseless rise in the global average temperature has led to extreme climates in which natural disasters, such as droughts, hurricanes, earthquakes and floods, are becoming increasingly serious. Recent research has found that social media typically reflects disasters earlier than official communication channels. In this study, the idea of collecting information on flood disasters caused during the periods of typhoons and heavy rains for a city from the plain text messages released by social media by means of a term frequency (TF) and sliding window approach is proposed. The dataset analysed here contains a total of 292 articles and 12,484 tweets. This research determines how to establish a warning mechanism, with an added notification time for flooding disasters, and it shows how to provide relevant disaster relief personnel with references. This article contributes by combining social media data with emergency management information cloud (EMIC) data, especially in the context of having a mechanism for warning about flooding disasters. According to the experimental results, a sliding window of 90 min and a sliding gap of 10 min obtained the best F-measure value (F = 0.315). The event studied was Typhoon Megi (September 2016), which caused major flooding in Tainan. For the Typhoon Megi event, the flood disaster location database had 161 streets available for matching. Based on the experimental results, it is possible to obtain a high-precision (90% or higher) accuracy rate from real-time tweet data by exploiting a social media dataset.
BACKGROUND: The Global Climate Risk Index 2020 ranked Vietnam as the sixth country in the world most affected by climate variability and extreme weather events over the period 1999-2018. Sea level rise and extreme weather events are projected to be more severe in coming decades, which, without additional action, will increase the number of people at risk of climate-sensitive diseases, challenging the health system. This article summaries the results of a health vulnerability and adaptation (V&A) assessment conducted in Vietnam as evidences for development of the National Climate Change Health Adaptation Plan to 2030. METHODS: The assessment followed the first 4 steps outlined in the World Health Organization’s Guidelines in conducting “Vulnerability and Adaptation Assessments.” A framework and list of indicators were developed for semi-quantitative assessment for the period 2013 to 2017. Three sets of indicators were selected to assess the level of (1) exposure to climate change and extreme weather events, (2) health sensitivity, and (3) adaptation capacity. The indicators were rated and analyzed using a scoring system from 1 to 5. RESULTS: The results showed that climate-sensitive diseases were common, including dengue fever, diarrheal, influenza, etc, with large burdens of disease that are projected to increase. From 2013 to 2017, the level of “exposure” to climate change-related hazards of the health sector was “high” to “very high,” with an average score from 3.5 to 4.4 (out of 5.0). For “health sensitivity,” the scores decreased from 3.8 in 2013 to 3.5 in 2017, making the overall rating as “high.” For “adaptive capacity,” the scores were from 4.0 to 4.1, which meant adaptive capacity was “very low.” The overall V&A rating in 2013 was “very high risk” (score 4.1) and “high risk” with scores of 3.8 in 2014 and 3.7 in 2015 to 2017. CONCLUSIONS: Adaptation actions of the health sector are urgently needed to reduce the vulnerability to climate change in coming decades. Eight adaptation solutions, among recommendations of V&A assessment, were adopted in the National Health Climate Change Adaptation Plan.
BACKGROUND: Although visceral leishmaniasis (VL), a disease caused by parasites, is controlled in most provinces in China, it is still a serious public health problem and remains fundamentally uncontrolled in some northwest provinces and autonomous regions. The objective of this study is to explore the spatial and temporal characteristics of VL in Sichuan Province, Gansu Province and Xinjiang Uygur Autonomous Region in China from 2004 to 2018 and to identify the risk areas for VL transmission. METHODS: Spatiotemporal models were applied to explore the spatio-temporal distribution characteristics of VL and the association between VL and meteorological factors in western China from 2004 to 2018. Geographic information of patients from the National Diseases Reporting Information System operated by the Chinese Center for Disease Control and Prevention was defined according to the address code from the surveillance data. RESULTS: During our study period, nearly 90% of cases occurred in some counties in three western regions (Sichuan Province, Gansu Province and Xinjiang Uygur Autonomous Region), and a significant spatial clustering pattern was observed. With our spatiotemporal model, the transmission risk, autoregressive risk and epidemic risk of these counties during our study period were also well predicted. The number of VL cases in three regions of western China concentrated on a few of counties. VL in Kashi Prefecture, Xinjiang Uygur Autonomous Region is still serious prevalent, and integrated control measures must be taken in different endemic areas. CONCLUSIONS: The number of VL cases in three regions of western China concentrated on a few of counties. VL in Kashi Prefecture, Xinjiang Uygur Autonomous Region is still serious prevalent, and integrated control measures must be taken in different endemic areas. Our findings will strengthen the VL control programme in China.
INTRODUCTION: Epidemic thunderstorm asthma (ETSA) is due to a complex interaction of environmental and individual susceptibility factors, with outbreaks reported globally over the last four decades. Australia has been particularly susceptible with nearly half of episodes reported internationally, culminating in the catastrophic Melbourne 2016 event. AREAS COVERED: Reported ETSA episodes are reviewed for common environmental and meteorological risk factors. Allergen aerobiology interaction with thunderstorm activity and rapid weather condition changes is examined. Assessment of the clinical and immunological data highlights risk factors for ETSA presentation, hospital admission, and intensive care admission. Risk factors associated with ETSA deaths are evaluated. Public health strategies, as well as pharmacological and immunological management approaches to reduce individual susceptibility and prevent ETSA are discussed. EXPERT OPINION: Improved understanding of the specific meteorological factors predisposing to the greatest risk of ETSA to improve forecasting is required. Better monitoring of aeroallergen levels in areas of greatest geographic risk, with further research into allergen aerobiology underpinning mechanisms of allergen exposure is needed. The role of climate change in increasing the risk of ETSA outbreaks requires further research. Public awareness and education are required to reduce exposure, and to improve uptake of pharmacological and immunological risk reduction and preventive strategies.
Nitrogen dioxide (NO(2)) is an air pollutant discharged from combustion of human activities. Nitrous acid (HONO), measured as NO(2), is thought to impact respiratory function more than NO(2). HONO and NO(2) have an equilibrium relationship, and their reaction is affected by climate conditions. This study was conducted to discuss the extent of HONO contained in NO(2), depending on the level of urbanization. Whether climate conditions that promote HONO production enhanced the level of NO(2) measured was investigated using time series analysis. Climate and outdoor air pollution data measured in April 2009-March 2017 in urban (Tokyo, Osaka, and Aichi) and rural (Yamanashi) areas in Japan were used for the analysis. Air temperature had a trend of negative associations with NO(2), which might indicate the decomposition of HONO in the equilibrium between HONO and NO(2). The associations of relative humidity with NO(2) did not have consistent trends by prefecture: humidity only in Yamanashi was positively associated with NO(2). In high relative humidity conditions, the equilibrium goes towards HONO production, which was observed in Yamanashi, suggesting the proportion of HONO in NO(2) might be low/high in urban/rural areas.
BACKGROUND: We assessed the association between multiple meteorological factors and air pollutants and the number of acute myocardial infarction (AMI) cases using a multi-step process. METHODS: Daily AMI hospitalizations matched with 16 meteorological factors and air pollutants in 7 metropolitan provinces of the Republic of Korea from 2002 to 2017 were analyzed. We chose the best fit model after conducting the Granger causality (GC) test and examined the daily lag time effect on the orthogonalized impulse response functions. To define dose-response relationships, we performed a time series analysis using multiple generalized additive lag models based on seasons. RESULTS: A total of 196,762 cases of AMI in patients older than 20 years admitted for hospitalization were identified. The distribution of meteorological factors and air pollutants showed characteristics of a temperate climate. The GC test revealed a complex interaction between meteorological factors, including air pollutants, and AMI. The final selected factors were NO(2) and temperature; these increased the incidence of AMI on lag day 4 during summer (NO(2): population-attributable fraction [PAF], 3.9%; 95% confidence interval [CI], 3.6-4.0; mean temperature: PAF, 3.3%; 95% CI, 2.7-3.9). CONCLUSIONS: This multi-step time series analysis found that average temperature and NO(2) are the most important factors impacting AMI hospitalizations, specifically during summer. Based on the model, we were able to visualize the effect-time association of meteorological factors and air pollutants and AMI.
Disaster risk is a complex, uncertain and evolving threat to society which changes based on broad drivers of hazard, exposure and vulnerability such as population, economic and climatic change, along with new technologies and social preferences. It also evolves as a function of decisions of public policy and public/private investment which alters future risk profiles. These factors however are often not captured within disaster risk assessments and explicitly excluded from the UN General Assembly definition of a disaster risk assessment which focuses on the current state of risk. This means that 1) we cannot adequately capture changes in risk and risk assessments are out of date as soon as published but also 2) we cannot show the benefit of proactive risk treatments in our risk assessments. This paper therefore outlines a generic, scale-neutral, framework for integrating foresight – thinking about the future – into risk assessment methodologies. This is demonstrated by its application to a disaster risk assessment of heatwave risk in Tasmania, Australia, and shows how risk changes across three future scenarios and what proactive treatments could be possible mitigating the identified drivers of future risk.
This paper explores the perceived adaptation preference of rural island communities in addressing future climate change risks, particularly those concerning sea-level rise. The research explores the role of culture and local politics, and differences among various age and gender groups within the community regarding preferred adaptation pathways for coping with the impacts of future sea-level rise. A participatory action approach, in the form of a community workshop, was employed, which separated participants into community identified groupings. Differences in community groups’ adaptation preferences emerged, though the range of adaptation measures considered were limited, probably due to the participants’ limited exposure to adaptation mechanisms in their immediate surroundings. Overall, the communities surveyed tended to be conservative, especially in their attitudes towards western adaptation solutions developed in non-island contexts.
The prediction of the occurrence of infectious diseases is of crucial importance for public health, as clearly seen in the ongoing COVID-19 pandemic. Here, we analyze the relationship between the occurrence of a winter low-pressure weather regime – Cyprus Lows – and the seasonal Influenza in the Eastern Mediterranean. We find that the weekly occurrence of Cyprus Lows is significantly correlated with clinical seasonal Influenza in Israel in recent years (R = 0.91; p < .05). This result remains robust when considering a complementary analysis based on Google Trends data for Israel, the Palestinian Authority and Jordan. The weekly occurrence of Cyprus Lows precedes the onset and maximum of Influenza occurrence by about one to two weeks (R = 0.88; p < .05 for the maximum occurrence), and closely follows their timing in eight out of ten years (2008-2017). Since weather regimes such as Cyprus Lows are more robustly predicted in weather and climate models than individual climate variables, we conclude that the weather regime approach can be used to develop tools for estimating the compatibility of the transmission environment for Influenza occurrence in a warming world. Furthermore, this approach may be applied to other regions and climate sensitive diseases. This study is a new cross-border inter-disciplinary regional collaboration for appropriate adaptation to climate change in the Eastern Mediterranean.
Meteorological conditions during pregnancy can affect birth outcome, which has been linked to the H19/H19-differentially methylated region (DMR). However, the detailed mechanisms underlying this association are unclear. This was investigated in the present study to provide epidemiological evidence for elucidating the pathogenesis of adverse birth outcomes. A total of 550 mother-newborn pairs were recruited in Zhengzhou, China from January 2010 to January 2012. Meteorological data including temperature (T), relative humidity (RH), and sunshine duration (SSD) were obtained from the China Meteorological Data Sharing Service System. Bisulfite sequencing PCR was performed to determine the methylation levels of H19/H19-DMR using genomic DNA extracted from maternal peripheral and umbilical cord blood. The results showed that H19-DMR methylation status in cord blood was positively associated with that in maternal blood. Neonatal H19-DMR methylation was negatively associated with T and RH during the first trimester and positively associated with these variables during the third trimester. There was a positive correlation between neonatal H19-DMR methylation and SSD during the second trimester and a negative correlation during the third trimester. Similar associations were observed between maternal H19-DMR methylation and prenatal meteorological conditions. We also observed significant interaction effects of maternal H19/H19-DMR methylation and most prenatal meteorological factors on neonatal methylation, and found that changes in the methylation status of maternal H19-DMR were responsible for the effects of prenatal meteorological conditions on neonatal methylation. In summary, neonatal H19-DMR methylation was significantly associated with prenatal meteorological conditions, which was modified and mediated by maternal H19-DMR methylation changes. These findings provide insights into the relationship between meteorological factors during pregnancy and adverse birth outcomes or disease susceptibility in offspring, and can serve as a reference for environmental policy-making.
PURPOSE: Global warming and air pollution are among the most important problems all over the world. Considering the key role of traffic officers who saliently deal with traffic management and are in full, constant and direct exposure to thermal stress and air pollution index, this study aims to investigate the simultaneous effects of these factors on the body temperature of traffic officers in the main squares of Tehran. METHODS: This study was conducted among 119 traffic officers who were working in 29 squares of Tehran, located near the active pollutant’s stations during 2017. Samples were selected by the census method. Environmental parameters such as air temperature (dry and wet), radiation temperature, the level of air pollution in the main squares and characteristics of officers such as body temperature and the Wet-Bulb-Globe-Temperature (WBGT) index were evaluated. Data were analyzed through independent samples t-test and factorial ANOVA with a p value of p???0.05 in SPSS software. RESULTS: There was no significant relationship between air pollution and ear temperature, but there was a statistically significant difference between the wet-bulb temperature and the ear temperature (t?=?26.4, P?
The Philippines suffers frequent typhoons every year hence the country is susceptible to experience disastrous flooding. This extreme event causes various effects in the community specifically infrastructural and social system damages. Flooding also causes numerous health effects that deteriorate the wellbeing of the affected population. Iligan City is known to be an area prone to flooding in the Philippines. This paper examines the state of health of communities affected by flooding occurrences through knowledge and preparedness, health impacts, and emergency response of various state actors during and after flooding incidents. Data were collected through an analysis of different documents, key informant interviews, and focus groups in the cities of Iligan and Cagayan de Oro. Results show data from various sources and narratives regarding the degree of preparedness before the flood among community members. During the flooding occurrence, different community damages were mentioned. Due to the destructive nature of floods, community members also stated different health impacts whether immediate, short term, or long term. After the flood, different emergency response and relief were provided. However, citizens and community also cited difficulties about the provision of relief and health care. This study can be used for initiatives in reducing risks and vulnerability in floods.
BACKGROUND: Previous studies have thoroughly elucidated the exposure-response relationship between ambient temperature and hand, foot, and mouth disease (HFMD), whereas very little concern has been to the lag-response relationship and related key time points. OBJECTIVES: We aimed to clarify the temporal characteristics of the lag-response relationship between ambient temperature and HFMD and how they may vary spatially. METHODS: We retrieved the daily time series of meteorological variables and HFMD counts for 143 cities in mainland China between 2009 and 2014. We estimated the city-specific lag-response curve between ambient temperature and HFMD and related key time points by applying common distributed lag nonlinear models (DLNM) and Monte Carlo simulation methods. Then, we pooled the city-specific estimates by performing a meta-regression with the city-specific characteristics as meta-predictors to explain the potential spatial heterogeneity. RESULTS: We found a robust lag pattern between temperature and HFMD for different levels of temperatures. The temporal change of risk obtained its maximum value on the current day but dropped sharply thereafter and then rebounded to a secondary peak, which implied the presence of a harvesting effect. By contrast, the estimation of key time points showed substantial heterogeneity, especially at high temperature (the I(2) statistics ranged from 47% to 80%). With one unit increase in the geographic index, the secondary peak would arrive 0.37 (0.02, 0.71) days later. With one unit increase in the economic index and climatic index, the duration time of the lag-response curve would be lengthened by 0.36 (0.1, 0.62) and 0.92 (0.54, 1.29) days, respectively. CONCLUSION: Our study examined the lag pattern and spatial heterogeneity of the lag-response relationship between temperature and HFMD. Those findings gave us new insights into the complex association and the related mechanisms between weather and HFMD and important information for weather-based disease early warning systems.
BACKGROUND: In Thailand, dengue fever is one of the most well-known public health problems. The objective of this study was to examine the epidemiology of dengue and determine the seasonal pattern of dengue and its associate to climate factors in Bangkok, Thailand, from 2003 to 2017. METHODS: The dengue cases in Bangkok were collected monthly during the study period. The time-series data were extracted into the trend, seasonal, and random components using the seasonal decomposition procedure based on loess. The Spearman correlation analysis and artificial neuron network (ANN) were used to determine the association between climate variables (humidity, temperature, and rainfall) and dengue cases in Bangkok. RESULTS: The seasonal-decomposition procedure showed that the seasonal component was weaker than the trend component for dengue cases during the study period. The Spearman correlation analysis showed that rainfall and humidity played a role in dengue transmission with correlation efficiency equal to 0.396 and 0.388, respectively. ANN showed that precipitation was the most crucial factor. The time series multivariate Poisson regression model revealed that increasing 1% of rainfall corresponded to an increase of 3.3% in the dengue cases in Bangkok. There were three models employed to forecast the dengue case, multivariate Poisson regression, ANN, and ARIMA. Each model displayed different accuracy, and multivariate Poisson regression was the most accurate approach in this study. CONCLUSION: This work demonstrates the significance of weather in dengue transmission in Bangkok and compares the accuracy of the different mathematical approaches to predict the dengue case. A single model may insufficient to forecast precisely a dengue outbreak, and climate factor may not only indicator of dengue transmissibility.
OBJECTIVE: The objective of this study was to investigate the association between the weather and epidemic condition and risk of febrile seizures (FSs) in Japan. STUDY DESIGN: This single-center, retrospective study included 560 children (age, 6-60?months) with FSs who were transported to our center by ambulance from January 2011 through December 2018. The weather (temperature, atmospheric pressure, relative air humidity, amount of rainfall, sunshine duration, and air concentration of nitrogen dioxide [NO(2)] and sulfur dioxide [SO(2)]) and epidemic (influenza virus infection, infectious gastroenteritis, and exanthem subitum) conditions in this region were compared between the periods (days or weeks) with the transportation of children with FS to our hospital and those without such transportation. RESULTS: In the univariate analyses, neither daily or weekly weather condition nor weekly epidemic condition was correlated to FS transportation. Furthermore, the multiple logistic regression analysis suggested that epidemic influenza virus infection (odds ratio [OR], 1.34; 95% confidence interval [CI], 1.08-1.73) and infectious gastroenteritis (OR, 1.64; 95% CI, 1.09-2.54) were the independent risk factors for FS occurrence and weather condition was not associated with FS risk. CONCLUSIONS: Febrile seizure incidence may be increased by epidemic febrile infections but not by weather condition.
OBJECTIVES: To investigate the effects of climatic variables on peritoneal dialysis-associated peritonitis (PDAP) among patients receiving PD, such as seasonal variations in temperature and humidity. METHODS: A retrospective analysis was performed on PD patients, from 1 January 2011, to 31 December 2019. We evaluated the influence of seasonal factors on peritonitis rates and outcomes. RESULTS: Over the 9-year study period, 667 peritonitis episodes occurred, in 401 PD patients. Diarrhea-associated peritonitis occurred more frequently in summer compared with other seasons. Eating raw and cold food was identified as the primary cause of peritonitis in the summer. More peritonitis episodes occurred during summer. The peritonitis rate associated with gram-negative bacteria (p?=?0.050) during summer was higher than those in all other seasons. The gram-negative bacterial peritonitis rate was positively correlated with monthly mean temperature (r?=?0.504, p?<?0.01) and humidity (r?=?0.561, p?<?0.01). A similar trend was observed for Enterobacterial peritonitis (temperature: r?=?0.518, p?<?0.01; humidity: r?=?0.456, p?=?0.001). Logistic regression analysis showed that summer was a risk factor for peritonitis (p?=?0.041). Peritonitis prognosis during summer was significantly worse than those for all other seasons (p?=?0.037). CONCLUSIONS: Seasonal variations exist in the incidence of dialysis-associated peritonitis, with peak incidents caused by gram-negative bacteria in the summer. High average temperature and humidity are associated with significant increases in the gram-negative bacteria and Enterobacterial peritonitis rates. Peritonitis prognosis during summer is worse.
The interactive effects between particulate matter (PM) and heat waves on circulatory mortality are under-researched in the context of global climate change. We aimed to investigate the interaction between heat waves and PM on circulatory mortality in Fuzhou, a city characterized by a humid subtropical climate and low level of air pollution in China. We collected data on deaths, pollutants, and meteorology in Fuzhou between January 2016 and December 2019. Generalized additive models were used to examine the effect of PM on circulatory mortality during the heat waves, and to explore the interaction between different PM levels and heat waves on the circulatory mortality. During heat waves, circulatory mortality was estimated to increase by 8.21% (95% confidence intervals (CI): 0.32-16.72) and 3.84% (95% CI: 0.28-7.54) per 10 ?g/m(3) increase of PM(2.5) and PM(10), respectively, compared to non-heat waves. Compared with low-level PM(2.5) concentration on non-heat waves layer, the high level of PM(2.5) concentration on heat waves layer has a significant effect on the cardiovascular mortality, and the effect value was 48.35% (95% CI: 6.37-106.89). Overall, we found some evidence to suggest that heat waves can significantly enhance the impact of PM on circulatory mortality.
Evidence on the long-term influence of climatic variables on pertussis is limited. This study aims to explore the long-term quantitative relationship between weather variability and pertussis. Data on the monthly number of pertussis cases and weather parameters in Chongqing in the period of 2004-2018 were collected. Then, we used a negative binomial multivariable regression model and cointegration testing to examine the association of variations in monthly meteorological parameters and pertussis. Descriptive statistics exhibited that the pertussis incidence rose from 0.251 per 100,000 people in 2004 to 3.661 per 100,000 persons in 2018, and pertussis was a seasonal illness, peaked in spring and summer. The results from the regression model that allowed for the long-term trends, seasonality, autoregression, and delayed effects after correcting for overdispersion showed that a 1 hPa increment in the delayed one-month air pressure contributed to a 3.559% (95% CI 0.746-6.293%) reduction in the monthly number of pertussis cases; a 10 mm increment in the monthly aggregate precipitation, a 1 °C increment in the monthly average temperature, and a 1 m/s increment in the monthly average wind velocity resulted in 3.641% (95% CI 0.960-6.330%), 19.496% (95% CI 2.368-39.490%), and 3.812 (95% CI 1.243-11.690)-fold increases in the monthly number of pertussis cases, respectively. The roles of the mentioned weather parameters in the transmission of pertussis were also evidenced by a sensitivity analysis. The cointegration testing suggested a significant value among variables. Climatic factors, particularly monthly temperature, precipitation, air pressure, and wind velocity, play a role in the transmission of pertussis. This finding will be of great help in understanding the epidemic trends of pertussis in the future, and weather variability should be taken into account in the prevention and control of pertussis.
Harmful algal blooms (HABs) can have dire repercussions on aquatic wildlife and human health, and may negatively affect recreational uses, aesthetics, taste, and odor in drinking water. The factors that influence the occurrence and magnitude of harmful algal blooms and toxin production remain poorly understood and can vary in space and time. It is within this context that we use machine learning (ML) and two 14-year (2005-2018) data sets on water quality and meteorological conditions of China’s lakes and reservoirs to shed light on the magnitude and associated drivers of HAB events. General regression neural network (GRNN) models are developed to predict chlorophyll a concentrations for each lake and reservoir during two study periods (2005-2010 and 2011-2018). The developed models with an acceptable model fit are then analyzed by two indices to determine the areal HAB magnitudes and associated drivers. Our national assessment suggests that HAB magnitudes for China’s lakes and reservoirs displayed a decreasing trend from 2006 (1363.3 km(2)) to 2013 (665.2 km(2)), and a slightly increasing trend from 2013 to 2018 (775.4 km(2)). Among the 142 studied lakes and reservoirs, most severe HABs were found in Lakes Taihu, Dianchi and Chaohu with their contribution to the total HAB magnitude varying from 89.2% (2013) to 62.6% (2018). HABs in Lakes Taihu and Chaohu were strongly associated with both total phosphorus and nitrogen concentrations, while our results were inconclusive with respect to the predominant environmental factors shaping the eutrophication phenomena in Lake Dianchi. The present study provides evidence that effective HAB mitigation may require both nitrogen and phosphorus reductions and longer recovery times; especially in view of the current climate-change projections. ML represents a robust strategy to elucidate water quality patterns in lakes, where the available information is sufficient to train the constructed algorithms. Our mapping of HAB magnitudes and associated environmental/meteorological drivers can help managers to delineate hot-spots at a national scale, and comprehensively design the best management practices for mitigating the eutrophication severity in China’s lakes and reservoirs.
BACKGROUND: Climate change is anticipated to have profound effects on mental health, particularly among populations that are simultaneously ecologically and economically vulnerable to its impacts. Various pathways through which climate change can impact mental health have been theorised, but the impacts themselves remain understudied. PURPOSE: In this article we applied psychological methods to examine if climate change is affecting individuals’ mental health in the Small Island Developing State of Tuvalu, a Pacific Island nation regarded as exceptionally vulnerable to climate change. We determined the presence of psychological distress and associated impairment attributed to two categories of climate change-related stressors in particular: 1) local environmental impacts caused or exacerbated by climate change, and 2) hearing about global climate change and contemplating its future implications. METHODS: The findings draw on data collected in a mixed-method study involving 100 Tuvaluan participants. Data were collected via face-to-face structured interviews that lasted 45?min on average and were subjected to descriptive, correlational, and between-group analyses. RESULTS: The findings revealed participants’ experiences of distress in relation to both types of stressor, and demonstrated that a high proportion of participants are experiencing psychological distress at levels that reportedly cause them impairment in one or more areas of daily life. CONCLUSIONS: The findings lend weight to the claim that climate change represents a risk to mental health and obliges decision-makers to consider these risks when conceptualizing climate-related harms or tallying the costs of inaction.
BACKGROUND: Growing evidence suggests that the diurnal temperature range (DTR) could modify the temperature-disease relationship for those environmentally-related infectious diseases. However, there is a lack of evidence on the hand, foot and mouth disease (HFMD). In this study, we thoroughly examined this hypothesis via a nationwide study. METHOD: We collected the daily time series of HFMD cases and meteorological factors of 143 cities in mainland China from 2009 to 2014. For each city, we calculated the arithmetic average of the meteorological factors as a proxy for the climatic differences. We then performed two-stage time series analyses for four different climatic regions. Specifically, a distributed lag nonlinear model was applied to estimate the temperature-HFMD relationship for each city, and then a multivariate meta-regression was implemented to examine whether the DTR could explain the potential heterogeneity as an effect modifier. In addition, we compared the modification effect of the DTR with those of other climatic factors. RESULT: We found a significant modification effect of DTR on the temperature-HFMD relationship in the moderate-temperature region. Besides, the modification effect was only observed at hot temperatures. Comparing the maximum temperature (32.2 °C) to the median temperature (11.9 °C), the risk ratio was 1.60 (1.33, 1.92) when DTR was in the 10th percentile (6.8 °C) and 0.81 (0.69, 0.96) when the DTR was in the 90th percentile (11.8 °C). By comparing DTR with other climatic variables, we found that the DTR had the best performance in improving the model fit (?QAIC= 10.1) and reducing the heterogeneity (?I(2) = 3.1%) in the multivariate meta-regression. CONCLUSION: Our findings verified that DTR can modify the temperature-HFMD relationship. Besides, our findings also implied that DTR could be used as a proxy variable to comprehensively reflect the modification effects of multiple climatic factors.
Cardiovascular disease is the most common cause of death globally. Examining the relationship between the extreme temperature events (e.g. heat and cold waves) and cardiovascular mortality has profound public significance. However, this evidence is scarce, particularly those from China. We collected daily data on cardiovascular mortality and meteorological conditions from 31 major Chinese cities during the maximum period of 2007-2013. A two-stage analysis was used to estimate the effects of heat and cold waves, and the potential effect modification of their characteristics (intensity, duration, and timing in season) on cardiovascular mortality. Firstly, a generalized quasi-Poisson regression combined with distributed lag nonlinear model was used to evaluate city-specific effects. Then, the meta-analysis was performed to pool effect estimates at the national scale. Overall, cardiovascular mortality risk increased by 19.03% (95%CI: 11.92%, 26.59%) during heat waves and 54.72% (95%CI: 21.20%, 97.51%) during cold waves. The effect estimates varied by the wave’s characteristics. In heat wave days, the cardiovascular mortality risks increased by 3.28% (95%CI: -0.06%, 6.73%) for every 1 degrees C increase in intensity, 2.84% (95%CI: 0.92%, 4.80%) for every 1-d more in duration and -0.07% (95%CI: -0.38%, 0.24%) for every 1-d late in the staring of heat wave; the corresponding estimates for cold wave were 1.82% (95%CI: -0.04%, 3.72%), 1.52% (95%CI: 0.60%, 2.44%) and -0.26% (95%CI: -0.67%, 0.16%). Increased susceptibility to heat and cold waves was observed among patients with ischemic heart disease, females, the elderly, and those with lower education level. And consistent vulnerable populations were found for the effects of changes in cold and heat wave’s characteristics. The findings have important implications for the development of early warning systems and plans in response to heat and cold waves, which may contribute to mitigating health threat to vulnerable populations.
(1) Background: The adverse health effect associated with extreme temperature has been extensively reported in the current literature. Some also found that temperature effect may vary among the population with different socioeconomic status (SES), but found inconsistent results. Previous studies on the socioeconomic vulnerability of temperature effect were mainly achieved by multi-city or country analysis, but the large heterogeneity between cities may introduce additional bias to the estimation. The linkage between death registry and census in Hong Kong allows us to perform a city-wide analysis in which the study population shares virtually the same cultural, lifestyle and policy environment. This study aims to examine and compare the high and low temperature on morality in Hong Kong, a city with a subtropical climate and address a key research question of whether the extreme high and low temperature disproportionally affects population with lower SES. (2) Methods: Poisson-generalized additive models and distributed-lagged nonlinear models were used to examine the association between daily mortality and daily mean temperature between 2007-2015 with other meteorological and confounding factors controlled. Death registry was linked with small area census and area-level median household income was used as the proxy for socioeconomic status. (3) Results: 362,957 deaths during the study period were included in the analysis. The minimum mortality temperature was found to be 28.9 °C (82nd percentile). With a subtropical climate, the low temperature has a stronger effect than the high temperature on non-accidental, cardiovascular, respiratory and cancer deaths in Hong Kong. The hot effect was more pronounced in the first few days, while cold effect tended to last up to three weeks. Significant heat effect was only observed in the lower SES groups, whilst the extreme low temperature was associated with significantly higher mortality risk across all SES groups. The older population were susceptible to extreme temperature, especially for cold. (4) Conclusions: This study raised the concern of cold-related health impact in the subtropical region. Compared with high temperature, low temperature may be considered a universal hazard to the entire population in Hong Kong rather than only disproportionally affecting people with lower SES. Future public health policy should reconsider the strategy at both individual and community levels to reduce temperature-related mortality.
BACKGROUND: Intense studies have been carried out on the effects of climate change on vector-borne diseases and vectors. Culex pipiens pallens and Culex pipiens quinquefasciatus are two medically concerned mosquito species in temperate and tropical areas, which serve as important disease-transmitting pests of a variety of diseases. The ongoing geographical expansion of these mosquitoes has brought an increasing threat to public health. RESULTS: Based on mosquito occurrence records and high-resolution environmental layers, an ecological niche model was established to model their current and future potential distribution in China. Our model showed that the current suitable area for Cx. p. pallens is distributed in the central, eastern and northern parts of China, while Cx. p. quinquefasciatus is distributed in vast areas in southern China. Under future climate change scenarios, both species are predicted to expand their range to varying degrees and RCP 8.5 provides the largest expansion. Northward core shifts will occur in ranges of both species. Environmental variables which have significant impact on the distribution of mosquitoes were also revealed by our model. CONCLUSION: Severe habitat expansion of vectors is likely to occur in the future 21st century. Our models mapped the high-risk areas and risk factors which needs to be paid attention. The results of our study can be referenced in further ecological surveys and will guide the development of strategies for the prevention and control of vector-borne diseases. © 2020 Society of Chemical Industry.
Previous studies that observed the fact that Middle Palaeolithic sites mainly were concentrated in arid and semi-arid areas in Africa and Southwest Asia, concluded that climate factors determined the distribution patterns. We argue that biological factors could have been equally important. In present-day sub-Saharan Africa, mosquito borne diseases and especially falciparum malaria have a serious impact on human populations. This study was aimed to investigate the possible former effect of falciparum malaria on Middle Palaeolithic site distribution patterns and explain why ancient humans avoided the humid areas in the tropical and subtropical regions. It was found that the early human settlements situated in those regions of Africa and Southwest Asia where the potential annual development period of falciparum parasites was short in the mosquitoes, the area was not too humid, and the potential falciparum malaria incidence values were low or moderate. In the Indian Peninsula, precipitation played a less significant role in determining human settlements. The number of the months when the extrinsic development of Plasmodium falciparum parasites was possible showed the strongest structural overlap with the modelled malaria incidences according to the spatial occurrence of the Middle Paleolithic archaeological sites in the case of Africa and in Southwest Asia. In the Indian Peninsula, climatic factors showed the strongest structural overlap with the modelled malaria incidences according to the occurrence patterns of the Middle Palaeolithic archaeological sites.
Although seasonal influenza viruses circulate globally, prevention and treatment occur at the level of regions, cities, and communities. At these scales, the timing, duration and magnitude of epidemics vary substantially, but the underlying causes of this variation are poorly understood. Here, based on analyses of a 15-year city-level dataset of 18,250 laboratory-confirmed and antigenically-characterised influenza virus infections from Australia, we investigate the effects of previously hypothesised environmental and virological drivers of influenza epidemics. We find that anomalous fluctuations in temperature and humidity do not predict local epidemic onset timings. We also find that virus antigenic change has no consistent effect on epidemic size. In contrast, epidemic onset time and heterosubtypic competition have substantial effects on epidemic size and composition. Our findings suggest that the relationship between influenza population immunity and epidemiology is more complex than previously supposed and that the strong influence of short-term processes may hinder long-term epidemiological forecasts.
BACKGROUND: Compared to hospital admissions (HAs), emergency ambulance dispatches (EADs) can be considered a real-time outcome for evaluating the public health impacts of ambient temperature. OBJECTIVES: This study aimed to assess if temperature has a causal effect on cause-specific EADs and its potential main and added effect in Shenzhen from 2013 to 2017. METHODS: A distributed lag nonlinear model (DLNM) with quasi-Poisson distribution was applied to quantify the association between temperature and EADs. Likewise, the fraction of EADs attributable to different temperature ranges was calculated to identify extreme temperature ranges affecting population health. We then explored the main and added wave effects of heatwaves. RESULTS: Ambient temperature showed a U-shaped association with EADs. The minimum risk temperature was 17 °C (16th percentile of the daily mean temperature). Compared with the cold, the relative risk (RR) of heat on EADs presented smaller but the attributable risk larger. The main effects of heatwaves on EADs varied with external causes; and the peak RR of heat on EADs was observed in suicidal behaviors with heatwaves defined as 3 or more days with temperatures above the 75th percentile (RR = 4.53, 95% CI: 1.23-16.68), followed by assault (RR = 2.36, 95% CI: 1.25-4.48) and accidents (RR = 1.72, 95% CI: 1.30-2.28), while the added wave effect was negligible. CONCLUSIONS: Heat was responsible for a higher proportion of EADs than cold. Most of the increase in health risk during warm season can be simply ascribed to the independent effects of daily temperature occurrences whether it is or not on the heat-wave day. And the main effects of heatwaves on cause-specific EADs showed varied change trends, of which the incidence of suicides seems more susceptible, followed by assault and accidents.
The ambient temperature-health relationship is of growing interest as the climate changes. Previous studies have examined the association between ambient temperature and mortality or morbidity, however, there is little literature available on the ambient temperature effects on year of life lost (YLL). Thus, we aimed to quantify the YLL attributable to non-optimum ambient temperature. We obtained data from 1 January 2013 to 31 December 2017 of 70 counties in Hunan, China. In order to combine the effects of each county, we used YLL rate as a health outcome indicator. The YLL rate was equal to the total YLL divided by the population of each county, and multiplied by 100,000. We estimated the associations between ambient temperature and YLL with a distributed lag non-linear model (DNLM) in a single county, and then pooled them in a multivariate meta-regression. The daily mean YLL rates were 22.62 y/(p·100,000), 10.14 y/(p·100,000) and 2.33 y/(p·100,000) within the study period for non-accidental, cardiovascular, and respiratory disease death. Ambient temperature was responsible for advancing a substantial fraction of YLL, with attributable fractions of 10.73% (4.36-17.09%) and 16.44% (9.09-23.79%) for non-accidental and cardiovascular disease death, respectively. However, the ambient temperature effect was not significantly for respiratory disease death, corresponding to 5.47% (-2.65-13.60%). Most of the YLL burden was caused by a cold temperature than the optimum temperature, with an overall estimate of 10.27% (4.52-16.03%) and 15.94% (8.82-23.05%) for non-accidental and cardiovascular disease death, respectively. Cold and heat temperature-related YLLs were higher in the elderly and females than the young and males. Extreme cold temperature had an effect on all age groups in different kinds of disease-caused death. This study highlights that general preventative measures could be important for moderate temperatures, whereas quick and effective measures should be provided for extreme temperatures.
BACKGROUND: For pediatric pneumonia, the meteorological and air pollution indicators had been frequently investigated for their association with viral circulation, however, not for their impact on disease severity. METHODS: We performed a 10-year prospective observational study in one hospital in Chongqing, China to recruit children with pneumonia. Eight commonly seen respiratory viruses were tested. Autoregressive distributed lag (ADL) and Random forest (RF) models were performed to fit monthly detection rates of each virus at population level and predict the possibility of severe pneumonia at individual level, respectively. RESULTS: Between 2009?2018, 6 611 pediatric pneumonia patients were included, and 4 846 (73.3%) tested positive for at least one respiratory virus. The median age of the patients was 9 (IQR: 4?20) months. ADL models demonstrated a decent fitting of detection rates of four viruses (R2 >0.7 for RSV, HRV, PIV, and HMPV). Based on the RF models, the AUC for host-related factors alone is 0.88 (95% CI: 0.87?0.89), 0.86 (95% CI: 0.85?0.88) for meteorological and air pollution indicators alone, and 0.62 (95% CI: 0.60?0.63) for viral infections alone. The final model indicated that nine weather and air pollution indicators were important determinants of severe pneumonia, with relative contribution of 62.53%, significantly higher than respiratory viral infections (7.36%). CONCLUSIONS: Meteorological and air pollution predictors contributed more to severe pneumonia in children than respiratory viruses. These meteorological data could help predict times when children would be at increased risk for severe pneumonia, and interventions such as reducing outdoor activities, may be warranted.
Introduction: Altered weather patterns and changes in precipitation, temperature and humidity resulting from climate change could affect the distribution and incidence of cholera. This study is to quantify climate-induced increase in morbidity rates of cholera. Material and Methods: Monthly cholera cases and monthly temperature, precipitation, and relative humidity data from 2004 to 2014 were obtained from the Malaysian Ministry of Health and Malaysian Meteorological Department, respectively. Poisson generalized linear models were developed to quantify the relationship between meteorological parameters and the number of reported cholera cases. Results: The findings revealed that the total number of cholera cases in Malaysia during the 11 year study period was 3841 cases with 32 deaths. Out of these, 45.1% of the cases were among children below 12 years old and 75% of the cases were from Sabah. Temperature and precipitation gave significant impact on the cholera cases in Sabah, (p<0.001) while precipitation were significant in Terengganu (p<0.001), and Sarawak (p=0.013). Monthly lag temperature data at Lag 0, 1, and 2 months were associated with the cholera cases in Sabah (p<0.001). The change in odds of having cholera cases were by the factor of 3.5 for every 1 degrees C increase in temperature. However, the contribution of rainfall was very mild, whereby an increase of 1 mm in precipitation will increase the excess risk of cholera by up to 0.8%. Conclusion: This study concludes that climate does influence the number of cholera cases in Malaysia.
BACKGROUND: Little is known about the association between ambient temperature and cause-specific mental disorders, especially in subtropical areas. OBJECTIVE: To investigate the effect of ambient temperature on mental disorders in subtropical cities. METHOD: Daily morbidity data for mental disorders in three Chinese cities (Shenzhen, Zhaoqing, and Huizhou) were collected from medical record systems of local psychiatric specialist hospitals, covering patients of all ages. Case-crossover design combined with a distributed lag nonlinear model (DLNM) was used to assess the nonlinear and delayed effects of temperatures on five specific mental disorders (affective disorders, anxiety, depressive disorders, schizophrenia, and organic mental disorders), with analyses stratified by gender and age. The temperature of minimum effect was used as the reference value to calculate estimates. RESULTS: We observed inversed J-shaped exposure-response curves between temperature and mental morbidity and observed that low temperatures had a significant and prolonged effect on most types of mental disorders in the three cities. For example, the effect of the cold (2.5th percentile) on anxiety was consistently observed in the three cities with an odds ratio (OR) of 1.29 (95% CI: 1.06-1.57) in Zhaoqing, 1.26 (95% CI: 1.18-1.34) in Shenzhen, and 1.45 (95% CI: 1.17-1.81) in Huizhou. Low temperature was also associated with an increased risk of depressive disorders and schizophrenia. For the high temperature exposure (97.5th percentile), we only observed a significant, harmful effect on anxiety [OR = 1.30 (95% CI: 1.08, 1.58) in Shenzhen, OR = 1.16 (95% CI: 1.00, 1.34) in Zhaoqing], affective disorders [OR = 1.32 (95% CI: 1.08, 1.62) in Shenzhen], and schizophrenia [OR = 1.24 (95% CI: 1.03, 1.48) in Zhaoqing, OR = 1.03 (95% CI: 1.00, 1.06) in Huizhou]. CONCLUSIONS: Our study suggests that both low and high temperatures might be important drivers of morbidity from mental disorders, and low temperature may have a more general and wide-spread effect on this cause-specific morbidity than high temperature.
By collecting daily data on measles cases, air pollutants, and meteorological data from 2005 to 2009 in Chengguan District of Lanzhou City, semi-parametric generalized additive model (GAM) was used to quantitatively study the impact of air pollutants and meteorological factors on daily measles cases. The results showed that air pollutants and meteorological factors had effect on the number of daily measles cases, and there was a certain lag effect. Except for SO(2) and relative humidity, other factors showed statistically significant associations with daily measles cases: NO(2) lag 6 days, PM(10) and maximum temperature lag 5 days, minimum temperature and average temperature and average air pressure lag 4 days, visibility, and wind speed lag 3 days had the greatest impact on the number of daily measles cases. Under the optimum lag conditions, the number of daily measles cases increased by 15.1%, 17.6%, 7.0%, 116.6%, 98.6%, 85.7%, and 14.4% with the increase of 1 IQR in SO(2), NO(2), PM(10), maximum temperature, minimum temperature, average temperature, and wind speed; with the increase of 1 IQR in average pressure, relative humidity, visibility, and daily measles cases decreased by 12.8%, 9.7%, and 13.1%, respectively. And different factors showed different seasonal effects. The effects of SO(2) and temperature factors on daily measles cases were greater in spring and winter, but PM(10) in summer.
Benign paroxysmal positional vertigo (BPPV) is one of the most common vestibular disorders. An investigation into the factors related to BPPV could contribute to its prevention and appropriate management. We investigated the association between climatic factors and incidence of BPPV in this study. A total of 365 patients who were diagnosed with idiopathic BPPV in the emergency room of our hospital in 2015 were included. The number of patients diagnosed with BPPV per week was calculated (every week). Climatic factors, including daily average humidity, temperature, atmospheric pressure, cloud amount, sunshine amount, and daylight time, were documented daily. The weekly mean climatic value in each week was calculated. Simple correlation analysis and multivariate regression analyses were performed to identify climatic factors associated with the number of patients diagnosed with BPPV. Simple correlation analysis revealed a significant association between the humidity (r?=?0.276, p?=?0.048), temperature (r?=?0.275, p?=?0.049), and cloud amount (r?=?0.293, p?=?0.035) and the number of BPPV patients diagnosed per week. Multivariate regression analysis revealed that only the cloud amount was a statistically significant factor associated with the number of BPPV patients diagnosed every week. A significant positive association was discovered between the cloud amount and BPPV incidence. Cloud amount can therefore have an association with the incidence of BPPV.
BACKGROUND: Diarrhoeal disease is common and imposes substantial health and economic burdens across the globe, especially in the African and Southeast Asian regions. Besides causing high mortality and morbidity, diarrhoeal disease has also been associated with growth and cognitive shortfalls in children in low-resource settings. Extreme weather events brought about by climate change may increase diarrhoeal disease and impact vulnerable populations in countries regardless of levels of development. We examined the seasonal and climatic influences of acute diarrhoeal disease reports in Singapore, a city-state located in Southeast Asia. METHODS: We used a time-series analysis, adjusting for time-varying potential confounders in a negative binomial regression model and fitting fractional polynomials to investigate the relationship between climatic factors (temperature, relative humidity and rainfall) and reported diarrhoeal disease. RESULTS: We included 1,798,198 reports of diarrhoeal disease from 2005 to 2018. We observed annual trimodal peaks in the number of reports. Every 10% increase in relative humidity in the present week was positively associated with an increase in reports one week later [Incidence Rate Ratio (IRR): 1.030, 95% CI 1.004-1.057] and negatively associated with a decrease in reports six weeks later (IRR: 0.979, 95% CI 0.961-0.997). We observed effect modification of relative humidity on the risk of diarrhoeal disease in the first calendar quarter (January to March). There was weak evidence of a delayed effect of ambient air temperature on reports of diarrhoeal disease one week later (IRR: 1.013, 95% CI 0.998-1.027). No threshold effects of climatic factors were observed. Each week of school holidays was associated with a 14.4% reduction in diarrhoeal disease reports (IRR: 0.856, 95% CI: 0.840 to 0.871). Public holidays were associated with a reduction in reports in the same week and an increase a week later. CONCLUSIONS: Diarrhoeal disease is highly seasonal and is associated with climate variability. Food safety and primary healthcare resource mitigation could be timed in anticipation of seasonal and climate driven increases in disease reports.
This paper investigates the effects of prenatal exposure to extreme temperatures on birth outcomes-specifically, the log of birth weight and an indicator for low birth weight-using a nationally representative dataset on rural China. During the time period we examine (1991-2000), indoor air conditioning was not widely available and migration was limited, allowing us to address identification issues endemic in the climate change literature related to adaptation and location sorting. We find substantial heterogeneity in the effects of extreme temperature exposure on birth outcomes. In particular, prenatal exposure to heat waves has stronger negative effects than exposure to cold spells on surviving births.
In recent years, dengue has been rapidly spreading and growing in the tropics and subtropics. Located in southern China, Hong Kong’s subtropical monsoon climate may favour dengue vector populations and increase the chance of disease transmissions during the rainy summer season. An increase in local dengue incidence has been observed in Hong Kong ever since the first case in 2002, with an outbreak reaching historically high case numbers in 2018. However, the effects of seasonal climate variability on recent outbreaks are unknown. As the local cases were found to be spatially clustered, we developed a Poisson generalized linear mixed model using pre-summer monthly total rainfall and mean temperature to predict annual dengue incidence (the majority of local cases occur during or after the summer months), over the period 2002-2018 in three pre-defined areas of Hong Kong. Using leave-one-out cross-validation, 5 out of 6 observations of area-specific outbreaks during the major outbreak years 2002 and 2018 were able to be predicted. 42 out of a total of 51 observations (82.4%) were within the 95% confidence interval of the annual incidence predicted by our model. Our study found that the rainfall before and during the East Asian monsoon (pre-summer) rainy season is negatively correlated with the annual incidence in Hong Kong while the temperature is positively correlated. Hence, as mosquito control measures in Hong Kong are intensified mainly when heavy rainfalls occur during or close to summer, our study suggests that a lower-than-average intensity of pre-summer rainfall should also be taken into account as an indicator of increased dengue risk.
Numerous studies have examined the effects of weather on emergency ambulance service (EAS) demand. Given Taipei’s unique physical and social environments, empirical evidence collected from other regions may not be applicable. Collecting more information about the characteristics of vulnerable groups and the effects of weather could help the EAS managing authority in formulating cost-effective EAS policies. This study aims to look at the effects of weather on EAS demand in Taipei and to make a comparison with Hong Kong, which is also an Asian city and has a similar cultural context. The study analyzed over 370,000 EAS usage records from the Taipei City Fire Department. These records were aggregated into time series data according to patients’ characteristics and then regressed on meteorological data via multivariate forward regression. The effect size differences of the variance explained by different groups of EAS users’ regression models were compared. Afterward, the results of the regression analysis from Taipei were compared with those from a Hong Kong study. Elderly and critical patients in both cities showed significantly more sensitivity to weather than other patients. Further analysis showed that non-trauma cases were related to weather in Taipei. Although both cities had similar results, the Taipei study clearly showed that elderly and critical patients were more sensitive to weather than other patient subgroups. Health education programs should focus on the vulnerable groups identified in this study in order to increase their awareness and help them protect themselves before the onset of adverse weather conditions. By generating results that are directly applicable to Taipei, the formulation of inappropriate EAS policies can be prevented.
BACKGROUND: Scrub typhus is a major cause of acute febrile illness in the tropics and is endemic over large areas of the Asia Pacific region. The national and global burden of scrub typhus remains unclear due to limited data and difficulties surrounding diagnosis. METHODOLOGY/PRINCIPAL FINDINGS: Scrub typhus reporting data from 2003-2018 were collected from the Thai national disease surveillance system. Additional information including the district, sub-district and village of residence, population, geographical, meteorological and satellite imagery data were also collected for Chiangrai, the province with the highest number of reported cases from 2003-2018. From 2003-2018, 103,345 cases of scrub typhus were reported with the number of reported cases increasing substantially over the observed period. There were more men than women, with agricultural workers the main occupational group affected. The majority of cases occurred in the 15-64 year old age group (72,144/99,543, 72%). Disease burden was greatest in the northern region, accounting for 53% of the total reported cases per year (mean). In the northern region, five provinces-Chiangrai, Chiangmai, Tak, Nan and Mae Hong Son-accounted for 84% (46,927/55,872) of the total cases from the northern region or 45% (46,927/103,345) of cases nationally. The majority of cases occurred from June to November but seasonality was less marked in the southern region. In Chiangrai province, elevation, rainfall, temperature, population size, habitat complexity and diversity of land cover contributed to scrub typhus incidence. INTERPRETATION: The burden of scrub typhus in Thailand is high with disease incidence rising significantly over the last two decades. However, disease burden is not uniform with northern provinces particularly affected. Agricultural activity along with geographical, meteorological and land cover factors are likely to contribute to disease incidence. Our report, along with existing epidemiological data, suggests that scrub typhus is the most clinically important rickettsial disease globally.
As climate change increases temperatures and the frequency of extreme heat events, farm workers are among the most affected. Because of the nature of the work, farmers working at hot temperatures may experience physiological changes in their body such as increases in body temperature, blood pressure, and heart rate, as well as leading to intolerance of blood glucose and blood cholesterol. This study speculates that extreme heat hazards may lead to incidence of heat-related diseases among farmers in the workplace and other metabolic disorders. The purpose of this study is to determine the potential health effects of heat exposure between agroecology and conventional rice farmers. This study recruited 33 agroecology and 25 conventional rice farmers in the northern state of peninsular Malaysia. The adapted questionnaire was used to obtain the respondent’s background information. Also, the environmental and physiological measurements were carried out to determine the heat stress index (HSI) and physiological strain index (PSI). The HSI was monitored by using WetBulb globe temperature meter, whereas the physiological parameters were assessed by using thermometer, blood pressure monitor, and blood cholesterol/glucose monitor kit. The study shows that there is a significant difference between HSI, blood pressure, and blood glucose levels among organic and conventional farmers. Both groups of farmers also have a significant association between blood glucose and blood pressure. The findings of this study suggest that pesticide use can act as a synergistic effect, resulting in more significant health effects for those who were exposed to heat in their work environment. Given the impact of climate change on the agriculture sector, the disparity in the heat-related health effects between pesticides used and nonpesticides used farming community may serve as a critical factor to consider while implementing the workplace heat stress program in the agricultural industry.
BACKGROUND: The disease burden of infectious diarrhea cannot be underestimated. Its seasonal patterns indicate that weather patterns may play an important role and have an important effect on it. The objective of this study was to clarify the relationship between temperature and infectious diarrhea, and diarrhea-like illness. METHODS: Distributed lag non-linear model, which was based on the definition of a cross-basis, was used to examine the effect. RESULTS: Viral diarrhea usually had high incidence in autumn-winter and spring with a peak at -6°C; Norovirus circulated throughout the year with an insignificant peak at 8°C, while related bacteria usually tested positive in summer and peaked at 22°C. The lag-response curve of the proportion of diarrhea-like cases in outpatient and emergency cases revealed that at -6°C, with the lag days increasing, the proportion increased. Similar phenomena were observed at the beginning of the curves of virus and bacterial positive rate, showing that the risk increased as the lag days increased, peaking on days 16 and 9, respectively. The shape of lag-response curve of norovirus positive rate was different from others, presenting m-type, with 2 peaks on day 3 and day 18. CONCLUSION: Weather patterns should be taken into account when developing surveillance programs and formulating relevant public health intervention strategies.
BACKGROUND: A large number of studies have found a positive association between diurnal temperature range (DTR) and cardiovascular diseases (CVDs) incidence and mortality. Few studies regarding the effects of DTR on blood pressure (BP) are available. OBJECTIVE: To investigate the effects of DTR on BP in Jinchang, northwestern China. METHODS: Based on a prospective cohort research, a total of 46,609 baseline survey data were collected from 2011 to 2015. The meteorological observation data and environmental monitoring data were collected in the same period. The generalized additive model (GAM) was used to estimate the relationship between DTR and BP after adjusting for confounding variables. RESULTS: Our study found that there was a positive linear correlation between DTR and systolic blood pressure (SBP) and plus pressure (PP), and a negative linear correlation between DTR and diastolic blood pressure (DBP). With a 1 °C increase of DTR, SBP and PP increased 0.058 mmHg (95%CI: 0.018-0.097) and 0.114 mmHg (95%CI: 0.059-0.168) respectively, and DBP decreased 0.039 mmHg (95%CI:-0.065 ~ -0.014). There was a significant interaction between season and DTR on SBP and PP. DTR had the greatest impact on SBP and PP in hot season. The association between DTR and BP varied significantly by education level. CONCLUSION: There was a significant association between DTR and BP in Jinchang, an area with large temperature change at high altitudes in northwestern China. These results provide new evidence that DTR is an independent risk factor for BP changes among general population. Therefore, effective control and management of BP in the face of temperature changes can help prevent CVDs.
Vulnerability to environmental hazards has widely been assessed in disaster risk science and climate change literature by integrating socio-economic and geographical features of a community or a place. However, the role of spatial proximity to cities – an important geographical feature – in influencing household vulnerability has not been scrutinized. This paper assesses how distance to cities affects the vulnerability of rural farming communities against flood hazard. This paper proposes a Vulnerability-Proximity Nexus (VPN) framework and operationalises it in the context of Pakistan. A household survey was conducted to collect primary data from three flood-affected sub-districts of Punjab province. A total of 325 samples were collected, out of which 164 samples were from villages located near to the cities and 161 were far from the cities. Vulnerability indices were developed through holistic (exposure, susceptibility, and capacity) and livelihood (human, social, financial, physical, and natural) perspective of vulnerability. Mann-Whitney U and Pearson’s correlation tests were performed to analyse linkages between distance and vulnerability. Results confirmed that the distance to the cities influences the vulnerability of surrounding farming communities. A significant and positive correlation between distance to city and rural livelihood vulnerability was found. Rural farming communities living close to the cities were less vulnerable, mainly due to better transfer of services and facilities from cities, which has also made rural communities more educated, informed, financially strong, and connected with easier access to public and private institutions. This study highlights the importance of regional and rural development discourse for vulnerability and can help disaster managers and planners to establish synergies for designing effective disaster risk reduction policies and strategies.
Rhegmatogenous retinal detachment (RRD) frequency was observed to be higher with an increase in the daily temperature range. This showed that a wide daily range of temperature, rather than the absolute value of the temperature, is associated with the occurrence of RRD. Purpose. To investigate the association between the frequency of rhegmatogenous retinal detachment (RRD) and the atmospheric temperature. Method. A retrospective review of consecutive eyes that had undergone primary RRD surgery from 1996 to 2016 at Chungbuk National University Hospital was conducted. Temperature data (highest, lowest, and mean daily temperatures and daily temperature range) in Chungbuk Province were obtained from the Korean Meteorological Administration database. We investigated the relationship between the daily temperature range and the frequency of RRD surgery. We also analyzed the association between various temperature data and the frequency of RRD surgery. Result. There were 1,394 RRD surgeries from 1996 to 2016. Among them, 974 eyes were included in this study. The monthly average number of RRD operations showed a bimodal peak (in April and October) throughout the year. With the same tendency as the frequency of RRD, the monthly average of the daily temperature range over 1 year also showed a bimodal peak in April and October. There was a significant positive correlation between the monthly average of the daily temperature range and the number of RRD surgeries (r?=?0.297, P < 0.001). However, there were no associations between RRD frequency and the mean temperature, highest temperature, and lowest temperature. Conclusion. The higher the daily temperature range, the higher was the RRD frequency observed. We speculated that dynamic changes in temperature during the day may affect degrees in chorioretinal adhesion and liquefaction of the vitreous, which may eventually result in retinal detachment. Therefore, further experimental studies on the correlation between temperature changes and retinal detachment are needed.
BACKGROUND: Suicidal ideation is subject to serious underestimation among existing public health studies. While numerous factors have been recognized in affecting suicidal thoughts and behaviors (STB), the associated environmental risks have been poorly understood. Foremost among the various environment risks were air pollution, in particular, the PM2.5. The present study attempted to examine the relationship between PM(2.5) level and local weekly index of suicidal ideation (ISI). METHODS: Using Internet search query volumes in Baidu (2017), the largest internet search engine in China, we constructed a prefectural panel data (278 prefectures, 52?weeks) and employed dynamic panel GMM system estimation to analyze the relationship between weekly concentration of PM2.5 (Mean?=?87??g·m(-?3)) and the index of suicidal ideation (Mean?=?49.9). RESULTS: The results indicate that in the spring and winter, a 10??g·m(-?3) increase in the prior week’s PM(2.5) in a Chinese city is significantly associated with 0.020 increase in ISI in spring and a 0.007 increase in ISI in winter, after taking account other co-pollutants and meteorological conditions. CONCLUSION: We innovatively proposed the measure of suicidal ideation and provided suggestive evidence of a positive association between suicidal ideation and PM(2.5) level.
BACKGROUND: The association between temperature and mortality has been widely reported. However, it remains largely unclear whether inflammation-related diseases, caused by excessive or inappropriate inflammatory reaction, may be affected by ambient temperature, particularly in low-income areas. OBJECTIVES: To explore the association between ambient temperature and clinical visits for inflammation-related diseases in rural villages in the Ningxia Hui Autonomous Region, China, during 2012?2015. METHODS: Daily data on inflammation-related diseases and weather conditions were collected from 258 villages in Haiyuan (161 villages) and Yanchi (97 villages) counties during 2012?2015. A Quasi-Poisson regression with distributed lag non-linear model was used to examine the association between temperature and clinical visits for inflammation-related diseases. Stratified analyses were performed by types of diseases including arthritis, gastroenteritis, and gynecological inflammations. RESULTS: During the study period, there were 724,788 and 288,965 clinical visits for inflammation-related diseases in Haiyuan and Yanchi, respectively. Both exposure to low (RR: 2.045, 95% CI: 1.690, 2.474) and high temperatures (RR: 1.244, 95% CI: 1.107, 1.399) were associated with increased risk of total inflammation-related visits in Haiyuan county. Low temperatures were associated with increased risks of all types of inflammation-related diseases in Yanchi county (RR: 4.344, 95% CI: 2.887, 6.535), while high temperatures only affected gastroenteritis (RR: 1.274, 95% CI: 1.040, 1.561). Moderate temperatures explained approximately 26% and 33% of clinical visits due to inflammation-related diseases in Haiyuan and Yanchi, respectively, with the burden attributable to cold exposure higher than hot exposure. The reference temperature values ranged from 17 to 19 in Haiyuan, and 12 to 14 in Yanchi for all types of clinical visits. CONCLUSIONS: Our findings add additional evidence for the adverse effect of suboptimal ambient temperature and provide useful information for public health programs targeting people living in rural villages.
BACKGROUND: Few epidemiological investigations have focused on the influence of environmental temperature on human sperm quality. Here, we evaluated the potential association between ambient temperature and human sperm quality in Wuhan, China, and examined the interactive effect of particulate matter (PM(2.5)) and temperature. METHODS: 1780 males who had been living in Wuhan for no less than three months and received semen analysis at the Department of Reproductive Medicine in Renmin Hospital of Wuhan University between April 8, 2013 and June 30, 2015 were recruited. Daily mean meteorological data and air pollution data (PM(2.5), O(3) and NO(2)) in Wuhan between 2013 and 2015 were collected. A generalized linear model was used to explore the associations between ambient temperature and sperm quality (including sperm concentration, percentage of normal sperm morphology, and progressive motility) at 0-9, 10-14, 15-69, 70-90, and 0-90?days before semen examination, and the interaction between temperature and PM(2.5). RESULTS: The associations between ambient temperature and sperm quality were an inverted U-shape at five exposure windows, except for a lag of 0-9?days for sperm concentration. A 1?°C increase in ambient temperature above the thresholds was associated with a 2.038 (1.292?~?2.783), 1.814 (1.217?~?2.411), 1.458 (1.138?~?1.777), 0.934(0.617?~?1.251) and 1.604 (1.258?~?1.951) decrease in the percentage of normal sperm morphology at lag 0-9, lag 10-14, lag 15-69, lag 70-90, and lag 0-90?days, respectively. The interaction p-values of PM(2.5) and temperature were mostly less than 0.05 at five exposure windows. When ambient temperature exposure levels were above the thresholds, a 0.979 (0.659-1.299) and 3.559 (0.251?~?6.867) decrease in percentage of normal sperm morphology per 1?°C increase in temperature at lag 0-90?days was observed in the PM(2.5)???P(50) group and PM(2.5)?>?P(50) group, respectively. CONCLUSIONS: Our results indicate that exposure to ambient temperature has a threshold effect on sperm quality, and PM(2.5) enhances the effect of temperature on sperm quality when temperatures are above the threshold.
BACKGROUND: The aim of this study was to investigate the possible relation of meteorological parameters and air pollutant particle concentrations with the incidence of spontaneous pneumothorax in the Bolu region of Turkey. METHODS: Between January 2015 and February 2019, a total of 200 patients (175 males, 25 females; mean age 42.5±19.9 years, range, 10 to 88 years) with spontaneous pneumothorax were retrospectively analyzed. For each day, standard weather parameters including daily average temperature, relative humidity, wind speed, actual pressure, and daily total precipitation and concentration of air pollutants (PM(10) and SO(2)) were recorded. RESULTS: During the study period, there were 200 cases with spontaneous pneumothorax within 178 days. The number of days with spontaneous pneumothorax represented 11.8% of the total number of days (1,504 days). In the study, 76.9% of the days with spontaneous pneumothorax were clustered. All meteorological (temperature, humidity, pressure, wind speed, and precipitation) and air pollution parameters (PM10 a nd SO(2)) were available for 1,438 days (95.61%) and 853 days (56.71%), respectively. There was a significant relationship between spontaneous pneumothorax and air temperature (r=-0.094, p=0.001), and air pollution (PM10, r=-0.080, p=0.020; SO(2), r=-0.067, p=0.045). CONCLUSION: Our study results show a relationship between spontaneous pneumothorax and air temperature, and air pollution. Preventing air pollution, which is a public health problem, can lead to a reduction in spontaneous pneumothorax.
BACKGROUND AND OBJECTIVES: The number of pediatric patients diagnosed with influenza types A and B is increasing annually, especially in temperate regions such as Shanghai (China). The onset of pandemic influenza viruses might be attributed to various ambient meteorological factors including temperature, relative humidity (Rh), and PM(1) concentrations, etc. The study aims to explore the correlation between the seasonality of pandemic influenza and these factors. METHODS: We recruited pediatric patients aged from 0 to 18?years who were diagnosed with influenza A or B from July 1st, 2017 to June 30th, 2019 in Shanghai Children’s Medical Centre (SCMC). Ambient meteorological data were collected from the Shanghai Meteorological Service (SMS) over the same period. The correlation of influenza outbreak and meteorological factors were analyzed through preliminary Pearson’s r correlation test and subsequent time-series Poisson regression analysis using the distributed lag non-linear model (DLNM). RESULTS: Pearson’s r test showed a statistically significant correlation between the weekly number of influenza A outpatients and ambient meteorological factors including weekly mean, maximum, minimum temperature and barometric pressure (P?
Hand, foot and mouth disease (HFMD) is a growing threat to children’s health, causing a serious public health burden in China. The relationships between associated meteorological factors and HFMD have been widely studied. However, the HFMD burden due to relative humidity from the perspective of attributable risk has been neglected. This study investigated the humidity-HFMD relationship in three comprehensive perspectives, humidity-HFMD relationship curves, effect modification and attributable risks in the Sichuan Basin between 2011 and 2017. We used multistage analyses composed of distributed lag nonlinear models (DLNMs), a multivariate meta-regression model and the calculations of attributable risk to quantify the humidity-HFMD association. We observed a J-shaped pattern for the pooled cumulative humidity-HFMD relationship, which presented significant heterogeneity relating to the geographical region and number of primary school students. Overall, 27.77% (95% CI 25.24-30.02%) of HFMD infections were attributed to humidity. High relative humidity resulted in the greatest burden of HFMD infections. The proportion of high humidity-related HFMD in the southern basin was higher than that in the northern basin. The findings provide evidence from multiple perspectives for public health policy formulation and health resource allocation to develop priorities and targeted policies to ease the HFMD burden associated with humidity.
In this study, the spatial pattern and temporal evolution of PM(2.5) over North China Plain (NCP) and Northeast China (NEC) during 2014-2018 was investigated. The annual mean PM(2.5) shows clear decreasing trends over time, but the seasonal mean PM(2.5) as well as the seasonal total duration and frequency of haze days shows large inter-annual fluctuation. Based on the atmospheric stagnation index (ASI), this study examined the correlation between ASI and haze events over NCP and NEC. Detailed analysis indicates that location dependency exists of ASI in the capability of capturing the haze events, and the ability is limited in NCP. Therefore, we first propose two alternative methods in defining the ASI to either account for the lag effect or enlarge the threshold value of wind speed at 500 hPa. The new methods can improve the ability of ASI to explain the haze events over NEC, though marginal improvement was achieved in NCP. Furthermore, this study constructed the equation based on the boundary layer height and wind speed at 10-meter, apparently improving the ability in haze capture rate (HCR), a ratio of haze days during the stagnation to the total haze days. Based on a multi-model ensemble analyses under Representative Concentration Pathway (RCP) 8.5, we found that by the end of this century, climate change may lead to increases in both the duration and frequency of wintertime stagnation events over NCP. In contrast, the models predict a decrease in stagnant events and the total duration of stagnation in winter over NEC.
Previous studies have revealed associations of meteorological factors with tuberculosis (TB) cases. However, few studies have examined their lag effects on TB cases. This study was aimed to analyse nonlinear lag effects of meteorological factors on the number of TB notifications in Hong Kong. Using a 22-year consecutive surveillance data in Hong Kong, we examined the association of monthly average temperature and relative humidity with temporal dynamics of the monthly number of TB notifications using a distributed lag nonlinear models combined with a Poisson regression. The relative risks (RRs) of TB notifications were >1.15 as monthly average temperatures were between 16.3 and 17.3 °C at lagged 13-15 months, reaching the peak risk of 1.18 (95% confidence interval (CI) 1.02-1.35) when it was 16.8 °C at lagged 14 months. The RRs of TB notifications were >1.05 as relative humidities of 60.0-63.6% at lagged 9-11 months expanded to 68.0-71.0% at lagged 12-17 months, reaching the highest risk of 1.06 (95% CI 1.01-1.11) when it was 69.0% at lagged 13 months. The nonlinear and delayed effects of average temperature and relative humidity on TB epidemic were identified, which may provide a practical reference for improving the TB warning system.
INTRODUCTION: This study aims to determine the association between temperature and preeclampsia and whether it is affected by seasonality and rural/urban lifestyle. METHODS: This cohort study included women who delivered at our medical center from 2004 to 2013 (31,101 women, 64,566 deliveries). Temperature values were obtained from a spatiotemporally resolved estimation model performing predictions at a 1×1km spatial resolution. In “Warm” pregnancies >50% of gestation occurred during the spring-summer period. In cold pregnancies >50% of gestation occurred during the fall and winter. Generalized estimating equation multivariable models were used to estimate the association between temperature and incidence of preeclampsia. RESULTS: 1) The incidence of preeclampsia in at least one pregnancy was 7% (2173/64,566); 2) during “warm” pregnancies, an elevation of one IQR of the average temperature in the 1st or the 3rd trimesters was associated with an increased risk to develop preeclampsia [patients with Jewish ethnicity: 1st trimester: relative risk (RR) of 2.38(95%CI 1.50; 3.80), 3rd trimester 1.94(95%CI 1.34;2.81); Bedouins: 1st trimester: RR = 2.91(95%CI 1.98;4.28), 3rd trimester: RR = 2.37(95%CI 1.75;3.20)]; 3) In “cold” pregnancies, an elevation of one IQR of average temperature was associated with a lower risk to develop preeclampsia among patients with Bedouin-Arab ethnicity RR = 0.68 (95% CI 0.49-0.94) for 1st trimester and RR = 0.62 (95% CI 0.44-0.87) for 3rd trimester. CONCLUSIONS: 1) Elevated averaged temperature during the 1st or 3rd trimesters in “warm” pregnancies confer an increased risk for the development of preeclampsia, especially in nomadic patients; 2) Of interest, during cold pregnancies, elevated averaged temperature was associated with a lower risk to develop preeclampsia for nomadic patients. 3) These findings suggest temperature might be associated with perturbations in maternal heat homeostasis resulting in reallocation of energy resources and their availability to the fetus that may increase the risk for preeclampsia. This observation is especially relevant in the context of global warming and its effects on maternal/fetal reproductive health.
OBJECTIVE: The aim was to use a novel statistical test to predict the trend of subarachnoid hemorrhage (SAH) incidence in response to temperature change and demonstrate its delayed effect in a short hazard period. PATIENTS AND METHODS: In a retrospective study, data collected between January 2005 and September 2019 were analyzed and 1682 consecutive SAH patients from one hospital were enrolled. Meteorological data in this period including temperature, atmospheric pressure, and humidity were obtained from the China Surface Meteorological Station. Using a case-crossover analysis and distributed lag linear model (DLM) with 4 days lag period to assess the association of temperature change from the previous day (TCP) and risk of SAH. Results were presented as overall cumulative odds ratios (ORs) and 95% CI. RESULTS: Temperature decline was associated with increased risks of SAH: overall cumulative OR was 1.14 (95% CI: 1.05-1.23) for -1.1°C; 2.11 (95% CI: 1.37-3.25) for -6.2°C, as compared with a reference TCP of 0°C. Temperature decline on the day of SAH onset was significantly associated with SAH incidence days, ORs 1.34 (95% CI: 1.19-1.52). In addition, December, ORs 1.49 (95% CI: 1.17-1.90) in winter was the ictus peak in Rizhao throughout the year. CONCLUSIONS: Temperature decline from the previous day is a trigger for the occurrence of SAH. Its effect was most apparent on the day of exposure.
Exposure to particulate matter of smaller than 2.5 ?m in diameter (PM(2.5)) is linked to increased human mortality, and could be further complicated by concurrent ambient air temperatures. Published reports indicate that the association between ambient temperatures and mortality due to PM(2.5) exposure is dissimilar across different geographic areas. Thus, it is unclear how ambient temperatures at different geographic locations can together modulate the influence of PM(2.5) on mortality. In this paper, we examined how temperature modulated the association between mortality and PM(2.5) exposure in 15 Chinese cities during 2014-2016. For analysis, First, Poisson generalized additive models under different temperature stratifications (<10th, 10-90th, and >90th temperature percentiles) was used to estimate PM(2.5) associations to mortality, which were specific to different cities. Second, we used a meta-analysis to combine the effects at each temperature stratum and region (southern and northern China). Results revealed that high temperatures (daily mean temperature >90th percentile) robustly amplified observed associations of mortality and PM(2.5) exposure, and the modifications were heterogeneous geographically. In the northern regions, a 10 ?g/m(3) increment in PM(2.5) was associated with 0.18%, 0.28%, and 1.54% increase in non-accidental mortalities and 0.33%, 0.39%, and 1.32% increase in cardiovascular mortalities at low, moderate, and high temperature levels, respectively. In the southern regions, a 10 ?g/m(3) increment in PM(2.5) was associated with 0.52%, 0.62%, and 1.90% increase in non-accidental mortalities and 0.55%, 0.98%, and 2.25% increase in cardiovascular mortalities at low, moderate, and high temperature levels, respectively. It is concluded that temperature altered PM(2.5)-mortality associations in southern and northern China synergistically, but the effect was more pronounced in the south. Therefore, geography and temperature need to be considered when studying how PM(2.5) affects health.
PURPOSE: Chronic obstructive pulmonary disease (COPD) is a major cause of chronic diseases causing considerable social and economic burden globally. Despite substantial evidence on temperature-COPD association, few studies have investigated the acute effect of temperature variability (TV), a potential trigger of exacerbation of COPD disease, and it remains unknown what fraction of the disease burden of COPD is attributable to TV. PATIENTS AND METHODS: Based on 71,070 COPD hospitalizations during 2013-2015 in Guangzhou, China, we conducted a time-series analysis using quasi-Poisson regression to assess the association between TV and hospital admission for COPD after adjusting for daily mean temperature. Short-term TV was captured by the standard deviation of hourly or daily temperatures across various exposure days. We also provided the fraction (total number) of COPD attributable to TV. Stratified analyses by admission route, sex, age, occupation, marital status and season were performed to identify vulnerable subpopulations. RESULTS: We found a linear relationship between TV and COPD hospitalization, with a 1°C increase in hourly TV and daily TV associated with 4.3% (95%CI: 2.2-6.4) and 4.0% (2.3-5.8) increases in COPD, respectively. The greater relative risks of TV identified males, people aged 0-64 years, blue collar, and divorced/widowed people as vulnerable population. There were 12.0% (8500 cases) of COPD hospitalization attributable to hourly TV during the study period. Daily TV produced similar estimates of relative effects (relative risk) but grater estimates of absolute effects (attributable fraction) than hourly TV. CONCLUSION: We concluded that TV was an independent risk factor of COPD morbidity, especially among the susceptible subgroups. These findings would be helpful to guide the development of targeted public intervention.
BACKGROUND: In the context of global warming, studies have turned to assess the temporal trend of the association between temperature and health outcomes, which can be used to reflect whether human beings have adapted to the local temperature. However, most studies have only focused on hot temperature and mortality. We aim to investigate the temporal variations in the association between ambient temperature and hospitalisations for cardiovascular diseases in Queensland, Australia from 1995 to 2016. METHODS AND FINDINGS: We obtained data on 1,855,717 cardiovascular hospitalisations (mean age: 65.9 years, 42.7% female) from all 443 postal areas in Queensland, Australia between January 1, 1995 and December 31, 2016. Grid-level meteorological data were downloaded from scientific information for landowners. We used a time-stratified case-crossover design fitted with a conditional quasi-Poisson regression model and time-varying distributed lag nonlinear model (DLNM) to evaluate the association between temperature and cardiovascular hospitalisations and the temporal trends of the associations. Stratified analyses were performed in different age, sex, and climate zones. In all groups, relative risks (RRs) of cardiovascular hospitalisations associated with high temperatures (heat effects) increased, but cold effects showed a decreasing trend from 1995 to 2016. The increasing magnitude of heat effects was larger (p = 0.002) in men than in women and larger (p < 0.001) in people aged ?69 years than in those aged ?70 years. There was no apparent difference amongst different climate zones. The study was limited by the switch from ICD-9 to ICD-10 coding systems, by being unable to separate first-time hospitalisation from repeated hospitalisations, and possibly by confounding by air pollution or by influenza infections. CONCLUSION: The impacts of cold temperatures on cardiovascular hospitalisations have decreased, but the impacts of high temperatures have increased in Queensland, Australia. The findings highlight that Queensland people have adapted to the impacts of cold temperatures, but not high temperatures. The burden of cardiovascular hospitalisations due to high temperatures is likely to increase in the context of global warming.
To investigate the correlation between environmental-meteorological factors and daily visits for acute otitis media (AOM) in Lanzhou, China. METHODS: Data were collected in 2014-2016 by the Departments of Otolaryngology-Head and Neck Surgery at two hospitals in Lanzhou. Relevant information, including age, sex and visiting time, was collected. Environmental data included air quality index, PM10, PM2.5, O(3), CO, NO(2) and SO(2), and meteorological data included daily average temperature (T, °C), daily mean atmospheric pressure (AP, hPa), daily average relative humidity (RH, %) and daily mean wind speed (W, m/s). The SPSS22.0 software was used to generate Spearman correlation coefficients in descriptive statistical analysis, and the R3.5.0 software was used to calculate relative risk (RR) and to obtain exposure-response curves. The relationship between meteorological-environmental parameters and daily AOM visits was summarized. RESULTS: Correlations were identified between daily AOM visits and CO, O(3), SO(2), CO, NO(2), PM2.5 and PM10 levels. NO(2), SO(2), CO, AP, RH and T levels significantly correlated with daily AOM visits with a lag exposure-response pattern. The effects of CO, NO(2), SO(2) and AP on daily AOM visits were significantly stronger compared to other factors (P < 0.01). O(3), W, T and RH were negatively correlated with daily AOM visits. The highest RR lagged by 3-4 days. CONCLUSIONS: The number of daily AOM visits appeared to be correlated with short-term exposure to mixed air pollutants and meteorological factors from 2014 through 2016 in Lanzhou.
BACKGROUND: Suicidal behavior is determined by the consequence of an interaction between biological, psychological and sociological factors, as well as between individual and environmental effects. Fluctuations in meteorological factors can modify human behavior and affect suicidal rates. We hypothesize that high temperatures can be associated with an increase rate of suicidal attempts. METHODS: We included all the patients admitted to Soroka University Medical Center (SUMC) due to suicide attempts between the years 2002-2017 and were residents of Southern Israel. We computed two sets of regression models: first, a time stratified case-crossover design to control for seasonality and individual differences. Results are presented as odds ratio (OR) with confidence interval (CI); and then, time-series analyses to calculate the incidence rate ratio (IRR) and the cumulative effect of temperature on the daily incidences of emergency department (ED) admissions after suicide attempts. We stratified the analyses by demographic variables to identify significant individual differences. RESULTS: We identified 3100 attempts, by 2338 patients who lived in Be’er Sheva between 16 and 90 years of age; 421 patients made 2+ attempts. Suicide attempts were associated with a 5 °C increase during the summer season (OR 1.59, 95% CI 1.22-2.08) and a 5 °C increase in all seasons was associated with those who have made multiple attempts (OR 1.18, 95% CI 1.0005-1.38). The cumulative effect of 5 °C increment is associated with more suicide attempts over 2 days (IRR 1.10, 95% CI 0.98; 1.24) and 5 days (IRR 1.04, 95% CI 1.00; 1.08). The associations were greater for patients with psychiatric diagnosis and patients with multiple attempts. In a stratified analysis by individual characteristics we didn’t find significant association. CONCLUSION: High temperatures and low amount of precipitations are evidently of great impact on people’s susceptibility to suicidal behavior, especially for individuals who have had a prior suicide attempt. Our findings indicate the need for public health attention in the summer when temperature increases precipitously over days, especially for those who have made a prior suicide attempt.
The sub-divided unit (SDU) is the major type of substandard housing in Hong Kong. This study monitored the microclimatic conditions in eight SDUs for 24 h in summer. The mean CO2 concentration (1012 mg/m(3)) under natural ventilation was much higher than the outdoor level (similar to 410 mg/m(3)), suggesting that ventilation was ineffective in most SDUs. The mean predicted mean vote (PMV) was 1.7 (warm), corresponding to 75% predicted percentage dissatisfied (PPD). None of the SDUs was thermally acceptable (PPD < 20%) at any time in the monitoring period. If the adaptive thermal comfort standard was considered, the acceptable temperature range would be between 23.4 degrees C and 30.4 degrees C in operative temperature and the thermally acceptable time would be 47%. Larger openable window size, larger external wall area and poor ventilation significantly contributed to higher maximum indoor air temperature.
The present study is a pilot study to examine the initial effectiveness of the Support for Students Exposed to Trauma (SSET) program (Jaycox et al. in Support for Students Exposed to Trauma: the SSET program. Lesson plans, worksheets, and materials. TR-675, RAND, Santa Monica, CA, 2009) in reducing PTSD symptoms and building resilience and social support among children living in flood-affected rural areas of Southern Punjab, Pakistan. One hundred and ninety-three children were screened for symptoms of post-traumatic stress, and 38% met eligibility criteria. Children were then randomly assigned into experimental (n = 38) and control (n = 37) groups. The findings of the study showed a significant reduction in PTSD symptoms, and improvement in resilience, and perceived social support in the experimental group. The result of the study demonstrates that SSET, delivered by a clinically trained provider, may be an effective intervention for treating traumatic stress symptoms among children affected by natural disasters like flooding, particularly in under-resourced contexts. This pilot lays the initial groundwork for SSET in this context, which may ultimately be implemented by non-clinicians to address trauma-related psychological issues.
Owing to global climate change, the global resurgence of vector-borne infectious diseases and their potential to inflict widespread casualties among human populations has emerged as a pivotal burden on public health systems. Tsutsugamushi disease (scrub typhus) in the Republic of Korea is steadily increasing and was designated as a legal communicable disease in 1994. The disease is a mite-borne acute febrile disease most commonly contracted from October to December. In this study, we tried to determine the prevalence of tsutsugamushi disease transmitted by chigger mites living on rodents and investigated their target vector diversity, abundance, and distribution to enable the mapping of hotspots for this disease in 2015. A total of 5 species belonging to 4 genera (109 mites): Leptotrombidium scutellare 60.6%, L. pallidum 28.4% Neotrombicula tamiyai 9.2%, Euschoengastia koreaensis/0.9%), and Neoschoengastia asakawa 0.9% were collected using chigger mite collecting traps mimicking human skin odor and sticky chigger traps from April to November 2015. Chigger mites causing tsutsugamushi disease in wild rodents were also collected in Hwaseong for the zoonotic surveillance of the vector. A total of 77 rodents belonging to 3 genera: Apodemus agrarius (93.5%), Crocidura lasiura (5.2%), and Micromys minutus (1.3%) were collected in April, October, and November 2015. The most common mite was L. pallidum (46.9%), followed by L. scutellare (18.6%), and L. orientale (18.0%). However, any of the chigger mite pools collected from rodent hosts was tested positive for Orientia tsutsugamushi, the pathogen of tsutsugamushi disease, in this survey.
The effects of heat waves (HW) are more pronounced in urban areas than in rural areas due to the additive effect of the urban heat island (UHI) phenomenon. However, the synergies between UHI and HW are still an open scientific question and have only been quantified for a few metropolitan cities. In the current study, we explore the synergies between UHI and HW in Seoul city. We consider summertime data from two non-consecutive years (i.e., 2012 and 2016) and ten automatic weather stations. Our results show that UHI is more intense during HW periods than non-heat wave (NHW) periods (i.e., normal summer background conditions), with a maximum UHI difference of 3.30°C and 4.50°C, between HW and NHW periods, in 2012 and 2016 respectively. Our results also show substantial variations in the synergies between UHI and HW due to land use characteristics and synoptic weather conditions; the synergies were relatively more intense in densely built areas and under low wind speed conditions. Our results contribute to our understanding of thermal risks posed by HW in urban areas and, subsequently, the health risks on urban populations. Moreover, they are of significant importance to emergency relief providers as a resource allocation guideline, for instance, regarding which areas and time of the day to prioritize during HW periods in Seoul.
BACKGROUND: This study aimed to describe the changing distribution of human brucellosis between 2004 and 2017 in mainland China and seek scientific evidence of the relationship between socio-economic, environmental, and ecological factors and human brucellosis incidence. METHODS: The annual numbers of brucellosis cases and incidence rates from 31 provinces in mainland China between 2004 and 2017 were obtained from the Data-Center for China Public Health Science. The number of monthly brucellosis cases in 2018 was obtained from the Chinese Center for Disease Control and Prevention. The electronic map of the People’s Republic of China was downloaded from the National Earth System Science Data Sharing Platform. Human population density, gross domestic product (GDP), and an inventory of cattle and sheep at the end of each year from 2004 to 2017 were obtained from the National Bureau of Statistics of China. Annual rainfall data from 31 provinces in the People’s Republic of China from 2004 to 2017 were collected from the China Meteorological Data Service Center. The risk distribution and changing trends of human brucellosis were mapped with ArcGIS. A cluster analysis was employed to identify geographical areas and periods with statistically significant incidence rates. Multivariate linear regression was used to determine possible factors that were significantly correlated with the presence of human brucellosis cases. RESULTS: Human brucellosis cases have spread throughout the whole country. Human brucellosis cases occurred mostly from March to August and were concentrated from April to July. The inventory of sheep, GDP, and climate were significantly correlated with the presence of brucellosis cases in mainland China. CONCLUSIONS: The geographical expansion of human brucellosis in mainland China was observed, so did the high-incidence clusters between 2004 and 2017. Most of the cases were reported during the early spring to early summer (February-August). Results from the multivariate linear regression suggested that the inventory of sheep, GDP, and climate were significantly associated with the incidence of human brucellosis in mainland China.
Hand, Foot, and Mouth Disease (HFMD) is a common and widespread infectious disease. Previous studies have presented evidence that climate factors, including the monthly averages of temperature, relative humidity, air pressure, wind speed and Cumulative Risk (CR) all have a strong influence on the transmission of HFMD. In this paper, the monthly time-lag geographically- weighted regression model was constructed to investigate the spatiotemporal variations of effect of climate factors on HFMD occurrence in Inner Mongolia Autonomous Region, China. From the spatial and temporal perspectives, the spatial and temporal variations of effect of climate factors on HFMD incidence are described respectively. The results indicate that the effect of climate factors on HFMD incidence shows very different spatial patterns and time trends. The findings may provide not only an indepth understanding of spatiotemporal variation patterns of the effect of climate factors on HFMD occurrence, but also provide helpful evidence for making measures of HFMD prevention and control and implementing appropriate public health interventions at the county level in different seasons.
In the past decades, severe heat waves have frequently occurred in many parts of the world. These conspicuous heat waves exerted terrible influences on human health, society, the economy, agriculture, the ecosystem and so on. Based on observed daily temperatures in China, an integrated index of heat waves and extreme-temperature days was established involving the frequency, duration, intensity and scale of these events across large cities in China. Heat waves and extreme-temperature days showed an increasing trend in most regions except northwest China from 1955 to 2014. After the late 1980s, the increasing trend was more obvious than the decades before. The cities in the middle and lower reaches of the Yangtze River were threatened by the most serious heat events in the past 60 years, especially Chongqing and Changsha. Due to the subtropical monsoon climate and special terrain, Chongqing experienced the most heat events in a long period of time. In particular, there was obvious fluctuation of hot years in 31 cities, which did not continuously rise with global warming; 21 cities mainly located in the eastern and southern regions of China had an obvious rising trend; eight cities had a clear declining trend which was mainly distributed in the western and northern regions of China; and there were no extreme-temperature days in Kunming and Lhasa in the past 60 years. The study revealed an obvious differentiation of heat events for 31 cities under climate change; heat threat in most cities is increasing but declining or remaining unchanged in the other cities. The trend is likely to intensify with global warming.
BACKGROUND: Human brucellosis imposes a heavy burden on the health and economy of endemic regions. Since 2011, China has reported at least 35,000 human brucellosis cases annually, with more than 90% of these cases reported in the northern. Given the alarmingly high incidence and variation in the geographical distribution of human brucellosis cases, there is an urgent need to decipher the causes of such variation in geographical distribution. METHOD: We conducted a retrospective epidemiological study in Shaanxi Province from January 1, 2005 to December 31, 2018 to investigate the association between meteorological factors and transmission of human brucellosis according to differences in geographical distribution and seasonal fluctuation in northwestern China for the first time. RESULTS: Human brucellosis cases were mainly distributed in the Shaanbei upland plateau before 2008 and then slowly extended towards the southern region with significant seasonal fluctuation. The results of quasi-Poisson generalized additive mixed model (GAMM) indicated that air temperature, sunshine duration, rainfall, relative humidity, and evaporation with maximum lag time within 7 months played crucial roles in the transmission of human brucellosis with seasonal fluctuation. Compared with the Shaanbei upland plateau, Guanzhong basin had more obvious fluctuations in the occurrence of human brucellosis due to changes in meteorological factors. Additionally, the established GAMM model showed high accuracy in predicting the occurrence of human brucellosis based on the meteorological factors. CONCLUSION: These findings may be used to predict the seasonal fluctuations of human brucellosis and to develop reliable and cost-effective prevention strategies in Shaanxi Province and other areas with similar environmental conditions.
Fecal coliform bacteria are a key indicator of human health risks; however, the spatiotemporal variability and key influencing factors of river fecal coliform have yet to be explored in a rural-suburban-urban watershed with multiple land uses. In this study, the fecal coliform concentrations in 21 river sections were monitored for 20 months, and 441 samples were analyzed. Multivariable regressions were used to evaluate the spatiotemporal dynamics of fecal coliform. The results showed that spatial differences were mainly dominated by urbanization level, and environmental factors could explain the temporal dynamics of fecal coliform in different urban patterns except in areas with high urbanization levels. Reducing suspended solids is a direct way to manage fecal coliform in the Beiyun River when the natural factors are difficulty to change, such as temperature and solar radiation. The export of fecal coliform from urban areas showed a quick and sensitive response to rainfall events and increased dozens of times in the short term. Landscape patterns, such as the fragmentation of impervious surfaces and the overall landscape, were identified as key factors influencing urban non-point source bacteria. The results obtained from this study will provide insight into the management of river fecal pollution.
Bacillary dysentery is a global public health problem that exhibits manifest spatiotemporal heterogeneity. However, long-term variations and regional determinant factors remain unclear. In this study, the Bayesian space-time hierarchy model was used to identify the long-term spatiotemporal heterogeneity of the incidence of bacillary dysentery and quantify the associations of meteorological factors with the incidence of bacillary dysentery in northern and southern China from 2013 to 2017. GeoDetector was used to quantify the determinant powers of socioeconomic factors in the two regions. The results showed that the incidence of bacillary dysentery peaked in summer (June to August), indicating temporal seasonality. Geographically, the hot spots (high-risk areas) were distributed in northwestern China (Xinjiang, Gansu, and Ningxia) and northern China (including Beijing, Tianjin, and Hebei), whereas the cold spots (low-risk areas) were concentrated in southeastern China (Jiangsu, Zhejiang, Fujian, and Guangdong). Moreover, significant regional differences were found among the meteorological and socioeconomic factors. Average temperature was the dominant meteorological factor in both northern and southern China. In northern and southern China, a 1 °C increase in the average temperature led to an increase of 1.01% and 4.26% in bacillary dysentery risk, respectively. The dominant socioeconomic factors in northern and southern China were per capita gross domestic product and the number of health technicians, with q statistic values of 0.81 and 0.49, respectively. These findings suggest that hot, moist, and overcrowded environments or poor health conditions increase the risk of bacillary dysentery. This study provides suggestions and serves as a basis for surveillance efforts. Further, the suggestions may aid in the control of bacillary dysentery and in the implementation of disease prevention policies.
OBJECTIVE: The study aimed to determine if and how environmental factors correlated with asthma admission rates in geographically different parts of Guangxi province in China. SETTING: Guangxi, China. PARTICIPANTS: This study was done among 7804 asthma patients. PRIMARY AND SECONDARY OUTCOME MEASURES: Spearman correlation coefficient was used to estimate correlation between environmental factors and asthma hospitalisation rates in multiple regions. Generalised additive model (GAM) with Poisson regression was used to estimate effects of environmental factors on asthma hospitalisation rates in 14 regions of Guangxi. RESULTS: The strongest effect of carbon monoxide (CO) was found on lag1 in Hechi, and every 10?µg/m(3) increase of CO caused an increase of 25.6% in asthma hospitalisation rate (RR 1.26, 95%?CI 1.02 to 1.55). According to the correlation analysis, asthma hospitalisations were related to the daily temperature, daily range of temperature, CO, nitrogen dioxide (NO(2)) and particulate matter (PM(2.5)) in multiple regions. According to the result of GAM, the adjusted R(2) was high in Beihai and Nanning, with values of 0.29 and 0.21, which means that environmental factors are powerful in explaining changes of asthma hospitalisation rates in Beihai and Nanning. CONCLUSION: Asthma hospitalisation rate was significantly and more strongly associated with CO than with NO(2), SO(2) or PM(2.5) in Guangxi. The risk factors of asthma exacerbations were not consistent in different regions, indicating that targeted measures should differ between regions.
INTRODUCTION: Resilient health systems have the capacity to continue providing health services to meet the community’s diverse health needs following floods. This capacity is related to how the community manages its own health needs and the community and health system’s joined capacities for resilience. Yet little is known about how community participation influences health systems resilience. The purpose of this study was to understand how community management of pregnancy and childbirth care during floods is contributing to the system’s capacity to absorb, adapt or transform as viewed through a framework on health systems resilience. METHODS: Eight focus group discussions and 17 semi-structured interviews were conducted with community members and leaders who experienced pregnancy or childbirth during recent flooding in rural Cambodia. The data were analysed by thematic analysis and discussed in relation to the resilience framework. RESULTS: The theme ‘Responsible for the status quo’ reflected the community’s responsibility to find ways to manage pregnancy and childbirth care, when neither the expectations of the health system nor the available benefits changed during floods. The theme was informed by notions on: i) developmental changes, the unpredictable nature of floods and limited support for managing care, ii) how information promoted by the public health system led to a limited decision-making space for pregnancy and childbirth care, iii) a desire for security during floods that outweighed mistrust in the public health system and iv) the limits to the coping strategies that the community prepared in case of flooding. CONCLUSIONS: The community mainly employed absorptive strategies to manage their care during floods, relieving the burden on the health system, yet restricted support and decision-making may risk their capacity. Further involvement in decision-making for care could help improve the health system’s resilience by creating room for the community to adapt and transform when experiencing floods.
INTRODUCTION: Human-induced climate change is increasing the likelihood and severity of wildfires across the globe. This has negative consequences for the health of affected communities through the loss of health systems’ infrastructure and disrupted health services. Community pharmacies are a central hub between patients and the health care system and can provide continuity of care during wildfires. However, there is little in peer-reviewed literature about the impacts of wildfires on community pharmacy operations. STUDY OBJECTIVE: The aim of this study was therefore to explore the impacts of the 2018/2019 summer bushfires in Tasmania, Australia on community pharmacy operations in affected areas. METHODS: Semi-structured telephone interviews were conducted with four community pharmacists who were working in the affected region during the bushfires. Interviews were audio recorded and transcribed verbatim. Qualitative data were analyzed using two methods- manual coding utilizing NVivo software and Leximancer analysis. Inter-rater reliability was ensured by two researchers analyzing the data independently. Differences in coding were discussed and agreement reached through negotiation amongst the research team. RESULTS: From the manual coding analysis, five key themes emerged – communication and collaboration; support; patient health challenges; pharmacist experiences in delivering health care; and future planning. These aligned with the five themes that emerged from the Leximancer analysis – community; local; town; patients; and work. Participants described working during the wildfires as difficult, with multiple challenges reported including communication difficulties, operational barriers such as power cuts, legislative barriers, logistical issues with obtaining and storing medication supplies, and lack of preparation, support, and funding. They highlighted a lack of operational and financial support from the government and received most assistance from local council bodies and local branches of professional pharmacy organizations. CONCLUSION: During disasters, community pharmacies help reduce the burden on public hospitals by maintaining medication supplies and treating patients with minor ailments. However, increased support and inclusion in disaster management planning is needed to continue this role.
Although several studies have reported that social isolation is one of the important health risk factors in the elderly population living in urban areas, its effects on vulnerability to heatwaves have been studied relatively less than climatic and other socio-economic factors. Thus, we investigated the association between social isolation levels and heatwave-related mortality risk in the elderly population in 119 urban administrative districts in Korea, using a time-series multi-city dataset (2008-2017). We used a two-stage analysis. In the first stage, we estimated the heatwave-related mortality risk in the elderly population (age ? 65) for each district using a time-series regression with a distributed lag model. Subsequently, in the second stage, we applied meta-regressions to pool the estimates across all the districts and estimate the association between social isolation variables and heatwave-related mortality risk. Our findings showed that higher social gathering and mutual aid levels were associated with lower heatwave-related mortality risk. Further, the lower percentage of single elderly households living in detached houses was also related to higher heatwave-related mortality risk. The associations were generally more evident in males compared to females. Our findings suggest that vulnerability to heatwave-related mortality among the urban, city-dwelling, elderly population may be amplified by higher isolation indicators.
We describe factors related to the social vulnerability of populations that experienced major river flooding in northern New South Wales (NSW), Australia. Using geographical information system methods, maps of 2017 flood-affected areas in the Lismore and Murwillumbah regions were combined with 2016 National census data to compare aspects of social vulnerability with the wider region and the region with Sydney. We also used individual-level data from the NSW 45 and Up Study to compare lifestyle, behavioural and health characteristics of residents of these flood-affected areas with the broader region (n = 13,561). Populations living in the Lismore Town Centre flood footprint exhibited significantly higher levels of social vulnerability over a range of factors; in particular, almost 82% resided in the most disadvantaged socio-economic quintile neighbourhoods. The flood-affected areas of Murwillumbah and Lismore regions included 47% and 60% of residents in the most disadvantaged quintile neighbourhoods compared to 27% for whole region and 16% for Sydney. This pattern of increased vulnerability was also apparent from the 45 and Up study; participants residing in the Lismore Town Centre flood footprint had significantly higher rates of riskier lifestyle-related behaviours (smoking, alcohol consumption), pre-existing mental health conditions (depression and anxiety) and poorer health. This detailed case study demonstrates extreme local vulnerability of flood-exposed populations, over and above the already highly vulnerable regional rural populations. This information is important to inform disaster planning and response and also reinforces the importance of having a detailed understanding of affected populations.
Based on the disaster census data of four types of meteorological disasters (floods induced by rainstorms, droughts, damages due to low temperatures and high temperatures and heat waves) in 637 counties (districts) of East China, the spatial distribution and inter-annual variation in the number of records and the amount of impacts or losses caused by the four types of disasters were analyzed. The results indicate that rainstorm-induced flood disasters had the largest number of records and the largest affected population, death population, affected crop, total crop failure and direct economic loss in East China. The yearly percentage of affected population and direct economic loss caused by the four types of meteorological disasters increased significantly at rates of 1.4 and 2.2% per decade, respectively, but the deaths decreased significantly at a rate of 2.2% per decade during 1984-2010. There was no statistical significance in the percentage change of affected crop area and total crop failure area in East China. Spatially, the total number of people affected by the four types of meteorological disasters was higher in Anhui and Jiangxi, and the deaths were more in southern Anhui, Jiangxi, Zhejiang, and Fujian. Both the affected area and the total failure area of crops were higher in northern Anhui, eastern Jiangsu and eastern Shandong, and the direct economic losses were higher in the southern part of East China and Anhui province.
The increasing frequency and intensity of heat events have weighty impacts on public health in Vietnam, but their effects vary across regions. In this study, we have applied a vulnerability assessment framework (VAF) to systematically assess the spatial pattern of health vulnerability to heatwaves in Vietnam. The VAF was computed as the function of three dimensions: exposure, sensitivity, and adaptive capacity, with the indicators for each dimension derived from the relevant literature, consultation with experts, and available data. An analytic hierarchy process (AHP) was used to determine the weight of indicators. Each province in Vietnam’s vulnerability to the health impacts of heatwaves was evaluated by applying the vulnerability index, computed using 13 indicators (sensitivity index, 9; adaptive capacity index, 3; and exposure index, 1). As a result of this analysis, this study has identified heatwave vulnerability ‘hotspots’, primarily in the Southeast, Central Highlands, and South Central Coast of Vietnam. However, these hotspots are not necessarily the same as the area most vulnerable to climate change, because some areas that are more sensitive to heatwaves may have a higher capacity to adapt to them due to a host of factors including their population characteristics (e.g. rates of the elderly or children), socio-economic and geographical conditions, and the availability of air-conditioners. This kind of information, provided by the vulnerability index framework, allows policymakers to determine how to more efficiently allocate resources and devise appropriate interventions to minimise the impact of heatwaves with strategies tailored to each region of Vietnam.
The lower Brahmaputra River in Bangladesh and Northeast India often floods during the monsoon season, with catastrophic consequences for people throughout the region. While most climate models predict an intensified monsoon and increase in flood risk with warming, robust baseline estimates of natural climate variability in the basin are limited by the short observational record. Here we use a new seven-century (1309-2004 C.E) tree-ring reconstruction of monsoon season Brahmaputra discharge to demonstrate that the early instrumental period (1956-1986 C.E.) ranks amongst the driest of the past seven centuries (13(th) percentile). Further, flood hazard inferred from the recurrence frequency of high discharge years is severely underestimated by 24-38% in the instrumental record compared to previous centuries and climate model projections. A focus on only recent observations will therefore be insufficient to accurately characterise flood hazard risk in the region, both in the context of natural variability and climate change.
BACKGROUND: Although the effects of seasonal variations and ambient temperature on the incidence of tuberculosis (TB) have been well documented, it is still unknown whether ambient temperature change is an independent risk factor for TB. The aim of this study was to assess the association between ambient temperature change and the risk of TB admissions. METHOD: A distributed lag non-linear model (DLNM) combined with Poisson generalized linear regression model was performed to assess the association between ambient temperature change and the risk of TB admissions from 2014 to 2018 in Hefei, China. Two temperature change metrics including temperature change between neighboring days (TCN) and diurnal temperature range (DTR) were used to assess the effects of temperature change exposure. Subgroup analyses were performed by gender, age and season. Besides, the attributable risk was calculated to evaluated the public health significance. RESULTS: The overall exposure-response curves suggested that there were statistically significant associations between two temperature change metrics and the risk of TB admissions. The maximum lag-specific relative risk (RR) of TB admissions was 1.088 (95%CI: 1.012-1.171, lag 4 day) for exposing to large temperature drop (TCN= -4 °C) in winter. Besides, the overall cumulative risk of TB admissions increased continuously and peaked at a lag of 7 days (RR=1.350, 95%CI: 1.120-1.628). Subgroup analysis suggested that exposure to large temperature drop had an adverse effect on TB admissions among males, females and adults. Similarly, large level of DTR exposure (DTR=15 °C) in spring also increased the risk of TB admissions on lag 0 day (RR=1.039, 95%CI: 1.016-1.063), and the cumulative RRs peaked at a lag of 1 days (RR=1.029, 95%CI: 1.012-1.047). We also found that females and elderly people were more vulnerable to the large level of DTR exposure. Additionally, the assessment of attributable risk suggested that taking target measures for the upcoming large temperature drop (b-AF = 4.17%, 95% eCI: 1.24%, 7.22%, b-AN = 1195) may achieve great public health benefits for TB prevention. CONCLUSION: This study suggests that ambient temperature change is associated with the risk of TB admissions. Besides, TCN may be a better predictor for the TB prevention and public health.
Extreme air temperature directly affected human health. However, the short-term effect of extreme air temperature on the incidence of cardiovascular diseases has rarely been reported in China. In this study, we focused on Beijing, China, and assessed the effects of cold/warm days and nights on the number of hospital emergency room (ER) visits for cardiovascular diseases from 2009 to 2012. We used a generalized additive model (GAM) to estimate the association between extreme air temperature and the number of hospital ER visits for cardiovascular diseases. We divided the entire study group into two gender subgroups and three age subgroups. The results showed that the short-term effect of extreme air temperature on hospital ER visits for cardiovascular diseases was more profound in females and the elderly (aged ??75 years). Among all the study subgroups, the highest relative risk (RR) of cardiovascular diseases associated with extremely cold days, warm days, cold nights, and warm nights was 3.0% (95% CI, 1.6%-4.4%), 0.8% (95% CI, -?0.9%-2.6%), 2.8% (95% CI, 1.6%-4.2%), and 1.8% (95% CI, 0.6%-4.3%), respectively. Overall, the effect of extremely low air temperature (during both days and nights) on the incidence of cardiovascular diseases was stronger and more acute than that of extremely high air temperature.
BACKGROUND: Evidence on the acute effect of short-term exposure to nitrogen dioxide (NO(2)) on years of life lost (YLL) is rare, especially in multicity setting. METHODS: We conducted a time series study among 48 major Chinese cities covering more than 403 million people from 2013 to 2017. The relative percentage changes of NO(2)-YLL were estimated by generalized additive models in each city, then were pooled to generate average effects using random-effect models. In addition, stratified analyses by individual demographic factors and temperature as well as meta-regression analyses incorporating city-specific air pollutant concentrations, meteorological conditions, and socioeconomic indicators were performed to explore potential effect modification. RESULTS: A 10 ?g/m(3) increase in two-day moving average (lag01) NO(2) concentration was associated with 0.64% (95% CI: 0.47%, 0.81%), 0.47% (95% CI: 0.27%, 0.68%), and 0.68% (95% CI: 0.34%, 1.02%) relative increments in YLL due to nonaccidental causes, cardiovascular diseases (CVD), and respiratory diseases (RD), respectively. These associations were generally robust to the adjustment of co-pollutants, except for NO(2)-CVD that might be confounded by fine particulate matter. The increased YLL induced by NO(2) were more pronounced in elderly people, hotter days, and cities characterized by less severe air pollution or higher temperature. CONCLUSIONS: Our results demonstrated robust evidence on the associations between NO(2) exposure and YLL due to nonaccidental causes, CVD, and RD, which provided novel evidence to better understand the disease burden related to NO(2) pollution and to facilitate allocation of health resources targeting high-risk subpopulation.
Diurnal temperature range (DTR) is a key indicator reflecting climate stability. Many previous studies have examined the effects of ambient temperature, both hot and cold, on human morbidity and mortality, but few studies have evaluated health effects of DTR, especially those in developing countries. This study aimed to investigate the association between short-term exposure to DTR and hospital admissions for cardiovascular and respiratory diseases in Bangkok, Thailand. We obtained daily meteorological variables from the Thai Meteorological Department from January 2006 through December 2014 and daily hospital admissions from the National Health Security Office during the same period. Quasi-Poisson generalized linear regression model combined with distributed lag non-linear model was used to examine the association between DTR and cardiovascular and respiratory hospital admissions controlling for daily average temperature, relative humidity, day of the week, public holiday, and seasonal and long-term trend. A J-shape relationship between DTR and hospital admissions was observed. With 7.8 °C DTR as a reference value, the relative risks for cardiovascular and respiratory hospital admission associated with extremely high DTR (11.6 °C) at cumulative lag 0-21 (21-day cumulative effects) were 1.206 (95% CI: 1.002-1.452) and 1.021 (95% CI: 0.856-1.218), respectively. The effects of extremely high DTR relative to a reference value did not significantly differ between males and females, as well as between young people (<65 years) and the elderly (?65 years) for both cardiovascular and respiratory admission. When stratifying the effects by season, the effect of extremely high DTR in winter was greater than that in summer and rainy season. This study showed that short-term exposure to extremely high DTR was significantly associated with increased risk of hospital admissions for cardiovascular disease in Bangkok, especially during winter. Results from this study could provide important scientific evidence for policy decision making to protect populations from adverse health effects of DTR.
Extreme temperature-related cardiovascular diseases (CVDs) have become a growing public health concern. However, the impact of temperature on the cause of specific CVDs has not been well studied in the study area. The objective of this study was to assess the impact of temperature on cause-specific cardiovascular hospital admissions in Beijing, China. We obtained data from 172 large general hospitals from the Beijing Public Health Information Center Cardiovascular Case Database and China. Meteorological Administration covering 16 districts in Beijing from 2013 to 2017. We used a time-stratified case crossover design with a distributed lag nonlinear model (DLNM) to derive the impact of temperature on CVD in hospitals back to 27 days on CVD admissions. The temperature data were stratified as cold (extreme and moderate ) and hot (moderate and extreme ). Within five years (January 2013-December 2017), a total of 460,938 (male 54.9% and female 45.1%) CVD admission cases were reported. The exposure-response relationship for hospitalization was described by a “J” shape for the total and cause-specific. An increase in the six-day moving average temperature from moderate hot (30.2 °C) to extreme hot (36.9 °C) resulted in a significant increase in CVD admissions of 16.1%(95% CI = 12.8%-28.9%). However, the effect of cold temperature exposure on CVD admissions over a lag time of 0-27 days was found to be non significant, with a relative risk of 0.45 (95% CI = 0.378-0.55) for extreme cold (-8.5 °C)and 0.53 (95% CI = 0.47-0.60) for moderate cold (-5.6 °C). The results of this study indicate that exposure to extremely high temperatures is highly associated with an increase in cause-specific CVD admissions. These finding may guide to create and raise awareness of the general population, government and private sectors regarding on the effects of current weather conditions on CVD.
BACKGROUND: Numerous studies have demonstrated the potential association between rainfall and hand, foot and mouth disease (HFMD), but the results are inconsistent. This study aimed to quantify the relationship between rainfall and HFMD based on a multicity study and explore the potential sources of spatial heterogeneity. METHODS: We retrieved the daily counts of childhood HFMD and the meteorological variables of the 143 cities in mainland China between 2009 and 2014. A common time series regression model was applied to quantify the association between rainfall and HFMD for each of the 143 cities. Then, we adopted the meta-regression model to pool the city-specific estimates and explore the sources of heterogeneity by incorporating city-specific characteristics. RESULTS: The overall pooled estimation suggested a nonlinear exposure-response relationship between rainfall and HFMD. Once rainfall exceeded 15?mm, the HFMD risk stopped increasing linearly and began to plateau with the excessive risk ratio (ERR) peaking at 21?mm of rainfall (ERR?=?3.46, 95% CI: 2.05, 4.88). We also found significant heterogeneity in the rainfall-HFMD relationships (I(2) =?52.75%, P
BACKGROUND: PM(2·5) is an important but modifiable environmental risk factor, not only for pulmonary diseases and cancers, but for cardiovascular health. However, the evidence regarding the association between air pollution and acute cardiac events, such as out-of-hospital cardiac arrest (OHCA), is inconsistent, especially at concentrations lower than the WHO daily guideline (25 ?g/m(3)). This study aimed to determine the associations between exposure to ambient air pollution and the incidence of OHCA. METHODS: In this nationwide case-crossover study, we linked prospectively collected population-based registry data for OHCA in Japan from Jan 1, 2014, to Dec 31, 2015, with daily PM(2·5), carbon monoxide (CO), nitrogen dioxide (NO(2)), photochemical oxidants (O(x)), and sulphur dioxide (SO(2)) exposure on the day of the arrest (lag 0) or 1-3 days before the arrest (lags 1-3), as well as the moving average across days 0-1 and days 0-3. Daily exposure was calculated by averaging the measurements from all PM(2·5) monitoring stations in the same prefecture. The effect of PM(2·5) on risk of all-cause or cardiac OHCA was estimated using a time-stratified case-crossover design coupled with conditional logistic regression analysis, adjusted for daily temperature and relative humidity. Single-pollutant models were also investigated for the individual gaseous pollutants (CO, NO(2), O(x), and SO(2)), as well as two-pollutant models for PM(2·5) with these gaseous pollutants. Subgroup analyses were done by sex and age. FINDINGS: Over the 2 years, 249?372 OHCAs were identified, with 149?838 (60·1%) presumed of cardiac origin. The median daily PM(2·5) was 11·98 ?g/m(3) (IQR 8·13-17·44). Each 10 ?g/m(3) increase in PM(2·5) was associated with increased risk of all-cause OHCA on the same day (odds ratio [OR] 1·016, 95% CI 1·009-1·023) and at lags of up to 3 days, ranging from OR 1·015 (1·008-1·022) at lag 1 to 1·033 (1·023-1·043) at lag 0-3. Results for cardiac OHCA were similar (ORs ranging from 1·016 [1·007-1·025] at lags 1 and 2 to 1·034 [1·021-1·047] at lag 0-3). Patients older than 65 years were more susceptible to PM(2·5) exposure than younger age groups but no sex differences were identified. CO, O(x), and SO(2) were also positively associated with OHCA while NO(2) was not. However, in two-pollutant models of PM(2·5) and gaseous pollutants, only PM(2·5) (positive association) and NO(2) (negative association) were independently associated with increased risk of OHCA. INTERPRETATION: Short-term exposure to PM(2·5) was associated with an increased risk of OHCA even at relatively low concentrations. Regulatory standards and targets need to incorporate the potential health gains from continual air quality improvement even in locations already meeting WHO standards. FUNDING: None.
Particulate matter from natural sources such as desert dust causes harmful effects for health. Asian dust (AD) increases the risk of acute myocardial infarction (AMI). However, little is known about the risk of myocardial infarction with nonobstructive coronary arteries (MINOCA), compared to myocardial infarction with coronary artery disease (MI-CAD). Using a time-stratified case-crossover design and conditional logistic regression models, the association between short-term exposure to AD whereby decreased visibility (
Hand, foot, and mouth disease (HFMD) is a common infectious disease in the Asia-Pacific region that primarily affects children younger than 5 years. Previous studies have confirmed that the seasonal transmission of this disease is strongly related to meteorological factors, but the results are not consistent. In addition, the associations between weather conditions and HFMD in northwestern China have not been investigated. Therefore, we aimed to examine this issue in Xi’an, the largest city of northwestern China that has been suffering from serious HFMD epidemics. In the current study, data for HFMD and six meteorological factors were collected from 2009 to 2018. Using cross-correlation analysis, the Granger causality test, and the distributed lag nonlinear model, we estimated the quantitative relationships and exposure-lag-response effects between weekly meteorological factors and HFMD incidence among children. We found that the seasonal distribution of HFMD in Xi’an has two peaks each year and is significantly impacted by the weekly temperature, precipitation, and evaporation over an 8-week period. Higher values of temperature and evaporation had positive associations with disease transmission, whereas the association between precipitation and HFMD showed an inverted-U shape. The maximum relative risks (RRs) of HFMD for the weekly mean temperature (approximately 31.1°C), weekly cumulative evaporation (57.9 mm), and weekly cumulative precipitation (30.0 mm) were 1.56 (95% CI: 1.35-1.81), 1.40 (95% CI: 1.05-1.88), and 1.16 (95% CI: 1.11-1.70), respectively. The identified risk determinants and lag effects could provide important information for early interventions to reduce the local disease burden.
BACKGROUND: Influenza is a disease under surveillance worldwide with different seasonal patterns in temperate and tropical regions. Previous studies have conducted modeling of influenza seasonality using climate variables. This study aimed to identify potential meteorological factors that are associated with influenza seasonality in Jinan, China. METHODS: Data from three influenza sentinel hospitals and respective climate factors (average temperature, relatively humidity (RH), absolute humidity (AH), sunshine duration, accumulated rainfall and speed of wind), from 2013 to 2016, were collected. Statistical and wavelet analyses were used to explore the epidemiological characteristics of influenza virus and its potential association with climate factors. RESULTS: The dynamic of influenza was characterized by annual cycle, with remarkable winter epidemic peaks from December to February. Spearman’s correlation and wavelet coherence analysis illuminated that temperature, AH and atmospheric pressure were main influencing factors. Multiple wavelet coherence analysis showed that temperature and atmospheric pressure might be the main influencing factors of influenza virus A(H3N2) and influenza virus B, whereas temperature and AH might best shape the seasonality of influenza virus A(H1N1)pdm09. During the epidemic season, the prevalence of influenza virus lagged behind the change of temperature by 1-8 weeks and atmospheric pressure by 0.5-3 weeks for different influenza viruses. CONCLUSION: Climate factors were significantly associated with influenza seasonality in Jinan during the influenza epidemic season and the optional time for influenza vaccination is before November. These finding should be considered in influenza planning of control and prevention.
More than 40% of the human population reside in global tropical zones despite the extreme climates that frequently approach the upper thermotolerance levels for human physical activity and societal flourishing. Many of these regions also regularly subject resident populations to extreme weather events. Australia’s tropical regions experience exceptionally high climatic variability, making it one of the world’s most challenging for human settlements. Adaptation planning, project management and health protection agencies working at local scales require localized analysis on long-term climatic trends and projections. Utility of existing large-scale analyses is constrained by climatic heterogeneity across expansive national scales. Here we track historical changes in seasonal climatic extremes for seven key population centres across Australia’s north between the periods 1911-1940 and 1988-2017 as measured against the 1961-1990 period. Shifts in daily minimum temperature (20 degrees C or more), maximum temperature (10th, 90th and 95th percentiles), trends in heatwaves (5 days or longer) and in 1- and 3-day heavy rainfall events (95th and 98th percentiles) are provided. Results indicate the greatest warming has occurred during the Dry season and in coastal locations. Rainfall extremes demonstrate a pattern of marked spatial non-uniformity. This location-centred approach to identifying shifts in climatic extremes has wide applicability for adaptation planning across diverse global climatic regions.
BACKGROUND: We purposed to evaluate the seasonality and associated factors of the incidence of gout attacks in Korea. METHODS: We prospectively enrolled patients with gout attacks who were treated at nine rheumatology clinics between January 2015 and July 2018 and followed them for 1-year. Demographic data, clinical and laboratory features, and meteorological data including seasonality were collected. RESULTS: Two hundred-five patients (men, 94.1%) were enrolled. The proportion of patients with initial gout attacks was 46.8% (n = 96). The median age, body mass index, attack duration, and serum uric acid level at enrollment were 50.0 years, 25.4, 5.0 days, and 7.4 mg/dL, respectively. Gout attacks were most common during spring (43.4%, P < 0.001) and in March (23.4%, P < 0.001). A similar pattern of seasonality was observed in the group with initial gout attacks. Alcohol was the most common provoking factor (39.0%), particularly during summer (50.0%). The median diurnal temperature change on the day of the attack was highest in the spring (9.8°C), followed by winter (9.3°C), fall (8.6°C), and summer (7.1°C) (P = 0.027). The median change in humidity between the 2 consecutive days (the day before and the day of the attack) was significantly different among the seasons (3.0%, spring; 0.3%, summer; -0.9%, fall; -1.2%, winter; P = 0.015). One hundred twenty-five (61%) patients completed 1-year follow-up (51% in the initial attack group). During the follow-up period, 64 gout flares developed (21 in the initial attack group). No significant seasonal variation in the follow-up flares was found. CONCLUSION: In this prospective study, the most common season and month of gout attacks in Korea are spring and March, respectively. Alcohol is the most common provoking factor, particularly during summer. Diurnal temperature changes on the day of the attack and humidity changes from the day before the attack to the day of the attack are associated with gout attack in our cohort.
PURPOSE: To delineate the seasonality of acute primary angle-closure (APAC) admission in a coastal city of southern China and its association with climatic factors. METHODS: A total of 1155 Chinese subjects with principal diagnosis of APAC attack were recruited from 2012 to 2016, and their medical records were retrieved. Monthly climatic factors were obtained from the Meteorological Bureau of Shantou. Monthly and seasonal APAC admissions were compared, and its correlation with climatic factors was evaluated. RESULTS: APAC admission was higher in female subjects (75.9%) with an overall mean age of 64.7 ± 9.3 years. APAC admission was highest in summer with the peak onset in June. The peak of APAC admission for female subjects aged ? 65 years was in June, and that for> 65 years was in July. The peak of APAC admission for male subjects aged > 65 years was in August. Precipitation was positively correlated with APAC admission rate for both aged ? 65 (? = 0.415, p = 0.001) and > 65 years old (? = 0.364, p = 0.004) female subjects. In contrast, surface temperature was positively correlated with APAC admission rate for male subjects aged > 65 years (? = 0.441, p < 0.001). No climatic factor was correlated with APAC admission rate for male subjects ? 65 years. CONCLUSIONS: This study revealed the peak season of APAC admission in summer, and surface temperature and precipitation are the associated factors. Close monitoring of climate changes could help to reduce the incidence of APAC attack.
Background: Benign paroxysmal positional vertigo (BPPV) is the most common cause of vertigo, especially in the elderly. Several studies have revealed a possible seasonality to BPPV. However, whether the seasonality of BPPV also exists in China is unclear. The characteristics of cardio-cerebrovascular risk factors for BPPV in the cold season have not yet been investigated. Objectives: (1) To investigate the seasonality of BPPV; (2) To explore the relationship between cardio-cerebrovascular risk factors and seasonality of BPPV. Methods: A retrospective observational study was performed in Beijing Tiantan Hospital from Jan 2016 to Dec 2018. The study included 1,409 new-onset BPPV patients aged 18-88 years. The demographic data, onset time, and medical history of BPPV were collected. The meteorological data, including temperature, atmospheric pressure, rainfall, and insolation, was obtained from Beijing Meteorological service. The x (2) goodness of fit test was used to evaluate whether BPPV patients’ numbers were significantly different among different months of the year. The Spearman correlation was used to detect the correlation between numbers of BPPV patients diagnosed monthly with each climatic parameter. The chi-square test for linear-by-linear association were used to investigate the relationship between cardio-cerebrovascular risk factor and seasonality of BPPV. Results: November to next March is the top 5 months with higher BPPV patient numbers (P < 0.001). The numbers of BPPV diagnosed monthly were conversely correlated with temperature and rainfall (r = -0.736, P = 0.010; r = -0.650, P = 0.022, respectively), positively correlated with atmospheric pressure (r = 0.708, P = 0.010), but no significant correlated with insolation. BPPV in the cold season (including January, February, March, November, and December) had a higher proportion, accounting for 54.2% of all BPPV patients. Among BPPV patients with ?2, 1, and none cardio-cerebrovascular risk factors, the cold season accounted for 57.0, 56.0, 49.8%, respectively. As the number of cardio-cerebrovascular risk factors increased, the proportion of patients in the cold season of BPPV increased (P = 0.025). Conclusions: BPPV patients are seen more in the months with low temperature, low rainfall, and high atmospheric pressure. Compared with the non-cold season, BPPV patients have more risk factors for cardio-cerebrovascular diseases in the cold season.
INTRODUCTION: Seasonal variations of allergic diseases have been of great interest in clinical practice, but large-scale epidemiological data in the real world is lacking. METHODS: We conducted a nationwide, population-based, cross-sectional study using the Korean National Health Insurance claims database to examine the seasonalities of allergic rhinitis (AR), asthma, allergic conjunctivitis (AC), and atopic dermatitis (AD). In addition, we investigated the correlations between the monthly patient numbers of each disease and climate factors such as daytime length, temperature, daily temperature range, humidity, solar radiation, rainfall, UVA dose, UVB dose, and PM10. RESULTS: The highest seasonal variation was identified in AC, followed by AR, asthma, and AD. AR was most prevalent in September and least prevalent in July and was positively correlated with a daily temperature range. Asthma had peaked in the winter and spring and was negatively correlated with both temperature and humidity. AC had dual peaks in May and September and the valley in winter. AD was prevalent between May and August with the lowest visits in winter and positively correlated with temperature. CONCLUSIONS: We demonstrated a clear seasonality of four allergic diseases. Korea is located in a temperate region with four distinct seasons, with 50 million people all having a single health insurance system. Therefore, our data reflects all hospital visits in Korea with the least chance for selection bias.
Respiratory syncytial virus (RSV) infects young children and causes influenza-like illness. RSV circulation and prevalence differ among countries and climates. To better understand whether climate factors influence the seasonality of RSV in Thailand, we examined RSV data from children???5 years-old who presented with respiratory symptoms from January 2012-December 2018. From a total of 8,209 nasopharyngeal samples, 13.2% (1,082/8,209) was RSV-positive, of which 37.5% (406/1,082) were RSV-A and 36.4% (394/1,082) were RSV-B. The annual unimodal RSV activity from July-November overlaps with the rainy season. Association between meteorological data including monthly average temperature, relative humidity, rainfall, and wind speed for central Thailand and the incidence of RSV over 7-years was analyzed using Spearman’s rank and partial correlation. Multivariate time-series analysis with an autoregressive integrated moving average (ARIMA) model showed that RSV activity correlated positively with rainfall (r?=?0.41) and relative humidity (r?=?0.25), but negatively with mean temperature (r?=?-?0.27). The best-fitting ARIMA (1,0,0)(2,1,0)(12) model suggests that peak RSV activity lags the hottest month of the year by 4 months. Our results enable possible prediction of RSV activity based on the climate and could help to anticipate the yearly upsurge of RSV in this region.
BACKGROUND: Protein and some minerals of rice seed are negatively affected by projected carbon dioxide (CO(2) ) levels. However, an in-depth assessment of rice quality that encompasses both CO(2) and temperature for a wide range of nutritional parameters is not available. Using a free-air CO(2) enrichment facility with temperature control, we conducted a field experiment with two levels of CO(2) (ambient; ambient?+?200?ppm) and two levels of temperature (ambient; ambient?+?1.5 °C). An in-depth examination of qualitative factors indicated a variable nutritional response. RESULTS: For total protein, albumin, glutelin, and prolamin, elevated CO(2) reduced seed concentrations irrespective of temperature. Similarly, several amino acids declined further as a function of higher temperature and elevated CO(2) relative to elevated CO(2) alone. Higher temperature increased the lipid percentage of seed; however, elevated CO(2) reduced the overall lipid content. At the nutrient elements level, whereas elevated CO(2) reduced certain elements, a combination of CO(2) and temperature could compensate for CO(2) reductions but was element dependent. CONCLUSION: Overall, these data are, at present, the most detailed analysis of rising CO(2) /temperature on the qualitative characteristics of rice. They indicate that climate change is likely to significantly impact the nutritional integrity of rice, with subsequent changes in human health on a global basis. © 2020 Society of Chemical Industry.
BACKGROUND: Research investigating the effect of air pollution on diabetes incidence is mostly conducted in Europe and the United States and often produces conflicting results. The link between meteorological factors and diabetes incidence remains to be explored. We aimed to explore associations between air pollution and diabetes incidence and to estimate the nonlinear and lag effects of meteorological factors on diabetes incidence. METHODS: Our study included 19,000 people aged ?60 years from the Binhai New District without diabetes at baseline. The generalized additive model (GAM) and the distributed lag nonlinear model (DLNM) were used to explore the effect of air pollutants and meteorological factors on the incidence of diabetes. In the model combining the GAM and DLNM, the impact of each factor (delayed by 30 days) was first observed separately to select statistically significant factors, which were then incorporated into the final multivariate model. The association between air pollution and the incidence of diabetes was assessed in subgroups based on age, sex, and body mass index (BMI). RESULTS: We found that cumulative RRs for diabetes incidence were 1.026 (1.011-1.040), 1.019 (1.012-1.026), and 1.051 (1.019-1.083) per 10??g/m(3) increase in PM(2.5), PM(10), and NO(2), respectively, as well as 1.156 (1.058-1.264) per 1?mg/m(3) increase in CO in a single-pollutant model. Increased temperature, excessive humidity or dryness, and shortened sunshine duration were positively correlated with the incidence of diabetes in single-factor models. After adjusting for temperature, humidity, and sunshine, the risk of diabetes increased by 9.2% (95% confidence interval (CI):2.1%-16.8%) per 10??g/m(3) increase in PM(2.5). We also found that women, the elderly (?75 years), and obese subjects were more susceptible to the effect of PM(2.5). CONCLUSION: Our data suggest that PM(2.5) is positively correlated with the incidence of diabetes in the elderly, and the relationship between various meteorological factors and diabetes in the elderly is nonlinear.
Global climate change has led to a significant increase in temperature over the last century and has been associated with significant increases in the severity and frequency of heat injury (HI). The consequences of HI included dehydration and rhabdomyolysis, leading to acute kidney injury, which is now recognized as a clear risk factor for chronic kidney disease (CKD). We aimed to investigate the effects of HI on the risk of CKD. This nationwide longitudinal population-based retrospective cohort study utilized the Taiwan National Health Insurance Research Database (NHIRD) data. We enrolled patients with HI who were followed in NHIRD system between 2000 and 2013.We excluded patients diagnosed with CKD or genital-urinary system-related disease before the date of the new HI diagnosis. The control cohort consisted of individuals without HI history. The patients and control cohort were selected by 1:4 matching according to the following baseline variables: sex, age, index year, and comorbidities. The outcome measure was CKD diagnosis. In total, 815 patients diagnosed with HI were identified. During the 13 year observation period, we identified 72 CKD events (8.83%) in the heat stroke group and 143 (4.38%) CKD events in the control group. Patients with heat stroke had an increased risk of CKD than the control patients (adjusted HR = 4.346, P < 0.001) during the follow-up period. The risk of end-stage renal disease was also significantly increased in the heat stroke group than in the control group (adjusted hazards ratio: 9.078, p < 0.001). HI-related CKD may represent one of the first epidemics due to global warming. When compared to those without HI, patients with HI have an increased CKD risk.
Saudi Arabia (SA) is one of the hottest countries in the world. This study was conducted to assess the impact of summer heat stress in Southeastern SA on short-term kidney injury (KI) among building construction workers and to identify relevant risk factors. Measurements of urinary albumin-creatinine ratio (ACR), height, weight, hydration, symptoms, daily work and behavioral factors were collected in June and September of 2016 from a cohort of construction workers (n = 65) in Al-Ahsa Province, SA. KI was defined as ACR ?30 mg/g. Multivariate linear regression analysis was used to assess factors related to cross-summer changes in ACR. A significant increase in ACR occurred among most workers over the study period; incidence of KI was 18%. Risk factors associated with an increased ACR included dehydration, short sleep, and obesity. The findings suggest that exposure to summer heat may lead to the development of KI among construction workers in this region. Adequate hydration and promotion of healthy habits among workers may help reduce the risk of KI. A reduction in work hours may be the most effective intervention because this action can reduce heat exposure and improve sleep quality.
BACKGROUND: More research is needed to understand the long-term effects of prenatal exposure to adverse events, such as floods and other natural disasters, on cognitive outcomes in childhood. We aimed to explore the risk of cognitive impairment in children following maternal exposure to the 1998 Yangtze River flood in China during pregnancy. METHODS: For this study we obtained and analysed individual-level data from the second China National Sample Survey on Disability (CNSSD), which was done in 2006. We defined the flood period as June-August, 1998. The analytical sample comprised children from four birth cohorts, defined according to their month of birth: the post-partum exposed cohort (children born between June, 1997, and May, 1998), the prenatal exposed cohort (children born between June, 1998, and May, 1999), the preconception exposed cohort (children born between June 1999, and May, 2000), and the unexposed cohort (children born between June, 2000, and May, 2001). In the CNSSD, cognitive impairment was assessed and diagnosed by validated screening tools and procedures. Difference-in-difference models were used to examine variations in the effects of maternal flood exposure on cognitive impairment in childhood across the different birth cohorts and regions. FINDINGS: 108?175 children born between June, 1997, and May, 2001, and aged 4-8 years at the time of the survey, were included in our analysis. 1131 children had a cognitive impairment; the prevalence of cognitive impairment was 1·05% (95% CI 0·99-1·11). Maternal exposure to flood during pregnancy increased the risk of cognitive impairment among children (adjusted odds ratio [OR] 2·18 [95% CI 1·54-3·08]; p<0·0001). No significant sex-specific differences were observed, and the risk of cognitive impairment was especially high when maternal flood exposure occurred during the first trimester of pregnancy (adjusted OR 5·05 [95% CI 3·88-6·58]; p<0·0001). The risk of cognitive impairment also increased with longer durations of maternal flood exposure and with increasing severity of flooding; the risk was highest in the prenatal exposed cohort with 3 months of flood exposure in the most severely affected area (adjusted OR 5·56 [95% CI 1·58-19·54]; p=0·007). INTERPRETATION: Prenatal flood exposure had a long-term negative effect on cognitive development of children. Greater maternal support and public health interventions during pregnancy and early life after a natural disaster are warranted to facilitate healthy cognitive development in later life. FUNDING: National Social Science Foundation of China.
AIMS: This study aimed to investigate the influence of climatic factors on the onset of Takotsubo syndrome (TTS). METHODS AND RESULTS: We performed a retrospective nationwide study among patients registered in the Japanese Registry of All Cardiac and Vascular Diseases and Diagnosis Procedure Combination (JROAD-DPC) discharge database, between 2012 and 2016. Before the analysis, a multicentre validation study was conducted for assessing the accuracy of the JROAD-DPC classification for TTS. First, we investigated the seasonal variation of incidences of TTS. Second, we analysed the associations between the incidence of TTS and climatic factors using the hierarchical Poisson regression modelling, and we also investigated the associations between typhoon landfalls and hospitalization for TTS, using the fixed-effects conditional Poisson regression model. The sensitivity and specificity for diagnosis were 83% and 100%, respectively. Then we analysed 5643 patients with TTS. The mean patient age was 74 (standard deviation ± 11) years; 79% were female. TTS was diagnosed significantly more frequently in the summer and early autumn. The incidence of TTS was related to higher temperatures; adjusted incidence rate ratios were 1.46 [95% confidence interval (CI): 1.33-1.60, P < 0.01] and 1.47 (95% CI: 1.34-1.62, P < 0.01) for temperatures of 20-25°C and >25°C, respectively. The incidence rate ratio for the first 2 days after a typhoon landfall was 1.85 (95% CI: 1.07-3.19; P = 0.03). CONCLUSIONS: This study demonstrates distinct patterns of seasonal variation in the incidence of TTS, as well as a significant association between its onset and climatic factors, including typhoon landfalls.
Ischemic heart disease (IHD) is one of the leading causes of mortality worldwide. Moreover, the effects of air pollution have been associated with several cardiovascular diseases (CVDs). The relationship between sandstorm weather and IHD is unknown. The Hexi Corridor is located in northwestern China and is a typical desert region comprising a large area of desert with a high incidence of sandstorms. This study aimed to explore the association between sandstorm weather and IHD-related mortality in this area. We acquired meteorological data of sandstorm weather from 2006 to 2015 from the Gansu Meteorological Bureau, and data regarding deaths due to IHD in five cities within the Hexi Corridor were collected from the death registration system of the Center for Disease Control of Gansu during the same period. Two other cities with few sandstorm events were selected as control regions. The time series method of the generalized additive model (GAM) was used to assess the association between sandstorm weather and IHD-related mortality in the Hexi Corridor. The results showed that the frequency of sandstorms in the Hexi Corridor was higher than that in the control regions (5.48% vs 1.64%, P
OBJECTIVE: The aim of this study was to screening PTSD among flood victims in Indonesia. METHOD: Quantitative non-experimental research method with a descriptive cross-sectional study. There were 356 flooding victims who participated in this study using purposive sampling techniques. The questionnaire used was PCL 5 DSM-V to determine the incidence of PTSD. RESULTS: The results of the study reported that 52% experiencing PTSD, and 48% did not experience PTSD. The majority of symptoms of PTSD were re-experiencing (98.3%). CONCLUSIONS: It can be concluded that the incidence of PTSD could arise at any age, gender, level of education and occupation by experiencing symptoms of re-experiencing, avoidance, negative alteration in mood cognition and hyperarousal. Hence, this study suggested improving intervention to decrease symptoms of PTSD.
OBJECTIVES: There has been increasing interest in identifying the adverse effects of ambient environmental factors on asthma exacerbations (AE), but season-stratified effects of meteorological factors on childhood asthma remain unclear. We explored the season-stratified effects of meteorological factors on childhood AE in Shanghai, China. METHODS: Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to examine the lagged and nonlinear effects of meteorological factors on childhood AE after adjustment for putative confounders. We also performed a season-stratified analysis to determine whether the season modified the relationship between meteorological factors and childhood AE. RESULTS: There were 23,103 emergency department visits (EDVs) for childhood AE, including 15,466 boys and 7637 girls during 2008-2017. Most meteorological factors (e.g., temperature, diurnal temperature range (DTR), relative humidity (RH) and wind speed (WS)) were significantly associated with EDVs for childhood AE, even after adjustment for the confounding effects of air pollutants. In the whole year, extreme cold, moderate heat, higher DTR, lower RH and WS increased the relative risk (RR) for childhood AE. In the cold season, lower RH and wind speed increased the risks of childhood AE (RR(lag0-28) for the 5th percentile (p5) of RH: 9.744, 95% CI: 3.567, 26.616; RR(lag0-28) for the p5 of wind speed: 10.671, 95% CI: 1.096, 103.879). In the warm season, higher temperature and DTR, lower RH and WS increased the RR for childhood AE (RR(lag0-5) for the p95 of temperature: 1.871, 95% CI: 1.246, 2.810; RR(lag0-2) for the p95 of DTR: 1.146, 95% CI: 1.010, 1.300; RR(lag0-5) for the p5 of RH: 1.931, 95% CI: 1.191, 3.128; RR(lag0-2) for the p5 of WS: 1.311, 95% CI: 1.005, 1.709). CONCLUSIONS: Extreme meteorological factors appeared to be triggers of EDVs for childhood AE in Shanghai and the effects modified by season. These findings provide evidence for developing season-specific and tailored strategies to prevent and control childhood AE.
On the basis of a newly developed observational dataset and a suite of climate model simulations, we evaluate changes in summer mean wet bulb globe temperature (WBGT) in China from 1961 through 2080. We show that summer mean WBGT has increased almost everywhere across China since 1961 as a result of human-induced climate change. Consequently, hot summers as measured by summer mean WBGT are becoming more frequent and more conducive to heat stress. Hot summers like the hottest on record during 1961-2015 in western or eastern China are now expected occur once every 3-4 years. These hot WBGT summers have become more than 140 times as likely in eastern China in the present decade (2010s) as in the 1961-90 baseline period and more than 1000 times as likely in western China. The substantially larger influence in western China is associated with its stronger warming signal, which is likely due to the high Bowen ratio of sensible to latent heat fluxes of dry soils and increases in absorbed solar radiation from the decline in mountain snow cover extent. Observation-constrained projections of future summer mean WBGT under the RCP8.5 emissions scenario indicate that, by the 2040s, almost every summer in China will be at least as hot as the hottest summer in the historical record, and by the 2060s it will be common (on average, every other year) for summers to be as much as 3.0 degrees C hotter than the historical record, pointing to potentially large increases in the likelihood of human heat stress and to a massive adaption challenge.
The first documented Rift Valley hemorrhagic fever outbreak in the Arabian Peninsula occurred in northwestern Yemen and southwestern Saudi Arabia from August 2000 to September 2001. This Rift Valley fever outbreak is unique because the virus was introduced into Arabia during or after the 1997-1998 East African outbreak and before August 2000, either by wind-blown infected mosquitos or by infected animals, both from East Africa. A wet period from August 2000 into 2001 resulted in a large number of amplification vector mosquitoes, these mosquitos fed on infected animals, and the outbreak occurred. More than 1,500 people were diagnosed with the disease, at least 215 died, and widespread losses of domestic animals were reported. Using a combination of satellite data products, including 2 x 2 m digital elevation images derived from commercial satellite data, we show rainfall and potential areas of inundation or water impoundment were favorable for the 2000 outbreak. However, favorable conditions for subsequent outbreaks were present in 2007 and 2013, and very favorable conditions were also present in 2016-2018. The lack of subsequent Rift Valley fever outbreaks in this area suggests that Rift Valley fever has not been established in mosquito species in Southwest Arabia, or that strict animal import inspection and quarantine procedures, medical and veterinary surveillance, and mosquito control efforts put in place in Saudi Arabia following the 2000 outbreak have been successful. Any area with Rift Valley fever amplification vector mosquitos present is a potential outbreak area unless strict animal import inspection and quarantine proceedures are in place.
OBJECTIVE: It is well known that air temperature is closely related to health outcomes. We investigated the relationship between air temperature parameters and the number of deaths stratified by cause in Gifu prefecture, Japan. METHODS: The number of deaths stratified by cause in Gifu prefecture Japan between January 2007 and December 2016 was obtained from the official homepage of Gifu prefecture, Japan. Air temperature parameters (?), i.e., the mean air temperature, mean of the highest air temperature, mean of the lowest air temperature, the highest air temperature, and the lowest air temperature during the same period in Gifu city were also obtained from the Japan Meteorological Agency official home page. The relationship between air temperature parameters and the number of deaths was evaluated in an ecological study. RESULTS: The number of deaths due to heart disease, cerebrovascular disease, pneumonia, accidents, or renal failure in January (coldest winter season in Japan) was the highest among the months. Simple correlation analysis also demonstrated a significant and negative relationship between air temperature parameters and the number of deaths due to heart disease, cerebrovascular disease, senility, pneumonia, accidents, and renal failure. CONCLUSION: Lower air temperature may be associated with a higher number of deaths due to diseases in Gifu prefecture, Japan.
Pollen is an important component of bioaerosol and the distribution of pollen and its relationship with meteorological parameters can be analyzed to better prevent hay fever. Pollen assemblages can also provide basic data for analyzing the relationship between bioaerosol and PM. We collected 82 samples of airborne pollen using a TSP large flow pollen collector from June 1, 2015 to June 1, 2016, from central Zhanjiang city in South China. We also conducted a survey of the nearby vegetation at the same time, in order to characterize the major plant types and their flowering times. We then used data on daily temperature, relative humidity, precipitation, vapor pressure and wind speed from a meteorological station in the center of Zhanjiang City to assess the relationship between the distribution of airborne pollen and meteorological parameters. Our main findings and conclusions are as follows: (1) We identified 15 major pollen types, including Pinus, Castanopsis, Myrica, Euphorbiaceae, Compositae, Gramineae, Microlepia and Polypodiaceae. From the vegetation survey, we found that the pollen from these taxa represented more than 75% of local pollen, while the pollen of Podocarpus, Dacrydium and other regional pollen types represented less than 25%. (2) The pollen concentrations varied significantly in different seasons. The pollen concentrations were at a maximum in spring, consisting mainly of tree pollen; the pollen concentrations were at an intermediate level in autumn and winter, consisting mainly of herb pollen and fern spores; and the pollen concentrations in summer were the lowest, consisting mainly of fern spores. (3) Analysis of the relationship between airborne pollen concentrations and meteorological parameters showed that variations in the pollen concentrations were mainly affected by temperature and relative humidity. In addition, there were substantial differences in these relationships in different seasons. In spring, pollen concentrations were mainly affected by temperature; in summer, they were mainly affected by the direction of the maximum wind speed; in autumn, they were mainly affected by relative humidity and temperature; and in winter, they were mainly affected by relative humidity and wind speed. Temperature and relative humidity promote plant growth and flowering. Notably, the variable wind direction in summer and the increased wind speed in winter and spring are conductive to pollen transmission. (4) Of the 15 major pollen types, Moraceae, Artemisia and Gramineae are the main allergenic pollen types, with peaks in concentration during April-May, August-September, and October-December, respectively. (5) Atypical weather conditions have substantial effects on pollen dispersal. In South China, the pollen concentrations in the sunny day were usually significantly higher than that of the rainy day. The pollen concentrations increased in short rainy days, which usually came from the Herb and Fern pollen. The pollen concentrations decreased in continuous rainy days especially for the Tree and Shrub pollen. the pollen concentrations in the sunny days were usually significantly higher than that in the rainy days. The pollen concentrations increased in short and strong rainfall.
BACKGROUND: Gastroesophageal reflux disease (GERD) is a highly prevalent disease of the upper gastrointestinal tract, and it is associated with environmental and lifestyle habits. Due to an increasing interest in the environment, several groups are studying the effects of meteorological factors and air pollutants (MFAPs) on disease development. AIM: To identify MFAPs effect on GERD-related medical utilization. METHODS: Data on GERD-related medical utilization from 2002 to 2017 were obtained from the National Health Insurance Service of Korea, while those on MFAPs were obtained from eight metropolitan areas and merged. In total, 20071900 instances of GERD-related medical utilizations were identified, and 200000 MFAPs were randomly selected from the eight metropolitan areas. Data were analyzed using a multivariable generalized additive Poisson regression model to control for time trends, seasonality, and day of the week. RESULTS: Five MFAPs were selected for the prediction model. GERD-related medical utilization increased with the levels of particulate matter with a diameter ? 2.5 ?m (PM(2.5)) and carbon monoxide (CO). S-shaped and inverted U-shaped changes were observed in average temperature and air pollutants, respectively. The time lag of each variable was significant around nine days after exposure. CONCLUSION: Using five MFAPs, the final model significantly predicted GERD-related medical utilization. In particular, PM(2.5) and CO were identified as risk or aggravating factors for GERD.
BACKGROUND: Numerous studies have been conducted to project temperature-related mortality under climate change scenarios. However, most of the previous evidence has been limited to the total or non-accidental mortality, resulting in insufficient knowledge on the influence of climate change on different types of disease. OBJECTIVES: We aimed to project future temperature impact on mortality from 16 causes under multiple climate change models in a coastal city of China. METHODS: We first estimated the baseline exposure-response relationships between daily average temperature and cause-specific mortality during 2009-2018. Then, we acquired downscaled future temperature projections from 28 general circulation models (GCMs) under two Representative Concentration Pathway (RCP4.5 and RCP8.5). Finally, we combined these exposure-response associations with projected temperature to estimate the change in the temperature-related death burden in different future decades in comparison to the 2010 s, assuming no demographic changes and population acclimatization. RESULTS: We found a consistently decreasing trend in cold-related mortality but a steep rise in heat-related mortality among 16 causes under climate change scenarios. Compared with the 2010 s, the net change in the fraction of total mortality attributable to temperature are projected to -0.54% (95% eCI: -1.69% to 0.71%) and -0.38% (95% eCI: -2.73% to 2.12%) at the end of the 21st century under RCP4.5 and RCP8.5, respectively. However, the magnitude of future cold and heat effects varied by different causes of death. A net reduction of future temperature-related death burden was observed among 10 out of 15 causes, with estimates ranging from -5.02% (95% eCI: -17.42% to 2.50%) in mental disorders to -1.01% (95% eCI: -5.56% to 3.28%) in chronic lower respiratory disease. Conversely, the rest diseases are projected to experience a potential net increase of temperature-related death burden, with estimates ranging from 0.44% (95% eCI: -4.40% to 6.02%) in ischemic heart disease and 4.80% (95% eCI: -0.04% to 9.84%) in external causes. CONCLUSIONS: Our study indicates that the mortality burden of climate change varied greatly by the mortality categories. Further investigations are warranted to comprehensively understand the impacts of climate change on different types of disease across various regions.
This time-series study collects data on stroke-related mortality, years of life lost (YLL), air pollution, and meteorological conditions in 96 Chinese cities from 2013 to 2016 and proposes a three-stage strategy to generate the national and regional estimations of avoidable YLL, gains in life expectancy and stroke-related population attributable fraction by postulating that the daily fine particulate matter (PM(2.5)) has been kept under certain standards. A total of 1 318 911 stroke deaths are analyzed. Each 10 µg m(-3) increment in PM(2.5) at lag(03) is associated with a city-mean increase of 0.31 (95% CI: 0.19, 0.44) years of life lost from stroke. A number of 914.11 (95% CI: 538.28, 1288.94) years of city-mean life lost from stoke could be avoided by attaining the WHO’s Air Quality Guidelines (AQG) (25 µg m(-3)). Moreover, by applying the AQG standard, 0.11 (0.08, 0.15) years of life lost might be prevented for each death, and about 0.91% (95% CI: 0.62%, 1.19%) of the total years of life lost from stroke might be explained by the daily excess PM(2.5) exposure. This study indicates that stroke patients can have a longer life expectancy if stricter PM(2.5) standards are put in place, especially ischemic stroke patients.
The Philippines is highly susceptible to both geophysical and climate-related disasters. This article explores Filipinos knowledge and perception of climate change and their association with what action Filipinos take to prepare for rapid onset natural hazards such as typhoons. Data for this study were collected from a nationally representative random survey of 5,184 adults conducted between March and April of 2017. Filipinos self-report relatively low levels of knowledge of climate change and cited increased temperatures, shifts in seasons, and heavier rains as the most likely consequences. Levels of disaster preparedness in the Philippines differ widely by region. Although most Filipinos perceive that natural hazards are a risk to them, only a third of Filipinos undertake measures to prepare for disasters. Filipinos who perceive climate-related changes directly impacting their households report taking greater action to prepare for disasters. Filipinos who believe they have been directly impacted by climate-related changes are also more likely to prepare for disasters, take planning actions, and undertake material actions to prepare, such as dwelling improvements. Other factors associated with disaster preparedness include gender, membership in an association, wealth, risk perception, and prior exposure to and losses due to disasters. The findings imply that, while posing different challenges and requiring different responses, adaptation to climate change and disaster preparedness are inherently associated and potentially mutually reinforcing. Policies and programs would arguably benefit from a more unified intervention framework that links climate change adaptation and disaster preparedness.
BACKGROUND: Hand, foot, and mouth disease (HFMD) is a widespread infectious disease in China. Associated meteorological factors have been widely studied, but their attributable risks have not been well quantified. OBJECTIVES: The study aimed to quantify the HFMD burden attributable to temperature and other meteorological factors. METHODS: The daily counts of HFMD and meteorological factors in all 574 counties of East China were obtained for the period from 2009 to 2015. The exposure-lag-response relationships between meteorological factors and HFMD were quantified by using a distributed lag non-linear model for each county and the estimates from all the counties were then pooled using a multivariate mete-regression model. Attributable risks were estimated for meteorological variables according to the exposure-lag-response relationships obtained before. RESULTS: The study included 4,058,702 HFMD cases. Non-optimal values of meteorological factors were attributable to approximately one third of all HFMD cases, and the attributable numbers of non-optimal ambient temperature, relative humidity, wind speed and sunshine hours were 815,942 (95% CI: 796,361-835,888), 291,759 (95% CI: 226,183-358,494), 92,060 (95% CI: 59,655-124,738) and 62,948 (95% CI: 20,621-105,773), respectively. The exposure-response relationship between temperature and HFMD was non-linear with an approximate “M” shape. High temperature had a greater influence on HFMD than low temperature did. There was a geographical heterogeneity related to water body, and more cases occurred in days with moderate high and low temperatures than in days with extreme temperature. The effects of meteorological factors on HFMD were generally consistent across subgroups. CONCLUSIONS: Non-optimal temperature is the leading risk factor of HFMD in East China, and moderate hot and moderate cold days had the highest risk. Developing subgroup-targeted and region-specific programs may minimize the adverse consequences of non-optimum weather on HFMD risk.
This study reveals the best combination of meteorological variables for the prediction of the number of emergency transport due to heat stroke over 64 years old in Tokyo metropolis based on a generalized linear model using 2008-2016 data. Temperature, relative humidity, wind speed, and solar radiation were used as candidates of the explanatory variables. The variable selection with Akaike’s information criterion (AIC) showed that all the four meteorological elements were selected for the prediction model. Additional analysis showed that the combination of daily mean temperature, maximum relative humidity, maximum wind speed, and total solar radiation as explanatory variables gives the best prediction, with approximately 19% less error than the conventional single-variable model which only uses the daily mean temperature. Finally, we quantitatively estimated the relative contribution of each variable to the prediction of the daily number of heat stroke patients using standardized partial regression coefficients. The result reveals that temperature is the largest contributor. Solar radiation is second, with approximately 20% of the temperature effect. Relative humidity and wind speed make relatively small contributions, each contributing approximately 10% and 9% of the temperature, respectively. This result provides helpful information to propose more sophisticated thermal indices to predict heat stroke risk.
Here, we develop a dry eye syndrome (DES) incidence rate prediction model using air pollutants (PM10, NO2, SO2, O-3, and CO), meteorological factors (temperature, humidity, and wind speed), population rate, and clinical data for South Korea. The prediction model is well fitted to the incidence rate (R-2= 0.9443 and 0.9388,p< 2.2 x 10(-16)). To analyze regional deviations, we classify outpatient data, air pollutant, and meteorological factors in 16 administrative districts (seven metropolitan areas and nine states). Our results confirm NO(2)and relative humidity are the factors impacting regional deviations in the prediction model.
BACKGROUND: Preterm birth is a major determinant of adverse health consequences, and early term births are also associated with increased risk of various outcomes. In light of climate change, the effect of ambient temperature on earlier delivery is an important factor to consider. Several studies have focused on associations of ambient air temperature (Ta) on preterm birth, but few have examined associations with early term births. AIMS: To investigate the association of prenatal exposure to Ta with preterm birth (<37 completed gestation weeks) and with early-term birth (<39 completed gestation weeks) in a semi-arid climate. METHODS: All singleton deliveries at the Soroka Medical Center from the Southern district of Israel, with estimated conception dates between May 1, 2004 and March 31, 2013 (N = 62,547) were linked to prenatal Ta estimates from a spatiotemporally resolved model, with daily 1 km resolution. We used time-dependent Cox regression models with weekly mean Ta throughout gestation, adjusted for calendar month and year of conception, ethnicity, census-level socio-economic status and population density. RESULTS: Ta was positively associated with late preterm birth (31 + 0/7 - 36 + 6/7 weeks), with increased risk in the upper Ta quintile as compared to the third quintile, hazard ratio (HR) = 1.31, 95% confidence interval (CI) = 1.11-1.56. Ta also associated with early term birth (37 + 0/6 - 38 + 6/7), with increased risk in the upper Ta quintile as compared to the third quintile, HR = 1.24, 95% CI = 1.13-1.36. CONCLUSION: Exposure to high ambient temperature during pregnancy is associated with a higher risk of preterm and early term birth in southern Israel.
Severe fever with thrombocytopenia syndrome (SFTS), a tick-borne infectious disease, is difficult to differentiate from other common febrile diseases. Clinically distinctive features and climate variates associated with tick growth can be useful predictors for SFTS. This retrospective study (2013-2019) demonstrated the role of climatic factors as predictors of SFTS and developed a clinical scoring system for SFTS using climate variables and clinical characteristics. The presence of the SFTS virus was confirmed using reverse transcription polymerase chain reaction (RT-PCR) tests. In the univariate analysis, the SFTS-positive group was significantly associated with higher mean ambient temperature and humidity compared with the SFTS-negative group (22.5 °C vs. 18.9 °C; 77.9% vs. 70.7%, all p < 0.001). In the multivariate analysis, poor oral intake (Odds ratio [OR] 5.87, 95% CI: 2.42-8.25), lymphadenopathy (OR 7.20, 95% CI: 6.24-11.76), mean ambient temperature ? 20 °C (OR 4.62, 95% CI: 1.46-10.28), absolute neutrophil count ? 2000 cells/?L (OR 8.95, 95% CI: 2.30-21.25), C-reactive protein level ? 1.2 mg/dL (OR 6.42, 95% CI: 4.02-24.21), and creatinine kinase level ? 200 IU/L (OR 5.94, 95% CI: 1.42-24.92) were significantly associated with the SFTS-positive group. This study presents the risk factors, including ambient temperature and clinical characteristics, that physicians should consider when suspecting SFTS.
Respiratory diseases cause significant morbidity and mortality, especially in developing countries. Recently, the influence of global warming on respiratory disease mortality has become a growing concern in research. Data on respiratory disease mortality, meteorological elements and air pollutants during 2014-2017 were collected from Yancheng in China. We applied the distributed lag non-linear model (DLNM) and performed a quasi-Poisson distribution fitting to evaluate the baseline relationship between the mean temperature and total respiratory diseases mortality, and then projected the future changes of total respiratory diseases mortality without adaptation and with adaptation in Yancheng during three future periods under two Representative Concentration Pathways (RCP) scenarios(RCP4.5 and RCP8.5) and three population scenarios including one constant and two Shared Socio-economic Pathways (SSP) scenarios (55P2 and 55P5). Under four combination scenarios, future warming causes additional heat-related mortality but reduced cold-related mortality in Yancheng from the 2030s to the 2070s. Under SSP population scenarios, the reduced numbers of cold-related deaths offsetting the additional numbers of heat-related deaths lead to the decreases in net temperature-related mortality in the 2050s and 2070s. Future population change has more influence on respiratory mortality than future climate change scenarios does. When the adaptation was adpoted, the heat-related mortality risks and the net temperature-related mortality risks become smaller, but the cold-related mortality risks become larger than that without adaptation.
When studying the thermal adaptation of building occupants, understanding the effects of different thermal experiences on adaptation is necessary, particularly for moderate and severe heat exposure. However, this area has seen limited research. Further, skin temperature, a common parameter for quantifying thermal sensation, may insufficiently reflect the automatic thermoregulation of the human body. This study investigates the effects of long-term heat exposure on the human body using multiple physiological and subjective indexes. Two heat exposure experiments were conducted on healthy male participants from northern and southern China. Participant responses, including skin temperature, heart rate, heart rate variability, blood volume pulse (BVP), subjective thermal comfort, thermal sensation, thermal acceptability, and normalized high and low frequency values were collected and compared. The results indicated that the subjective responses of northern and southern participants were not significantly different; however, the subjective physiological symptoms and self-reported discomfort of the latter were less than those of the former, indicating that the southern participants had superior heat tolerance. Additionally, the physiological responses of all the participants were largely similar. However, southern participants showed slightly higher normalized high frequency and BVP values, indicating that they have more active vagus nerves and better vasodilation. They also showed a wider acceptable temperature range and better acclimation to heat exposure. Notably, the mean skin temperature could not effectively predict thermal sensation during heat exposure; this was more accurately achieved using the rate of change of skin temperature. These findings suggest that long-term thermal experiences can affect building occupants’ thermal adaptability.
Heatwaves are likely to increase over different regions of the world as the climate warms, which poses potential risk to the environment, society, and public health. Concurrent daytime and nighttime heatwaves have a more significant impact on human health than individually occurring heatwaves, especially in regions with high population density. The Huai River Basin (HRB) is taken as a case in this study to explore the characteristics of concurrent daytime and nighttime heatwaves in a high-population-density area, including quantification of the population’s exposure to concurrent heatwaves. Nighttime hot events are found to increase to greater extent than daytime hot events from 1961 to 2017. A single daytime or nighttime hot event can provide 40-60 % capacity for the concurrent daytime and nighttime hot events. The concurrent daytime and nighttime heatwaves show an obvious southeast-northwest gradient with high values in the southeast and low values in the northwest of the HRB. Daytime hot events, nighttime hot events, and concurrent daytime and nighttime heatwave events all show significant upward trends from 1987 to 2017. The population exposed to the heat extremes increased significantly over this period, especially in regards to concurrent daytime and nighttime heatwaves. The population exposure in terms of the quantity, duration, and magnitude of concurrent daytime and nighttime heatwaves increased by around 5-, 9-, and 35-fold from 1984 to 2017. Atmospheric circulation analysis of the 2013 concurrent daytime and nighttime heatwaves in the HRB shows a long-lasting anomalous circulation background (e.g., anomalous high pressure system and low cloud water content) leading to severe concurrent daytime and nighttime heatwaves.
Research on population exposure to extreme heat is hindered by the limited spatial coverage of weather station and single exposure characteristic. In this study, a random forest regression model was developed to estimate monthly mean maximum temperature and extreme temperature. A cross-regional statistics in mean maximum temperature and extreme temperature was created to calculate a threshold which was used to reflect extreme temperature events. The threshold was used to develop the frequency, intensity and duration in extreme heat exposure for mean maximum temperature and extreme temperature, and quantified their spatiotemporal trends across residential areas in China in summer, 2001-2013. Results show that the risk of extreme heat was the highest in East China and was lower in Northeast and Northwest. The frequency of extreme heat exposure increased in most areas for mean maximum temperature, decreased in northern areas and increased in southern areas for extreme temperature. The intensity of extreme heat exposure increased in East, Central, South, and Southwest China for both mean maximum temperature and extreme temperature. The duration of extreme heat exposure increased nationwide for mean maximum temperature, and decreased in northern areas for extreme temperature. Frequency, intensity and duration of extreme heat exposure increased significantly, accompanied by high frequency, intense intensity and long-lasting in East, Central, Southwest, and South China. Overall, the results identify the high-risk hotspots over China in summer, 2000-2013.
BACKGROUND: Limited research has evaluated distinct aspects of disaster experience as predictors of affective symptoms. In this study, we examined the extent to which maternal depression and anxiety over time were predicted by (1) objective hardship from a flood during pregnancy, (2) peritraumatic distress and (3) cognitive appraisal of the flood’s consequences. METHODS: Data were drawn from the 2011 Queensland Flood Study, a prospective, longitudinal study of pregnancy (n = 183). Mothers’ disaster experience was measured within 1 year after the flood. Their levels of depression, anxiety and stress were measured at 16 months, 30 months, 4 years and 6 years after childbirth. Linear mixed models were employed to evaluate symptom trajectories. RESULTS: There were no time-dependent effects of disaster-related variables. Objective hardship did not predict outcomes. Peritraumatic distress significantly predicted depression and anxiety symptoms when cognitive appraisal was negative. Conversely, when cognitive appraisal was neutral or positive, the effect of peritraumatic distress was “buffered”. For anxiety, but not depression, this interaction survived Bonferroni correction. Neutral/positive cognitive appraisal similarly moderated the effect of peritraumatic dissociation. LIMITATIONS: The generalizability of our findings is limited by overall low levels of depression and anxiety, along with a predominantly Caucasian, higher socioeconomic status sample. Potential confounders such as pre-disaster anxiety were not controlled for. CONCLUSION: In line with previous evidence, this study supports the predictive validity of peritraumatic distress for post-disaster depression and anxiety. Our findings suggest that cognitive appraisal could be a relevant target for interventions aimed at fostering maternal resilience.
PURPOSE: The effects of meteorological parameters on stroke occurrence remain debated. The aim of the study was to assess the association between meteorological parameters and ischemic stroke onset in cold seasons in Tianjin. PATIENTS AND METHODS: Patients with acute ischemic stroke (946) were identified by standard sampling from one stroke unit in the Second Hospital of Tianjin Medical University, Tianjin, China, from 10/1/2014 to 4/30/2019. Generalized linear Poisson regression models were used to explore the effect of meteorological parameters (air temperature, barometric pressure, and relative humidity) on daily ischemic stroke onset after adjusting for air pollutants, day of week, and public holiday. RESULTS: The results showed that ischemic stroke onset was positively associated with the diurnal variation of temperature (? coefficient: 0.020, 95% CI [0.001, 0.038] p<0.05). Significant positive correlation between ischemic stroke onset and barometric pressure (mean, minimum) was found (? coefficient: 0.010, 95% CI [0.001,0.019] p<0.05; 0.010, 95% CI [0.001,0.019] p<0.05). The subgroup analysis considering age and gender difference showed that the older and the female were more vulnerable to weather conditions. CONCLUSION: Our study demonstrated that there was a measurable effect of weather parameters on daily ischemic stroke onset in colder seasons, suggesting that meteorological variables may, at least in part, play as risk factors for ischemic stroke onset, especially for the aging and female population.
Based on the micro-survey data of rural households in China’s Loess Plateau and Qinba Mountains, this paper empirically examines the poverty reduction effect and mechanism of adaptation to climate change. The research conclusions show that the adaptation actions can significantly reduce the poverty vulnerability of farmers, especially the future incidence of poverty in agricultural or poor households to a greater extent, which is characterized by a “pro-poor” effect. Adaptation actions can reduce poverty from two aspects: decreasing the expected income volatility (loss mitigation effect) and increasing the expected income level (opportunity effect), and the former is stronger than the latter. In the post-2020 period, China should enhance policy support in rural areas to adapt to climate change, improve the resilience of farmers’ livelihoods and climate change resilience of rural areas, and promote sustainable poverty reduction.
As climate change progresses, understanding the impact on human health associated with the temperature and air pollutants has been paramount. However, the predicted effect on temperature associated with particulate matter (PM(10)) is not well understood due to the difficulty in predicting the local and regional PM(10). We compared temperature-attributable mortality for the baseline (2003-2012), 2030s (2026-2035), 2050s (2046-2055), and 2080s (2076-2085) based on a distributed lag non-linear model by simultaneously considering assumed levels of PM(10) on historical and projected temperatures under representative concentration pathway (RCP) scenarios. The considered projected PM(10) concentrations of 35, 50, 65, 80, and 95 ?g/m(3) were based on historical concentration quantiles. Our findings confirmed greater temperature-attributable risks at PM(10) concentrations above 65 ?g/m(3) due to the modification effect of the pollutants on temperature. In addition, this association between temperature and PM(10) was higher under RCP8.5 than RCP4.5. We also confirmed regional heterogeneity in temperature-attributable deaths by considering PM(10) concentrations in South Korea with higher risks in heavily populated areas. These results demonstrated that the modification association of air pollutants on health burdens attributable to increasing temperatures should be considered by researchers and policy makers.
Particulate matter (PM), a major component of air pollution, is an important carrier medium of various chemical and microbial compounds. Air pollution due to PM could increase the level of bacteria and associated adverse health effects. Staphylococci as important opportunistic pathogens that cause hospital- and community-acquired infections may transmit through air. This study aimed to obtain knowledge about the concentration of airborne bacteria as well as staphylococci associated with particulate matter with a diameter of less than 2.5 micrometers (PM(2.5)) in ambient air. The impact of meteorological factors including ultraviolet (UV) index, wind speed, temperature, and moisture on microbial concentrations was also investigated. Quartz filters were used to collect PM(2.5) and associated bacteria in ambient air of a semiarid area. Airborne bacteria were quantified by culture method and Staphylococcus species identified by molecular methods. The mean (SD) concentration of PM(2.5) and airborne bacteria was 64.83 (24.87) µg/m(3) and 38 (36) colony forming unit (CFU)/m(3), respectively. The results showed no significant correlation between the levels of PM(2.5) and concentrations of bacteria (p?<?0.05). Staphylococcus species were detected in 8 of 37 (22%) samples in a concentration from 3 to 213 CFU/m(3). S. epidermidis was detected with the highest frequency followed by S. gallinarum and S. hominis, but S. aureus and methicillin-resistant Staphylococcus aureus (MRSA) were not detected. No significant correlation between the concentrations of bacteria with meteorological parameters was observed (p?<?0.05). Our finding showed that, although the study area is sometimes subject to air pollution from PM(2.5), the concentration of PM(2.5)- associated bacteria is relatively low. According to the results, PM(2.5) may not be a source of community-associated staphylococcal infections.
In 2015, Karachi saw its first ever epidemic of severe heatrelated illnesses that resulted in an extraordinary number of hospital admissions, especially in the intensive care, for fatal heat stroke within-hospital mortality of 3.7%.We conducted this study to elucidate the patient-related factors that lead to an increase in hospital admissions with heat-related illnesses in a tertiary care hospital. It was a descriptive case series conducted in the department of medicine at the Aga Khan University in June 2015. A total of 134 patients were admitted with heat-related illnesses of which 76(56.7%) were males. The mean age of the patients was 66 ±14.5 years. Heatstroke was present in 86 (64.2%) patients, followed by heat exhaustion in 48 (35.8%) and in-hospital mortality from heat-related illnesses was 5(3.7%). Hypertension (OR 2(95 % CI 1.0, 3.6) and insufficient sleep or food or water intake (OR 1.7(95 % CI 0.8, 3.8) was associated with severe heat-related illnesses. The effects remained even after adjusting for type and area of residence.
Infectious diseases are emerging and re-emerging due to climate change. Understanding how climate variability affects the transmission of infectious diseases is important for both researchers and the general public. Yet, the widespread knowledge of the general public on this matter is unknown, and quantitative research is still lacking. A survey was designed to assess the knowledge and perception of 1) infectious diseases, 2) climate change and 3) the effect of climate change on infectious diseases. Participants were recruited via convenience sampling, and an anonymous cross-sectional survey with informed consent was distributed to each participant. Descriptive and inferential analyses were performed primarily focusing on the occupational background as well as nationality of participants. A total of 458 individuals participated in this study, and most participants were originally from Myanmar, the Netherlands, Spain, United Kingdom and the United States. Almost half (44%) had a background in natural sciences and had a higher level of knowledge on infectious diseases compared to participants with non-science background (mean score of 12.5 and 11.2 out of 20, respectively). The knowledge of the effect of climate change on infectious diseases was also significantly different between participants with and without a background in natural sciences (13.1 and 11.8 out of 20, respectively). The level of knowledge on various topics was highly correlated with nationality but not associated with age. The general population demonstrated a high awareness and strong knowledge of climate change regardless of their background in natural sciences. This study exposes a knowledge gap in the general public regarding the effect of climate change on infectious diseases, and highlights that different levels of knowledge are observed in groups with differing occupations and nationalities. These results may help to develop awareness interventions for the general public.
Climate change, especially as reflected in heat waves, is a rising threat worldwide. Appropriate use of cooling devices can protect people from health impacts during a heat wave. A population-based telephone survey was conducted in a representative sample of residents in Hong Kong to investigate ownership and use of domestic cooling devices, identify correlates, and examine their associations with risk perception of potential health impact of climate change. More than 90% of the 1002 respondents owned and used cooling devices at home. The majority (57.7%) perceived the potential health risk of climate change at a high level. However, risk perception had no relationship with ownership and utilization of cooling devices. Old people (>= 65 years), the low-educated, those with low income, and those with chronic diseases were more likely not to use air conditioners when feeling hot. Our findings suggest that there are no signs showing people have taken more protective actions although half of respondents recognized climate change as a threat. Familial economic condition may be a major determinant in ownership and use of air conditioners at home. Old people and those with chronic diseases are at high risk of adverse exposure to climate change and therefore should be equipped with appropriate measures to use cooling devices.
Heat stress caused by high air temperature and high humidity is a serious health concern for urban residents. Mobile measurement of these two parameters can complement weather station observations because of its ability to capture data at fine spatial scales and in places where people live and work. In this paper, we describe a smart temperature and humidity sensor (Smart-T) for use on bicycles to characterize intracity variations in human thermal conditions. The sensor has several key characteristics of internet of things (IoT) technology, including lightweight, low cost, low power consumption, ability to communicate and geolocate the data (via the cyclist’s smartphone), and the potential to be deployed in large quantities. The sensor has a reproducibility of 0.03 degrees-0.05 degrees C for temperature and of 0.18%-0.33% for relative humidity (one standard deviation of variation among multiple units). The time constant with a complete radiation shelter and moving at a normal cycling speed is 9.7 and 18.5 s for temperature and humidity, respectively, corresponding to a spatial resolution of 40 and 70 m. Measurements were made with the sensor on street transects in Nanjing, China. Results show that increasing vegetation fraction causes reduction in both air temperature and absolute humidity and that increasing impervious surface fraction has the opposite effect.
In response to more frequent heatwaves, various regional or national heat-health warning systems (HHWSs) have been developed recently as adaptation measures. A wide range of methodologies have been utilized to issue warnings, as there is no universal definition of “heat event” or “heatwave”, nor are there quantified thresholds of human-health tolerance to extreme weather. The performance of these warning systems has rarely been evaluated with actual heat-health data, especially the morbidity data, in regions with severe impact. In this study, we assessed the performance of the Shanghai HHWS based on heat-related illness data collected by the Chinese Center for Disease Control and Prevention (China CDC) and then conducted a comparative analysis among the Shanghai HHWS, the China Meteorological Administration HHWS, the Chinese national standard for heatwave indexes, the heat index adopted by the USA’s National Weather Service and the definition suggested by the World Meteorological Organization to understand their potential performance for application in Shanghai and to evaluate the temperature thresholds and different meteorological indices employed. The results show that: 1) during the research period, 50% of heat-related illnesses and 58.2% of heat-related deaths in Shanghai occurred on dates that had no heat warnings; 2) for the current threshold (35 °C), the single metric of temperature outperformed the temperature-duration two-parameter method; 3) different from existing studies, while infants and seniors are deemed as vulnerable population groups to heat, young and middle-aged males were found to suffer more heat-related illnesses in hot weather. More detailed analyses reveal that the performance of heat-health warning systems needs to be evaluated and revised periodically, and warning thresholds utilized must be localized to reflect public tolerance to heat and to address the vulnerability of target population groups. Temperature is the dominant threshold in heat-related morbidity and mortality analysis. While a decrease in the temperature threshold would definitely increase the warning frequency and socioeconomic costs, it might also cause warning fatigue. The trade-off between these two aspects is essential for decision-makers and other stakeholders in HHWS design and improvement.
The duration and intensity of future heat waves are analyzed for 53 cities in the Middle East and the North Africa (MENA) region for the 21st century under two different scenarios (RCP4.5 and RCP8.5). A consistent approach is carried out using data from 13 Regional models within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX). By the end of the century, 80% of the most populated MENA cities are expected to be at least 50% of the days under heat wave conditions during the warm season. In addition, the mean and maximum intensity of the heat waves will also increase. Changes in the duration and intensity of heat waves have shown to be negatively correlated. Therefore, the vulnerability of the MENA cities to future heat waves was determined using a cumulative index (CI) that takes into account both duration and intensity. This CI indicates that Middle East and the eastern part of Africa will suffer the most unfavorable temperature conditions in the future. Assuming no intervention trough adaptation/mitigation strategies, these results, together with the particular properties of the MENA region, such as aridity or lack of precipitation, make it likely that the area will be affected by disease or famine.
This study aims to assess the physical and social vulnerability of floods, which occurred in the year 2015 in Adyar Basin of Chennai, Tamil Nadu. Thematic layers, such as rainfall, land use land cover (LULC), drainage density, slope, soil, and roads per watershed, were prepared and assigned the ranks using rank sum method. The knowledge based weighted indexed overlay analysis was employed based on causative factors, to prepare vulnerability map of the Adyar Basin. This research would help the community to find the vulnerability based on multi criteria analysis, by considering certain indicators like household, residential properties of the people living in Adyar basin. This engineering geological study, can play a vital role in comparing the physical and social vulnerability along with the real time vulnerability to ensure public safety, cost-effective solution for planning mitigation measures and preparedness in flood prone areas.
Organophosphate esters (OPEs) in atmospheric fine particles (PM(2.5)) were comprehensively investigated in the Beijing-Tianjin-Hebei (BTH) region from April 2016 to March 2017. The concentrations of ?(8)OPEs in all the five sampling sites ranged from 90 to 8291 pg/m(3) (mean 1148 ± 1239 pg/m(3); median 756 pg/m(3)). The highest level (median 1067 pg/m(3)) was found at one of the urban sites in Beijing, followed by Tianjin (746 pg/m(3)) and Shijiazhuang (724 pg/m(3)). Tris(2-chloroethyl) phosphate (TCEP) and tri[(2R)-1-chloro-2-propyl] phosphate (TCPP) were the dominant compounds across the five sampling locations. Generally, the concentrations of chlorinated OPEs were relatively higher in summer than in winter (p < 0.05), but no significant seasonal difference was discovered for non-chlorinated individual OPEs. The concentrations of tri-n-butyl phosphate (TBP), TCEP, TCPP and triphenyl phosphate (TPP) were positively correlated with the meteorological parameters (i.e. temperature and relative humidity) (p < 0.05), indicating an evident influence of meteorological condition on OPE distribution. We observed a negative correlation (p < 0.05) between octanol-air partition coefficients (logK(oa)) and the ratio of PM(2.5)-bound OPE concentrations to total suspended particulates-bound OPE concentrations, suggesting that physicochemical properties affect the particle-size distribution of OPEs. Furthermore, the median value of cancer hazard quotients (HQs) of TCEP was higher than TBP and tris(2-ethylhexyl) phosphate (TEHP). The health risk assessment showed that HQ values for children were ~1.6 times higher than those for adults. Relatively higher health risk induced by PM(2.5)-bound OPEs via inhalation was found during severe hazy days than in clear days.
Climate change is one of the most significant environmental issues facing communities, while poor construction and absence of effective air-conditioning (AC) predominantly cause indoor overheating. Although AC may help meeting indoor comfort, it increases the vulnerability of low-income residents, triggers large energy consumption, and generates anthropogenic heat, which worsens heat stress out-door. The capacity of buildings to maintain comfortable thermal conditions without mechanical cooling is the key factor protecting occupants against the rising temperature. Residents of Darwin, Australia, will be largely affected by increasing temperature where the annual peak ambient temperature may increase by 7.4 degrees C in 2060, while the number of hours above 30 degrees C will rise by 70%. Based on regional climate modelling for the Australian area and using a building energy simulation platform, we computed that by 2060 the indoor air temperature in a typical residential building may exceed 30 degrees C for over 4000 h under free-floating condition, with a peak daytime and night-time temperatures of 39 degrees C and 36.5 degrees C, respectively. The sensible thermal energy need for cooling per unit area under thermostatically controlled condition will increase from the current level of 110.7 kWh/m 2 to 196.8 kWh/m(2) in 2060. Different adaptation techniques when applied to the typical residential building yield to the peak indoor air temperature drop by 3.3-12 degrees C, and cooling energy needs reductions by 23.5-195.3 kWh/m(2) (12-99.7%) for low, medium, and high retrofit buildings compared to the typical residential building in 2060. Our study indicates that improved building quality is necessary to enhance survivability and energy efficiency in Darwin considering the role of building adaptation measures to counterbalance the impacts of global warming. (C) 2020 Elsevier B.V. All rights reserved.
Fine particulate matter (PM(2.5), aerodynamic diameter ?2.5?µm) impacts the climate, reduces visibility and severely influences human health. The Indo-Gangetic Plain (IGP), home to about one-seventh of the world’s total population and a hotspot of aerosol loading, observes strong enhancements in the PM(2.5) concentrations towards winter. We performed high-resolution (12?km × 12?km) atmospheric chemical transport modeling (WRF-Chem) for the post-monsoon to winter transition to unravel the underlying dynamics and influences of regional emissions over the region. Model, capturing the observed variations to an extent, reveals that the spatial distribution of PM(2.5) having patches of enhanced concentrations (?100 µgm(-3)) during post-monsoon, evolves dramatically into a widespread enhancement across the IGP region during winter. A sensitivity simulation, supported by satellite observations of fires, shows that biomass-burning emissions over the northwest IGP play a crucial role during post-monsoon. Whereas, in contrast, towards winter, a large-scale decline in the air temperature, significantly shallower atmospheric boundary layer, and weaker winds lead to stagnant conditions (ventilation coefficient lower by a factor of ~4) thereby confining the anthropogenic influences closer to the surface. Such changes in the controlling processes from post-monsoon to winter transition profoundly affect the composition of the fine aerosols over the IGP region. The study highlights the need to critically consider the distinct meteorological processes of west-to-east IGP and changes in dominant sources from post-monsoon to winter in the formulation of future pollution mitigation policies.
Extreme heat and associated health risks increasingly become threats to urban populations, especially in developing countries of the tropics. Although human thermal exposure in cities has been studied across the globe, current narratives insufficiently discuss mixed-used spaces, informal economic activity settings, and informal settlements. This study assessed outdoor human thermal comfort in the tropical city of Kolkata, India where uncomfortable hot and humid climatic conditions prevail year-round. Thermal Comfort Perception Surveys (TCPS) and biometeorological observations were conducted during summer and winter in three microentrepreneurial neighborhoods (Kumartuli, Boipara, and Mallickghat). A one-way ANOVA was performed to investigate the variance in Physiologically Equivalent Temperature (PET) values of 318 survey samples across neighborhoods. Through multiple linear regression and ANCOVA, significant relationships were established between various climatic and non-climatic parameters. No respondent reported a neutral thermal sensation during the summer. Annual neutral PET across neighborhoods was 23.6 °C with a neutral PET range of 19.5 °C to 27.6 °C. Annual neutral PET was 22.7 °C and 26.5 °C in Mallickghat and Boipara, respectively. Respondents in Boipara were more sensitive towards warmer sensation than in Mallickghat. Even in the winter, people reported warmer sensation votes. PET was a better predictor of the mean Thermal Sensation Vote (mTSV) compared to air temperature. In a few cases, acclimatization and expectations improved thermal comfort. Results can be useful in formulating strategies towards improving outdoor microclimate and heat health in tropical cities.
In this study, we applied the Weather Research and Forecasting model to project 2050 urban and rural temperature. We applied a time-stratified analysis to compare it with mortality between 2001 and 2014 and between 2011 and 2014, to estimate the elevated risk of a 2050 heat event. We included change in daytime versus nighttime and urban versus rural temperatures as factors to project mortality, to evaluate the potential influence of climate change on mortality risk. Increases of 2.9 degrees C and 2.6 degrees C in maximum and minimum air temperature are projected in a 2050 heat event, with a day and a night that will have respective temperatures 9.8 degrees C and 4.9 degrees C higher than 2001-2014. Significantly higher mortality risk is forecasted in 2050 compared to 2001-2014 (IRR 1.721 [1.650, 1.796]) and 2011-2014 (IRR 1.622 [1.547, 1.701]) without consideration of temperature change. After consideration of changing temperature, change in maximum temperature in rural areas will induce the highest mortality risk during 2050, possibly due to rapid urbanization across the city, and with the second highest mortality risk induced by the change in minimum temperature in urbanized areas, possibly because local people in the city have been adapted to the maximum level of urban thermal stress during a summer day. Improvements to heat warning systems and sustainable planning protocols are urgently needed for climate change mitigation.
Continuous climate change has increased the intensity and frequency of abnormal weather, temperature fluctuations, and natural disasters, along with their subsequent damages. The temperature rise is related to the increased number of days with heat waves and tropical nights, which generate problems in many different areas. The risks from heat waves appear in multiple forms, such as disease severity and energy shortages. To respond effectively to such complex risks, it is necessary to analyze where and what risks occur. Recently, Bayesian Network methodology has been applied in various fields, and the causality and probability of occurrence of complex events can be evaluated. Particularly, it is suitable for fields, such as climate change and disaster because of its consideration to uncertainty. Therefore, in this study, multi-risk networks were built, and a multi risk assessment using Bayesian Network was performed considering statistical probabilities. In addition, this study examined the change in future risks by reflecting the climate scenarios proposed by Intergovernmental Panel on Climate Change. The disease risks related to heat waves have increased with time, particularly in the areas adjacent to the coast, centering on the southeast side of South Korea. As for energy shortage, the risk increased in the region around Daegu, a city known for its high temperatures as well as in the Seoul metropolitan areas. Through this study, it is possible to improve the methodology for evaluating multi-risks, and the analyzed results will be able to provide support for effective responses to risks caused by heat waves in Korea.
Air pollution and heat are significant threats to public health, especially in urban areas with intensive human activities under the trend of climate change. However, the mediation effects of urban form on health via air pollution and heat have been overlooked in previous investigations. This study explored the potential impacts and pathways of urban form on cardiovascular mortality through air pollutants and heat by using partial least squares model with data from Taiwan. The measurable characteristics of urban form include city size, urban sprawl, and mixed land use. Other factors that influence cardiovascular mortality, such as urban industrial level, economic status, aging population, and medical resource, were also considered in the model. Results revealed that maximizing mixed land use and minimizing city size and urban sprawl can help reduce cardiovascular mortality, and the minimizing city size was the most important one. Urban industrial level, economic status, aging population, and medical resource were also influential factors. This is the first study to consider the pathways and impacts of urban form on cardiovascular mortality, and our results indicate that proper urban planning and policy could reduce cardiovascular mortality.
Reported dengue fever cases are increasing day by day in the world as well as in Sri Lanka. Model, Prediction and Control are three major parts of the process of analysis of the dengue incidence which leads to reduce the burden of the dengue. There is an increasing trend in the applications and developments in interval-valued data analysis over recent years. Particularly, under regressions there have being developed various techniques to handle interval-valued dependent and independent variables. Representation of data as intervals is very much useful to capture uncertainty and missing details associated with variables. Further, the predictions in intervals suit well when the situations of exact forecasts may not necessary. In this study interval-valued dengue data with interval-valued minimum temperature, maximum temperature and rainfall from 2009 to 2015 in the Colombo district, Sri Lanka were model using three interval valued regression procedures, namely, Center Method (CM), Center and Range Method (CRM) and Constrained Center and Range Method (CCRM). Predicted dengue cases in a range is particularly important because actions taking towards controlling the dengue do not depend on exact number but on magnitude of the values represent in the interval. Data in the year 2016 used for the validation of the models which is developed under three methods. Root of the mean square error, coefficient of determination as well as square root of variance of the models were used to select the best procedure to predict dengue cases. Among the three regression procedures both CRM and CCRM perform well in predicting monthly dengue cases in Colombo.
Although previous studies have reported that meteorological factors might affect the risk of Japanese encephalitis (JE), the relationship between meteorological factors and JE remains unclear. This study aimed to evaluate the relationship between meteorological factors and JE and identify the threshold temperature. Daily meteorological data and JE surveillance data in Dazhou, Sichuan, were collected for the study period from 2005 to 2012 (restricting to May-October because of the seasonal distribution of JE). A distributed lag nonlinear model was used to analyze the lagged and cumulative effect of daily average temperature and daily rainfall on JE transmission. A total of 622 JE cases were reported over the study period. We found JE was positively associated with daily average temperature and daily rainfall with a 25-day lag and 30-day lag, respectively. The threshold value of the daily average temperature is 20°C. Each 5°C increase over the threshold would lead to a 13% (95% CI: 1-17.3%) increase in JE. Using 0 mm as the reference, a daily rainfall of 100 mm would lead to a 132% (95% CI: 73-311%) increase in the risk of JE. Japanese encephalitis is climate-sensitive; meteorological factors should be taken into account for the future prevention and control measure making, especially in a warm and rainy weather condition.
To examine the effects of temperature on the daily cases of hand, foot, and mouth disease (HFMD).Data on the daily cases of HFMD in Lanzhou from 2008 to 2015 were obtained, and meteorological data from the same period were collected. A distributed lag nonlinear model was fitted to reveal the relationship between the daily mean temperature and the daily cases of HFMD.From 2008 to 2015, 25,644 cases were reported, of which children under 5 years of age accounted for 78.68% of cases. The highest peak of HFMD cases was usually reported between April to July each year. An inverse V-shaped relationship was observed between daily mean temperature and HFMD cases; a temperature of 18°C was associated with a maximum risk of HFMD. The relative risk (RR) was 1.57 (95% confidence interval: 1.23-1.23), and boys and children aged 3 to 5 years were populations with the highest risk. The cumulative risks of high temperature (20.2°C and 25.2°C) in the total, age-specific, and gender-specific groups peaked on lag 14 days; RR was higher in girls than in boys and in children aged 1 to 2 years than in other age groups. However, the effects of low temperature (-5.3°C, 2.0°C, and 12.8°C) were not significant for both gender-specific and age-specific patients.High temperature may increase the risk of HFMD, and boys and children aged 3 to 5 years were at higher risks on lag 0 day; however, the cumulative risks in girls and children aged 1 to 2 years increased with the increasing number of lag days.
It has been reported that suicide is associated with ambient temperature; however, the heterogeneity in this association and its underlying factors have not been extensively investigated. Therefore, we investigated the spatial and temporal variation in the temperature-suicide association and examined climatic, demographic, and socioeconomic factors that may underlie such heterogeneity. We analyzed the daily time-series data for the suicide counts and ambient temperature, which were collected for the 47 prefectures of Japan from 1972 to 2015, using a two-stage analysis. In the first stage, the prefecture-specific temperature-suicide association was estimated by using a generalized linear model. In the second stage, the prefecture-specific associations were pooled, and key factors explaining the spatial and temporal variation were identified by using mixed effects meta-regression. Results showed that there is an inverted J-shape nonlinear association between temperature and suicide; the suicide risk increased with temperature but leveled off above 24.4 °C. The nationwide relative risk (RR) for the maximum suicide temperature versus 5th temperature percentile (2.9 °C) was estimated as 1.26 (95% CI: 1.22, 1.29). The RRs were larger for females than for males (1.32 vs. 1.22) and larger for elderly people (?65 y) than for the non-elderly (15-64 y) (1.51 vs. 1.18). The RRs were larger for rural prefectures, which are characterized by smaller population, higher proportions of females and elderly people, and lower levels of financial capability and the proportion of highly educated people. The RRs were also larger in colder and less humid prefectures. These findings may help in understanding the potential mechanism of the temperature-suicide association and projecting the future risk of suicide under climate change.
Influenza usually breaks out seasonally in temperate regions, especially in winter, infection rates and mortality rates of influenza increase significantly, which means that dry air and cold temperatures accelerate the spread of influenza viruses. However, the meteorological factors that lead to seasonal influenza outbreaks and how these meteorological factors play a decisive role in influenza transmission remain unclear. During the epidemic of infectious diseases, the neglect of unreported cases leads to an underestimation of infection rates and basic reproduction number. In this paper, we propose a new non-autonomous periodic differential equation model with meteorological factors including unreported cases. First, the basic reproduction number is obtained and the global asymptotic stability of the disease-free periodic solution is proved. Furthermore, the existence of periodic solutions and the uniformly persistence of the model are demonstrated. Second, the best-fit parameter values in our model are identified by the MCMC algorithm on the basis of the influenza data in Gansu province, China. We also estimate that the basic reproduction number is 1.2288 (95% CI:(1.2287, 1.2289)). Then, to determine the key parameters of the model, uncertainty and sensitivity analysis are explored. Finally, our results show that influenza is more likely to spread in low temperature, low humidity and low precipitation environments. Temperature is a more important factor than relative humidity and precipitation during the influenza epidemic. In addition, our results also show that there are far more unreported cases than reported cases.
Ciguatera poisoning (CP), arising from ciguatoxins produced by toxic dinoflagellate Gambierdiscus, is one of the most common food-borne diseases in the South Pacific. Climate change as well as its related events have been hypothesized to a higher abundance and wider presence of toxic dinoflagellates, hence a higher risk of the disease. Yet existing studies assessing the relationship between climate factors and CP are limited or based on old data. In this study, we used prewhitened cross-correlation analysis and auto-regressive integrated moving-average (ARIMA) modeling to develop predictive models of monthly CP incidence in Cook Islands and French Polynesia, two ciguatera-endemic regions in the South Pacific, utilizing the latest epidemiological data. Results reveal the significant time-lagged associations between the monthly CP incidence rate and several indicators relating to sea surface temperature (SST). In particular, SST anomaly is proven to be a strong positive predictor of an increased ciguatera incidence for both countries. If these time-lags can be supported by more investigations, it will allow health authorities to take appropriate actions, to limit or avoid an epidemic risk, especially on high-risk climate scenarios.
This study statistically identified the association of remotely sensed environmental factors, such as Land Surface Temperature (LST), Night Time Light (NTL), rainfall, the Normalised Difference Vegetation Index (NDVI) and elevation with the incidence of leptospirosis in Thailand based on the nationwide 7,495 confirmed cases reported during 2013-2015. This work also established prediction models based on empirical findings. Panel regression models with random-effect and fixed-effect specifications were used to investigate the association between the remotely sensed environmental factors and the leptospirosis incidence. The Local Indicators of Spatial Association (LISA) statistics were also applied to detect the spatial patterns of leptospirosis and similar results were found (the R2 values of the random-effect and fixed-effect models were 0.3686 and 0.3684, respectively). The outcome thus indicates that remotely sensed environmental factors possess statistically significant contribution in predicting this disease. The highest association in 3 years was observed in LST (random- effect coefficient = -9.787, P<0.001; fixed-effect coefficient = -10.340, P=0.005) followed by rainfall (random-effect coefficient = 1.353, P<0.001; fixed-effect coefficient = 1.347, P<0.001) and NTL density (random-effect coefficient = -0.569, P=0.004; fixed-effect coefficient = -0.564, P=0.001). All results obtained from the bivariate LISA statistics indicated the localised associations between remotely sensed environmental factors and the incidence of leptospirosis. Particularly, LISA’s results showed that the border provinces in the northeast, the northern and the southern regions displayed clusters of high leptospirosis incidence. All obtained outcomes thus show that remotely sensed environmental factors can be applied to panel regression models for incidence prediction, and these indicators can also identify the spatial concentration of leptospirosis in Thailand.
Both ozone exposure and extreme temperatures are found to be significantly associated with mortality; however, inconsistent results have been obtained on the modification effects of temperature on the ozone-mortality association. In the present study, we conducted a nationwide time-series analysis in 128 counties from 2013-2018 to examine whether temperature modifies the association between short-term ozone exposure with nonaccidental and cause-specific mortality in China. First, we analyzed the effects of ozone exposure on mortality at different temperature levels. Then, we calculated the pooled effects through a meta-analysis across China. We found that high-temperature conditions (>75th percentile in each county) significantly enhanced the effects of ozone on nonaccidental, cardiovascular, and respiratory mortality, with increases of 0.44% (95% confidence interval (CI): 0.36 and 0.51%), 0.42% (95% CI: 0.32 and 0.51%) and 0.50% (95% CI: 0.31 and 0.68%), respectively, for a 10 ?g/m(3) increase in ozone at high temperatures. Stronger effects on nonaccidental and cardiovascular mortality were observed at high temperatures among elderly individuals aged 65 years and older compared with the younger people. Our findings provide evidence that health damage because of ozone may be influenced by the impacts of increasing temperatures, which point to the importance of mitigating ozone exposure in China under the context of climate change to further reduce the public health burden.
Ozone (O-3) pollution in China tends to become increasingly severe despite recent emission reductions. O(3 )is sensitive to atmospheric conditions, but its modulations by changing synoptic systems and climate are unclear, especially in mountain-basin areas such as the Sichuan Basin (SCB). This study examines the impacts of typical synoptic systems and their secular changes on O-3 pollution and its health risks in mountain-basin areas, by taking SCB as an example. Seven dominant synoptic patterns are identified and three typical synoptic patterns with high- (low-) pressure are associated with high (low) O-3 concentrations over entire SCB, while the pattern with uniform-pressure is accompanied by heavy (light) pollution in western (eastern) SCB. Under the synoptic patterns with high-pressure, clear weather with fewer clouds, strong solar radiation, weak convection, and hot and dry atmosphere enhances the photochemical reactions of O-3 precursors and weakens the vertical mixing of O-3 and its precursors, thus favoring heavy O-3 pollution and posing higher health risks; whereas, the synoptic patterns with low-pressure induce the opposite changes in O-3 concentration and health risks. The uniform-pressure pattern is accompanied by district spatial variations of O-3 via favoring O-3-related physical and chemical processes in eastern SCB and inhibiting that in the west. Under climatic changes, increasing synoptic pattern with high-pressure and decreasing synoptic pattern with low-pressure over SCB significantly increased O-3 concentration and the resultant health risks over the past 40 years. Our findings provide scientific evidence from synoptic and climatic views for forecasting O-3 and its health risks and for mitigating O-3 pollution in mountain-basin areas.
The flaviviruses are small single-stranded RNA viruses that are typically transmitted by mosquitoes or tick vectors and are etiological agents of acute zoonotic infections. The viruses are found around the world and account for significant cases of human diseases. We investigated population of culicine mosquitoes in central region of Korean Peninsula, Incheon Metropolitan City and Hwaseong-si. Aedes vexans nipponii was the most frequently collected mosquitoes (56.5%), followed by Ochlerotatus dorsalis (23.6%), Anopheles spp. (10.9%), and Culex pipiens complex (5.9%). In rural regions of Hwaseong, Aedes vexans nipponii was the highest population (62.9%), followed by Ochlerotatus dorsalis (23.9%) and Anopheles spp. (12.0%). In another rural region of Incheon (habitat of migratory birds), Culex pipiens complex was the highest population (31.4%), followed by Ochlerotatus dorsalis (30.5%), and Aedes vexans vexans (27.5%). Culex pipiens complex was the predominant species in the urban region (84.7%). Culicine mosquitoes were identified at the species level, pooled up to 30 mosquitoes each, and tested for flaviviral RNA using the SYBR Green-based RT-PCR and confirmed by cDNA sequencing. Three of the assayed 2,683 pools (989 pools without Anopheles spp.) were positive for Culex flaviviruses, an insect-specific virus, from Culex pipiens pallens collected at the habitats for migratory birds in Incheon. The maximum likelihood estimation (the estimated number) for Culex pipiens pallens positive for Culex flavivirus was 25. Although viruses responsible for mosquito-borne diseases were not identified, we encourage intensified monitoring and long-term surveillance of both vector and viruses in the interest of global public health.
Many studies have reported effects of global climate change on wildlife, including changes in species distributions and population sizes but perspectives on interactions between the biosphere and the anthroposphere are limited. Bears have a worldwide range and often come into conflict with humans. We assessed the effects of weather variables including temperature, precipitation, and sunshine on human-bear conflicts. Given that the relationship between climate and bear physiology is poorly understood, we first conducted an exploratory analysis using regression techniques. We then built a final predictive model using generalized linear mixed modelling and Akaike’s Information Criterion (AIC)-based model selection. Our model highlighted the influence of cold temperatures during denning on the frequency of human-bear conflicts. Cold temperatures during denning are related to increased energy requirements for thermoregulation. It is likely that the resulting increase in demand for food following denning leads to an increase in human-bear conflicts. Our results also indicate that cool springs, lingering winter snowpacks, and hot summers may increase human-bear conflicts due to associated reductions in key food sources.
INTRODUCTION AND OBJECTIVES: Typhoon Haiyan partially destroyed the Ormoc District Hospital in the Philippines. A field hospital was established to replace its outpatient department for 5 weeks. We investigated the reasons for medical consultation in the field hospital. METHODS: We described the consultations by sex, age, week, and diagnosis according to the Surveillance in Post-Extreme Emergencies and Disasters system. We compared the number and proportion of upper respiratory tract infections (URTIs) with a control season in 2014. RESULTS: We included 6785 consultations, 55.9% from women. The majority of consultations were communicable diseases (88.2%) followed by noncommunicable (7.1%) and injuries (5.6%). Males suffered more often from injuries than women (66.0% vs 34.0%). Consultations due to injuries decreased from 10.0% in the first to 2.9% in the last week. The most frequent diagnosis over the study period was acute respiratory infections (ARIs) (73.1%), of which 83.0% were children. The number of daily URTIs was higher than in a similar 2014 period. CONCLUSIONS: ARI was the most prevalent diagnosis. We recommend ARI treatments being fully accessible after such a disaster. During the first week, injury prevention should focus on adult men. Studies after natural disasters should include control periods to better understand disease distribution, ultimately improving the prioritization in disasters.
Although a number of studies have demonstrated seasonal variations in acute cardiovascular events, the association between winter and low temperatures and the incidence rate of acute aortic dissection has not been fully elucidated. In this study, we investigated the association between meteorological and chronobiological factors and the occurrence of acute aortic dissection classified by the Stanford type, sex and age. We retrospectively collected 131 patients who had been admitted consecutively to our institution with acute aortic dissection, including 58 type A patients and 73 type B patients, from January 2013 to December 2017. The meteorological data were downloaded from the homepage of the Japan Meteorological Agency. The daily incidence of aortic dissection was higher in winter (10.2%) than in fall (5.3%) (P?=?0.04), and a significant winter peak was also observed in the sub-groups of males and type B, while there were no significant differences in the proportions of type A, female, and ??70- and >?70-year-old patients. The maximum, mean and minimum temperatures on the days with aortic dissection were significantly lower than on the days without aortic dissection. Divided into four seasons, lower temperatures were found only in spring. The most significant and greatest difference was observed between the maximum temperature on the day of aortic dissection and that at 2 days earlier. The multivariate logistic regression analysis showed that the difference in the maximum temperature between the day of and 2 days before the incident (odds ratio 0.91; 95% confidence interval 0.87-0.96; P?
OBJECTIVE: The aim of this study was to investigate the status of Vitamin D deficiency and the effect of environmental factors on Vitamin D levels so as to provide theoretical support for public health promotion in this region. METHODS: A total of 22,387 subjects who underwent a physical examination at the center in the West China Hospital, Sichuan University, between April, 2018 and May, 2020 were enrolled in this study. Their data on gender, age, inspection date, serum 25 hydroxyvitamin D (25-(OH) D), parathyroid hormone (PTH), and total calcium were retrospectively reviewed. Next, the percentage of Vitamin D status was compared in different sex and age groups, and the fluctuation of Vitamin D level was described in relation to the change of environment. Finally, the univariable and multivariable linear regression analyses were performed to explore the risk and protective factors of Vitamin D deficiency. RESULTS: The proportion of Vitamin D deficiency in this area was 42.17%, and it was significantly higher among women and young people. The fluctuation trend of 25-(OH) D levels are consistent with temperature and solar radiation, and opposite to air quality, in the whole year. There was a positive relationship between 25-(OH) D levels with temperature and solar radiation; however, parathyroid hormone, female and AQI were negatively correlated with Vitamin D levels. CONCLUSION: Vitamin D deficiency is common in subtropic areas, such as Sichuan Basin, which is related to solar radiation and air pollution.
Meteorological drivers are known to affect transmissibility of respiratory viruses including respiratory syncytial virus (RSV), but there are few studies quantifying the role of these drivers. We used daily RSV hospitalization data to estimate the daily effective reproduction number (R(t)), a real-time measure of transmissibility, and examined its relationship with environmental drivers in Singapore from 2005 through 2015. We used multivariable regression models to quantify the proportion of the variance in R(t) explained by each meteorological driver. After constructing a basic model for RSV seasonality, we found that by adding meteorological variables into this model we were able to explain a further 15% of the variance in RSV transmissibility. Lower and higher value of mean temperature, diurnal temperature range (DTR), precipitation and relative humidity were associated with increased RSV transmissibility, while higher value of maximum wind speed was correlated with decreased RSV transmissibility. We found that a number of meteorological drivers were associated with RSV transmissibility. While indoor conditions may differ from ambient outdoor conditions, our findings are indicative of a role of ambient temperature, humidity and wind speed in affecting RSV transmission that could be biological or could reflect indirect effects via the consequences on time spent indoors.
INTRODUCTION: Respiratory syncytial virus (RSV) infection is a major cause of hospitalization in children. Meteorological factors are known to influence seasonal RSV epidemics, but the relationship between meteorological factors and RSV infection in children is not well understood. We aimed to explore the relationship between meteorological factors and RSV infections among hospitalized children, using different statistical models. METHODS: We conducted a retrospective review concerning children with RSV infections admitted to a tertiary pediatric hospital in Wenzhou, China, between January 2008 and December 2017. The relationship between meteorological factors (average daily temperatures, average daily relative humidity, rainfall, rainfall days, and wind speed) and the incidence of RSV in hospitalized children was analyzed using three time-series models, namely an autoregressive integrated moving average (ARIMA) model, a generalized additive model (GAM), and a least absolute shrinkage and selection operator (LASSO)-based model. RESULTS: In total, 15?858 (17.6%) children tested positive for RSV infection. The ARIMA model revealed a marked seasonal pattern in the RSV detection rate, which peaked in winter and spring. The model was a good predictor of RSV incidence (R(2) : 83.5%). The GAM revealed that a lower temperature and higher wind speed preceded increases in RSV detection. The LASSO-based model revealed that temperature and relative humidity were negatively correlated with RSV detection. CONCLUSIONS: Seasonality of RSV infection in hospitalized children correlated strongly with temperature. The LASSO-based model can be used to predict annual RSV epidemics using weather forecast data.
Numerous studies in epidemiology, meteorology, and climate change research have demonstrated a significant association between abnormal ambient temperature and mortality. However, there is a shortage of research attention to a systematic assessment of potential mitigation measures which could effectively reduce the heat-related morbidity and mortality risks. This study first illustrates a conceptualization of a systems analysis version of urban framework for climate service (UFCS). It then constructs a system dynamics (SD) model for the UFCS and employs this model to quantify the impacts of heat waves on public health system in Shanghai and to evaluate the performances of two mitigation measures in the context of a real heat wave event in July 2013 in the city. Simulation results show that in comparison with the baseline without mitigation measures, if the hospital system could prepare 20% of beds available for emergency response to heat waves once receiving the warning in advance, the number of daily deaths could be reduced by 40-60 (15.8-19.5%) on the 2 days of day 7 and day 8; if increasing the minimum living allowance of 790 RMB/month in 2013 by 20%, the number of daily deaths could be reduced by 50-70 (17.7-21.9%) on the 2 days of day 8 and day 12. This tool can help policy makers systematically evaluate adaptation and mitigation options based on performance assessment, thus strengthening urban resilience to changing climate.
Background This ecological study aims to model the trend of changes in exposure of outdoor workers to heat stress in outdoors in the coming decades with the use of the Wet-Bulb Globe Temperature (WBGT), Hadley Coupled Atmosphere- Ocean General Circulation Model, version 3 (HADCM3), and Long Ashton Research Station Weather Generator (LARS-WG) in Tehran, Iran, considering the climate change and the global warming. Methods The hourly values of environmental parameters including minimum and maximum air temperature, relative humidity, precipitation and radiation related to Prakash , Shahriar and Damavand cities were obtained from the Meteorological Organization of Iran. These data were recorded during 1965 to 2015. The climate modeling was done for 2011-2030, 2046-2065, and 2080-2099. Results The minimum and maximum air temperatures in the different months of the year in the three studied cities show an increasing trend. Our finding shows that the WBGT will be increased by 2099. In Pakdasht, this index will be close to the danger zone in the coming years, especially in 2080-2099. Conclusions All the results obtained indicate an increase in risk of heat stress in outdoor workplaces, given the global warming.
Little evidence is available about the relationship between ambient temperatures and hypoglycemia in Taiwan. The purpose of the present paper is to investigate whether there is an association between ambient temperatures and hypoglycemia in patients with type 2 diabetes.An ecological study was conducted to analyze the type 2 diabetes dataset of the Taiwan National Health Insurance Program. Every episode of hypoglycemia diagnosed at emergency department among subjects with type 2 diabetes was identified monthly between 2006 and 2013. Average monthly ambient temperatures in Celsius between 2006 and 2013 were measured according to the database of the Central Weather Bureau in Taiwan.The incidence rates of hypoglycemia were higher during the period of cold ambient temperatures (from December to March) than the period of warm ambient temperatures (from April to November). The peak period of hypoglycemia always occurred in winter months (January and February).Patients with type 2 diabetes in Taiwan are more susceptible to hypoglycemia during the period of cold ambient temperatures, particularly in winter months. Clinicians in Taiwan should remind patients to make a preventive strategy for hypoglycemia during the periods of cold ambient temperatures.
BACKGROUND: Accumulating evidence has linked environmental exposure, such as ambient air pollution and meteorological factors, to the development and severity of cardiovascular diseases (CVDs), resulting in increased healthcare demand. Effective prediction of demand for healthcare services, particularly those associated with peak events of CVDs, can be useful in optimizing the allocation of medical resources. However, few studies have attempted to adopt machine learning approaches with excellent predictive abilities to forecast the healthcare demand for CVDs. This study aims to develop and compare several machine learning models in predicting the peak demand days of CVDs admissions using the hospital admissions data, air quality data and meteorological data in Chengdu, China from 2015 to 2017. METHODS: Six machine learning algorithms, including logistic regression (LR), support vector machine (SVM), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM) were applied to build the predictive models with a unique feature set. The area under a receiver operating characteristic curve (AUC), logarithmic loss function, accuracy, sensitivity, specificity, precision, and F1 score were used to evaluate the predictive performances of the six models. RESULTS: The LightGBM model exhibited the highest AUC (0.940, 95% CI: 0.900-0.980), which was significantly higher than that of LR (0.842, 95% CI: 0.783-0.901), SVM (0.834, 95% CI: 0.774-0.894) and ANN (0.890, 95% CI: 0.836-0.944), but did not differ significantly from that of RF (0.926, 95% CI: 0.879-0.974) and XGBoost (0.930, 95% CI: 0.878-0.982). In addition, the LightGBM has the optimal logarithmic loss function (0.218), accuracy (91.3%), specificity (94.1%), precision (0.695), and F1 score (0.725). Feature importance identification indicated that the contribution rate of meteorological conditions and air pollutants for the prediction was 32 and 43%, respectively. CONCLUSION: This study suggests that ensemble learning models, especially the LightGBM model, can be used to effectively predict the peak events of CVDs admissions, and therefore could be a very useful decision-making tool for medical resource management.
This research examines flood risk and adaption to it, including the possibility of out-migration, in two flood-prone coastal locations in the Philippines through the lens of Protection Motivation Theory. Much of the country is at risk of coastal flooding due to sea-level rise and from severe weather-related events. The data analyzed were obtained in 2016 and 2018 from focus group discussions with local residents, individual interviews with local government officials, and field observations. Residents’ and officials’ reports reveal a number of consistent themes in both places and over time, with some important differences. Both locations were grappling with regular minor to moderate flooding in 2016, as well as with occasional severe flooding. Respondents reported serious economic, health, and safety threats associated with flooding events. Recent infrastructure improvements appear to have reduced routine flood risk in one location, but considerable risk from major storms remains in both places. While some housing has been abandoned because of flood damage, and while some better-off residents have moved away, most are not currently considering retreat as a near-term solution. Instead, most people are adapting in place and attempting to devise strategies to mitigate flood risk in their communities.
BACKGROUND AND OBJECTIVE: Malaria is an arthropod-borne infectious disease transmitted by the mosquito Anopheles and claims millions of lives globally every year. Reasons for failure to eradicate this disease are multifactorial. The seasonality of the malaria is principally determined by climatic factors conducive for breeding of the vector. We aimed to study the relationship between climatic variability and the seasonality of malaria over an eight-year duration. METHODS: This was a retrospective medical chart review of 8,844 confirmed cases of malaria which presented to The Indus Hospital, Karachi from January 2008 to November 2015. Cases were plotted against meteorological data for Karachi to elicit monthly variation. RESULTS: A secular incline and seasonality in malaria cases over the duration of eight years was seen. More cases were reported in the summer, rainy season compared with the other three seasons in each year. There was significant association with specific climate variables such as temperature, moisture, and humidity. CONCLUSION: There is a marked seasonal variation of malaria in Karachi, influenced by various environmental factors. Identification of the ‘the concentrated period’ of malaria can be helpful for policymakers to deploy malaria control interventions.
Heat-health risk is a growing concern in many regions of China due to the more frequent occurrence of extremely hot weather. Spatial indexes based on various heat assessment frameworks can be used for the assessment of heat risks. In this study, we adopted two approaches-Crichton’s risk triangle and heat vulnerability index (HVI) to identify heat-health risks in the Northern Jiangxi Province of China, by using remote sensing and socio-economic data. The Geographical Information System (GIS) overlay and principal component analysis (PCA) were separately used in two frameworks to integrate parameters. The results show that the most densely populated community in the suburbs, instead of city centers, are exposed to the highest heat risk. A comparison of two heat assessment mapping indicates that the distribution of HVI highlights the vulnerability differences between census tracts. In contrast, the heat risk index of Crichton’s risk triangle has a prominent representation for regions with high risks. The stepwise multiple linear regression zero-order correlation coefficient between HVI and outdoor workers is 0.715, highlighting the vulnerability of this particular group. Spearman’s rho nonparametric correlation and the mean test reveals that heat risk index is strongly correlated with HVI in most of the main urban regions in the study area, with a significantly lower value than the latter. The analysis of variance shows that the distribution of HVI exhibits greater variety across urban regions than that of heat risk index. Our research provides new insight into heat risk assessment for further study of heat health risk in developing countries.
Extreme heat is the leading cause of heat-related mortality around the world. Extracting heat vulnerability information from the urban complexity system is crucial for urban health studies. Using heat vulnerability index (HVI) is the most common approach for urban planners to locate the places with high vulnerability for intervention and protection. Previous studies have demonstrated that HVI can play a vital role in determining which areas are at risk of heat-related deaths. Both equal weight approach (EWA) and principal component analysis (PCA) are the conventional methods to aggregate indicators to HVI. However, seldom studies have compared the differences between these two approaches in estimating HVI. In this paper, we evaluated the HVIs in Hangzhou in 2013, employing EWA and PCA, and assessed the accuracies of these two HVIs by using heat-related deaths. Our results show that both HVI maps showed that areas with high vulnerability are located in the central area while those with low vulnerability are located in the suburban area. The comparison between HVI(EWA)and HVI(PCA)shows significantly different spatial distributions, which is caused by the various weight factors in EWA and PCA. The relationship between HVI(EWA)and heat-related deaths performs better than the relationship between HVI(PCA)and deaths, implying EWA could be a better method to evaluate heat vulnerability than PCA. The HVI(EWA)can provide a spatial distribution of heat vulnerability at intracity to direct heat adaptation and emergency capacity planning.
We aimed to investigate whether month of birth is associated with blood pressure (BP) and prevalent hypertension in adults from a region with frost-free days of <150 days and average temperatures - 13°C in winter, Xinjiang, China. We analyzed data for 6158 subjects from several surveys. We divided participants into April to August (n = 2624) and September to March (n = 3534) groups, based on length of maternal exposure to cold months, and analyzed BP, prevalent hypertension, and related factors. Diastolic BP in total subjects and systolic and diastolic BP in male subjects born between April and August were significantly higher than in those born between September and March. In sensitivity analysis, untreated males born between April and August showed significantly higher systolic and diastolic BP than did their counterparts. Subjects born between April and August showed significantly higher prevalence of hypertension (31.3% vs 27.8%, P = .003), and isolated systolic (23.3% vs 20.8%, P = .018) and diastolic hypertension (24.5% vs 21.4%, P = .004), than those born between September and March, which is similar for men. Birth between April and August showed 1.68 (95% CI: 1.06-2.67, P = .027)-fold increased odds for the prevalence of hypertension, independent of gender, age, body mass index, waist circumference, cigarette consumption, alcohol intake, and family history, compared with their counterparts. In conclusion, maternal exposure to cold spells during pregnancy may be associated with the increased risk of hypertension in offspring later in life, particularly among males, suggesting the involvement of maternal cold exposure during pregnancy in offspring hypertension development.
Environmental hazards increase the health morbidity and mortality burden. This study compared the knowledge and perceptions about the health effects of environmental hazards among medical and engineering students of Hamdard University Karachi. A total of 263 (44.1%) engineering students, and 333 (55.9%) medical students participated in the study. Cumulatively, the three most commonly identified environmental hazards included tobacco smoking 561 (94.1%), global climate change 518 (86.9%), and solar ultraviolet radiation 511 (85.7%). The study results suggest the need for better quantifying the magnitude of understanding environmental hazards, and for health education and promotion programmes at the graduate level for medical and engineering students in Karachi.
Climate Change and malnutrition are two global phenomena that affect millions of population groups. The Philippines is considered one of the most vulnerable countries for extreme natural events and at the same time has a high prevalence of underweight (19.0%) and stunting (28.8%) in 2019 among under five children. The nutritionally vulnerable groups are children, pregnant and lactating women, and elderly. These groups are also greatly affected by climate change-related events then the malnutrition situation is exacerbated. The local nutrition workers are the frontline workers who plan, implement, and monitor nutrition programs. Mainstreaming climate change in the local nutrition planning processes will be facilitated if nutrition workers are knowledgeable. This study aimed to determine the current knowledge, attitudes and practices of nutrition workers and perceptions on how to mainstream climate change in the nutrition sector’s local planning system. A survey was conducted among local nutrition workers. Ninety-five percent of nutrition workers were highly knowledgeable, 86% were with high level of attitudes and 50% were exhibiting moderate level of practices related to climate change. The gaps can be narrowed by capacity building and possibly this can lead to mainstreaming climate change in the local nutrition planning process.
The association between temperature and cardiovascular disease has been widely reported. In the city of Jiuquan, a developing area that has seldom been studied, the association is still unclear. The hospital data of cardiovascular disease (CVD) admissions and meteorological data were collected from the new rural cooperative medical insurance of Gansu Province and China Meteorological Science Data Sharing Service, respectively. A total of 26,383 cases were admitted during the research period. Poisson regression with a distributed lag nonlinear model was selected to evaluate the association between temperature and the hospital admissions of CVD. Subgroup analysis was performed according to gender and age. At first, the low temperature effect was obvious, but it then attenuated at lags 0-7 days. The maximum impact caused by high temperature occurred on the current day (lag 0) and then attenuated along the lag days. The cold effect was more harmful than heat effect. The adults and males were found to be more vulnerable to the temperature than the elderly and females, respectively. The study provides some reference for the development of the local public health by quantifying these impacts.
Leptospirosis is one of the most common and neglected tropical waterborne diseases in China, causing serious economic losses, and constituting a significant public health threat. Leptospirosis has recently received increased attention and is considered a re-emerging infectious disease in many countries. The incidence of leptospirosis among people suggests that occupation, age, season, sex and water recreational activities are significant risk factors. The aim of this study was to describe the epidemiological profiles of leptospirosis in China during the 2007-2018 period. The morbidity data of leptospirosis by age, season (month), gender, occupation and geographic location (different provinces) were obtained from the public health science data centre of China for subsequent epidemiological analysis. The results indicate that the incidence of leptospirosis has shown a slow downward trend from 2007 to 2018, but morbidity rates were still relatively high (0.0660-0.0113). The incidence of leptospirosis varied in different provinces of China; cases localized mainly to the Southern and Central provinces, areas with warm weather and ample rainfall. Older people (aged 60-75), males, farmers, students and field workers were high-risk populations. During the 2007-2018 observation period, morbidity rates increased beginning in May, remained at high levels in August and September and decreased after November. The present investigation highlights the re-emergence of leptospirosis in some provinces of China (especially in Yunnan and Fujian) and shows that leptospirosis remains a serious public health threat. The results of this study should enhance measures taken for the prevention, control, and surveillance of leptospirosis in China.
BACKGROUND: Although the effect of ambient temperature on cardiovascular disease (CVDs) has been well explored, studies using years of life lost (YLLs) as the outcome especially evaluating the average life loss per death attributable to temperatures were rare. We examine the associations between ambient temperature and YLLs of CVDs, and further quantify temperature-related life loss per death. METHODS: Daily YLL rates were calculated using death data from 364 locations across China during 2006-2017, and meteorological data were collected for the same period. A distributed-lag nonlinear model and meta-regression were applied to examine the relationships between temperature and YLL rates of CVDs. Subgroup analyses by age, gender, region, and cause-specific CVDs were investigated. The total YLLs and average YLLs per death attributable to temperature were further quantified to assess life loss caused by non-optimal temperature. RESULTS: Both high and low temperatures significantly increased YLL rates of CVDs, with greater effects for cold than heat. Cerebrovascular diseases (CEDs) account for the largest proportion (47.17%) of total YLLs of CVDs attributable to non-optimal temperature. On average, life loss per CVD death attributable to non-optimal temperatures was 1.51 (95% eCI: 1.33, 1.69) years, with 1.07 (95% eCI: 1.00, 1.15) years from moderate cold. Average life losses per death were observed higher for males (1.71, 95% eCI: 1.43, 1.99), younger population (3.82, 95% eCI: 2.86, 4.75), central China (1.62; 95% eCI: 1.41, 1.83) and hemorrhagic stroke (2.86, 95% eCI: 2.63, 3.10) than their correspondents. CONCLUSIONS: We found that non-optimal temperature significantly aggravated premature death of CVD, with CEDs being the most affected, and most of temperature-related life loss of CVD was attributed to moderate cold. Our findings imply that peoples with CEDs in moderate cold days are vulnerable populations, which may contribute to a better understanding the adverse effects and pathogenesis of temperature on CVDs.
BACKGROUND: Climate change and extreme weather poses significant threats to community health, which need to be addressed by local health workforce. This study investigated the perceptions of primary healthcare professionals in Southern China on individual and institutional strategies for actions on health impacts of climate change and the related barriers. METHODS: A mixed methodological approach was adopted, involving a cross-sectional questionnaire survey of 733 primary healthcare professionals (including medical doctors, nurses, public health practitioners, allied health workers and managers) selected through a multistage cluster randomized sampling strategy, and in-depth interviews of 25 key informants in Guangdong Province, China. The questionnaire survey investigated the perceptions of respondents on the health impacts of climate change and the individual and institutional actions that need to be taken in response to climate change. Multivariate logistic regression models were established to determine sociodemographic factors associated with the perceptions. The interviews tapped into coping strategies and perceived barriers in primary health care to adapt to tackle challenges of climate change. Contents analyses were performed to extract important themes. RESULTS AND CONCLUSION: The majority (64%) of respondents agreed that climate change is happening, but only 53.6% believed in its human causes. Heat waves and infectious diseases were highly recognized as health problems associated with climate change. There was a strong consensus on the need to strengthen individual and institutional capacities in response to health impacts of climate change. The respondents believed that it is important to educate the public, take active efforts to control infectious vectors, and pay increased attention to the health care of vulnerable populations. The lack of funding and limited local workforce capacity is a major barrier for taking actions. Climate change should be integrated into primary health care development through sustainable governmental funding and resource support.
The impacts of climate change and human activities are challenging water sustainability in many cities around the world. Advanced understanding of the future long-term coevolution of coupled urban human-water systems is of considerable interest in this context. This study uses a previously developed sociohydrologic model to explore the coevolutionary trajectories of Beijing City’s human-water system over the 2015-2099 period under possible climate changes. The effects of multiple human adaptive actions under alternative climate scenarios are investigated in particular. Results show that there might be a recurrent competition for water between humans and the natural environment (e.g., groundwater aquifer) in the long-term future, indicating that effective water management needs to ensure that this competition remains within a safe operating space. Three regimes of the human-environment competition are revealed, including a sustainable development regime in which human society and groundwater aquifer are both safe throughout their coevolutionary trajectories, a regime that may lead to severe population loss due to overaggressive population control actions, and a regime that may cause aquifer depletion due to under-perception of the drawdown of groundwater table. Results also show that relying too much on interbasin water diversion project might slacken human water conservation measures and eventually cause more severe aquifer depletion in the long run. Maintaining a high community sensitivity to drawdown of groundwater table and moderate measures to control population growth are keys to avoid unintended, negative consequences.
The risk levels of heat-related extreme events need to be estimated for prediction and real-time monitoring to mitigate their impacts on air quality, public health, the ecosystem, and critical infrastructure. Many countries have adopted meteorological variable base thresholds for assessing the risk level of heat-related extreme events. These thresholds provide an approximate risk level for a specific event but do not consider its intensity and duration in the risk assessment. The current study provides a statistical tool to assess the risk of heat-related extreme events while concurrently considering their intensities and durations based on the wet-bulb globe temperature (WBGT). To this end, the intensity-duration-frequency (IDF) relationship of the extreme WBGT in South Korea was derived. Regional frequency analysis was employed to understand the IDF relationship. Return levels of heat-related extreme events in South Korea were calculated and their characteristics were investigated based on the annual maximum WBGT observations. The results showed that the IDF relationship could provide the risks of heat-related extreme events while concurrently considering their intensities and durations. The extreme WBGT in South Korea was used to categorize two regions such as coastal and inland based on their statistical characteristics. The return levels of the annual maximum WBGT events were found to vary largely by location. The return levels corresponding to 32 °C with 3-h duration for stations in the coastal and inland regions ranged from 1- to 100-years and 3- to 1000-years, respectively. Mean values of return levels for heatwave events in Seoul, Incheon, Daejon, Gwangju, Daegu, and Busan were 2.8-, 8.4-, 15.3-, 2.8-, 1.6-, and 2.2-years, respectively. The return levels of heatwaves for the warmer cities are smaller than those for cooler cities. The return levels of the heatwave events in South Korea showed a significant increasing trend in several cities, supporting the notion that the impact of heatwave events on South Korea might become more severe in the future.
Several studies have reported that air pollution and climatic factors are major contributors to human morbidity and mortality globally. However, the combined interactive effects of air pollution and climatic factors on human health remain largely unexplored. This study aims to investigate the interactive effects of air pollution and climatic factors on circulatory and respiratory mortality in Xi’an, China. Time-series analysis and the distributed lag non-linear model (DLNM) were employed as the study design and core statistical method. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) for temperature and Air Quality Index (AQI) interaction on circulatory mortality were 0.973(0.969, 0.977) and -0.055(-0.059, -0.048), respectively; while for relative humidity and AQI interaction, 1.098(1.011, 1.072) and 0.088(0.081, 0.107) respectively, were estimated. Additionally, the IRR and RERI for temperature and AQI interaction on respiratory mortality were 0.805(0.722, 0.896) and -0.235(-0.269, -0.163) respectively, while 1.008(0.965, 1.051) and -0.031(-0.088, 0.025) respectively were estimated for relative humidity and AQI interaction. The interaction effects of climatic factors and AQI were synergistic and antagonistic in relation to circulatory and respiratory mortality, respectively. Interaction between climatic factors and air pollution contributes significantly to circulatory and respiratory mortality.
BACKGROUND: Haemorrhagic fever with renal syndrome (HFRS) is climate sensitive. HFRS-weather associations have been investigated by previous studies, but few of them looked into the interaction of meteorological factors on HFRS in different climate zones. OBJECTIVE: We aim to explore the interactions and marginal effects of meteorological factors on HFRS in China. METHODS: HFRS surveillance data and meteorological data were collected from 254 cities during 2006-2016. A monthly time-series study design and generalized estimating equation models were adopted to estimate the interactions and marginal effects of meteorological factors on HFRS in different climate zones of China. RESULTS: Monthly meteorological variables and the number of HFRS cases showed seasonal fluctuations and the patterns varied by climate zone. We found that maximum lagged effects of temperature on HFRS were 1-month in temperate zone, 2-month in warm temperate zone, 3-month in subtropical zone, respectively. There is an interaction effect between mean temperature and precipitation in temperate zone, while in warm temperate zone the interaction effect was found between mean temperature and relative humidity. CONCLUSION: The interaction effects and marginal effects of meteorological factors on HFRS varied from region to region in China. Findings of this study may be helpful for better understanding the roles of meteorological variables in the transmission of HFRS in different climate zones, and provide implications for the development of weather-based HFRS early warning systems.
BACKGROUND: Daily air quality index (AQI) forecast can provide early warning information, and it is not clear whether it is appropriate for childhood asthma hospitalizations (CAHs). Furthermore, little is known about the effects of AQI on CAHs, as well as the interactions between temperature, humidity and AQI. METHODS: We collected 32,238 cases in Hefei from 2013 to 2016 and estimated the association between daily CAHs and AQI by combining the Poisson Generalized Linear Models (PGLMs) with the Distributed Lag Nonlinear Models (DLNMs). The interaction between AQI and temperature was tested by stratifying AQI and temperature, as well as humidity. RESULTS: AQI was associated with an increased risk of hospitalizations for childhood asthma. The adverse effect first appeared on the 3rd day, with the RR of 1.011 (95%CI: 1.000-1.023) and continued until the 19th day of lag (RR = 1.010, 95%CI: 1.001-1.020). In the subgroup analysis, the male and pre-school children were more sensitive to AQI, and there are seasonal differences in the effects of AQI on CAHs. Besides, in a stratified analysis with an AQI of 150, we found synergies between temperature, humidity and AQI. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) for the interaction between temperature and AQI were 1.157 (95%CI: 1.029-1.306) and 0.122 (95%CI: 0.022-0.223) respectively. For the humidity, the IRR and RERI were 1.090 (95%CI: 1.056-1.206) and 0.083 (95%CI: 0.083-0.143) respectively. Exploring different subgroups in the interaction analyses, it was worth noting that female and pre-school children were more sensitive to the interaction between AQI and temperature, while school-age children were more sensitive to the interaction between AQI and humidity. CONCLUSIONS: The study found that not only AQI can significantly increase the risk of CAHs, but also that under the context of climate change, temperature and humidity have a synergistic effect on AQI, suggesting that considering only the warning information of air pollution is not enough to strengthen the prevention of childhood asthma hospitalization.
The weather is arguably one of the most common topics in daily conversation. However, it is also a well-known factor in psychiatric problems worldwide such as depression, where particularly elders and females are prone to the condition. Previous studies have mostly focused on the association between long-term climate/season change and depressive symptoms to test the belief that people feel depressed when the weather is bad. Yet, little is known about the relationship between intraday weather conditions and depressive symptoms. This study aimed to decompose this association and explore age and gender differences in depressive symptoms’ report under different intraday weather conditions. We analyzed data with a total sample size of 20,987 individuals aged 15-96 years obtained via the China Labor-force Dynamic Survey (CLDS) project in 2016. The surveyors filled in the intraday weather conditions (i.e., sunny, cloudy, overcast, light rain, moderate rain, and heavy rain) in the questionnaire with depression being self-reported using the Center for Epidemiologic Studies Depression (CES-D) Scale. In the survey, 17.3% [95% confidence interval (CI) = 16.8%, 17.8%] individuals were assessed to have depressive symptoms (CES-D scores >15). Overcast day was the peak weather condition for depressive symptoms, while gender and age differences of depressive symptoms were biggest in the weather condition of moderate rain. Multivariate logistic regression revealed that female and middle-old age individuals were more likely to report having depressive symptoms, and people under overcast day were more likely to report having depressive symptoms compared to under sunny day [odds ratio (OR) = 1.25, 95%CI = 1.11, 1.39]. This intraday weather conditions-depression link was significant in males and middle-old age individuals but not in females and youngsters.
Urbanization is one of the most significant contributing factors to anthropogenic climate change. However, a lack of projected city land use data has posed significant challenges to factoring urbanization into climate change modeling. Thus, the results from current models may contain considerable errors in estimating future climate scenarios. The Pearl River Delta region was selected as a case study to provide insight into how large-scale urbanization and different climate change scenarios impact the local climate. This study adopts projected land use data from freely available satellite imagery and applies dynamic simulation land use results to the Weather Research and Forecasting Model (WRF). The simulation periods cover the summer periods in 2010 and 2029-2031, the latter of which is averaged to represent the year 2030. The WRF simulation used the observed local climate conditions in 2010 to represent the current scenario and the projected local climate changes for 2030 as the future scenario. Under all three future climate change scenarios, the warming trend is prominent (around 1-2 degrees C increase), with a widespread reduction in wind speed in inland areas (1-2 ms(-1)). The vulnerability of human health to thermal stress was evaluated by adopting the wet-bulb globe temperature (WBGT). The results from the future scenarios suggest a high public health risk due to rising temperatures in the future. This study provides a methodology for a more comprehensive understanding of future urbanization and its impact on regional climate by using freely available satellite images and WRF simulation tools. The simulated temperature and WBGT results can serve local governments and stakeholders in city planning and the creation of action plans that will reduce the potential vulnerability of human health to excessive heat.
The increasing frequency of extreme hot days has a considerable impact on health and energy. Heat stress related to high temperatures cause increased rates of mortality and morbidity, particularly amongst vulnerable populations such as those belonging to lower socio-economic groups. Most studies on heat related mortality and morbidity generally use temperatures from weather stations that do not consider the urban heat island (UHI) effect, leading to inaccurate predictions, particularly during heat waves. This study uses data collected by citizen scientists in predicting outdoor thermal comfort as well as indoor heat stress and peak cooling energy for low income housing in Australia. The results show that the outdoor Universal thermal climate index (UTCI) values estimated during hot afternoon ranged from 26 degrees C to 46 degrees C which equate to moderate to extreme heat stress. The indoor Discomfort index (DI) values calculated inside the living and bedrooms were below the heat stress limits (DI < 28) when Bureau of Meteorology (BoM) data was used as the input for calculation. However, indoor DI exceeded the threshold when actual on-ground data was used in the calculations, indicating that people will be at severe risks of heat related illnesses. It was also found that 60% of the time DI exceeded the threshold value as opposed to 2% with the use of BoM data. Furthermore, the peak cooling load was increased by 24% when on-ground data was used. The results show that low income houses and the neighbourhoods where they are located can cause significant heat related health risks which are normally overlooked in typical simulation studies. This study demonstrated a cost-effective way of collecting microclimate data for urban heat island mitigation and adaptation studies. (C) 2020 Published by Elsevier B.V.
Climate change has led to increases in global temperatures, raising concerns regarding the threat of lethal heat waves and deterioration of the thermal environment. In the present study, we adopted two methods for spatial modelling of the thermal environment based on sensible heat and temperature. A vulnerability map reflecting daytime temperature was derived to plot thermal vulnerability based on sensible heat and climate change exposure factors. The correlation (0.73) between spatial distribution of sensible heat vulnerability and mortality rate was significantly greater than that (0.30) between the spatial distribution of temperature vulnerability and mortality rate. These findings indicate that deriving thermally vulnerable areas based on sensible heat are more objective than thermally vulnerable areas based on existing temperatures. Our findings support the notion that the distribution of sensible heat vulnerability at the community level is useful for evaluating the thermal environment in specific neighbourhoods. Thus, our results may aid in establishing spatial planning standards to improve environmental sustainability in a metropolitan community.
Natural disasters have negative health impacts on chronic diseases in affected populations. Severely affected areas are usually rural areas with limited basic infrastructure and a population have that has limited access to optimal healthcare after a disaster. Patients with cardiovascular diseases are required to maintain quality care, especially after disasters. A population-based case-control study enrolled adults from the National Health Insurance Registry who had ischemic heart disease and cerebrovascular disease histories and lived in the area affected by Typhoon Morakot in 2009. Monthly medical visits for acute cerebrovascular and ischemic heart diseases markedly increased at approximately 1-2 months after the typhoon. Survival analysis during the two years following the typhoon indicated a significant increase in mortality in adults with an acute ischemic heart disease history who lived in the severely affected area. Mortality hazard analysis showed that among affected adults with previous cerebrovascular diseases and acute ischemic heart diseases, patients with diabetes (adjusted hazard ratio [HR]: 1.3-1.7), Chronic Kidney Disease (CKD) (adjusted HR: 2.0-2.7), chronic obstructive pulmonary diseases (COPD) and asthma (adjusted HR: 1.7-2.1), liver cirrhosis (adjusted HR: 2.3-3.3) and neoplasms (adjusted HR: 1.1-2.1) had significantly increased mortality rates. Consequently, high-quality and accessible primary healthcare plans should be made available to maintain and support affected populations after disasters.
BACKGROUND: Both extreme heat and air pollution exposure during pregnancy have been associated with preterm birth; however, their combined effects are unclear. OBJECTIVES: Our goal was to estimate the independent and joint effects of heatwaves and fine particulate matter [PM < 2.5 ?m in aerodynamic diameter (PM2.5)], exposure during the final gestational week on preterm birth. METHODS: Using birth registry data from Guangzhou, China, we included 215,059 singleton live births in the warm season (1 May-31 October) between January 2015 and July 2017. Daily meteorological variables from 5 monitoring stations and PM2.5 concentrations from 11 sites were used to estimate district-specific exposures. A series of cut off temperature thresholds and durations (2, 3, and 4 consecutive d) were used to define 15 different heatwaves. Cox proportional hazard models were used to estimate the effects of heatwaves and PM2.5 exposures during the final week on preterm birth, and departures from additive joint effects were assessed using the relative excess risk due to interaction (RERI). RESULTS: Numbers of preterm births increased in association with heatwave exposures during the final gestational week. Depending on the heatwave definition used, hazard ratios (HRs) ranged from 1.10 (95% CI: 1.01, 1.20) to 1.92 (1.39, 2.64). Associations were stronger for more intense heatwaves. Combined effects of PM2.5 exposures and heatwaves appeared to be synergistic (RERIs > 0) for less extreme heatwaves (i.e., shorter or with relatively low temperature thresholds) but were less than additive (RERIs < 0) for more intense heatwaves. CONCLUSIONS: Our research strengthens the evidence that exposure to heatwaves during the final gestational week can independently trigger preterm birth. Moderate heatwaves may also act synergistically with PM2.5 exposure to increase risk of preterm birth, which adds new evidence to the current understanding of combined effects of air pollution and meteorological variables on adverse birth outcomes. https://doi.org/10.1289/EHP5117.
BACKGROUND: Due to variations in climatic conditions, the effects of meteorological factors and PM(2.5) on influenza activity, particularly in subtropical regions, vary in existing literature. In this study, we examined the relationship between influenza activity, meteorological parameters, and PM(2.5) . METHODS: A total of 20 165 laboratory-confirmed influenza cases in Hangzhou, Zhejiang province, were documented in our dataset and aggregated into weekly counts for downstream analysis. We employed a combination of the quasi-Poisson-generalized additive model and the distributed lag non-linear model to examine the relationship of interest, controlling for long-term trends, seasonal trends, and holidays. RESULTS: A hockey-stick association was found between absolute humidity and the risk of influenza infections. The overall cumulative adjusted relative risk (ARR) was statistically significant when weekly mean absolute humidity was low (<10 µg/m(3) ) and high (>17.5 µg/m(3) ). A slightly higher ARR was observed when weekly mean temperature reached over 30.5°C. A statistically significantly higher ARR was observed when weekly mean relative humidity dropped below 67%. ARR increased statistically significantly with increasing rainfall. For PM(2.5) , the ARR was marginally statistically insignificant. In brief, high temperature, wet and dry conditions, and heavy rainfall were the major risk factors associated with a higher risk of influenza infections. CONCLUSIONS: The present study contributes additional knowledge to the understanding of the effects of various environmental factors on influenza activities. Our findings shall be useful and important for the development of influenza surveillance and early warning systems.
Dengue, a mosquito-borne infectious disease caused by the dengue viruses, is present in many parts of the tropical and subtropical regions of the world. All four serotypes of dengue viruses are endemic in Singapore, an equatorial city-state. Frequent outbreaks occur, sometimes leading to national epidemics. However, few studies have attempted to characterize breakpoints which precede large rises in dengue case counts. In this paper, Bayesian regime switching (BRS) models were employed to infer epidemic and endemic regimes of dengue transmissions, each containing regime specific autoregressive processes which drive the growth and decline of dengue cases, estimated using a custom built multi-move Gibbs sampling algorithm. Posterior predictive checks indicate that BRS replicates temporal trends in Dengue transmissions well and nowcast accuracy assessed using a post-hoc classification scheme showed that BRS classification accuracy is robust even under limited data with the AUC-ROC at 0.935. LASSO-based regression and bootstrapping was used to account for plausibly high dimensions of climatic factors affecting Dengue transmissions, which was then estimated using cross-validation to conduct statistical inference on long-run climatic effects on the estimated regimes. BRS estimates epidemic and endemic regimes of dengue in Singapore which are characterized by persistence across time, lasting an average of 20 weeks and 66 weeks respectively, with a low probability of transitioning away from their regimes. Climate analysis with LASSO indicates that long-run climatic effects up to 20 weeks ago do not differentiate epidemic and endemic regimes. Lastly, by fitting BRS to simulated disease data generated from a stochastic Susceptible-Infected-Recovered model, mechanistic links between infectivity and regimes classified using BRS were provided. The model proposed could be applied to other localities and diseases under minimal data requirements where transmission counts over time are collected.
International reports indicate a rising incidence of nontuberculous mycobacterial (NTM) disease. Many infectious diseases have seasonal variation in incidence, and major weather events and climate change have been implicated. The aim of this study was to explore the relationship between climate variables and NTM incident cases in Queensland, Australia. METHODS: NTM data were obtained from the Queensland notifiable conditions database for the period 2001-2016. Rainfall and temperature data were obtained from the Australian Bureau of Meteorology. Poisson regression models were used to assess notification rates (incidence cases per 100,000 population) over time and to estimate incidence rate ratios (IRR). Cross correlation coefficients were used to examine the relationship between rainfall and temperature data and NTM incidence over time in each Hospital and Health Service (HHS). RESULTS: 12,219 NTM cases were reported. The most common species was M. intracellulare (39.1%), followed by M. avium (9.8%), M abscessus (8.5%), M. fortuitum (8.3%), M. chelonae (3.3%), and M. kansasii (2.4%). The estimated incidence rate increased from 11.10 (95% CI 8.10-15.22) in 2001 to 25.88 (95%CI 21.78-30.73) per 100,000 in 2016. The estimated IRR increased for all common species, except M. kansasii. Although increased IRRs were observed for most NTM species, geospatial heterogeneity was observed. The effect of rainfall and temperature on NTM incidence differed between species and geographic regions. CONCLUSIONS: The incidence of NTM infections increased between 2001 and 2016. Variations in temperature and rainfall may play a role in environmental exposure to some species of NTM. Spatial variation in IRR suggests that there may also be other environmental factors that influence transmission.
OBJECTIVE: To explore associations between temperature, humidity and hand, foot and mouth disease (HFMD) incidence in Guangzhou, China from 2013 to 2017. METHODS: A distributed lag non-linear model was applied to estimate the effects of daily temperature and humidity on HFMD incidence after adjusting for long-term trends, seasonal trends, and day of the week. RESULTS: In total, 353,431 confirmed HFMD cases were reported in Guangzhou over the study period. A bimodal seasonal pattern was observed. High temperatures had acute short-term effects on HFMD incidence that declined quickly over time. The effects of low humidity declined over lag periods, but increased when the humidity surpassed 60.5%. Temperature and humidity were both inversely associated with HFMD incidence during lag days 0 to 3 and with lag periods. CONCLUSIONS: Temperature and humidity play important roles in HFMD incidence. These data are important for developing public health strategies.
BACKGROUND: The aim of this study was to investigate the correlation between meteorological factors and the occurrence of acute aortic dissection (AAD) in Fujian Province, China. METHODS: The clinical data of 2004 patients diagnosed with AAD in our hospital and the relevant local meteorological data from January 2013 to November 2019 were retrospectively analyzed. RESULTS: The incidence of AAD had a clear tendency toward concentration, and the corresponding peak in terms of the occurrence date was from January 13 to 14. The average minimum temperature, the average maximum temperature, and the average daily temperature differences on the “day with AAD” were significantly lower than those on the “day without AAD”. From 5?days to 3?days before AAD onset, the average daily temperature difference showed a downward trend, but statistical analysis showed that the average minimum, average maximum and average daily temperature differences were not significantly different from the values 5?days to 0?days before AAD onset. CONCLUSIONS: The incidence of AAD is related to the season and month. The lowest average temperature may increase the incidence of AAD in patients with complicated cardiovascular diseases.
BACKGROUND: Many studies have shown an association of childhood respiratory diseases with short-term temperature variability such as diurnal temperature range (DTR) and temperature change between two neighboring days (TCN). However, the impact of temperature variability on allergic rhinitis (AR) has not been investigated so far. This study sought to evaluate the short-term effect of temperature variability (i.e., TCN and DTR) on AR, as well as to identify vulnerable subpopulations. METHOD: We collected daily data on emergency room visits and outpatients for AR and weather variables in Hefei, China during 2014-2016. A distributed lag non-linear model that controlled for long-term trend and seasonality, mean temperature, relative humidity, day of week was used to fit the associations of AR with DTR and TCN. Stratified analyses by age, sex and occupation were also performed. RESULTS: During the study period, there were a total of 53,538 cases and the average values of DTR and TCN were 8.4?°C (range: 1.0?°C to 21.2?°C) and 0?°C (range: -?12.2?°C to 5.9?°C), respectively. While we did not observe an adverse effect of DTR on AR, TCN was significantly associated with increased risk of AR. Specifically, a large temperature drop between two adjacent days (3.8?°C, 5th percentile of TCN) has a delayed and short-lasting effect on AR, with the estimated relative risk of 1.02 (95% confidence interval: 1.01 to 1.04) at lag 12. Moreover, boys and children older than 15?years seemed to be more vulnerable to the effect of TCN. CONCLUSIONS: This study provided evidence of an adverse effect of large temperature drops between two adjacent days on childhood AR. Attention paid to boys and older children may help prevent AR attacks.
The ongoing pandemic of 2019 novel coronavirus disease (COVID-19) is challenging global public health response system. We aim to identify the risk factors for the transmission of COVID-19 using data on mainland China. We estimated attack rate (AR) at county level. Logistic regression was used to explore the role of transportation in the nationwide spread. Generalized additive model and stratified linear mixed-effects model were developed to identify the effects of multiple meteorological factors on local transmission. The ARs in affected counties ranged from 0.6 to 9750.4 per million persons, with a median of 8.8. The counties being intersected by railways, freeways, national highways or having airports had significantly higher risk for COVID-19 with adjusted odds ratios (ORs) of 1.40 (p = 0.001), 2.07 (p < 0.001), 1.31 (p = 0.04), and 1.70 (p < 0.001), respectively. The higher AR of COVID-19 was significantly associated with lower average temperature, moderate cumulative precipitation and higher wind speed. Significant pairwise interactions were found among above three meteorological factors with higher risk of COVID-19 under low temperature and moderate precipitation. Warm areas can also be in higher risk of the disease with the increasing wind speed. In conclusion, transportation and meteorological factors may play important roles in the transmission of COVID-19 in mainland China, and could be integrated in consideration by public health alarm systems to better prevent the disease.
Urbanization and climate change have been rapidly occurring globally. Evidence-based healthy city development is required to improve living quality and mitigate the adverse impact of the outdoor neighborhood environment on public health. Taking Guangzhou as an example to explore the association of neighborhood environment and public health and preferably to offer some implications for better future city development, we measured ten environmental factors (temperature (T), wind-chill index (WCI), thermal stress index (HSI), relative humidity (RH), average wind speed (AWS), negative oxygen ions (NOI), PM2.5, luminous flux (LF), and illuminance (I)) in four seasons in four typical neighborhoods, and the SF-36 health scale was employed to assess the physical and mental health of neighborhood residents in nine subscales (health transition(HT), physiological functions (PF), general health status (GH), physical pain (BP), physiological functions (RP), energy vitality (VT), mental health (MH), social function (SF), and emotional functions (RE)). The linear mixed model was used in an analysis of variance. We ranked the different environmental factors in relation to aspects of health and weighted them accordingly. Generally, the thermal environment had the greatest impact on both physical and mental health and the atmospheric environment and wind environment had the least impact on physical health and mental health, respectively. In addition, the physical health of the resident was more greatly affected by the environment than mental health. According to the results, we make a number of strategic suggestions for the renewal of the outdoor neighborhood environment in subtropical monsoon climate high-density cities and provide a theoretical basis for improving public health through landscape architecture at the neighborhood scale.
Background: Few studies have previously explored the relationship between hand, foot, and mouth disease (HFMD) and meteorological factors with the effect modification of air pollution, and these studies had inconsistent findings. We therefore applied a time-series analysis assessing the effects of temperature and humidity on the incidence of HFMD in Wuhan, China to deepen our understanding of the relationship between meteorological factors and the risk of HFMD. Methods: Daily HFMD cases were retrieved from Hubei Provincial Center for Disease Control and Prevention from 1 February 2013 to 31 January 2017. Daily meteorological data including 24 h average temperature, relative humidity, wind velocity, and atmospheric pressure were obtained from Hubei Meteorological Bureau. Data on Air pollution was collected from 10 national air-monitoring stations in Wuhan city. We adopted a distributed lag non-linear model (DLNM) combined with Poisson regression and time-series analysis to estimate the effects of temperature and relative humidity on the incidence HFMD. Results: We found that the association between temperature and HFMD incidence was non-linear, exhibiting an approximate “M” shape with two peaks occurring at 2.3 °C (RR = 1.760, 95% CI: 1.218-2.542) and 27.9 °C (RR = 1.945, 95% CI: 1.570-2.408), respectively. We observed an inverted “V” shape between relative humidity and HFMD. The risk of HFMD reached a maximum value at a relative humidity of 89.2% (RR = 1.553, 95% CI: 1.322-1.824). The largest delayed cumulative effects occurred at lag 6 for temperature and lag 13 for relative humidity. Conclusions: The non-linear relationship between meteorological factors and the incidence of HFMD on different lag days could be used in the early targeted warning system of infectious diseases, reducing the possible outbreaks and burdens of HFMD among sensitive populations.
It is an overwhelming concern that increases in global average temperature lead to serious consequences on the natural environment in the form of deteriorating water resource quality and damaging healthcare sustainability agenda. The sustainable innovation forum (COP21) shows a high concern on climate changes and suggested to reduce global average temperature less than 2 °C. The study brings an idea from the stated theme and analyzed the relationship between climate change and water resource quality in order to redesign economic and environmental policies to improve water quality and healthcare sustainability in the context of Pakistan. The country has serious issues regarding the provision of safe drinking water, improved water resource quality, and healthcare sustainability, which can be achieved by sustainable policies to handle the extreme temperature in Pakistan. The study employed simultaneous generalized method of moments (GMM) technique in order to estimate parameters of the study during the period of 1980-2016. The results show that energy demand and industry value added substantially decrease water resource quality (WRQ), while agriculture value added and per capita income significantly increase WRQ in a country. The other regression apparatus, where health expenditures serve as the response variable, shows that average temperature, industry value added, population growth, and foreign direct investment (FDI) inflows significantly increase healthcare expenditures while WRQ has a negative impact on healthcare expenditures in a country. The final regression model shows that average temperature and per capita income decrease, while WRQ and industrial value added increase mortality rate in a country. The overall results confirm that WRQ affected by climate change, energy demand, and population growth that need sustainable water resource policies in order to achieve long-term sustained growth. The climate actions required more policy instruments to combat environmental challenges that should support healthcare sustainability agenda across the globe.
BACKGROUND: Taiwan is geographically located in a zone that is vulnerable to earthquakes, typhoons, floods, and landslide hazards and has experienced various disasters. Six Regional Emergency Medical Operation Centers (REMOCs) are integrated and administered by the Ministry of Health and Welfare (MOHW) to be responsible for emergency situations during disastrous events, such as the emission of chemical toxicants, traffic accidents, industrial materials containment, and typhoons. OBJECTIVE: To analyze events reported by the six REMOCs during the 2014 to 2018 for the government policy reference. METHODS: Data were collected from injured and death toll reports provided by local designated hospitals in the emergency medical reporting system. Disaster events were categorized into three categories: natural disaster (NDs), disasters associated with technology (DTs), and disasters associated with security/violence/others (DSVOs). The three categories were further subdivided into sub-categories. Variables considered for trend analyses included the number of wounded and deaths, event characteristics, date/time, and triage. The frequency of disaster events among the six REMOCs was compared using the chi-square test. We used the global information system (GIS) to describe the distribution of events in Taiwan metropolitan cities. The ?-level was set at 0.05. RESULTS: Of 580 events during the study period, the distribution of disaster characteristics in the jurisdictions of the six REMOCs were different. The majority of disaster events were DTs (64.5%), followed by NDs (24.5%) and DSVOs (11.0%). Events for the three disaster categories in the six REMOCs were different (?(2)-test, p < 0.001). Furthermore, for the Taipei branch (Northern Taiwan), other NDs, especially heatwaves and cold spells, were most reported in New Taipei City (92.2%) and showed an increasing annual trend; for the Kaohsiung branch (Southern Taiwan), DT events were the most reported, especially in Kaohsiung City; and for the Taichung branch (Central Taiwan), DSVOs were the most reported, especially in Taichung City. CONCLUSION: Our data revealed that extreme weather precautions reported in the Taipei branch were increasing. Disaster characteristics were different in each metropolitan city. Upgrading the ability to respond to natural disasters is ineluctable.
Dengue fever is an important arboviral disease in many countries. Its incidence has increased during the last decade in central Vietnam. Most dengue studies in Vietnam focused on the northern area (Hanoi) and southern regions but not on central Vietnam. Dengue transmission dynamics and relevant environmental risk factors in central Vietnam are not understood. This study aimed to evaluate spatiotemporal patterns of dengue fever in central Vietnam and effects of climatic factors and abundance of mosquitoes on its transmission. Dengue and mosquito surveillance data were obtained from the Department of Vector Control and Border Quarantine at Nha Trang Pasteur Institute. Geographic Information System and satellite remote sensing techniques were used to perform spatiotemporal analyses and to develop climate models using generalized additive models. During 2005-2018, 230,458 dengue cases were reported in central Vietnam. Da Nang and Khanh Hoa were two major hotspots in the study area. The final models indicated the important role of Indian Ocean Dipole, multivariate El Niño-Southern Oscillation index, and vector index in dengue transmission in both regions. Regional climatic variables and mosquito population may drive dengue transmission in central Vietnam. These findings provide important information for developing an early dengue warning system in central Vietnam.
More than four hundred million people suffer from respiratory diseases each year. Respiratory diseases are associated with a large disease burden. Heatwaves and cold spells, the two most common extreme weather events, have been shown to have crucial negative effects on the prevalence of respiratory diseases. However, impacts of extreme weather on the prevalence of respiratory diseases has been largely overlooked in western China, where more intense and frequent extreme temperature events have been occurring over the past decades. This research gap will obtain an attribution bias in the effects of extreme weather events on the prevalence of respiratory diseases. Therefore, in this study, we analyzed the impact of heatwaves and cold spells on the morbidity of respiratory diseases using a distributed lag nonlinear model with daily disease cases from 2013 to 2016 in Lanzhou, one of the largest cities in western China. A reverse U-shaped relationship depicted the relationship between temperature and the morbidity of respiratory diseases. The highest relative risk was found at 2.6 degrees C by 1.15 (95% confidence interval: 1.09-1.21). Furthermore, we found a significant decrease in the relative risk for heatwaves and a significant increase in the relative risk of cold spells when the temperature exceeded the corresponding threshold by 1 degrees C. Heatwaves and cold spells play harvest effects on the morbidity of respiratory diseases. Our study suggest that the relative risk of respiratory diseases will increase as the climate warms in the future, and thus a preventive system is needed for individuals and medical policy-makers.
Southwestern Japan suffered its worst rains in 2018 causing floods and mudslides, claiming 225 lives and forcing millions for evacuations. Referred as “Heisei san-j?-nenshichi-gatsug?u”, the disaster was the result of incessant precipitation caused by the interaction of typhoon “Prapiroon” with the seasonal rain front “Baiu”. The present epidemiological study aims to investigate disaster-induced health issues in 728 residents of Innoshima island in the Hiroshima Prefecture by comparing their clinical data in pre-disaster (2017) and disaster-hit (2018) years which was obtained from annual health screening. Comparison of data showed a significant increase in the urine protein concentration in victims following the disaster. Probing further into the household conditions, showed that a total of 59,844 households were affected with water outage during the heavy rains, which was accompanied by severe damage of sewerage pipelines with complete recovery process taking two weeks. This two weeks of the crisis forced victims to refrain from using restrooms which in turn led to infrequent urination, thereby explaining the increased urine protein concentration in victims following the disaster. The present study addresses the acute health implications caused by the water crisis and serves as a precautionary measure for disaster management council to provide enhanced aftercare services in victims in further events of natural disasters.
Background: Air pollution is a global problem and also linked to respiratory diseases. Wildfire smog is a major cause of air pollution in the upper northern area of Thailand. Thus, in the current study, we examined whether long-term exposure to wildfire smog induces lung function changes in a population from the upper northern area of Thailand. Methods: The lung function of 115 participants with long-term exposure smog was determined using peak flow meter. Results: Long-term smoke exposure participants decreased FEV1 (forced expiratory volume in 1 second)/FVC (forced vital capacity) ratio (56.49 +/- 23.88 in males and 56.29 +/- 28.23 in females) compared with general Thai population. Moreover, the reduction of FVC, FEV1, and peak expiratory flow rate (PEFR) values also showed in both male and female subjects. These results suggest that long-term smoke exposure induces obstructive lung abnormality. Moreover, itchy/watery nose, cough, phlegm, and chest pain also reported in these subjects. Conclusion: Wildfire smog could be induced respiratory pathway inflammation and easily collapsible respiratory airways.
The purpose of the present study is to explore the associations between novel coronavirus disease 2019 (COVID-19) case counts and meteorological factors in 30 provincial capital cities of China. We compiled a daily dataset including confirmed case counts, ambient temperature (AT), diurnal temperature range (DTR), absolute humidity (AH) and migration scale index (MSI) for each city during the period of January 20th to March 2nd, 2020. First, we explored the associations between COVID-19 confirmed case counts, meteorological factors, and MSI using non-linear regression. Then, we conducted a two-stage analysis for 17 cities with more than 50 confirmed cases. In the first stage, generalized linear models with negative binomial distribution were fitted to estimate city-specific effects of meteorological factors on confirmed case counts. In the second stage, the meta-analysis was conducted to estimate the pooled effects. Our results showed that among 13 cities that have less than 50 confirmed cases, 9 cities locate in the Northern China with average AT below 0 °C, 12 cities had average AH below 4 g/m(3), and one city (Haikou) had the highest AH (14.05 g/m(3)). Those 17 cities with 50 and more cases accounted for 90.6% of all cases in our study. Each 1 °C increase in AT and DTR was related to the decline of daily confirmed case counts, and the corresponding pooled RRs were 0.80 (95% CI: 0.75, 0.85) and 0.90 (95% CI: 0.86, 0.95), respectively. For AH, the association with COVID-19 case counts were statistically significant in lag 07 and lag 014. In addition, we found the all these associations increased with accumulated time duration up to 14 days. In conclusions, meteorological factors play an independent role in the COVID-19 transmission after controlling population migration. Local weather condition with low temperature, mild diurnal temperature range and low humidity likely favor the transmission.
Political and environmental factors-e.g., regional conflicts and global warming-increase large-scale migrations, posing extraordinary societal challenges to policymakers of destination countries. A common concern is that such a massive arrival of people-often from a country with a disrupted healthcare system-can increase the risk of vaccine-preventable disease outbreaks like measles. We analyze human flows of 3.5 million (M) Syrian refugees in Turkey inferred from massive mobile-phone data to verify this concern. We use multilayer modeling of interdependent social and epidemic dynamics to demonstrate that the risk of disease reemergence in Turkey, the main host country, can be dramatically reduced by 75 to 90% when the mixing of Turkish and Syrian populations is high. Our results suggest that maximizing the dispersal of refugees in the recipient population contributes to impede the spread of sustained measles epidemics, rather than favoring it. Targeted vaccination campaigns and policies enhancing social integration of refugees are the most effective strategies to reduce epidemic risks for all citizens.
STUDY OBJECTIVES: This study investigated the association between ambient nighttime temperature and sleep problems assessed by the prescription dose of sleeping pills in South Korean adults. METHODS: We used the 2002-2015 National Health Insurance Service-National Sample Cohort. A total of 711,079 adults who were 20 years old or older were included, wherein 42,858 adults (~6%) had been prescribed hypnotic medications including zolpidem (N05CF02) and triazolam (N05CD05). Ambient temperature data was calculated as the mean highest temperature of nighttime (23:00-07:00) for every month from January to December. We combined the drug-prescribed date with the administrative districts-level daily nighttime temperature between 2002 and 2015. RESULTS: We found that a non-linear, U-shaped relationship between nighttime temperature and hypnotic medication prescription. With an increase per 1°C temperature or an increase in a square per 1°C, the prescription dose of sleeping pills was significantly increased (both p < 0.05). At each 5°C nighttime temperature, subjects belonging to low (?0°C and 0-5°C) or high (20-25°C and ?25°C) temperature categories had significantly higher doses of sleeping pills than those at the reference temperature (10-15°C). Changes in nighttime temperature had a significant non-linear effect on the prescribed dosage of hypnotic medications for both adults (p < 0.0001) and the elderly (p = 0.0006). CONCLUSION: We found that either a high or low nighttime temperature was significantly associated with a high daily dose of hypnotic medications in the Korean population.
High temperatures are one of the main causes of work safety accidents associated with cognitive impairment. However, the effects of elevated ambient temperature on cognitive performance during moderate-intensity activities are unclear. In this study, subjects (N = 32) were exposed to four different air temperatures, i.e., 26, 30, 33, and 37 degrees C, and a relative humidity of 70% in a climate chamber. During the experiment, the subjects were required to complete neurobehavioral cognitive tests while walking on a treadmill with an estimated metabolic rate of 165 W/m(2). During the 90-min experiment, the tympanic temperature, weight loss, heart rate, and percentage of adjacent inter-beat cardiac intervals differing by > 50 ms (pNN50) were measured. Subjective responses were collected using questionnaires.The accuracy of subjects’ responses to the semantic interference and visual perception tests were significantly decreased at 37 degrees C after 45 min of exercise. Additionally, over the exposure period at 37 degrees C, the accuracy of various cognitive tests also decreased, while the speed increased. The changes in the cognitive test results at 37 degrees C were associated with the elevation of the tympanic temperature, heart rate, dehydration rate, and decline of the pNN50. Similarly, the elevated thermal discomfort and intensity of neurobehavioral symptoms were related to these changes.In conclusion, exposure to a temperature of 37 degrees C for 45 min has a negative impact on the accuracy of personnel with moderate-activity intensity. Therefore, 45 min is recommended as a safe time for continuous work with moderate intensity at 37 degrees C.
BACKGROUND: Health impacts of high temperatures on hospital emergency department visits (EDVs) have been less reported, especially from developing countries. OBJECTIVES: To investigate high temperature-EDVs relationship in various regions with different climatic characteristics, to explore the regional differences, to identify vulnerable populations, and to provide scientific evidence for climate change adaptation strategies in China. METHODS: Daily data on weather, air pollution and EDVs were collected from 18 sites in China from June to August during 2014-2017. A quasi-Poisson generalized additive regression model was applied to examine the high temperature-EDVs relationship in each site. Site-specific risks of EDVs were pooled using a random effect meta-analysis model. Stratified analyses were performed by gender, age-groups, cause-specific EDVs and regions. Attributable fractions of EDVs due to high temperatures were calculated in different regions. RESULTS: 1 °C increase in daily mean temperature was associated with 1.07% (95% CI, 0.46-1.67%) increase in EDVs across all study regions. The negative health effects from high temperatures were worse for the people living in southern China, in subtropical monsoon climate zone or in counties, with percentage change of 1.96% (95% CI, 0.92-3.02%), 1.35% (95% CI, 0.95-1.76%) and 1.41% (95% CI, 0.48-2.34%), respectively. People under 18 were more vulnerable to high temperatures. Exposure to high temperatures increased EDVs risks from endocrine, respiratory, and digestive diseases and injury. The attributable fraction due to high temperatures was 8.64% for overall EDVs, 11.70% for the people living in southern China, 10.80% for people living in subtropical monsoon climate zone and 12.65% for the county population. CONCLUSIONS: Exposure to high temperatures resulted in extra burden to China’s already overloaded hospital emergency departments. More resources are needed to meet increasing demands and effective preventative measurements are warranted to tackle such a challenge. Further studies should pay more attention to both heat and cold-related EDVs risks and socioeconomic cost for better climate change adaptation.
Overheated outdoor environments adversely impact urban sustainability and livability. Urban areas are particularly affected by heat waves and global climate change, which is a serious threat due to increasing heat stress and thermal risk for residents. The tropical city of Darwin, Australia, for example, is especially susceptible to urban overheating that can kill inhabitants. Here, using a modeling platform supported by detailed measurements of meteorological data, we report the first quantified analysis of the urban microclimate and evaluate the impacts of heat mitigation technologies to decrease the ambient temperature in the city of Darwin. We present a holistic study that quantifies the benefits of city-scale heat mitigation to human health, energy consumption, and peak electricity demand. The best-performing mitigation scenario, which combines cool materials, shading, and greenery, reduces the peak ambient temperature by 2.7 °C and consequently decreases the peak electricity demand and the total annual cooling load by 2% and 7.2%, respectively. Further, the proposed heat mitigation approach can save 9.66 excess deaths per year per 100,000 people within the Darwin urban health district. Our results confirm the technological possibilities for urban heat mitigation, which serves as a strategy for mitigating the severity of cumulative threats to urban sustainability.
Findings of the association between hot weather and suicide in a subtropical city such as Hong Kong are inconsistent. This study aimed to revisit the association by identifying meteorological risk factors for older-adult suicides in Hong Kong using a time-series approach. A retrospective study was conducted on older-adult (aged ?65) suicide deaths in Hong Kong from 1976 to 2014. Suicides were classified into those involving violent methods and those involving nonviolent methods. Meteorological data, including ambient temperature, were retrieved. Transfer function time-series models were fitted. In total, 7314 older-adult suicide deaths involving violent methods and 630 involving nonviolent methods were recorded. For violent-method suicides, a monthly average daily minimum ambient temperature was determined to best predict the monthly rate, and a daily maximum ambient temperature of 30.3 °C was considered the threshold. For suicide deaths involving nonviolent methods, the number of days in a month for which the daily maximum ambient temperature exceeded 32.7 °C could best predict the monthly rate. Higher ambient temperature was associated with more older-adult suicide deaths, both from violent and nonviolent methods. Weather-focused preventive measures for older-adult suicides are necessary, such as the provision of more public air-conditioned areas where older adults can shelter from extreme hot weather.
Infectious diseases are a major health challenge for the worldwide population. Since their rapid spread can cause great distress to the real world, in addition to taking appropriate measures to curb the spread of infectious diseases in the event of an outbreak, proper prediction and early warning before the outbreak of the threat of infectious diseases can provide an important basis for early and reasonable response by the government health sector, reduce morbidity and mortality, and greatly reduce national losses. However, if only traditional medical data is involved, it may be too late or too difficult to implement prediction and early warning of an infectious outbreak. Recently, medical big data has become a research hotspot and has played an increasingly important role in public health, precision medicine, and disease prediction. In this paper, we focus on exploring a prediction and early warning method for influenza with the help of medical big data. It is well known that meteorological conditions have an influence on influenza outbreaks. So, we try to find a way to determine the early warning threshold value of influenza outbreaks through big data analysis concerning meteorological factors. Results show that, based on analysis of meteorological conditions combined with influenza outbreak history data, the early warning threshold of influenza outbreaks could be established with reasonable high accuracy.
Sand and dust storms in arid and semiarid regions deteriorate regional air quality and threaten public health security. To quantify the negative effects of river dust on regional air quality, this study selected the estuary areas located in central Taiwan as a case study and proposed an integrated framework to measure the fugitive emission of dust from riverbeds with the aid of satellite remote sensing and wind tunnel test, together with the concentrations of particulate matter with a diameter of <10 ?m (PM(10)) around the river system by using The Air Pollution Model. Additionally, the effects of 25 types of meteorological conditions on the health risk due to exposure to dust were evaluated near the estuary areas. The results reveal landscape changes in the downstream areas of Da'an and Dajia rivers, with an increase of 370,820 m(2) and 1,554,850 m(2) of bare land areas in the dry season compared with the wet season in Da'an and Dajia rivers, respectively. On the basis of the maximum emission of river dust, PM(10) concentration increases considerably during both wet and dry seasons near the two rivers. Among 25 different types of weather conditions, frontal surface transit, outer-region circulation from tropical depression system, weak northeast monsoons, and anticyclonic outflow have considerable influence on PM(10) diffusion. In particular, weak northeast monsoons cause the highest health risk in the areas between Da'an and Dajia rivers, which is the densely populated Taichung City. Future studies should attempt to elucidate the environmental impact of dust in different weather conditions and understand the spatial risks to human health due to PM(10) concentration. Facing the increasing threat of climate and landscape changes, governments are strongly encouraged to begin multimedia assessments in environmental management and propose a long-term and systematic framework in resources planning.
BACKGROUND: The substantial disease burden attributed to heat waves, and their increasing frequency and intensity due to climate change, highlight the importance of understanding the health consequences of heat waves. We explore the mortality risk due to heat wave characteristics, including the timing in the seasons, the day of the heat wave, the intensity and the duration, and the modifying effect of temperature zones. METHODS: Heat waves were defined as ? 2?days with a temperature ?99th percentile for the county from 1 May through 30 September. Heat waves were characterized by their intensity, duration, timing in the season, and day of the heat wave. Within each county, we estimated the total non-accidental death and cardiovascular disease mortality during each heat wave compared with non-heat wave days by controlling for potential confounders in summer. We combined individual heat wave effect estimates using a random-effects model to calculate overall effects at the temperature zone and national levels. RESULTS: The average daily total number of non-accidental deaths was nine in the warm season (across all the counties). Approximately half of the daily total number of non-accidental deaths were cardiovascular-related deaths (approximately four persons per day). The average and maximum temperatures across the study area were 23.1?°C (range: -1.2-35.9?°C) and 28.3?°C (range: 5.4-42.8?°C), respectively. The average relative humidity during the study was 68.9% (range: 8.0-100.0%). Heat waves increase the risk of total non-accidental death by 15.7% [95% confidence interval (CI): 12.5, 18.9] compared with non-heat wave periods, and the risk of cardiovascular-related death increases by 22.0% (95% CI: 16.9, 27.4). The risk of non-accidental death during the first heat wave of the season increases by 16.3% (95% CI: 12.6, 20.2), the risk during the second heat wave increases by 6.3% (95% CI: 2.8, 9.9) and during subsequent heat waves increases by -2.1% (95% CI: -4.6, 0.4). The first day and the second to third days of heat waves increase the risk of total non-accidental death by 11.7% (95% CI: 7.6, 15.9) and 17.0% (95% CI: 13.1, 21.0), respectively. Effects of heat waves on mortality lasted more than 4?days (6.3%, 95% CI: 2.4, 10.5) and are non-significantly different from the first day of heat waves. We found non-significant differences of the heat wave-associated mortality risks across mid-, Warm and subtropical temperature zones. CONCLUSIONS: In China, the effect of heat waves on mortality is acute, and varies by certain characteristics of heat waves. Given these results, national heat wave early warning systems should be developed, as well as precautions and protection warranted according to characteristics of heat waves.
Introduction: Hot weather poses occupational health and safety concerns for people working in hot environments. It is known that work-related injuries increase during hot weather, yet there is an incomplete understanding of the underlying factors. Methods: A national online survey was conducted in Australia among health and safety representatives (HSRs) to better understand factors contributing to heat-related injuries in workplaces. Risk factors and preventive measures associated with reported injuries were identified using log-poisson regression models. Results: In total, 222 HSRs completed the survey. Overall, 43% reported that injuries or incidents caused by hot/very humid weather occur sometimes or often in their workplace. Factors found to be associated with reported heat-related injuries included ‘the wearing of personal protective equipment (PPE)’ which can hinder the loss of body heat, and ‘inadequate resources and facilities’. ‘Piece-rate workers’ and ‘new workers’ were identified as being at high risk. The most frequently adopted preventive measures for outdoor and indoor workers were the provision of PPE (despite some identified issues) and access to cool drinking water. HSRs reported that less injuries occurred in hot weather among outdoor workers if work was rescheduled to cooler times and shade was provided; and in indoor environments where there was adequate ventilation, heat sources were shielded and workers were able to self-pace. Conclusion: Organisational issues, workplace hazards, personal factors and preventive measures, are all determinants of heat-related injuries in Australian workplaces. Wider adoption of identified prevention measures could reduce the incidence of heat-related injuries in outdoor and indoor workplaces.
Climate change increases the frequency and intensity of heatwaves, causing significant human and material losses every year. Big data, whose volumes are rapidly increasing, are expected to be used for preemptive responses. However, human cognitive abilities are limited, which can lead to ineffective decision making during disaster responses when artificial intelligence-based analysis models are not employed. Existing prediction models have limitations with regard to their validation, and most models focus only on heat-associated deaths. In this study, a random forest model was developed for the weekly prediction of heat-related damages on the basis of four years (2015-2018) of statistical, meteorological, and floating population data from South Korea. The model was evaluated through comparisons with other traditional regression models in terms of mean absolute error, root mean squared error, root mean squared logarithmic error, and coefficient of determination (R-2). In a comparative analysis with observed values, the proposed model showed an R-2 value of 0.804. The results show that the proposed model outperforms existing models. They also show that the floating population variable collected from mobile global positioning systems contributes more to predictions than the aggregate population variable.
Assessing heatwave-induced human health risk is of critical importance in order to mitigate hazards caused by extreme environmental events. Air temperature or land surface temperature in previous studies was often used to characterize the severity of heatwaves, and human perception of the thermal environment was neglected as a key component in the heatwave-induced risk assessment. In order to redress this issue, in this study we applied the Universal Thermal Climate Index (UTCI) to represent human thermal comfort perception and embedded the measure within an assessment framework of heat stress-social vulnerability-human exposure. The heatwave-induced human health risk was then evaluated in Wuhan City, China across 177 blocks covering the entire city area and local risk governance measures were also explored based on risk zoning. The results showed that spatial patterns of heatwave-induced human health risk followed a decreasing trend from the city center towards the surrounding areas, with the average risk of the main urban area being 1.6 times that beyond the metropolitan development area. Through the heatwave-induced human health risk zoning, about 73.45% of the 177 blocks in Wuhan City demonstrated a positive relationship between heat stress and human exposure, and both were opposite with social vulnerability. Multiple linear regression between UTCI and the proportion of greenspace, water body and construction land indicated that, more blue or green infrastructure should be integrated within the urban fabric to help mitigate heat stress particularly in the main urban area, while in the metropolitan development area construction land dominating heat stress should be strictly regulated. Furthermore, protecting vulnerable groups such as left-behind children and elderly people should be a priority in rural areas that were generally associated with higher levels of social vulnerability. This study proposed a new heatwave-induced human health risk framework with a local evidence in Wuhan City, and further emphasized that risk zoning could be used as a basic yet important approach to facilitating more effective urban planning guidelines for risk governance.
Studies on the pattern of heatwave mortality using nationwide data that include rural areas are limited. This study aimed to assess the risk of heatwave-related mortality and evaluate the health risk-based definition of heatwave. We collected data on daily temperature and mortality from 229 districts in South Korea in 2011-2017. District-specific heatwave-related mortality risks were calculated using a distributed lag model. The estimates were pooled in the total areas and for each urban and rural area using meta-regression. In the total areas, the threshold point of heatwave mortality risk was estimated at the 93rd percentile of temperature, and it was lower in urban areas than in rural areas (92nd percentile vs. 95th percentile). The maximum risk of heatwave-related mortality in the total area was 1.11 (95% CI: 1.01-1.22), and it was slightly greater in rural areas than in the urban areas (RR: 1.23, 95% CI: 0.99-1.53 vs. RR: 1.10, 95% CI: 1.01-1.20). The results differ by age- and cause-specific deaths. In conclusion, the patterns of heatwave-related mortality risk vary by area and sub-population in Korea. Thus, more target-specific heatwave definitions and action plans should be established according to different areas and populations.
BACKGROUND: Many studies have shown associations between rising temperatures, El Niño events and dengue incidence, but the effect of sustained periods of extreme high temperatures (i.e., heatwaves) on dengue outbreaks has not yet been investigated. This study aimed to compare the short-term temperature-dengue associations during different dengue outbreak periods, estimate the dengue cases attributable to temperature, and ascertain if there was an association between heatwaves and dengue outbreaks in Hanoi, Vietnam. METHODOLOGY/PRINCIPAL FINDINGS: Dengue outbreaks were assigned to one of three categories (small, medium and large) based on the 50th, 75th, and 90th percentiles of distribution of weekly dengue cases during 2008-2016. Using a generalised linear regression model with a negative binomial link that controlled for temporal trends, temperature variation, rainfall and population size over time, we examined and compared associations between weekly average temperature and weekly dengue incidence for different outbreak categories. The same model using weeks with or without heatwaves as binary variables was applied to examine the potential effects of extreme heatwaves, defined as seven or more days with temperatures above the 95th percentile of daily temperature distribution during the study period. This study included 55,801 dengue cases, with an average of 119 (range: 0 to 1454) cases per week. The exposure-response relationship between temperature and dengue risk was non-linear and differed with dengue category. After considering the delayed effects of temperature (one week lag), we estimated that 4.6%, 11.6%, and 21.9% of incident cases during small, medium, and large outbreaks were attributable to temperature. We found evidence of an association between heatwaves and dengue outbreaks, with longer delayed effects on large outbreaks (around 14 weeks later) than small and medium outbreaks (4 to 9 weeks later). Compared with non-heatwave years, dengue outbreaks (i.e., small, moderate and large outbreaks combined) in heatwave years had higher weekly number of dengue cases (p<0.05). Findings were robust under different sensitivity analyses. CONCLUSIONS: The short-term association between temperature and dengue risk varied by the level of outbreaks and temperature seems more likely affect large outbreaks. Moreover, heatwaves may delay the timing and increase the magnitude of dengue outbreaks.
Heatwaves are defined as unusually high temperature events that occur for at least three consecutive days with major impacts to human health, economy, agriculture and ecosystems. This paper investigates: 1) changes in heatwave characteristics such as peak temperature, number of events, frequency and duration over a past 67-year period in Australia; 2) projected changes in heatwave characteristics for this century in Queensland, northeast Australia; and 3) the avoided heatwave impacts of limiting global warming by 1.5 °C, 2.0 °C and 3.0 °C. The results reveal that heatwaves have increased in intensity, frequency and duration across Australia over the past 67 years, such intensification was particularly higher on recent decades. Downscaled future climate projections for Queensland suggest that heatwaves will further intensify over the current century. The projections also highlight that distinct climatic regions within Queensland may have different heatwave responses under global warming, where tropical and equatorial heatwaves appear to be more sensitive to elevated atmospheric CO(2) concentrations than temperate and arid regions. The results offer new insights to support climate adaptation and mitigation at regional scales. These findings are already being used by health and emergency services to inform the development of statewide policies to mitigate heatwave impacts.
The effect of tropical deforestation on heat exposure and subsequent human health outcomes remains understudied, especially among an increasingly vulnerable population-healthy, adult subsistence workers in rural industrializing tropical countries. We report on a field experiment that estimated the short-term effects of heat exposure from deforestation on cognitive performance. We randomly assigned rural, adult subsistence workers in East Kalimantan, Indonesia to deforested or forested settings, and standard or high incentive piece rate payments. Participants worked in forested or deforested settings for up to 90 min, where ambient and black globe temperatures in deforested areas were, on average, 2.1 degrees C and 10 degrees C higher. After completing the experimental task, participants were asked to take a validated general cognitive assessment test (CAT) and episodic memory test (EMT). We found participants in deforested settings had statistically significant lower scores on both CAT and EMT. Effects were largely driven by heat effects on male participants and those working after noon. Our results highlight how heat exposure from tropical deforestation may lead to declines in cognitive performance even in favorable work settings. Policymakers should consider how land use planning that takes into account the cooling services of trees can play a significant role in increasing resilience to heat from climate and land use change in the tropics.
More than half of the world’s population currently live in urban areas and are particularly at risk from the combined effects of the urban heat island phenomenon and heat increases due to climate change. Here, by using remotely sensed surface temperature data and social-ecological indicators, focusing on the hot dry season, and applying the risk framework of the Intergovernmental Panel on Climate Change, we assessed the current heat health risk in 139 Philippine cities, which account for about 40% of the country’s total population. The cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high. The most vulnerable cities are, however, found mainly outside the national capital region, where sensitivity is higher and capacity to cope and adapt is lower. Cities with high levels of heat vulnerability and exposure must be prioritized for adaptation. Our results will contribute to risk profiling in the Philippines and to the understanding of city-level heat health risks in developing regions of the Asia-Pacific.
Extreme heat stress has a deep impact on physiological reactions, which results in occupational injuries and deaths. In this paper, an attempt is made to understand the impact of heat stress on construction accidents in Oman. A literature review on heat stress is discussed in the first section followed by an analysis of 623 accidents that occurred in a highway project. The analysis of these accidents reveals that more severe accidents on this project took place from 11:00 to 17:00. The semi-structured interview held with some of the workers involved in these accidents confirmed excessive heat as one of the main reason behind these accidents. The health profile of the same workers is measured in terms of their body mass index and blood pressure. The results show that 80% of the workers from the selected sample were found to be overweight or obese and 40% of the participants were hypertensive. The safety performance of such workers is particularly discussed in relation to heat stress. The effective implementations of day time break in summer, a healthy diet, appropriate sleeping habit, scheduling physically demanding tasks during early morning and evening and adopting light colour and loose fitting uniform could reduce the impact of heat stress.
Prolonged or intense exposure to heat can lead to a range of health effects. This study investigated heat exposure and heat-related symptoms which sugarcane workers (90 sugarcane cutters and 93 factory workers) experienced during a harvesting season in Thailand. During the hottest month of harvesting season, wet bulb globe temperature was collected in the work environment, and workloads observed, to assess heat stress. Urine samples for dehydration test, blood pressure, heart rate, and body temperature were measured pre- and post-shift to measure heat strain. Fluid intake and heat-related symptoms which subjects had experienced during the harvesting season were gathered via interviews at the end of the season. From the results, sugarcane cutters showed high risk for heat stress and strain, unlike factory workers who had low risk based on the American Conference of Governmental Industrial Hygiene (ACGIH) threshold limit values (TLVs) for heat stress. Dehydration was observed among sugarcane cutters and significant physiological changes including heart rate, body temperature, and systolic blood pressure occurred across the work shift. Significantly more sugarcane cutters reported experiencing heat-related symptoms including weakness/fatigue, heavy sweating, headache, rash, muscle cramp, dry mouth, dizziness, fever, dry/cracking skin, and swelling, compared to sugarcane factory workers. We conclude that the heat stress experienced by sugarcane cutters working in extremely hot environments, with high workloads, is associated with acute health effects. Preventive and control measures for heat stress are needed to reduce the risk of heat strain.
Accounting for only a limited fraction of Earth’s land surface, urban areas accommodate more than half the global population. The projected increasing severe heat waves with global warming exert a profound threat to the dense urban population and infrastructure. Despite abundant past studies on heat waves, there was a lack of attention to the daytime-nighttime compound heat waves. Here, we categorize summertime heat waves into three distinct types, that is, independent daytime or nighttime heat waves and compound heat waves. Using a universal heat wave metric, we identify the strongest compound heat waves on record (1961-2015) in three vast urban agglomerations in China. We demonstrate substantial increase of the land areas affected by severe compound heat waves over the past three decades. We further quantify the changes in areal and population exposures to future unprecedented compound heat waves. Our results show that under a high-end emission scenario, 50% (100%) of the land area in the Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Pearl River Delta will be exposed to historically unprecedented compound heat waves on a regular basis by 2050 (2090), 2050 (2070), and 2030 (2050), respectively. Such enhancing heat hazard will induce increasing population exposure of nearly 70, 90, and 60 million to unprecedented compound heat waves by the end of this century (relative to the 2010s). Our findings call for effective mitigation and adaptation strategies to alleviate the risks of unprecedented compound heat waves in rapidly developing populous urban areas. Plain Language Summary Extreme heat waves impose devastating impacts on human health, economy, and the environment. The risk of extreme heat stress tends to be higher in urban areas than in surroundings, due to greater population exposure and added heat stress from urban heat island. Compared to daytime- or nighttime-only heat waves, the risk of compound heat waves that combine scorching days and sweltering nights sequentially tends to be higher. Focusing on top three populous urban agglomerations in China, this study dissects summertime heat waves into three nonoverlapping types and identifies the strongest heat waves on record based on a universal metric of heat wave magnitude. Projections show that unprecedented compound heat waves will become the norm since around 2045 (2060), 2045 (2065), and 2030 (2040) in the Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Pearl River Delta, respectively, under RCP8.5 (RCP4.5) emission scenario. Enhancing heat hazards will translate into increasing population exposure of about 70, 90, and 60 million to unprecedented compound heat waves by the end of this century, which are concentrated on the highly urbanized areas, such as Beijing, Shanghai, Guangzhou, and Shenzhen. This study highlights the urgent adaptation and mitigation efforts for cities against compound heat waves in particular.
PURPOSE: The time-of-day variations in environmental heat stress have been known to affect thermoregulatory responses and the risk of exertional heat-related illness during outdoor exercise in the heat. However, such effect and risk are still needed to be examined during indoor sports/exercises. The current study investigated the diurnal relationships between thermoregulatory strain and environmental heat stress during regular judo training in a judo training facility without air conditioning on a clear day in the heat of summer. METHODS: Eight male high school judokas completed two 2.5-h indoor judo training sessions. The sessions were commenced at 09:00 h (AM) and 16:00 h (PM) on separate days. RESULTS: During the sessions, indoor and outdoor heat stress progressively increased in AM but decreased in PM, and indoor heat stress was less in AM than PM (mean ambient temperature: AM 32.7±0.4°C; PM 34.4±1.0°C, P<0.01). Mean skin temperature was higher in AM than PM (P<0.05), despite greater dry and evaporative heat losses in AM than PM (P<0.001). Infrared tympanic temperature, heart rate and thermal sensation demonstrated a trial by time interaction (P<0.001) with no differences at any time point between trials, showing relatively higher responses in these variables in PM compared to AM during the early stages of training and in AM compared to PM during the later stages of training. There were no differences between trials in body mass loss and rating of perceived exertion. CONCLUSIONS: This study indicates a greater thermoregulatory strain in the morning from 09:00 h than the late afternoon from 16:00 h during 2.5-h regular judo training in no air conditioning facility on a clear day in the heat of summer. This observation is associated with a progressive increase in indoor and outdoor heat stress in the morning, despite a less indoor heat stress in the morning than the afternoon.
BACKGROUND: Over the past four decades, drought episodes in the Eastern Mediterranean Region (EMR) of the of the World Health Organization (WHO) have gradually become more widespread, prolonged and frequent. We aimed to map hotspot countries and identified key strategic actions for health consequences. METHODS: We reviewed scientific literature and WHO EMR documentation on trends and patterns of the drought health consequences from 1990 through 2019. Extensive communication was also carried out with EMR WHO country offices to retrieve information on ongoing initiatives to face health consequences due to drought. An index score was developed to categorize countries according vulnerability factors towards drought. RESULTS: A series of complex health consequences are due to drought in EMR, including malnutrition, vector-borne diseases, and water-borne diseases. The index score indicated how Afghanistan, Yemen and Somalia are “hotspots” due to poor population health status and access to basic sanitation as well as other elements such as food insecurity, displacement and conflicts/political instability. WHO country offices effort is towards enhancing access to water and sanitation and essential healthcare services including immunization and psychological support, strengthening disease surveillance and response, and risk communication. CONCLUSIONS: Drought-related health effects in the WHO EMR represent a public health emergency. Strengthening mitigation activities and additional tailored efforts are urgently needed to overcome context-specific gaps and weaknesses, with specific focus on financing, accountability and enhanced data availability.
BACKGROUND: As a mosquito-borne infectious disease, dengue fever (DF) has spread through tropical and subtropical regions worldwide in recent decades. Dengue forecasting is essential for enhancing the effectiveness of preventive measures. Current studies have been primarily conducted at national, sub-national, and city levels, while an intra-urban dengue forecasting at a fine spatial resolution still remains a challenging feat. As viruses spread rapidly because of a highly dynamic population flow, integrating spatial interactions of human movements between regions would be potentially beneficial for intra-urban dengue forecasting. METHODOLOGY: In this study, a new framework for enhancing intra-urban dengue forecasting was developed by integrating the spatial interactions between urban regions. First, a graph-embedding technique called Node2Vec was employed to learn the embeddings (in the form of an N-dimensional real-valued vector) of the regions from their population flow network. As strongly interacting regions would have more similar embeddings, the embeddings can serve as “interaction features.” Then, the interaction features were combined with those commonly used features (e.g., temperature, rainfall, and population) to enhance the supervised learning-based dengue forecasting models at a fine-grained intra-urban scale. RESULTS: The performance of forecasting models (i.e., SVM, LASSO, and ANN) integrated with and without interaction features was tested and compared on township-level dengue forecasting in Guangzhou, the most threatened sub-tropical city in China. Results showed that models using both common and interaction features can achieve better performance than that using common features alone. CONCLUSIONS: The proposed approach for incorporating spatial interactions of human movements using graph-embedding technique is effective, which can help enhance fine-grained intra-urban dengue forecasting.
Climate policies can bring local air quality and health co-benefits, which may partially or entirely offset the costs of implementing these policies. In this study, we introduce an integrated health co-benefits assessment model, the Regional Emissions-Air quality-Climate-Health (REACH) Modeling Framework, which is capable of evaluating the impact of policies on air pollution-related mortality and morbidity in the whole economic system overtime at the provincial level for China. We first provide a detailed description of the modeling framework and conduct a case study to estimate the health benefits of different climate policy scenarios. We show that a scenario consistent with the 2 degrees C target that peaks China’s emissions before 2025 could avoid around 190 thousand premature deaths in 2030. The health benefits could partially or fully cover the policy costs under different assumptions of the value of a statistical life (VSL). Our framework also illustrates that estimated costs and health benefits distribute unevenly across regions in China.
The flow of the Earth’s atmosphere not only largely determines its temperature status, but also profoundly affects aerosol concentrations. Therefore, exploring how to evaluate the synthetical effects of temperature and aerosol pollution on human health is an important topic. Regarding the atmosphere as a whole, we quantified the mortality burden attributable to short-term exposure to abnormal temperatures and PM2.5 in Beijing from the perspective of atmospheric flow. We first divided the atmospheric stability into three levels (including disturbed, normal, and stable conditions) according to the variations in meteorological conditions and PM2.5 concentrations across the stable weather index levels. We then applied a generalized additive model to separately evaluate the short-term effects of temperature and PM2.5 on mortality under each level of atmospheric stability. We further estimate the associated mortality burden using two indicators, namely attributable fraction and attributable number of deaths. Abnormal temperatures were responsible for most of the mortality burden. Cold temperatures accounted for a substantially higher mortality burden than hot temperatures. The synthetical mortality effects of temperature and PM2.5 varied for different atmospheric stabilities. A stable atmosphere poses the strongest synthetical effects of temperature and PM2.5, while a normal atmosphere provides comparatively beneficial conditions for human health. Our results indicated that the synthetical health impacts of temperature and PM2.5 driven by atmospheric flow need to be considered in the further promulgation of public health policies and air pollution abatement strategies, particularly in the context of climate change.
Narratives, human experiences, life histories and stories are powerful tools to understand a social phenomenon. Different kinds of pandemics and disasters create different types of stories and experiences. The human response to disasters seems to be generating or at least permitting an increase in property losses, especially in societies where economic growth is rapid and modern technology is spreading fast. Some hazards are created by persistent inhabitance of dangerous areas or by alteration of land or water, while others are exacerbated by efforts to reduce the risk. The disasters adversely affect societies but also give rise to heroic stories of survival and resilience. The North-Western Himalayan region is prone to several kinds of disasters like floods, earthquakes, landslides etc. One of the most disaster prone regions in North-Western Himalayas is Kashmir Valley. Kashmir Valley has witnessed several disastrous floods in the last century but the most disastrous flood in the recent history of the Union Territory is the September 2014 flood which affected all the aspects of life and resulted into death of 277 people. It also witnessed floods in 2015, 2017 and most recently in 2019 but they were not as devastating as the 2014 flood. The present study gives the ethnographic account of the recent floods in Kashmir Valley with special focus on 2014 flood. It gives account of the devastating loss and suffering of people due to the floods. The present ethnographic study goes deeper into understanding narratives of people, their experiences of the floods, account of several survival stories, the politics involved in relief and rescue, history of the people of Kashmir, the meaning behind the narratives and the meaning of belonging and communitarianism. It also provides insight into vulnerability of different classes of people to floods.
Ciguatera poisoning (CP) results from the consumption of seafood contaminated with ciguatoxins (CTXs). This disease is highly prevalent in French Polynesia with several well-identified hotspots. Rapa Island, the southernmost inhabited island in the country, was reportedly free of CP until 2007. This study describes the integrated approach used to investigate the etiology of a fatal mass-poisoning outbreak that occurred in Rapa in 2009. Symptoms reported in patients were evocative of ciguatera. Several Gambierdiscus field samples collected from benthic assemblages tested positive by the receptor binding assay (RBA). Additionally, the toxicity screening of ?250 fish by RBA indicated ?78% of fish could contain CTXs. The presence of CTXs in fish was confirmed by liquid chromatography tandem mass spectrometry (LC-MS/MS). The potential link between climate change and this range expansion of ciguatera to a subtropical locale of French Polynesia was also examined based on the analysis of temperature time-series data. Results are indicative of a global warming trend in Rapa area. A five-fold reduction in incidence rates was observed between 2009 and 2012, which was due in part to self-regulating behavior among individuals (avoidance of particular fish species and areas). Such observations underscore the prominent role played by community outreach in ciguatera risk management.
Hyperthermia stimulates endogenous carbohydrate metabolism during exercise; however, it is not known if exercise intensity impacts the metabolic effect of heat stress. In the first study of this two-part investigation, endurance-trained male cyclists performed incremental exercise assessments in 18 and 35 degrees C (60% rH). The stimulatory effect of heat stress on carbohydrate oxidation rates was greater at high vs. moderate vs. low relative intensity (P < 0.05). In agreement, no effects of heat stress on carbohydrate oxidation rates were observed during 60-min of subsequent low-intensity cycling. In study two, endurance-trained male cyclists performed 20-min of moderate-intensity (power at the first ventilatory threshold) and 5-min of high-intensity (power at the second ventilatory threshold) cycling in 18, 28, 34, and 40 degrees C (60% rH). At moderate-intensity, carbohydrate oxidation rates were significantly elevated by heat stress in 40 degrees C (P < 0.05), whereas at high-intensity carbohydrate oxidation rates were significantly elevated by heat stress in 34 and 40 degrees C (P < 0.05). This exercise intensity-mediated regulation of the effect of heat stress on carbohydrate oxidation may be partially attributable to observed plasma adrenaline responses. Our data suggest that under moderate environmental heat stress (34-35 degrees C, 60% rH), heat stress-induced changes in CHO oxidation rates are unlikely to occur unless the relative exercise intensity is high (81 +/- 8%(V)over dotO(2max)), whereas under more extreme environmental heat stress (40 degrees C, 60% rH), these changes occur at lower relative intensities (69 +/- 8%(V)over dotO(2max)). This provides indication of when heat stress-induced metabolic changes during exercise are likely to occur.
Leptospirosis outbreaks in various parts of the world have been linked to changes in the weather. Furthermore, the effects have been shown to occur at different lags of up to 10 months, affecting the performance of simulation models that predict leptospirosis occurrence. In Malaysia, the link between different weather parameters, at different time lags, has yet to be established despite an increasing number of cases in recent years. In this study, a combination of data mining and machine learning is used to analyze, capture, and predict the relation between leptospirosis occurrence and temperature, rainfall, and relative humidity using the Seremban district in Malaysia as a case study. First, the optimal time lags for rainfall were determined using graphical exploratory data analysis (EDA) while non-graphical EDA was used for temperature. Then, an artificial neural network (ANN) model is developed to classify the combination of selected features into disease occurrence and non-occurrence using back-propagation training, optimizing the number of hidden layers and hidden nodes. The success is measured using accuracy, sensitivity, and specificity of each model. EDA has shown that leptospirosis occurrence in Seremban is highly correlated with weekly average temperature at lag 16 weeks and weekly rainfall amount at lag 12-20 weeks. Using these selected features, the ANN model achieved the highest accuracy, sensitivity, and specificity at 84.00, 86.44, and 79.33%, respectively. Overall, the EDA approach has increased the accuracy of the predictive model by 13.30-31.26% from the baseline models.
BACKGROUND: Climate change may contribute to higher incidence and wider geographic spread of vector borne diseases (VBDs). Effective monitoring and surveillance of VBDs is of paramount importance for the prevention of and timely response to outbreaks. Although international regulations exist to support this, barriers and operational challenges within countries hamper efficient monitoring. As a first step to optimise VBD surveillance and monitoring, it is important to gain a deeper understanding of system characteristics and experiences in to date non-endemic regions at risk of becoming endemic in the future. Therefore, this study qualitatively analyses the nature and flexibility of VBD surveillance and response in Beijing. METHODS: In this qualitative study, eleven experts working in Beijing’s vector-borne diseases surveillance and response system were interviewed about vector-borne disease surveillance, early warning, response, and strengths and weaknesses of the current approach. RESULTS: Vector-borne disease surveillance occurs using passive syndromic surveillance and separate vector surveillance. Public health authorities use internet reporting networks to determine vector-borne disease risk across Beijing. Response toward a vector-borne disease outbreak is uncommon in this setting due to the currently low occurrence of outbreaks. CONCLUSIONS: A robust network of centralised institutions provides the continuity and flexibility needed to adapt and manage possible vector-borne disease threats. Opportunities exist for population-based health promotion and the integration of environment and climate monitoring in vector-borne disease surveillance.
Background: Determination of the key factors affecting dengue occurrence is of significant importance for the successful response to its outbreak. Yunnan and Guangdong Provinces in China are hotspots of dengue outbreak during recent years. However, few studies focused on the drive of multi-dimensional factors on dengue occurrence failing to consider the possible multicollinearity of the studied factors, which may bias the results. Methods: In this study, multiple linear regression analysis was utilized to explore the effect of multicollinearity among dengue occurrences and related natural and social factors. A principal component regression (PCR) analysis was utilized to determine the key dengue-driven factors in Guangzhou city of Guangdong Province and Xishuangbanna prefecture of Yunnan Province, respectively. Results: The effect of multicollinearity existed in both Guangzhou city and Xishuangbanna prefecture, respectively. PCR model revealed that the top three contributing factors to dengue occurrence in Guangzhou were Breteau Index (BI) (positive correlation), the number of imported dengue cases lagged by 1 month (positive correlation), and monthly average of maximum temperature lagged by 1 month (negative correlation). In contrast, the top three factors contributing to dengue occurrence in Xishuangbanna included monthly average of minimum temperature lagged by 1 month (positive correlation), monthly average of maximum temperature (positive correlation), monthly average of relative humidity (positive correlation), respectively. Conclusion: Meteorological factors presented stronger impacts on dengue occurrence in Xishuangbanna, Yunnan, while BI and the number of imported cases lagged by 1 month played important roles on dengue transmission in Guangzhou, Guangdong. Our findings could help to facilitate the formulation of tailored dengue response mechanism in representative areas of China in the future.
The WHO Housing and health guidelines recommend a minimum indoor temperature of 18°C to prevent cold-related diseases. In Japan, indoor temperatures appear lower than in Euro-American countries because of low insulation standards and use of partial intermittent heating. This study investigated the actual status of indoor temperatures in Japan and the common characteristics of residents who live in cold homes. We conducted a nationwide real-world survey on indoor temperature for 2 weeks in winter. Cross-sectional analyses involving 2190 houses showed that average living room, changing room, and bedroom temperatures were 16.8°C, 13.0°C, and 12.8°C, respectively. Comparison of average living room temperature between prefectures revealed a maximum difference of 6.7°C (Hokkaido: 19.8°C, Kagawa: 13.1°C). Compared to the high-income group, the odds ratio for living room temperature falling below 18°C was 1.38 (95% CI: 1.04-1.84) and 2.07 (95% CI: 1.28-3.33) for the middle- and low-income groups. The odds ratio was 1.96 (95% CI: 1.19-3.22) for single-person households, compared to households living with housemates. Furthermore, lower room temperature was correlated with local heating device use and a larger amount of clothes. These results will be useful in the development of prevention strategies for residents who live in cold homes.
When drought hits water-scarce regions, there are significant repercussions for food and water security, as well as serious issues for the stability of broader social and environmental systems. To mitigate these effects, environmental monitoring and early warning systems aimed at detecting the onset of drought conditions can facilitate timely and effective responses from government and private sector stakeholders. This study uses multistage, participatory research methods across more than 135 interviews, focus groups, and workshops to assess extant climatic, agricultural, hydrological, and drought monitoring systems; key cross-sector drought impacts; and drought monitoring needs in four countries in the Middle East and North Africa (MENA) region: Morocco, Tunisia, Lebanon, and Jordan. This extensive study of user needs for drought monitoring across the MENA region is informing and shaping the ongoing development of drought early warning systems, a composite drought indicator (CDI), and wider drought management systems in each country. Overarching themes of drought monitoring needs include technical definitions of drought for policy purposes; information-sharing regimes and data-sharing platforms; ground-truthing of remotely sensed and modeled data; improved data quality in observation networks; and two-way engagement with farmers, organizations, and end-users of drought monitoring products. This research establishes a basis for informing enhanced drought monitoring and management in the countries, and the broad stakeholder engagement can help foster the emergence of effective environmental monitoring coalitions.
An energy supply dominated by the use of fossil fuels causes both climate change and air pollution, which have negative impacts on human capital via both health and productivity. In addition, different people are affected differently because of factors such as age, gender and education level. To enhance the understanding of the benefits of low carbon transition from the labor supply perspective and help to identify strategies of collaborative control for CO2 and local air pollutants in China, an integrated assessment model linking the air quality module and the health impact module with a disaggregated labor sector computable general equilibrium (CGE) economic system is developed and applied in this study. Results show some key findings. First, renewable energy development and carbon capture and storage (CCS) technologies will contribute significantly to GDP in terms of their impact on air quality improvement by 0.99% and 0.54%, respectively, in 2050. Second, due to differences in labor composition, air pollution has, and will continue to have, the greatest impact on sectors with a higher proportion of male and lower-educated workers – such as the coal sector, and it will have the least impact on sectors with a higher proportion of female and higher-educated workers – such as the public administration sector. Third, the different impacts of sector output will increase economic inequality.
Children are worried about climate change. Environmental education aims to increase knowledge and pro-environmental behavior but typically gives little attention to meeting children’s emotional needs. This is particularly important as direct and indirect impacts of climate change, including the Australian bushfires in 2019-20, become more salient. This study explored caretaker perceptions of children’s climate change emotions, and the needs and challenges around supporting children, through an online survey of Australian parents and teachers (n = 141). Parents and teachers similarly reported that children experience anxiety and express interest in talking about climate change. They described challenges that inhibit their ability to talk to the children, whilst also identifying positive experiences of doing so. We conclude that parents and teachers would benefit from resources to help them support their children’s environmental learning in a way that fosters emotional wellbeing and promotes hopefulness. We suggest principles that acknowledge feelings, emphasize solutions, and encourage action.
The effectiveness of urban hydrological processes in mitigating the urban heat island (UHI) effect and human thermal stress in the megacity of Nanjing during an extreme heat wave event (6th-10th August 2013) was assessed using Weather Research and Forecasting Single-Layer Urban Canopy Models. The inclusion of urban hydrological processes improved model performance, with more reasonable diurnal cycles and smaller mean errors, root mean square errors, and normalized root mean square errors for meteorological variables. Through evaporative cooling, urban hydrological processes can greatly increase specific and relative humidity, while reducing near-surface and surface temperatures, wind speed, and planetary boundary layer (PBL) height, and the cooling and wetting effects could affect the entire PBL, especially in low-intensity residential areas. Urban hydrological processes can effectively mitigate both the near-surface and surface UHI effect. The city-wide mitigation effectiveness of near-surface UHI ranged between 0.9 degrees C and 1.1 degrees C throughout the day, while the city-wide mitigation effectiveness of surface UHI at noon reached similar to 5 degrees C. The maximum reduction of near-surface and surface UHI in low-intensity residential areas reached 1.3 degrees C and 10.0 degrees C, respectively. Changes in heat stress indices indicate that the cooling effect improves human thermal comfort at night, while the increased humidity outweighs the cooling effect and exacerbates human thermal discomfort during daytime. The city-wide thermal stress increased by up to 0.4 degrees C, 0.2 degrees C, and 0.5 degrees C during daytime and decreased by up to 0.4 degrees C, 0.3 degrees C, and 0.6 degrees C at night for wet-bulb globe temperature, apparent temperature, and humidity index, respectively.
OBJECTIVE: Diurnal temperature range (DTR) is an important meteorological indicator of global climate change; high values of DTR may induce stroke morbidity, while the related high-risk periods and sensitive populations are not clear. This study aims to evaluate the effects of DTR on first-ever strokes in different seasons and in relation to sensitive populations. METHODS: We collected data on 142?569 first-ever strokes during 2005-2016 in Shenzhen. We fitted a time-series Poisson model in our study, estimating the associations between DTR and first-ever strokes, with a distributed lag non-linear model. Then, we calculated strokes attributable to high DTR in different genders, age groups, education levels and stroke subtypes. RESULTS: High DTR had a significant association with first-ever strokes, and the risk of stroke increased with the rise of DTR in the summer and winter. In total, 3.65% (95% empirical CI (eCI) 1.81% to 5.53%) of first-ever strokes were attributable to high DTR (5.5°C and higher) in the summer, while 2.42% (95% eCI 0.05% to 4.42%) were attributable to high DTR (8°C and higher) in the winter. In the summer, attributable fraction (AF) was significant in both genders, middle-aged and old patients, patients with different levels of education, as well as patients with cerebral infarction (CBI); in the winter, AF was significant in middle-aged patients, patients with primary and lower education level, as well as patients with CBI. CONCLUSIONS: High DTR may trigger first-ever strokes in the summer and winter, and CBI is more sensitive than intracerebral haemorrhage to DTR. Most people are sensitive to high DTR in the summer, while middle-aged and low-education populations are sensitive in the winter. It is recommended that the DTR values be reported and emphasised in weather forecast services, together with the forecasts of heat and cold.
This study evaluated the association between flood-related variables and morbidity. Since Typhoon Morakot affected entire Taiwan, the Morakot flood data and the geographically-coded morbidity data were analyzed together to examine the effect of flood and flood-control engineering on morbidity. It was concluded that the Morakot flood was associated with increased eczema morbidity. River landscape construction was associated with a decrease in adult eczema morbidity cases after the Morakot flood. However, depressive disorder, anxiety disorder, pneumonia, septicemia, cellulitis and abscess, and atopic dermatitis were not associated with the Morakot flood and river landscape construction.
Solar radiation intensity affects both subjective reactions and physiological functions, especially for people who exercise heavily. Field experiments including a questionnaire survey at various ambient temperatures were performed; outdoor activities under shading (irradiance I = 50 +/- 20 W/m(2)) and non-shading (I = 700 +/- 50 W/m(2)) conditions during summer in Xi’an were recorded. The results of questionnaires indicated that when the human body reached an extremely hot state, the corresponding environmental temperature was 3.7 degrees C lower under the non-shading condition, and the range of actual acceptable temperatures was narrower. In terms of thermal sensation, there was a significant difference for people who exercise heavily and those who do not. The results also showed that the curve of fatigue sensation exhibited an inverse Gaussian distribution. Namely, fatigue was promoted under both colder and hotter conditions. Moreover, under non-shading condition, the lowest fatigue incidence was higher, and the corresponding ambient temperature was lower. Changes in objective physiological responses indicated that the solar radiation might cause heat stress. Therefore, when the ambient temperature was higher than 32 degrees C, physiological stress was higher. Under the same exercise load, the blood pressure was higher under the non-shading condition and systolic blood pressure increased with ambient temperature.
There has been growing concern over the effects of heat waves on health. However, the effects of heat waves on the health of individuals in vulnerable groups have rarely been examined. We aimed to investigate the acute health effects of heat waves in elderly individuals living in rural areas and to survey their adaptation capacity. Repeated measurements of body temperature (BT), blood pressure, sleep disturbance, and indoor temperature were conducted up to six times for each of 104 elderly individuals living in rural areas of South Korea during the 2018 heat wave. Changes in BT, systolic blood pressure (SBP), and diastolic blood pressure (DBP) according to variations in indoor and outdoor temperature were analyzed using linear mixed effect models controlling for age, sex, smoking, and drug use. We also surveyed heat wave adaptation capacity, heat wave shelters, and self-reported health problems. The average indoor temperature measured during the study period was 30.5°C (range: 22.9-38.3°C) and that of ambient temperature was 30.6°C (range: 24.6-36.3°C). BT significantly increased with indoor and outdoor temperatures. The effect on BT was greater in elderly women and the elderly with hypertension. DBP generally decreased with increasing indoor temperature, though the correlation was only statistically significant among the elderly with hypertension. Only 22 (21.2%) individuals used air conditioners during the heat wave. Most did not use an air conditioner mainly to avoid high electricity costs. Of the participants, 58.7% reported experiencing sleep disturbance, which was the most frequent self-reported health problem. Elderly individuals living in rural areas are directly exposed to high temperatures during heat waves, and their vital signs are sensitive to increases in indoor temperature due to poor adaptation capacity. Well-designed strategies for alleviating health-related stress during heat waves are necessary.
Dengue is a re-emerging global public health problem, the most common arbovirus causing human disease in the world, and a major cause of hospitalization in endemic countries causing significant economic burden. Data were analyzed from passive surveillance of hospital-attended dengue cases from 2002 to 2018 at Phramongkutklao Hospital (PMKH) located in Bangkok, Thailand, and Kamphaeng Phet Provincial Hospital (KPPH) located in the lower northern region of Thailand. At PMKH, serotype 1 proved to be the most common strain of the virus, whereas at KPPH, serotypes 1, 2, and 3 were the most common strains from 2006 to 2008, 2009 to 2012, and 2013 to 2015, respectively. The 11-17 years age-group made up the largest proportion of patients impacted by dengue illnesses during the study period at both sites. At KPPH, dengue virus (DENV)-3 was responsible for most cases of dengue fever (DF), whereas it was DENV-1 at PMKH. In cases where dengue hemorrhagic fever was the clinical diagnosis, DENV-2 was the predominant serotype at KPPH, whereas at PMKH, it was DENV-1. The overall disease prevalence remained consistent across the two study sites with DF being the predominant clinical diagnosis as the result of an acute secondary dengue infection, representing 40.7% of overall cases at KPPH and 56.8% at PMKH. The differences seen between these sites could be a result of climate change increasing the length of dengue season and shifts in migration patterns of these populations from rural to urban areas and vice versa.
While the associations of heat with health outcomes is well researched, there is less consensus on the measures used to define heat exposure and the short-term and delayed impacts of different temperature metrics on health outcomes. We investigate the nonlinear and short-term relationship of three temperature metrics and reported incidence of three gastrointestinal illnesses: salmonellosis, campylobacteriosis and cryptosporidiosis in the Australian Capital Territory (ACT). We also examine the nonlinear association of these illnesses with extreme heat (5th, 75th, 90th percentile of all heat measures). Generalized linear models with Poisson regression accounting for overdispersion, seasonal and long-term trend, weekly number of outbreaks and rainfall were developed for mean and maximum weekly temperature and the heat stress index (EHI(accl)). Bacterial illnesses (salmonellosis and campylobacteriosis) showed an overall positive association with extreme heat (75th and 90th percentile of all three heat measures) and an inverse association with low temperature (5th percentile). The shape of the exposure-response curve across a range of temperatures and the lagged effects varied for each disease. Modelling the short-term and delayed effects of heat using different metrics across a range of illnesses can help identify the most appropriate measure to inform local public health intervention planning for heat-related emergencies.
Because of fast-paced industrialization, urbanization, and population growth in Indonesia, there are serious health issues in the country resulting from air pollution. This study uses geospatial modelling technologies, namely land-use regression (LUR), geographically weighted regression (GWR), and geographic and temporal weighted regression (GTWR) models, to assess variations in particulate matter (PM(10)) and nitrogen dioxide (NO(2)) concentrations in Surabaya City, Indonesia. This is the first study to implement spatiotemporal variability of air pollution concentrations in Surabaya City, Indonesia. To develop the prediction models, air pollution data collected from seven monitoring stations from 2010 to 2018 were used as dependent variables, while land-use/land cover allocations within a 250 m to 5000 m circular buffer range surrounding the monitoring stations were collected as independent variables. A supervised stepwise variable selection procedure was applied to identify the important predictor variables for developing the LUR, GWR, and GTWR models. The developed models of LUR, GWR, and GTWR accounted for 49%, 50%, and 51% of PM(10) variations and 46%, 47%, and 48% of NO(2) variations, respectively. The GTWR model performed better (R(2) = 0.51 for PM(10) and 0.48 for NO(2)) than the other two models (R(2) = 0.49-0.50 for PM(10) and 0.46-0.47 for NO(2)), LUR and GWR. In the PM(10) model four predictor variables, public facility, industry and warehousing, paddy field, and normalized difference vegetation index (NDVI), were selected during the variable selection procedure. Meanwhile, paddy field, residential area, rainfall, and temperature played important roles in explaining NO(2) variations. Because of biomass burning issues in South Asia, the paddy field, which has a positive correlation with PM(10) and NO(2), was selected as a predictor. By using long-term monitoring data to establish prediction models, this model may better depict PM(10) and NO(2) concentration variations within areas across Asia.
It is speculated that floods in many areas of the world have become more severe with global warming. This study describes the 2017 spring floods in Kazakhstan, which, with about six people dead or missing, prompted the government to call for more than 7,000 people to leave their homes. Then, based on the Climatic Research Unit (CRU), the NCEP/NCAR Reanalysis 1, and the Coupled Model Intercomparison Project 5 (CMIP5) simulations, the seasonal trends of temperature were calculated using the linear least-squares regression and the Mann-Kendall trend test. The correlation between the surface air temperature and atmospheric circulation was explored, and the attributable risk of the 2017 spring floods was evaluated using the conventional fraction of the attributable risk (FAR) method. The results indicate that the north plains of Kazakhstan had a higher (March-April) mean temperature anomaly compared to the south plains, up to 3 degrees C, relative to the 1901 – 2017 average temperature. This was the primary cause of flooding in Kazakhstan. March and April were the months with a higher increasing trend in temperature from 1901 to 2017 compared with other months. In addition, a positive anomaly of the geopotential height and air temperature for the March-April 2017 period (based on the reference period 1961 – 1990) was the reason for a warmer abnormal temperature in the northwest region of Kazakhstan. Finally, the FAR value was approximately equal to 1, which supported the claim of a strong anthropogenic influence on the risk of the 2017 March-April floods in Kazakhstan. The results presented provide essential information for a comprehensive understanding of the 2017 spring floods in Kazakhstan and will help government officials identify flooding situations and mitigate damage in future.
Though a number of studies have shown positive relationships between flooding events and infectious diarrhea, there is a paucity of rigorous evidence regarding the net effect of flooding on diarrhea incidence, controlling for existing pre-trends and meteorological confounders. The study treats the 2016 catastrophic flood event in Anhui Province, China as a natural experiment using a difference-in-differences design with propensity score matching to exclude background variations of diarrhea occurrence and meteorological effects, thus isolating the net effect of flooding on diarrhea. A triple-differences analysis was further deployed to identify the potential effect modifiers, including gender, age, occupation and community health resources. By analyzing 359 580 cases of diarrhea that occurred before, during and after the flooding, we show that the 2016 flood event significantly increased the risk of dysentery (RR: 1.29, 95%CI: 1.15-1.46) in during-flood period, and also increased the risk of all-cause diarrhea (RR: 1.21, 95%CI: 1.17-1.26), typhoidal diarrhea, dysentery, and other infectious diarrhea in post-flood period. Children, males and non-farmers were particularly vulnerable to flooding impacts and the density of health professionals was found to be protective against diarrheal risk in both during-flood (RR: 0.81, 95% CI: 0.72-0.92) and post-flood (RR: 0.83, 95% CI: 0.77-0.88) periods. This study employs quasi-experimental design and provides a better understanding on both acute and sustained effects of flooding on diarrhea, which is important for accurate health impact assessments and developing targeted intervention strategies.
Aims: Leptospirosis is an infectious disease that is endemic to many tropical regions. Large epidemics usually happen after heavy rainfall and flooding. This potentially fatal zoonosis is caused by pathogenic bacteria belonging to the genus Leptospira. Leptospirosis can be diagnosed using specific biomarkers such as target genes and virulence indicators that are well preserved across various Leptospira spp., including those that are prevalent in clinical samples and in the environment. To date, several pathogenicity-determinant genes, including lipL32 and lipL41, have been described and used for diagnosing leptospirosis. However, prevalence of these genes in leptospiral strains is unclear. Methodology and results: In the present study, we assessed the distribution of eight pathogenicity-determinant genes in reference Leptospira strains and environmental isolates in Malaysia, by polymerase chain reaction (PCR). We found that only lipL32 and ligB were consistently expressed in all pathogenic Leptospira strains compared with the other tested genes. Moreover, our results suggested that the use of lipL41, lipL21, ompL1, lfb1, ligA, and ligC as biomarkers could incorrectly misdetect pathogenic Leptospira strains present in the environment. Conclusion: Thus, our results suggest that the pathogenicity-determinant genes lipL32 and ligB can be used as biomarkers for detection pathogenic Leptospira.
In 2017, marginalised groups were disproportionately impacted by extensive flooding in a rural community in Northern New South Wales, Australia, with greater risk of home inundation, displacement and poor mental health. While social capital has been linked with good health and wellbeing, there has been limited investigation into its potential benefits in post-disaster contexts, particularly for marginalised groups. Six months post-flood, a cross-sectional survey was conducted to quantify associations between flood impact, individual social capital and psychological distress (including probable post-traumatic stress disorder). We adopted a community-academic partnership approach and purposive recruitment to increase participation from socio-economically marginalised groups (Aboriginal people and people in financial hardship). These groups reported lower levels of social capital (informal social connectedness, feelings of belonging, trust and optimism) compared to general community participants. Despite this, informal social connectedness and belonging were important factors for all participant groups, associated with reduced risk of psychological distress. In this flood-prone, rural community, there is a pressing need to build social capital collectively through co-designed strategies that simultaneously address the social, cultural and economic needs of marginalised groups. Multiple benefits will ensue for the whole community: reduced inequities; strengthened resilience; improved preparedness and lessened risk of long-term distress from disaster events.
We investigated the geographical character of the COVID-19 infection in China and correlated it with satellite- and ground-based measurements of air quality. Controlling for population density, we found more viral infections in those prefectures (U.S. county equivalent) afflicted by high Carbon Monoxide, Formaldehyde, PM 2.5, and Nitrogen Dioxide values. Higher mortality was also correlated with relatively poor air quality. When summarizing the results at a greater administrative level, we found that the 10 provinces (U.S. state equivalent) with the highest rate of mortality by COVID-19, were often the most polluted but not the most densely populated. Air pollution appears to be a risk factor for the incidence of this disease, despite the conventionally apprehended influence of human mobility on disease dynamics from the site of first appearance, Wuhan. The raw correlations reported here should be interpreted in a broader context, accounting for the growing evidence reported by several other studies. These findings warn communities and policymakers on the implications of long-term air pollution exposure as an ecological, multi-scale public health issue.
Introduction: Overexposure to heat conditions can affect the functioning of the cardiovascular system and may promote cardiovascular disorders. Heat shock induced myocardial injury via increasing endoplasmic reticulum response-mediated apoptosis. This study investigated the impact of pretreatment with Rosa canina (RC), a natural antioxidant, on myocardial damage induced by heat stress exposure and underlying mechanisms in cardiomyocytes in rats. Methods: Sixty adult male Wistar rats were allocated into five groups, including Control: received normal saline (NS), Heat Stress (HS), and HS+RC groups. Animals in the HS groups were subjected to heat stress (43 degrees C) for 15 minutes once a day for two weeks. Animals in the HS+RC groups received three doses of RC (250, 500, and 1000 mg/mL) one hour before being subjected to heat shock. The endoplasmic reticulum (ER) transmembrane kinases, including PKR-like endoplasmic reticulum kinase (PERK), immunoreactivity of CCAAT/enhancer-binding protein homologous protein (CHOP), and eukaryotic translation initiation factor 2-alpha (eIF2 alpha) as well as caspase 8 were detected by Western blot. The levels of reactive oxygen species (ROS) were assessed. Moreover, histopathological changes and apoptosis were also assayed in the heart tissue by using histopathological and TUNEL assays. Results: Heat exposure increased the level of ROS and induced oxidative damage in the heart tissue. The results demonstrated that RC administration decreased the overproduction of ROS induced by heat stress in cardiomyocytes. Moreover, heat stress upregulated the expression of p-PERK, p-eIF2 alpha, and CHOP protein while pretreatment with RC decreased expression of ER stress-related markers in cardiomyocytes. Besides, RC diminished heat stress-induced cellular damage and apoptosis associated with inhibition of caspase 8 activation, a pro-apoptotic protein in cardiomyocytes. Conclusion: These findings indicate that RC exerts a protective effect on heart tissue, at least in part, through inactivation of PERK/eIF2 alpha/CHOP pathway or inhibition of ER stress and oxidative stresstriggered apoptosis in cardiomyocytes induced by heat stress.
BACKGROUND AND PURPOSE: Studies looking at seasonal variation on cerebral venous thrombosis (CVT) are few with conflicting conclusions. In this region-specific study, we looked for climatic influence and seasonal trends on the incidence of CVT. METHODS: Imaging proven adult CVT cases treated over a period of 18 years from a specific geographical location with similar seasons and climatic conditions were studied. Metrological parameters prepared using 30 years of data was used. Quantum geographical information system (QGIS software) and SPSS v 22 were used for patient plotting and analysis. RESULTS: Total of 970 cases were studied. The incidence was significantly higher in summer 411 (42.3%) compared with autumn 317 (32.7%) and winter 242 (25.05); P = 0.038. This trend was consistent across all the 18 years in time series analysis. Mean age was 33.5 years (range 18-88 years). A significant majority 673 (69.4%) were below 40 years of age; P = 0.012. Females constituted 394 (40.6%) of cases. Postpartum CVT cases constituted 237 (30%). Interaction analysis showed younger age (<40 years) were more vulnerable for CVT in summer; P = 0.009. There was no seasonal influence on postpartum CVT. Apart for a weak positive correlation between rain fall (r = 0.18, P < 0.01); humidity and cloud cover was not influencing the incidence. CONCLUSIONS: Higher ambient temperatures were consistently associated with higher incidence of CVT. This is the largest region-specific study on CVT in the world. These results may be applicable to other regions with similar climatic conditions.
Wet bulb globe temperature (WBGT), a combined measure of temperature and humidity effects on thermal comfort, is used to define heat stress waves (HSWs). While emerging research has raised concerns on future changes in heat stress, for the first time, this study examines spatiotemporal changes in multiple HSW characteristics (intensity, duration, frequency, and cumulative mean intensity) in the 21st century under three emissions scenarios. It is the sustained nature of HSWs that impose more adverse impacts than extreme heat on a single day. HSWs are expected to be more intense, persistent, frequent, and influential due to anthropogenic influence. Models project the largest increases in multiple HSW characteristics will occur over the tropics and subtropics. The exception is maximum intensity, which displays a relative uniform increase over most global land areas. Analysis of regional population exposure to HSWs under different climate and socioeconomic scenarios emphasizes the importance of aggressive mitigation to minimize the potential impacts of HSWs. We further investigate how different regional HSW characteristics are projected to change relative to increasing global mean surface temperature (GMST). Our results confirm the varying rates and different trajectories at which regional HSWs change, independent of forcing pathway, strongly related to GMST. On both globally aggregated and regional scales, the maximum intensity and GMST are highly linearly associated, with an approximately 1:1 increase. However, the other three HSW characteristics are projected to change at a nonlinear rate per degree of GMST increase in general and display large regional variation in the rates of their changes. Plain Language Summary Besides air temperature, air humidity is another important factor in determining the impact of heat waves on humans. High humidity will reduce the efficiency of evaporative cooling and, when combined with high temperature, could pose a serious threat to human health or even life safety. Heat stress indices, taking into account both temperature and humidity effects, are considered to be better indicators of environmental conditions conducive to heat stress on human health. We here employ a widely used heat stress index, wet bulb globe temperature, to define heat waves, namely, heat stress waves (HSWs). Heat waves can be considered through a number of characteristics, and it is their distinctive characteristics that result in the vast array of adverse impacts. This also applies to HSWs. Our results show that more intense, longer-lasting, frequent, and influential HSWs are anticipated during the 21st century, and anthropogenic warming substantially increases the occurrence of HSWs. Except intensity, tropical regions will generally witness the largest increases in multiple HSW characteristics and the number of people that may be exposed to HSWs. Changes in HSW characteristics are confirmed not to depend on whether a particular warming is reached sooner or later; they are strongly related to global mean surface temperature.
Oceanic and coastal ecosystems have undergone complex environmental changes in recent years, amid a context of climate change. These changes are also reflected in the dynamics of water-borne diseases as some of the causative agents of these illnesses are ubiquitous in the aquatic environment and their survival rates are impacted by changes in climatic conditions. Previous studies have established strong relationships between essential climate variables and the coastal distribution and seasonal dynamics of the bacteria Vibrio cholerae, pathogenic types of which are responsible for human cholera disease. In this study we provide a novel exploration of the potential of a machine learning approach to forecast environmental cholera risk in coastal India, home to more than 200 million inhabitants, utilising atmospheric, terrestrial and oceanic satellite-derived essential climate variables. A Random Forest classifier model is developed, trained and tested on a cholera outbreak dataset over the period 2010-2018 for districts along coastal India. The random forest classifier model has an Accuracy of 0.99, an F1 Score of 0.942 and a Sensitivity score of 0.895, meaning that 89.5% of outbreaks are correctly identified. Spatio-temporal patterns emerged in terms of the model’s performance based on seasons and coastal locations. Further analysis of the specific contribution of each Essential Climate Variable to the model outputs shows that chlorophyll-a concentration, sea surface salinity and land surface temperature are the strongest predictors of the cholera outbreaks in the dataset used. The study reveals promising potential of the use of random forest classifiers and remotely-sensed essential climate variables for the development of environmental cholera-risk applications. Further exploration of the present random forest model and associated essential climate variables is encouraged on cholera surveillance datasets in other coastal areas affected by the disease to determine the model’s transferability potential and applicative value for cholera forecasting systems.
If the alarming climate change and sea-level rise scenario occurs without coping solutions, it will greatly affect the socio-economic development and the environment of the the Mekong River Delta region. Recognizing this, the Government has soon developed both policies and action plans to adapt to climate change for the region. However, the policies and programs to cope with climate change are still inadequate and limited. In order to complete the climate change adaptation policies in the Mekong Delta in the current context, the Government and localities in the region need to implement more comprehensive and practical solutions for it.
Climate change is an incessant global phenomenon and has turned contentious in the present century. Malaysia, a developing Asian country, has also undergone significant vicissitudes in climate, which has been projected with significant deviations in forthcoming decades. As per the available studies, climate changes may impact on the fertility, either via direct effects on the gonadal functions and neuroendocrine regulations or via several indirect effects on health, socioeconomic status, demeaning the quality of food and water. Malaysia is already observing a declining trend in the Total fertility rate (TFR) over the past few decades and is currently recorded below the replacement level of 2.1 which is insufficient to replace the present population. Moreover, climate changes reportedly play a role in the emergence and cessation of various infectious diseases. Besides its immediate effects, the long-term effects on health and fertility await to be unveiled. Despite the huge magnitude of the repercussion of climate changes in Malaysia, research that can explain the exact cause of the present reduction in fertility parameters in Malaysia or any measures to preserve the national population is surprisingly very scarce. Thus, the present review aims to elucidate the possible missing links by which climate changes are impairing fertility status in Malaysia.
Snakebite envenoming is an important public health problem in Iran, despite its risk not being quantified. This study aims to use venomous snakes’ habitat suitability as an indicator of snakebite risk, to identify high-priority areas for snakebite management across the country. Thus, an ensemble approach using five distribution modelling methods: Generalized Boosted Models, Generalized Additive Models, Maximum Entropy Modelling, Generalized Linear Models, and Random Forest was applied to produce a spatial snakebite risk model for Iran. To achieve this, four venomous snakes’ habitat suitability (Macrovipera lebetinus, Echis carinatus, Pseudocerastes persicus and Naja oxiana) were modelled and then multiplied. These medically important snakes are responsible for the most snakebite incidents in Iran. Multiplying habitat suitability models of the four snakes showed that the northeast of Iran (west of Khorasan-e-Razavi province) has the highest snakebite risk in the country. In addition, villages that were at risk of envenoming from the four snakes were identified. Results revealed that 51,112 villages are at risk of envenoming from M. lebetinus, 30,339 from E. carinatus, 51,657 from P. persicus and 12,124 from N. oxiana. Precipitation seasonality was identified as the most important variable influencing distribution of the P. persicus, E. carinatus and M. lebetinus in Iran. Precipitation of the driest quarter was the most important predictor of suitable habitats of the N. oxiana. Since climatic variables play an important role in shaping the distribution of the four venomous snakes in Iran, thus their distribution may alter with changing climate. This paper demonstrates application of species distribution modelling in public health research and identified potential snakebite risk areas in Iran by using venomous snakes’ habitat suitability models as an indicating factor. Results of this study can be used in snakebite and human-snake conflict management in Iran. We recommend increasing public awareness of snakebite envenoming and education of local people in areas which identified with the highest snakebite risk.
Future heat stress under six future global warming (Delta T-GW) scenarios (IPCCRCP8.5) in an Asian megacity (Osaka) is estimated using a regional climate model with an urban canopy and air-conditioning (AC). An urban heat ‘stress’ island is projected in all six scenarios (Delta T-GW = +0.5 to +3.0 degrees C in 0.5 degrees C steps). Under. TGW = +3.0 degrees C conditions, people outdoors experience ‘extreme’ heat stress, which could result in dangerously high increases in human body core temperature. AC-induced feedback increases heat stress roughly linearly as Delta T-GW increases, reaching 0.6 degrees C(or 12% of the heat stress increase). As this increase is similar to current possible heat island mitigation techniques, this feedback needs to be considered in urban climate projections, especially where AC use is large.
Indigenous Solomon Islanders, like many living in Pacific Small Island Developing States (PSIDS), are currently experiencing the global syndemic-the combined threat of obesity, undernutrition, and climate change. This mixed-method study aimed to assess nutrition transitions and diet quality by comparing three geographically unique rural and urban indigenous Solomon Islands populations. Participants in rural areas sourced more energy from wild and cultivated foods; consumed a wider diversity of foods; were more likely to meet WHO recommendations of >400g of non-starchy fruits and vegetables daily; were more physically active; and had significantly lower body fat, waist circumference, and body mass index (BMI) when compared to urban populations. Urban populations were found to have a reduced ability to self-cultivate agri-food products or collect wild foods, and therefore consumed more ultra-processed foods (classified as NOVA 4) and takeout foods, and overall had less diverse diets compared to rural populations. Clear opportunities to leverage traditional knowledge and improve the cultivation and consumption of underutilized species can assist in building more sustainable and resilient food systems while ensuring that indigenous knowledge and cultural preferences are respected.
Recurrent floods are severely affecting the built assets and people of numerous Indian cities. Urban flood being a comparatively nascent area of research is often dealt with strategies apt for other disasters. The conventional approach of hazard zonation lacks vital information on human vulnerability. This paper addresses this lacuna by identifying vulnerable population and their precise cause of vulnerability for a case study of the city of Guwahati. It is the largest urban and financial centre of north-east India, a disaster hotspot and exclusive link connecting the region and the mainland. Guwahati’s 31 municipal wards were gradedparallel for flood hazard and human vulnerability in five categories each (very high to very low). Analytic Hierarchy Process based survey with 16 domain experts and Geographic Information System were used for hazard mapping using factors causing urban flood grouped under environment and urbanization. For vulnerability mapping, questionnaire survey, based on the Human Development Index and other published disaster vulnerability indices, was carried out with 1023 citizens. For 38.70% cases, wards descended by one category from hazard grouping to vulnerability grouping i.e. a ward prone to flooding may not be perceived as equally vulnerable. A strong correlation of 73.5% validated this fact. For obtaining a holistic picture, the top-down approach from experts was tallied with its bottom-up counterpart of citizen’s observation. The knowledge will help in making focused policies and prioritize funds for development planning, that are critical for cities of developing countries which lack resources to tackle the growing wrath of urban floods.
Background. Evacuation and sheltering are commonly used strategies for disaster risk reduction and climate change adaptation, but may negatively affect mental health of internally displaced persons (IDPs). Recently, Chinese governments have developed planned settlements providing integrated and intensive health services and environmental interventions to reduce immediate disastrous impacts and support the mental health of IDPs. Methods. Here we selected 69 planned shelters by stratified sampling to describe the implemented interventions conducted in Anhui Province of China after the 2016 severe floods, and we used standardized psychological scales to survey the intervention group (IDP who lived in these planned shelters) and the matched control group (victims living in their homes). Multivariable logistic regression was used to examine the association between social-demographic characteristics, flooding exposure, environmental conditions and the psychological diseases. Adjusted odds ratios (ORs) were calculated to compare their prevalence of psychological diseases, and to identify its influencing factors though comparing multiple interventions. Finally, the structural equation modeling was used to identify their influencing pathways. Results. Compared with the control group, the intervention group had a significantly lower risk of anxiety (OR = 0.36; 95% CI: 0.18-0.71), depression (OR = 0.36; 95% CI: 0.19-0.68) and post-traumatic stress disorder (OR = 0.29; 95% CI: 0.15-0.56). Environmental interventions providing clean water, safe food, environmental hygiene, risk communication and sufficient accommodation had a protective effect (standardized indirect effect = -0.153, p < 0.01) on the risk of psychological problems, mediating the negative effect caused by displacement and sheltering. Conclusions. How planned shelters were used to achieve better mental health outcomes in Anhui could inform other flood-prone areas to mitigate psychological vulnerability of IDPs.
This paper describes the development of a scenario-based approach that couples 2D hydrodynamic modeling with Geographic Information System (GIS) network analysis to assess the vulnerability of emergency services to surface water flooding at a large city scale. The method is demonstrated for Emergency Medical Service and Fire & Rescue Service in the city of Shanghai, China. Considering four representative traffic conditions, accessibility in terms of service area, response time, and population coverage within specified timeframes (8-, 12-, and 15-minute for Emergency Medical Service and 5-, 10-, and 15-minute for Fire & Rescue Service) is quantified and mapped under normal as well as pluvial flood scenarios of various magnitudes (5-, 20-, and 100-year return periods). Results show that the performance of operational responses largely depends on the functioning of transportation system, dramatically decreasing from unobstructed to congested traffic. Surface water flooding is found to result in limited (i.e. site-specific) but nonlinear impacts on the city-wide emergency service provisions. The results provide detailed information for optimizing the distribution of emergency stations and developing strategic contingency planning for vulnerable populations and facilities.
OBJECTIVES: We examine the public health response to an unprecedented multiple mortality event in bats following an extreme heat event. The main public health risk associated with the event and the environmental clean-up was potential human infection with Australian bat lyssavirus. We also consider the public health implications as we enter an age of climate change, vulnerability and unexpected events. Type of service: The Tropical Public Health Service of Far North Queensland worked collaboratively with the local council to coordinate a practical public health and health protection response to a mass mortality event in bats in late 2018. METHODS: A coordinated response was instigated to remove thousands of decaying bat corpses from residential areas. This occurred alongside a health education campaign advising the public to avoid handling bats. RESULTS: The combined efforts were successful; those requiring vaccination and post-exposure prophylaxis were treated appropriately and owing to a successful campaign, exposures were minimised. However, significant issues with misinformation and social media messaging were noted, alongside amateur bat carers handling sick and injured bats inappropriately, compounding the challenge for public health services. This mass mortality event has implications regarding the preparation for and management of other unexpected public health crises related to climate change. LESSONS LEARNT: It is vital that areas populated with bats be prepared for extreme heat events (EHEs). Public health units need to be prepared for the unexpected events of climate change, advocate for a ‘one health’ approach to public health, and work with local and national governments to become ‘climate ready’.
Measures to mitigate climate change are being considered all over the world. Reducing the use of air conditioners is one such measure. While it seems to be effective in mitigating climate change, it may also reduce individuals’ well-being and increase the risk of heatstroke. To compare the impact of reducing air conditioner use and the mortality risks, the indicator Loss of Happy Life Expectancy (LHpLE), which measures the reduction in the length of life that individuals can spend happily, was used. The reduction in well-being due to non-use of air conditioners was obtained by applying the propensity score matching method to the results of a questionnaire. We evaluated the impact of reducing air conditioner use in both the current and future situation in comparison to the mortality risk from flood and heatstroke, respectively. The increase in mortality risk due to flooding was estimated based on numerical simulation, and the increase in the risk of mortality due to heatstroke was estimated based on existing reports in Japan. Using these results, the magnitude of the impacts on LHpLE caused by the reduction in well-being due to the non-use of an air conditioner and the increase in the mortality risks were compared, both for the current situation and the future. The results show that LHpLE due to non-use of air conditioners was much greater than that due to the risk of mortality due to flood and heatstroke, and implied that reducing air conditioner use is not necessarily a good way as a mitigation measure. This result would be useful for creating and implementing measures to counter climate change and could also be applied in many other fields.
Coronaviruses are a family of viruses causing mild to severe upper respiratory tract syndrome. Recent pandemic threat caused by SARS-CoV-2 first appeared in Wuhan, China in December 2019. Whether the COVID-19 might be affected by warming global temperatures like some of previous pandemic flues. Therefore, the current study aims to analyze the effect of temperature and relative humidity (RH) on the spreading of the SARS-CoV-2 infection. The confirmed cases of COVID-19 in 31 different provinces in China and 274 provinces and/or countries were obtained from an online database. The real time temperature and humidity of the respective regions were taken from another online weather reporting data source. Spearman [R(s)] rank correlation was performed to identify the relationship between the variables (e.g., temperature, number of confirmed cases etc.). The overall spreading of SARS-CoV-2 in relations to temperature was inversely correlated. Among 29 of 31 provinces of China the overall correlation coeffient of the relationship between temperature and viral spread was negative [-R(s)] where in 15 provinces the correlation was at significant level (p<0.05). Furthermore, there was a significant negative relationship observed between the SARS-CoV-2 spreading and air temperature throughout the 274 provinces and/or countries of the world. However, there was no significant corelationship between humidity and COVID-19 spreading either in China or among countries and/or various regions of the world. The SARS-CoV-2 infection seems to be spread in a wide range of temperature throughout the world. Thus, several factors including temperature, may influnce the SARS-CoV-2 spreading. As a results, relatively elevated air temperature could not completely prevent viral spread but it might be one of the important detrimental factors for SARS-CoV-2 rapid spread.
With the ultrahigh-speed, large-scale development of tourism and the increasing frequency, intensity, and scope of extreme natural hazards in the context of climate warming, tourism has entered a high-risk era. Based on the central urban area within the outer ring of Shanghai as the research area and the tourism attraction as the research object, this paper takes the flood scenario simulation combined with GIS network analysis to evaluate the spatial accessibility of the emergency response of urban key public service departments (120) under current and future river flood scenarios in different return periods. The results of the study show that, (1) under the current and future flood scenarios, the submergence range is mainly distributed within 2 similar to 3 km along the banks of the Huangpu River, and it tends to increase from north to south; (2) there are 6, 9, and 21 tourism attractions in the emergency blind area under the once-in-a-century floods in 2010, 2030, and 2050 and 98, 105, and 112 tourism attractions in the emergency blind area under the once-in-a-millennium floods in 2010, 2030, and 2050, respectively; (3) in the flood scene, local road traffic in the inundation area is interrupted by water, and 120 first aid cannot get or be delayed to some tourist attraction (blind area); and (4) in 2030, under the normal and flooding scenarios, 120 first aid in the downtown area of Shanghai has the fastest route to tourism attractions according to the speed of S1, S2, S3, and S4. The flooding intensity (range and water depth), road traffic conditions (vehicle flow speed), and the number and location of key public service departments jointly determine the service scope and response time of medical emergency in urban floods. Since the flood control area of the central city in Shanghai is mainly distributed in the 2 similar to 3 km area on both banks of the Huangpu River, the impact of flood on the emergency medical service in the entire central city is limited, mainly in some hospitals in the riverside area, where 120 emergency vehicles are unable or delayed to reach some tourism attractions. The research indicates that the quantitative assessment method of spatial accessibility of the emergency response under flood scenario simulation has important scientific value and practical significance, which can provide decision-making basis for emergency management of tourism in China’s urban flood disaster.
With over one million cases worldwide annually and a high fatality in symptomatic forms, human leptospirosis is a growing public health concern for the most vulnerable populations, especially in the context of global warming and unplanned urbanization. Although the Asia-Pacific region is particularly affected, accurate epidemiological data are often lacking. We conducted an eleven-year retrospective laboratory-based epidemiological survey of human leptospirosis in New Caledonia. From 2006 to 2016, 904 cases were laboratory-confirmed, including 29 fatalities, corresponding to an average annual incidence of 30.6/100,000 and a case fatality rate of 3.2%. Over the period, there was a major shift from indirect serological diagnosis by MAT to direct diagnosis by real-time PCR, a more specific and sensitive test when performed early in the course of the disease. The systematic implementation of genotyping informed on the variety of the infective strains involved, with a predominance of serogroups Icterohaemorrhagiae and Pyrogenes. The epidemiological pattern showed a marked seasonality with an annual peak in March-April. Interestingly, the seasonal peak in children of school age was significantly earlier and corresponded to school holidays, suggesting that attending school from February on could protect children from environment-borne leptospirosis.
China’s gains in food production over the past four decades have been associated with substantial agricultural nitrogen losses, which contribute to air and water pollution, greenhouse gas emissions and damage to human health. Here, we explore the potential to improve agricultural production practices that simultaneously increase yields while addressing these environmental challenges. We link agronomic research with air quality modelling for an integrated assessment of four improved nitrogen management strategies: improved farm management practices with nitrogen use reductions; machine deep placement of fertilizer; enhanced-efficiency fertilizer use; and improved manure management. We find that simultaneous implementation of the four strategies provides the largest benefits, which include: reductions in PM2.5 concentrations and associated premature deaths; increases in grain yields and grain nitrogen use efficiency; reductions in NO3- leaching and runoff and greenhouse gas emissions. Total benefits of US$30 billion per year exceed the US$18 billion per year in costs. Our findings indicate that policies that improve farmers’ agricultural nitrogen management in China will improve both food security and public health while addressing multiple environmental challenges. Similar increases in attention on agricultural policy around the world are likely to provide large benefits in food security, environmental integrity and public health.
