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.
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.
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: 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.
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 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) 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.
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.
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.
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.
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.
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.
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: 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.
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: 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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: 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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).
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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: 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.
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.
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.
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.
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.
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.
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.
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.
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: 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.
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 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.
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.
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.
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.
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.
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.
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 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.
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?
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.
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.
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).
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.
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.
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.
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.
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.
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.
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: 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.
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.
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.
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.
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.
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.
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.
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.
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: 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.
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.
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.
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.
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.
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
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.
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: 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.
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
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.
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.
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: 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
