Climate change is creating an increase in temperatures, which is harming the quality of life of people all over the world, particularly those with minimal financial resources. While 30% of the world’s population is now vulnerable to extreme heat, estimates show that ratio will rise to 74% in the next 20 years, according to forecasts. Using the UrbClim climate model, this study examines the space-time variability of the heat stress index (HI) in different local climate zones (LCZs), as well as how heat wave conditions might affect this index based on land use and land cover. To that end, Seville, in Southern Spain, was investigated during the summer of 2017, when it had four heat waves. The following indices were considered for each urban sub-area: Normalized Difference Vegetation, Proportion Vegetation, Normalized Difference Built, and Urban Index. The goal is to conduct a statistical analysis of the link between the aforementioned elements and the heat stress index in order to recommend mitigation and resilience techniques. Our findings showed that compact and industrial LCZs (2, 3, and 10) are less resistant to HI than open and rural regions (5, 6, B, D, and G), which are more resistant to HI due to higher vegetation rates. The heat wave condition exacerbates the HI in all LCZs. As a result, initiatives such as enhancing open space, increasing green space, or using green roofs and façades might alleviate heat stress and improve people’s quality of life.
The warming of the global climate system is expected to result in significant socio-economic stress, primarily through the occurrence of extreme weather and climate events, with the potential for severe impacts on societies. This was evidenced by the vulnerability of European nations during the 2003 summer heatwave, which resulted in the death of tens of thousands of individuals due to heat-related complications. In this analysis, we examine the summer of 2022 in Spain, a Mediterranean country that is among the most impacted by the effects of climate change. A distinct pattern of the subtropical ridge in the 500 hPa geopotential height, which is typically linked to the occurrence of heatwaves in the Iberian Peninsula (IP), and the atmospheric blocking in the North Atlantic region facilitated the southerly flow of exceptionally warm air masses from Africa towards the IP, contributing to the sustained high temperatures throughout the summer season. Our results show that Spain experienced record -breaking temperatures in nearly half of the country that favored more frequent, intense, and longer-lasting heatwaves compared to previous historical records available from 1893. In general, despite normal rainfall conditions, the extremely high temperatures led to intense drought conditions in most areas. Finally, the pa-leoclimatic records suggest that the average summer temperature of 2022 was unprecedented within the last 700 years, and the driest within the last 279 in NE Spain. These findings highlight the need for measures to mitigate the effects of heat on at-risk populations, and to increase resilience and adaptation to climate change in the future.
BACKGROUND AND PURPOSE: Climate change is one of the most important threats to human health nowadays. The healthcare industry produces a significant part of greenhouse gases (GHG) emissions. The aim of this study is to assess direct and indirect GHG emissions due to cataract surgery in Spain to identify opportunities for improving. METHODS: This observational case series study estimates and analyses the carbon footprint of a single cataract surgery using phacoemulsification in Ávila Hospital. ISO standard 14064 was applied. RESULTS: The carbon footprint of a single cataract surgery in Ávila Hospital was 86.62kg CO(2)eq. Medical and pharmaceutical equipment were responsible for 85% of GHG emissions. CONCLUSIONS: Collaboration between pharmaceuticals and ophthalmologists is important to improve the environmental impact of cataract surgery. Future research is needed to introduce changes that do not compromise patient and surgeon safety. Green surgery models could play an encouraging role in the new global health scene.
Climate change is currently regarded as the greatest global threat to human health, and its health-related consequences take different forms according to age, sex, socioeconomic level, and type of territory. The aim of this study is to ascertain the differences in vulnerability and the heat-adaptation process through the minimum mortality temperature (MMT) among the Spanish population aged ≥65 years by territorial classification. A retrospective, longitudinal, ecological time-series study, using provincial data on daily mortality and maximum daily temperature across the period 1983-2018, was performed, differentiating between urban and nonurban populations. The MMTs in the study period were higher for the ≥65-year age group in urban provinces, with a mean value of 29.6 °C (95%CI 29.2-30.0) versus 28.1 °C (95%CI 27.7-28.5) in nonurban provinces. This difference was statistically significant (p < 0.05). In terms of adaptation levels, higher average values were obtained for nonurban areas, with values of 0.12 (95%CI -0.13-0.37), than for urban areas, with values of 0.09 (95%CI -0.27-0.45), though this difference was not statistically significant (p < 0.05). These findings may contribute to better planning by making it possible to implement more specific public health prevention plans. Lastly, they highlight the need to conduct studies on heat-adaptation processes, taking into account various differential factors, such as age and territory.
Although adaptation to continuously rising ambient temperatures is an emerging topic and has been widely studied at a global scale, detailed analysis of the joint indicators for long-term adaptation in Spain are scarce. This study aims to explore temporal variations of the minimum mortality temperature and mortality burden from heat and cold between 1979 and 2018. METHODS: We collected individual all-cause mortality and climate reanalysis data for 4 decades at a daily time step. To estimate the temperature-mortality association for each decade, we fitted a quasi-Poisson time-series regression model using a distributed lag non-linear model with 21 days of lag, controlling for trends and day of the week. We also calculated attributable mortality fractions by age and sex for heat and cold, defined as temperatures above and below the optimum temperature, which corresponds to the minimum mortality in each period. RESULTS: We analysed over 14 million deaths registered in Spain between 1979 and 2018. The optimum temperature estimated at a nationwide scale declined from 21 °C in 1979-1988 to 16 °C in 1999-2008, and raised to 18 °C in 2009-2018. The mortality burden from moderate cold showed a 3-fold reduction down to 2.4% in 2009-2018. Since 1988-1999, the mortality risk attributable to moderate (extreme) heat reduced from 0.9% (0.8%) to 0.6% (0.5%). The mortality risk due to heat in women was almost 2 times larger than in men, and did not decrease over time. CONCLUSION: Despite the progressively warmer temperatures in Spain, we observed a persistent flattening of the exposure-response curves, which marked an expansion of the uncertainty range of the optimal temperatures. Adaptation has been produced to some extent in a non-uniform manner with a substantial decrease in cold-related mortality, while for heat it became more apparent in the most recent decade only.
There is worldwide concern about how climate change -which involves rising temperatures- may increase the risk of contracting and developing diseases, reducing the quality of life. This study provides new research that takes into account parameters such as land surface temperature (LST), surface urban heat island (SUHI), urban hotspot (UHS), air pollution (SO(2), NO(2), CO, O(3) and aerosols), the normalized difference vegetation index (NDVI), the normalized difference building index (NDBI) and the proportion of vegetation (PV) that allows evaluating environmental quality and establishes mitigation measures in future urban developments that could improve the quality of life of a given population. With the help of Sentinel 3 and 5P satellite images, we studied these variables in the context of Granada (Spain) during the year 2021 to assess how they may affect the risk of developing diseases (stomach, colorectal, lung, prostate and bladder cancer, dementia, cerebrovascular disease, liver disease and suicide). The results, corroborated by the statistical analysis using the Data Panel technique, indicate that the variables LST, SUHI and daytime UHS, NO(2), SO(2) and NDBI have important positive correlations above 99% (p value: 0.000) with an excess risk of developing these diseases. Hence, the importance of this study for the formulation of healthy policies in cities and future research that minimizes the excess risk of diseases.
While some studies report a possible association between heat waves and kidney disease and kidney-related conditions, there still is no consistent scientific consensus on the matter or on the role played by other variables, such as air pollution and relative humidity. Ecological retrospective time series study 01-01-2013 to 31-12-2018). Dependent variables: daily emergency hospitalisations due to kidney disease (KD), acute kidney injury (AKI), lithiasis (L), dysnatraemia (DY) and hypovolaemia (HPV). Independent variables: maximum and minimum daily temperature (Tmax, Tmin, °C), and daily relative humidity (RH, %). Other variables were also calculated, such as the daily temperature for risk of kidney disease (Theat, °C) and low daily hazardous relative humidity (HRH%). As variables of air pollution, we used the daily mean concentrations of PM(10), PM(2.5), NO(2) and O(3) in μg/m3. Based on these, we then calculated their daily excesses over World Health Organisation (WHO) guideline levels ((h)PM(10), (h)PM(2.5), (h)NO(2) and (h)O(3) respectively). Poisson family generalised linear models (GLMs) (link = log) were used to calculate relative risks (RRs), and attributable risks and attributable admissions. In the models, we controlled for the covariates included: seasonalities, trend, autoregressive component, day of the week, month and year. A statistically significant association was found between Theat and all the dependent variables analysed. The greatest AKI disease burden was attributable to Theat (2.2 % (1.7, 2.6) of attributable hospital admissions), followed by (h)NO(2) (1.7 % (0.9, 3.4)) and HRH (0.8 (0.6, 1.1)). In the case of hypovolaemia and dysnatraemia, the greatest disease burden again corresponded to Theat, with 6.9 % (6.2, 7.6) and 5.7 (4.8, 6.6) of attributable hospital admissions respectively. Episodes of extreme heat exacerbate daily emergency hospital admissions due to kidney disease and kidney-related conditions; and attributable risks are likewise seen for low relative humidity and high ozone levels.
In a national sample of 5087 Spaniards, we examine the prevalence of 10 specific misperceptions over five separate science and health domains (climate change, 5G technology, genetically modified foods, vaccines, and homeopathy). We find that misperceptions about genetically modified foods and general health risks of 5G technology are particularly widespread. While we find that partisan affiliation is not strongly associated with any of the misperceptions aside from climate change, we find that two distinct dimensions of an anti-elite worldview-anti-expert and conspiratorial mindsets-are better overall predictors of having science and health misperceptions in the Spanish context. These findings help extend our understanding of polarization around science beyond the most common contexts (e.g. the United States) and support recent work suggesting anti-elite sentiments are among the most important predictors of factual misperceptions.
Global warming is precipitating an amplification of severe meteorological occurrences such as prolonged dry spells and episodes of elevated temperatures. These phenomena are instigating substantial elevations in environmental warmth, with metropolitan regions bearing the brunt of these impacts. Currently, extreme heat is already impacting 30% of the global populace, and forecasts suggest that this figure will escalate to 74% in the forthcoming years. One of the objectives outlined in the United Nations 2030 agenda, specifically within Sustainable Development Goal 11 (SDG11), is the attainment of sustainable urban development. To achieve this, it is imperative to scrutinize and delve into urban environmental conditions in order to understand their dynamics comprehensively. This understanding serves as the foundation for implementing mitigation and resilience strategies against climate change, ultimately enhancing the well-being of city residents. In this context, the field of remote sensing and geographic information systems has made substantial advancements. Notably, the UrbClim model, developed by the European Space Agency, facilitates the assessment of environmental conditions within numerous European urban centers. This research, utilizing data from UrbClim, examines the evolution of the heat stress index (Hi) during extreme heat conditions in Barcelona during the summer of 2017. Leveraging Landsat 8 satellite imagery, we derived the following variables: the normalized difference vegetation index and the normalized building difference index. Our findings reveal that during extreme heat conditions, the Hi index experiences an escalation, with areas characterized by a higher population density and industrial zones displaying lower resistance in contrast to regions with a lower population density and rural areas, which exhibit greater resilience to Hi. This disparity can be attributed to higher vegetation coverage and reduced building density in the latter areas. In this way, Hi increases more quickly and intensely and decreases more slowly when using high temperatures compared to average temperatures. This is of utmost importance for the future planning of new urban developments.
Nowadays, the measurement of heat stress indices is of principal importance due to the escalating impact of global warming. As temperatures continue to rise, the well-being and health of individuals are increasingly at risk, which can lead to a detrimental effect on human performance and behavior. Hence, monitoring and assessing heat stress indices have become necessary for ensuring the safety and comfort of individuals. Thermal comfort indices, such as wet-bulb globe temperature (WBGT), Tropical Summer Index (TSI), and Predicted Heat Strain (PHS), as well as parameters like mean radiant temperature (MRT), are typically used for assessing and controlling heat stress conditions in working and urban environments. Therefore, measurement and monitoring of these parameters should be obtained for any environment in which people are constantly exposed. Modern cities collect and publish this relevant information following the Smart City concept. To monitor large cities, cost-effective solutions must be developed. This work presents the results of a Heat Stress Monitoring (HSM) system prototype network tested in the Benicalap-Ciutat Fallera district in Valencia, Spain. The scope of this work is to design, commission, and test a low-cost prototype that is able to measure heat stress indices. The Heat Stress Monitoring system comprises a central unit or receiver and several transmitters communicating via radiofrequency. The transmitter accurately measures wind speed, air temperature, relative humidity, atmospheric pressure, solar irradiation, and black globe temperature. The receiver has a 4G modem that sends the data to an SQL database in the cloud. The devices were tested over one year, showing that radio data transmission is reliable up to 700 m from the receiver. The system’s power supply, composed of a Photovoltaic panel and Lithium-ion batteries, provided off-grid capabilities to the transmitter, with a tested backup autonomy of up to 36 days per charge. Then, indicators such as WBGT, TSI, and MRT were successfully estimated using the data collected by the devices. The material cost of a 12-point network is around EUR 2430 with a competitive price of EUR 190 per device.
West Nile virus (WNV) is a re-emerging zoonotic pathogen with increasing incidence in Europe, producing a recent outbreak in 2020 in Spain with 77 human cases and eight fatalities. However, the factors explaining the observed changes in the incidence of WNV in Europe are not completely understood. Longitudinal monitoring of WNV in wild animals across Europe is a useful approach to understand the eco-epidemiology of WNV in the wild and the risk of spillover into humans. However, such studies are very scarce up to now. Here, we analysed the occurrence of WNV and Usutu virus (USUV) antibodies in 2102 samples collected between 2005 and 2020 from a population of feral horses in Doñana National Park. The prevalence of WNV antibodies varied between years, with a mean seroprevalence of 8.1% (range 0%-25%) and seasonally. Climate conditions including mean minimum annual temperatures and mean rainy days per year were positively correlated with WNV seroprevalence, while the annual rainfall was negatively. We also detected the highest incidence of seroconversions in 2020 coinciding with the human outbreak in southern Spain. Usutu virus-specific antibodies were detected in the horse population since 2011. The WNV outbreak in humans was preceded by a long period of increasing circulation of WNV among horses with a very high exposure in the year of the outbreak. These results highlight the utility of One Health approaches to better understand the transmission dynamics of zoonotics pathogens.
Urban heat islands (UHIs) have become an especially relevant phenomenon as a consequence of global warming and the growing proportion of people living in cities. The health impacts that are sometimes attributed to the rise in temperature generated in an UHI are not always adequately justified. The objective is to analyse what effect UHIs have on maximum (Tmax) and minimum daily temperatures (Tmin) recorded in urban and non-urban observatories, and quantify the impact on morbidity and mortality during heat waves in Spain’s five cities. Data were collected on natural-cause daily mortality and unscheduled emergency hospital admissions (ICD-10: A00-R99) registered in these 5 cities across the period 2014-2018. We analysed daily Tmax and Tmin values at urban and non-urban observatories in these cities, and quantified the impact of Tmax and Tmin values during heat waves in each of these cities, using GLM models that included Tmax only, Tmin only, and both. We controlled for air pollution and other meteorological variables, as well as for seasonalities, trend and the autoregressive nature of the series. The UHI effect was observed in Tmin but not in Tmax, and proved to be greater in coastal cities than in inland and more densely populated cities. The UHI value in relation to the mean Tmin in the summer months ranged from 1.2 °C in Murcia to 4.1 °C in Valencia (difference between urban/non-urban observatories). The modelling process showed that, while a statistically significant association (p < 0.05) was observed in inland cities with Tmax for mortality and hospital admissions in heat waves, in coastal cities the association was obtained with Tmin, and the only impact in this case was the UHI effect on morbidity and mortality. No generalisations can be made about the impact of UHI on morbidity and mortality among the exposed population in cities. Studies on a local scale are called for, since it is local factors that determine whether the UHI effect will have a greater or lesser impact on health during heat-wave events.
BACKGROUND: Studies which analyse the joint effect of acoustic or chemical air pollution variables and different meteorological variables on neuroendocrine disease are practically nonexistent. This study therefore sought to analyse the impact of air pollutants and environmental meteorological variables on daily unscheduled admissions due to endocrine and metabolic diseases in the Madrid Region from January 01, 2013 to December 31, 2018. MATERIAL AND METHODS: We conducted a longitudinal, retrospective, ecological study of daily time series analysed by Poisson regression, with emergency neuroendocrine-disease admissions in the Madrid Region as the dependent variable. The independent variables were: mean daily concentrations of PM(10), PM(2.5), NO(2) and O(3); acoustic pollution; maximum and minimum daily temperatures; hours of sunlight; relative humidity; wind speed; and air pressure above sea level. Estimators of the statistically significant variables were used to calculate the relative risks (RRs). RESULTS: A statistically significant association was found between the increase in temperatures in heat waves, RR: 1.123 95% CI (1.001-1.018), and the number of emergency admissions, making it the main risk factor. An association between a decrease in sunlight and an increase in hospital admissions, RR: 1.005 95% CI (1.002 1.008), was likewise observed. Similarly, ozone, in the form of mean daily concentrations in excess of 44 μg/m(3), had an impact on admissions due to neuroendocrine disease, RR: 1.010 95% CI (1.007-1.035). The breakdown by sex showed that in the case of women, NO(2) was also a risk factor, RR: 1.021 95% CI (1.007-1.035). CONCLUSION: The results obtained in this study serve to identify risk factors for this disease, such as extreme temperatures in heat waves, O(3) or NO(2). The robust association found between the decrease in sunlight and increase in hospital admissions due to neuroendocrine disease serves to spotlight an environmental factor which has received scant attention in public health until now.
BACKGROUND: Heat stroke is a significant cause of mortality in response to high summer temperatures. There is limited evidence on the pattern and magnitude of the association between temperature and heat stroke mortality. We examined this association in Spain, using data from a 27-year follow-up period. METHODS: We used a space-time-stratified case-crossover design. We analyzed data using conditional quasi-Poisson regression with distributed lag nonlinear models. RESULTS: Spain recorded a total of 285 heat stroke deaths between 1990 and 2016. Heat stroke deaths occurred in 6% of the days in the summer months. The mean temperature was, on average, 5 °C higher on days when a heat stroke was recorded than on days without heat stroke deaths. The overall relative risk was 1.74 (95% confidence interval = 1.54, 1.96) for a 1 °C rise in mean temperature above the threshold of 16 °C, at which a heat stroke death was first recorded. We observed lagged effects as long as 10 days. CONCLUSIONS: Although heat stroke represents a small fraction of total heat-attributable mortality during the summer, it is strongly associated with high temperatures, providing an immediately visible warning of heat-related risk.
While climate change and population ageing are expected to increase the exposure and vulnerability to extreme heat events, there is emerging evidence suggesting that social inequalities would additionally magnify the projected health impacts. However, limited evidence exists on how social determinants modify heat-related cardiovascular morbidity. This study aims to explore the association between heat and the incidence of first acute cardiovascular event (CVE) in adults in Madrid between 2015 and 2018, and to assess how social context and other individual characteristics modify the estimated association. We performed a case-crossover study using the individual information collected from electronic medical records of 6514 adults aged 40-75 living in Madrid city that suffered a first CVE during summer (June-September) between 2015 and 2018. We applied conditional logistic regression with a distributed lag non-linear model to analyse the heat-CVE association. Estimates were expressed as Odds Ratio (OR) for extreme heat (at 97.5th percentile of daily maximum temperature distribution), compared to the minimum risk temperature. We performed stratified analyses by specific diagnosis, sex, age (40-64, 65-75), country of origin, area-level deprivation, and presence of comorbidities. Overall, the risk of suffering CVE increased by 15.3% (OR: 1.153 [95%CI 1.010-1.317]) during extreme heat. Males were particularly more affected (1.248, [1.059-1.471]), vs 1.039 [0.810-1.331] in females), and non-Spanish population (1.869 [1.28-2.728]), vs 1.084 [0.940-1.250] in Spanish). Similar estimates were found by age groups. We observed a dose-response pattern across deprivation levels, with larger risks in populations with higher deprivation (1.228 [1.031-1.462]) and almost null association in the lowest deprivation group (1.062 [0.836-1.349]). No clear patterns of larger vulnerability were found by presence of comorbidity. We found that heat unequally increased the risk of suffering CVE in adults in Madrid, affecting mainly males and deprived populations. Local measures should pay special attention to vulnerable populations.
The capacity for adaptation to climate change is limited, and the elderly rank high among the most exposed population groups. To date, few studies have addressed the issue of heat adaptation, and little is known about the long-term effects of exposure to heat. One indicator that allows the ascertainment of a population’s level of adaptation to heat is the minimum mortality temperature (MMT), which links temperature and daily mortality. The aim of this study was to ascertain, firstly, adaptation to heat among persons aged ≥ 65 years across the period 1983 to 2018 through analysis of the MMT; and secondly, the trend in such adaptation to heat over time with respect to the total population. A retrospective longitudinal ecological time series study was conducted, using data on daily mortality and maximum daily temperature across the study period. Over time, the MMT was highest among elderly people, with a value of 28.6 °C (95%CI 28.3-28.9) versus 28.2 °C (95%CI 27.83-28.51) for the total population, though this difference was not statistically significant. A total of 62% of Spanish provinces included populations of elderly people that had adapted to heat during the study period. In general, elderly persons’ level of adaptation registered an average value of 0.11 (°C/decade).
BACKGROUND: A number of studies have reported reductions in mortality risk due to heat and cold over time. However, questions remain about the drivers of these adaptation processes to ambient temperatures. We aimed to analyse the demographic and socioeconomic drivers of the downward trends in vulnerability to heat- and cold-related mortality observed in Spain during recent decades (1980-2018). METHODS: We collected data on all-cause mortality, temperature and relevant contextual indicators for 48 provinces in mainland Spain and the Balearic Islands between Jan 1, 1980, and Dec 31, 2018. Fourteen contextual indicators were analysed representing ageing, isolation, urbanicity, heating, air conditioning (AC), house antiquity and ownership, education, life expectancy, macroeconomics, socioeconomics, and health investment. The statistical analysis was separately performed for the range of months mostly causing heat- (June-September) and cold- (October-May) related mortality. We first applied a quasi-Poisson generalised linear regression in combination with distributed lag non-linear models (DLNM) to estimate province-specific temperature-mortality associations for different periods, and then we fitted univariable and multivariable multilevel spatiotemporal meta-regression models to evaluate the effect modification of the contextual characteristics on heat- and cold-related mortality risks over time. FINDINGS: The average annual mean temperature has risen at an average rate of 0·36 °C per decade in Spain over 1980-2012, although the increase in temperature has been more pronounced in summer (0·40 °C per decade in June-September) than during the rest of the year (0·33 °C per decade). This warming has been observed, however, in parallel with a progressive reduction in the mortality risk associated to both hot and cold temperatures. We found independent associations for AC with heat-related mortality, and heating with cold-related mortality. AC was responsible for about 28·6% (31·5%) of the decrease in deaths due to heat (extreme heat) between 1989 and 1993 and 2009-2013, and heating for about 38·3% (50·8%) of the reductions in deaths due to cold (extreme cold) temperatures. Ageing (ie, proportion of population over 64 years) attenuated the decrease in cold-related mortality. INTERPRETATION: AC and heating are effective societal adaptive measures to heat and cold temperatures. This evidence holds important implications for climate change health adaptation policies, and for the projections of climate change impacts on human health.
OBJECTIVE: Heat exposure and heat stress/strain is a concern for many workers. There is increasing interest in potential chronic health effects of occupational heat exposure, including cancer risk. We examined potential associations of occupational heat exposure and colorectal cancer (CRC) risk in a large Spanish multi-case–control study. METHODS: We analyzed data on 1198 histologically confirmed CRC cases and 2690 frequency-matched controls. The Spanish job-exposure matrix, MatEmEsp, was used to assign heat exposure estimates to the lifetime occupations of participants. Three exposure indices were assessed: ever versus never exposed, cumulative exposure and duration (years). We estimated odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression adjusting for potential confounders. RESULTS: Overall, there was no association of ever, compared with never, occupational heat exposure and CRC (OR 1.09, 95% CI 0.92-1.29). There were also no associations observed according to categories of cumulative exposure or duration, and there was no evidence for a trend. There was no clear association of ever occupational heat exposure and CRC in analysis conducted among either men or women when analyzed separately. Positive associations were observed among women in the highest categories of cumulative exposure (OR 1.81, 95% CI 1.09-3.03) and duration (OR 2.89, 95% CI 1.50-5.59) as well as some evidence for a trend (P<0.05). CONCLUSION: Overall, this study provides no clear evidence for an association between occupational heat exposure and CRC.
Sanitary issues, combined with the effects of climate change, emphasize the comfort of outdoor spaces in cities. Numerous comfort models exist and can predict thermal sensation. However, these comfort indices need to be validated in hot zones and quantify the neutral range considering people’s thermal resilience. The present study investigates the outdoor thermal comfort of people who live in hot areas and are accustomed to this and quantifies this effect. For that, predictions provided by the COMFA thermal comfort model were compared with the occupants’ perceptions given in the field campaigns’ questionnaires. The field campaigns were associated with on-site monitoring of local climate variables. It was observed that during the survey period, the entire space was predicted to be uncomfortable by the COMFA model. On the contrary, the results of the questionnaires showed that the most frequently encountered thermal sensations were distributed between the comfort zone and the hot zone. The proposed methodology has been designed to be used by other researchers, and it is adaptable to other outdoor thermal comforts such as PET or ITS. The comparison between the model’s predictions and the users’ responses to space highlighted the tendency of the COMFA to overestimate the thermal sensations. This work’s results allow extending the neutral comfort band from 50 W/m(2) (value of literature) to 80 W/m(2). So, the paper quantifies that the effect of the thermal resilience of the people increases the thermal band of comfort by around 60%. These results will allow an accurate assessment of the effectiveness of future mitigation solutions implemented to improve outdoor thermal comfort in other world areas. It is due to the propose of a higher neutrality range researchers or designers could achieve outdoor thermal comfort in effective and reliable ways, even in hot climates.
Over the last two decades there has been an increase in outbreaks of arboviral diseases, being Spain at high risk for disease emergence. This paper reviews the current evidence regarding the transmissibility, disease epidemiology, control strategies and mosquito-borne disease drivers and maintaining factors in Spain. There is risk of autochthonous cases and outbreaks in Spain due to recent transmission occurrence. Recently, there has been an expansion of Aedes Albopticus, a vector for Dengue, Zika and Chikungunya; and Cullex spp., vector for West Nile Virus, already endemic in Spain. Their establishment has been facilitated by climate and environmental drivers. If climate change projections are to be met, an increase in disease transmission is to be expected, as well as the re-establishment of other vectors such as Aedes Aegypti. Our review supports the need to understand the threat of these emerging diseases and implement preventive strategies in order to minimise their impact.
BACKGROUND: The objective was to analyze whether there are differences in vulnerability to Extreme Cold Days (ECD) between rural and urban populations in Spain. METHODOLOGY: Time series analysis carried out from January 1, 2000, through December 31, 2013. Municipalities with over 10,000 inhabitants were included from 10 Spanish provinces, classified into 42 groups by isoclimate and urban/rural character as defined by Eurostat criteria. The statistical strategy was carried out in two phases. First: It was analyzed the relationship between minimum daily temperature (Tmin) (source: AEMET) and the rate of daily winter mortality due to natural causes -CIE-10: A00 – R99- (source: National Statistics Institute). Then, It was determinated the threshold of Tmin that defines the ECD and its percentile in the series of winter Tmin (Pthreshold), which is a measure of vulnerability to ECD so that the higher the percentile, the higher the vulnerability. Second: possible explanatory variables of vulnerability were explored using Mixed Generalized Models, using 13 independent variables related to meteorology, environment, socioeconomics, demographics and housing quality. RESULTS: The average Pthreshold was 18 %. The final model indicated that for each percentage point increase in unemployment, the vulnerability to ECD increased by 0.4 (0.2, 0.6) points. Also, with each point increase in rurality index, this vulnerability decreased by -6.1 (-2.1, -10.0) points. Although less determinant, other factors that could contribute to explaining vulnerability at the province level included minimum winter daily temperatures and the percentage of housing with poor insulation. CONCLUSIONS: The vulnerability to ECD was greater in urban zones than in rural zones. Socioeconomic status is a key to understanding how this vulnerability is distributed. These results suggest the need to implement public health prevention plans to address ECD at the state level. These plans should be based on threshold temperatures determined at the smallest scale possible.
The data presented in this article is part in essence of a more extensive dataset aimed at evaluating patterns of change in the temperature-mortality relationship on population health in the city of Valencia, Spain on population health in the city of Valencia, Spain. The complete dataset was used in the framework of the European multi-city project PHASE (Public Health Adaptation Strategies to Extreme weather events) [1]. The data includes daily counts of all-cause mortality, excluding external causes and cardiovascular and respiratory diseases. All-cause mortality is also classified by gender and age groups. Besides temperature, we included other meteorological variables and air pollutants from the PHASE dataset, as well as influenza epidemics. The variable Saharan dust events was also added. All these data were collected from public Governmental data repositories accessible under request. The dataset of this article provides a basis for comparison with similar models for time-series regression, allowing researchers to integrate additional model components without duplication of effort.
OBJECTIVES: Recreational physical activity is an integral part of our society, and the injuries caused by sports activities are a concern for public health. We studied the effect of outdoor ambient temperature on hospital emergency department visits caused by sports injuries in Madrid, Spain, and accounted for its seasonal changes. METHODS: We used a time-series design. Data was analysed with quasi-Poisson regression models. We calculated the proportion of emergency visits attributable to seasonal changes before and after adjusting for daily ambient temperature. We modelled the association between emergency visits and temperature using distributed lag non-linear models. RESULTS: The proportion of emergency visits attributable to seasonal changes was 24.1% and decreased to 7.6% after adjusting for temperature. We found a high risk of emergency visits associated with cold and hot temperatures, whereas the risk was higher for heat. CONCLUSION: Sports and recreational physical activity injuries are not rare events; therefore, appropriate healthcare decisions should consider the impact of outdoor ambient temperature and seasonal changes.
Changes in the frequency and magnitude of extreme weather events represent one of the key indicators of climate change and variability. These events can have an important impact on mortality rates, especially in the ageing population. This study assessed the spatial and seasonal distributions of mortality rates in mainland Spain and their association with climatic conditions over the period 1979-2016. The analysis was done on a seasonal and annual basis using 79 climatic indices and regional natural deaths data. Results indicate large spatial variability of natural deaths, which is mostly related to how the share of the elderly in the population varied across the studied regions. Spatially, both the highest mortality rates and the largest percentage of elders were found in the northwest areas of the study domain, where an extreme climate prevails, with very cold winters and hot summers. A strong seasonality effect was observed, winter shows more than 10% of natural deaths compared to the rest of the seasons. Also, results suggest a strong relation between climatic indices and natural deaths, albeit with a high spatial and seasonal variability. Climatic indices and natural deaths show a stronger correlation in winter and summer than in spring and autumn.
Major floods in Spain in September 9-13, 2019 resulted in seven casualties and massive losses to agriculture, property and infrastructure. This paper investigates the utility of satellite data to: (1) characterize the event when input into a hydrological model, and to provide an accurate picture of the evolution of the floods; and (2) inform meteorologists in real time in order to complement model forecasts. It is shown that the precipitation estimates from the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO, available since 2014) and the merged satellite estimates provide an extraordinary improvement over previous technologies to monitor severe hydrometeorological episodes in near real time. In spite of known biases and errors, these new satellite precipitation estimates can be of broad practical interest to deal with emergencies and long-term readiness, especially for semi-arid areas potentially affected by ongoing global warming. Comparisons of satellite data of the September event with model outputs and more direct observations such as rain gauges and ground radars reinforce the idea that satellites are fundamental for an appropriate management of hydrometeorological events.
Featured Application This review contribute to understand the mechanisms underlying the observed rockfall activity during and after a wildfire, to advance in the solutions and methods to address the study of the problem, and to assess the hazard during and after wildfire, and its impact on not only transportation infrastructure and urban areas, but also the population. The results will help the decision makers and emergencies authorities to evaluate the exposure of elements at risk, to define actions to reduce their vulnerability and to identify measures to mitigate damages and social impact. Understanding processes and conditions that lead to rockfalls during and after a wildfire in different geological contexts is crucial since this phenomenon is one of the major hazards in mountainous regions across Europe. Spain is one of the European countries with the highest rate of wildfires, and rockfalls cause high economic and social impact, with many fatalities every year. The increase of rockfalls during and after wildfires is connected with the merging of different factors, not only in the detached area but also in the propagation and potentially affected area. When wildfire occurred, many actions take place: changes in the mechanical conditions of the rocks, the loss of protective capacity from vegetation, the effect induced by firefighting activities and/or the impact by the high temperatures in the adopted protective measures. After the wildfire, there is an increase in frequency and intensity of rockfalls in the burned area, causing a major impact of rockfalls on not only road networks and built-up areas but also people living. Additionally, the removal of vegetation by wildfires causes an increase in the risk perception, related not only to detached blocks but also to the general appearance of the rock mass. In this review, the main factors that influence the occurrence of rockfalls after a wildfire are analyzed, and three actual case studies in Spain are presented to support the variety of conclusions obtained.
INTRODUCTION: There is currently little knowledge and few published works on the subject of vulnerability to heat in rural environments at the country level. Therefore, the objective of this study was to determine whether rural areas are more vulnerable to extreme heat than urban areas in Spain. This study aimed to analyze whether a pattern of vulnerability depends on contextual, environmental, demographic, economic and housing variables. METHODS: An ecological, longitudinal and retrospective study was carried out based on time series data between January 01, 2000 and December 31, 2013 in 42 geographic areas in 10 provinces in Spain. We first analyzed the functional relationship between the mortality rate per million inhabitants and maximum daily temperature (Tmax). We then determined the summer temperature threshold (Pthreshold) (June-September) at which increases in mortality are produced that are attributable to heat. In a second phase, based on Pthreshold, a vulnerability variable was calculated, and its distribution was analyzed using mixed linear models from the Poisson family (link = log). In these models, the dependent variable was vulnerability, and the independent variables were exposure to high temperatures, aridity of the climate, deprivation index, percentage of people over age 65, rurality index, percentage of housing built prior to 1980 and condition of dwellings. RESULTS: Rurality was a protective factor, and vulnerability in urban areas was six times greater. In contrast, risk factors included aridity (RR = 5.89 (2.26 15.36)), living in cool summer zones (2.69 (1.23, 5.91)), poverty (4.05 (1.91 8.59)) and the percentage of dysfunctional housing (1.13 (1.04 1.24)). CONCLUSIONS: Rural areas are less vulnerable to extreme heat than the urban areas analyzed. Also, population groups with worse working conditions and higher percentages of dwellings in poor conditions are more vulnerable.
Background An area of current study concerns analysis of the possible adaptation of the population to heat, based on the temporal evolution of the minimum mortality temperature (MMT). It is important to know how is the evolution of the threshold temperatures (Tthreshold) due to these temperatures provide the basis for the activation of public health prevention plans against high temperatures. The objective of this study was to analyze the temporal evolution of threshold temperatures (Tthreshold) produced in different Spanish regions during the 1983-2018 period and to compare this evolution with the evolution of MMT. The dependent variable used was the raw rate of daily mortality due to natural causes ICD X: (A00-R99) for the considered period. The independent variable was maximum daily temperature (Tmax) during the summer months registered in the reference observatory of each region. Threshold values were determined using dispersion diagrams (annual) of the prewhitened series of mortality temperatures and Tmax. Later, linear fit models were carried out between the different values of Tthreshold throughout the study period, which permitted detecting the annual rate of change in Tthreshold. Results The results obtained show that, on average, Tthreshold has increased at a rate of 0.57 oC/decade in Spain, while Tmax temperatures in the summer have increased at a rate of 0.41 oC/decade, suggesting adaptation to heat. This rate of evolution presents important geographic heterogeneity. Also, the rate of evolution of Tthreshold was similar to what was detected for MMT. Conclusions The temporal evolution of the series of both temperature measures can be used as indicators of population adaptation to heat. The temporal evolution of Tthreshold has important geographic variation, probably related to sociodemographic and economic factors, that should be studied at the local level.
In Spain the average temperature has increased by 1.7 °C since pre-industrial times. There has been an increase in heat waves both in terms of frequency and intensity, with a clear impact in terms of population health. The effect of heat waves on daily mortality presents important territorial differences. Gender also affects these impacts, as a determinant that conditions social inequalities in health. There is evidence that women may be more susceptible to extreme heat than men, although there are relatively few studies that analyze differences in the vulnerability and adaptation to heat by sex. This could be related to physiological causes. On the other hand, one of the indicators used to measure vulnerability to heat in a population and its adaptation is the minimum mortality temperature (MMT) and its temporal evolution. The aim of this study was to analyze the values of MMT in men and women and its temporal evolution during the 1983-2018 period in Spain’s provinces. An ecological, longitudinal retrospective study was carried out of time series data, based on maximum daily temperature and daily mortality data corresponding to the study period. Using cubic and quadratic fits between daily mortality rates and the temperature, the minimum values of these functions were determined, which allowed for determining MMT values. Furthermore, we used an improved methodology that provided for the estimation of missing MMT values when polynomial fits were inexistent. This analysis was carried out for each year. Later, based on the annual values of MMT, a linear fit was carried out to determine the rate of evolution of MMT for men and for women at the province level. Average MMT for all of Spain’s provinces was 29.4 °C in the case of men and 28.7 °C in the case of women. The MMT for men was greater than that of women in 86 percent of the total provinces analyzed, which indicates greater vulnerability among women. In terms of the rate of variation in MMT during the period analyzed, that of men was 0.39 °C/decade, compared to 0.53 °C/decade for women, indicating greater adaptation to heat among women, compared to men. The differences found between men and women were statistically significant. At the province level, the results show great heterogeneity. Studies carried out at the local level are needed to provide knowledge about those factors that can explain these differences at the province level, and to allow for incorporating a gender perspective in the implementation of measures for adaptation to high temperatures.
BACKGROUND: In Spain, two synoptic-scale conditions influence heat wave formation. The first involves advection of warm and dry air masses carrying dust of Saharan origin (North African Dust (NAF) = 1). The second entails anticyclonic stagnation with high insolation and stability (NAF) = 0). Some studies show that the meteorological origin of these heat waves may affect their impact on morbidity and mortality. OBJECTIVE: To determine whether the impact of heat waves on health outcomes in Madrid (Spain) during 2013-2018 varied by synoptic-scale condition. METHODOLOGY: Outcome data consist of daily mortality and daily hospital emergency admissions (morbidity) for natural, circulatory, and respiratory causes. Predictors include daily maximum and minimum temperatures and daily mean concentrations of NO(2), PM(10), PM(2.5), NO(2), and O(3). Analyses adjust for insolation, relative humidity, and wind speed. Generalized linear models were performed with Poisson link between the variables controlling for trend, seasonality, and auto-regression in the series. Relative Risks (RR) and Attributable Risks (AR) were determined. The RRs for mortality attributable to high temperatures were similar regardless of NAF status. For hospital admissions, however, the RRs for hot days with NAF = 0 are higher than for days with NAF = 1. We also found that atmospheric pollutants worsen morbidity and mortality, especially PM(10) concentrations when NAF = 1 and O(3) concentrations when NAF = 0. RESULTS: The effect of heat waves on morbidity and mortality depends on the synoptic situation. The impact is greater under anticyclonic stagnation conditions than under Saharan dust advection. Further, the health impact of pollutants such as PM(10) and O(3) varies according to the synoptic situation. CONCLUSIONS: Based on these findings, we strongly recommend prevention plans to include data on the meteorological situation originating the heat wave, on a synoptic-scale, as well as comprehensive preventive measures against the compounding effect of high temperatures and pollution.
The European Union is currently immersed in policy development to address the effects of climate change around the world. Key plans and processes for facilitating adaptation to high temperatures and for reducing the adverse effects on health are among the most urgent measures. Therefore, it is necessary to understand those factors that influence adaptation. The aim of this study was to provide knowledge related to the social, climate and economic factors that are related to the evolution of minimum mortality temperatures (MMT) in Spain in the rural and urban contexts, during the 1983-2018 time period. For this purpose, local factors were studied regarding their relationship to levels of adaptation to heat. MMT is an indicator that allows for establishing a relationship to between mortality and temperature, and is a valid indicator to assess the capacity of adaptation to heat of a certain population. MMT is obtained through the maximum daily temperature and daily mortality of the study period. The evolution of MMT values for Spain was established in a previous paper. An ecological, longitudinal and retrospective study was carried out. Generalized linear models (GLM) were performed to identify the variables that appeared to be related to adaptation. The adaptation was calculated as the difference in variation in MMT based on the average increase in maximum daily temperatures. In terms of adaptation to heat, urban populations have adapted more than non-urban populations. Seventy-nine percent (n = 11) of urban provinces have adapted to heat, compared to twenty-one percent (n = 3) of rural provinces that have not adapted. In terms of urban zones, income level and habituation to heat (values over the 95th percentile) were variables shown to be related to adaptation. In contrast, among non-urban provinces, a greater number of housing rehabilitation licenses and a greater number of health professionals were variables associated with higher increases in MMT, and therefore, with adaptation. These results highlight the need to carry out studies that allow for identifying the local factors that are most relevant and influential in population adaptation. More studies carried out at a small scale are needed.
The objective of this study was to analyze at the level of Spain’s 52 provinces province level the temporal evolution of minimum mortality temperatures (MMT) from 1983 to 2018, in order to determine whether the increase in MMT would be sufficient to compensate for the increase in environmental temperatures in Spain for the period. It also aimed to analyze whether the rate of evolution of MMT would be sufficient, were it to remain constant, to compensate for the predicted increase in temperatures in an unfavorable (RCP 8.5) emissions scenario for the time horizon 2051-2100. The independent variable was made up of maximum daily temperature data (Tmax) for the summer months in the reference observatories of each province for the 1983-2018 period. The dependent variable was daily mortality rate due to natural causes (ICD 10: A00-R99). For each year and province, MMT was determined using a quadratic or cubic fit (p < 0.05). Based on the annual MMT values, a linear fit was carried out that allowed for determining the time evolution of MMT. These values were compared with the evolution of Tmax registered in each observatory during the 1983-2018 analyzed period and with the predicted values of Tmax obtained for an RCP8.5 scenario for the period 2051-2100. The rate of global variance in Tmax in the summer months in Spain during the 1983-2018 period was 0.41 °C/decade, while MMT across the whole country increased at a rate of 0.64 °C/decade. Variations in the provinces were heterogeneous. For the 2051-2100 time horizon, there was predicted increase in Tmax values of 0.66 °C/decade, with marked geographical differences. Although at the global level it is possible to speak of adaptation, the heterogeneities among the provinces suggest that the local level measures are needed in order to facilitate adaptation in those areas where it is not occurring.
BACKGROUND: The increased risk of mortality during periods of high and low temperatures has been well established. However, most of the studies used daily counts of deaths or hospitalisations as health outcomes, although they are the ones at the top of the health impact pyramid reflecting only a limited proportion of patients with the most severe cases. OBJECTIVES: This study evaluates the relationship between short-term exposure to the daily mean temperature and medication prescribed for the respiratory system in five Spanish cities. METHODS: We fitted time series regression models to cause-specific medical prescriptions, including different respiratory subgroups and age groups. We included a distributed lag non-linear model with lags up to 14 days for daily mean temperature. City-specific associations were summarised as overall-cumulative exposure-response curves. RESULTS: We found a positive association between cause-specific medical prescriptions and daily mean temperature with a non-linear inverted J- or V-shaped relationship in most cities. Between 0.3% and 0.6% of all respiratory prescriptions were attributed to cold for Madrid, Zaragoza and Pamplona, while in cities with only cold effects the attributable fractions were estimated as 19.2% for Murcia and 13.5% for Santander. Heat effects in Madrid, Zaragoza and Pamplona showed higher fractions between 8.7% and 17.2%. The estimated costs are in general higher for heat effects, showing annual values ranging between €191,905 and €311,076 for heat per 100,000 persons. CONCLUSIONS: This study provides novel evidence of the effects of the thermal environment on the prescription of medication for respiratory disorders in Spain, showing that low and high temperatures lead to an increase in the number of such prescriptions. The consumption of medication can reflect exposure to the environment with a lesser degree of severity in terms of morbidity.
Extreme temperatures are a threat to public health, increasing mortality in the affected population. Moreover, there is substantial research showing how age and gender shape vulnerabilities to this environmental risk. However, there is only limited knowledge on how socioeconomic status (SES), operationalized using educational attainment, stratifies the effect of extreme temperatures on mortality. Here, we address this link using Poisson regression and administrative data from 2012 to 2018 for 50 Spanish Provinces on individuals aged above 65 matched with meteorological data provided by the E-OBS dataset. In line with previous studies, results show that hot and cold days increase mortality. Results on the interaction between SES and extreme temperatures show a positive and significant effect of exposure to heat and cold for individuals with medium and low SES level. Conversely, for high SES individuals we do not find evidence of a robust association with heat or cold. We further investigate how the local climate moderates these associations. A warmer climate increases risks with exposures to low temperatures and vice versa for hot temperatures in the pooled sample. Moreover, we observe that results are mostly driven by low SES individuals being particularly vulnerable to heat in colder climates and cold in warmer climates. In conclusion, results highlight how educational attainment stratifies the effect of extreme temperatures and the relevance of the local climate in shaping risks of low SES individuals aged above 65.
BACKGROUND: Evidence from the scientific literature shows a significant variation in greenhouse gas (GHG) emissions from the diet, according to the type of food consumed. We aim to analyze the relationship between the daily dietary GHG emissions according to red meat, fruit and vegetables consumption and their relationship with risk of total mortality, and incident risk of chronic diseases. METHODS: We examined data on the EPIC-Spain prospective study, with a sample of 40 621 participants. Dietary GHG emission values were calculated for 57 food items of the EPIC study using mean emission data from a systematic review of 369 published studies. RESULTS: Dietary GHG emissions (kgCO2eq/day), per 2000 kcal, were 4.7 times higher in those with high red-meat consumption (>140 g/day) than those with low consumption (<70 g/day). The average dietary GHG emissions were similar in males and females, but it was significantly higher in youngest people and in those individuals with lower educational level, as well as for northern EPIC centers of Spain. We found a significant association with the risk of mortality comparing the third vs. the first tertile of dietary GHG emissions [hazard ratio (HR) 1.095; 95% confidence interval (CI) 1.007-1.19; trend test 0.037]. Risk of coronary heart disease (HR 1.26; 95% CI 1.08-1.48; trend test 0.003) and risk of type 2 diabetes (HR 1.24; 95% CI 1.11-1.38; trend test 0.002) showed significant association as well. CONCLUSIONS: Decreasing red-meat consumption would lead to reduce GHG emissions from diet and would reduce risk of mortality, coronary heart disease and type 2 diabetes.
Los productos suministrados son: concentraciones en superficie con salidas gráficas horarias de las concentraciones en superficie de NO2, NO, O3, SO2, CO, PM10 y PM2.5 expresadas en µg/m3; índice previsto diario de calidad del aire
calculado a partir de valores de concentración, utilizando la información procedente de las directivas vigentes relacionadas con los distintos contaminantes atmosféricos, e Índice previsto horario de calidad del aire con un horizonte temporal de 48 horas
El Plan Nacional de Predicción y Vigilancia de Fenómenos Meteorológicos Adversos (Meteoalerta) pretende facilitar la mejor y más actualizada información posible sobre los fenómenos atmosféricos adversos que se prevean, con un adelanto de hasta 72 horas. En ese sentido, uno de los avisos corresponde a tormentas, con cuatro niveles básicos (de menor a mayor riesgo): verde (sin riesgo), amarillo (tormentas fuertes), naranja (tormentas muy fuertes) y rojo (tormentas muy fuertes que por sus características excepcionales pueden tener un alto impacto).
Aerosol atmosférico es un término general utilizado para describir partículas sólidas secas suspendidas en la atmósfera que pueden presentar tamaños desde submicrométricos hasta varias decenas de micras. Los aerosoles pueden viajar miles de kilómetros y tener graves impactos en la salud pública mundial además de degradar la calidad del aire y ocasionar efectos negativos sobre el medio ambiente y algunas actividades económicas. La proximidad de Canarias al continente africano convierte a las islas en un área de elevado interés por la frecuencia de las intrusiones de polvo mineral desértico y el impacto que produce en la población; por tanto, es de suma relevancia la caracterización de las intrusiones de polvo desértico que afectan al archipiélago canario.
En el capítulo 1 de esta nota técnica se exponen generalidades y conceptos básicos del polvo mineral atmosférico. En el capítulo 2 se desarrolla la metodología utilizada y se describen la red de observación y las series históricas de PM10. En el capítulo 3 se presentan los resultados de la caracterización de las intrusiones de polvo desértico en Canarias que incluyen datos relevantes sobre la duración de los eventos, el efecto de las intrusiones en la calidad del aire y la caracterización de los valores PM10 de fondo. En el capítulo 4 se exponen varios casos de estudio que muestran distintos tipos de eventos de intrusión de polvo en Canarias. El capítulo 5 recoge las conclusiones principales de este trabajo. El capítulo 6 incluye una guía básica que pretende servir de ayuda a la hora de afrontar un posible evento de intrusión de polvo desértico.
Esta publicación resume los resultados obtenidos en casi cinco años del proyecto de “Impacto de las intrusiones atmosféricas africanas en la calidad del aire en Canarias y de la Península Ibérica” (2004-2009), entre los que cabe destacar una caracterización completa de los pólenes y esporas de hongos muestreados en el aire de Santa Cruz de Tenerife, la elaboración de predicciones semanales de pólenes y esporas de hongos, así como la obtención de un calendario polínico de utilidad para aquellos profesionales de la medicina que trabajan en alergias y afecciones respiratorias, y para los ciudadanos de Santa Cruz de Tenerife y visitantes que sean alérgicos al polen.
Esta nota técnica es el resultado de un trabajo interdisciplinar en el que han intervenido meteorólogos, biólogos y médicos, con el objetivo final de mejorar la calidad de vida de las personas aquejadas por problemas de alergia. Con el fin de avanzar en el conocimiento de todos los aspectos ligados a la emisión de polen de plátano en primavera, poder así mejorar el actual sistema de vigilancia de dicho polen y optimizar los recursos del sistema sanitario, han colaborado AEMET, que ha aportado su banco de datos de variables meteorológicas para diferentes horas y distintos emplazamientos, y la Consejería de Salud de la Comunidad de Madrid, que ha proporcionado los recuentos de polen diarios de su red Palinocam. El objetivo de esta colaboración ha sido avanzar en el conocimiento de todos los aspectos ligados a la emisión del polen del plátano para poder predecir con antelación suficiente su aparición en la primavera.
El Plan Nacional de Predicción y Vigilancia de Fenómenos Meteorológicos Adversos (Meteoalerta) pretende facilitar la mejor y más actualizada información posible sobre los fenómenos atmosféricos adversos que se prevean, con un adelanto de hasta 72 horas. En ese sentido, uno de los avisos se corresponde con temperaturas mínimas y máximas extremas, con cuatro niveles básicos (de menor a mayor riesgo en modo semafórico) a partir del posible alcance de determinados umbrales: verde, amarillo, naranja y rojo. Estos umbrales se han establecido con criterios climatológicos cercanos al concepto de “poco o muy poco frecuente” y de adversidad, en función de la amenaza que puedan suponer para la población.
El nivel de riesgo meteorológico diario de incendios forestales está basado en el sistema canadiense y se calcula a partir de los datos de las estaciones meteorológicas de AEMET y de las salidas de un modelo numérico de predicción del tiempo. Las variables de entrada del modelo de estimación de riesgo son: la temperatura del aire seco T (ºC), la humedad relativa del aire Hr (%), la velocidad del viento Vv (km/h) y la precipitación registrada en las últimas 24 horas Pp (mm). Los datos del análisis y pronóstico se refieren a las 12 UTC con el fin de obtener el valor de máximo riesgo diario, lo que sucede en torno al mediodía, si bien su valor tiene validez desde varias horas antes hasta varias horas después de las 12 UTC.
En la AEMET los datos que intervienen en el cálculo de los niveles de riesgo proceden de su red de estaciones sinópticas y automáticas y del modelo CEPPM (resolución espacial de 0.05º y ventana de trabajo de 47.367 puntos de rejilla). Cada punto de rejilla se sitúa en el centro de un cuadrado o píxel de 5 km de lado, por tanto, las variables de cálculo son representativas de un área de 25 km2 o 2500 ha.
El riesgo de incendio se estratifica en cinco clases o niveles de riesgo (bajo, moderado, alto, muy alto y extremo) que serán indicadores de la probabilidad de ocurrencia del fuego así como de la extensión e intensidad del mismo.
El sistema de monitorización de sequías meteorológicas está diseñado para el seguimiento, alerta temprana y evaluación de la sequía meteorológica, para lo que utiliza en tiempo real la información climática y satelital disponible que muestra el desarrollo de las condiciones de sequía meteorológica y la posible evolución de la misma. El sistema incorpora el desarrollo de productos tecnológicos operativos con implicaciones directas para la gestión de los recursos hídricos, las áreas naturales y para la gestión del riesgo de sequía meteorológica en sectores económicos afectados.
El sistema de predicción de radiación ultravioleta de la AEMET pronostica valores del índice UV hasta 5 días utilizando los valores de ozono previstos por el modelo dinámico global del Centro Europeo de Predicción a Plazo Medio, para las capitales de provincia, ciudades autónomas e islas. Estos valores de ozono, junto con otras variables, constituyen la entrada al modelo de Transferencia Radiativa Radtran, que ejecutado diariamente en los ordenadores de la AEMET, proporciona los datos de irradiancia solar en las longitudes de onda del UV, necesarios para calcular el UVI previsto en condiciones de cielo despejado. En un futuro próximo se espera poder proporcionar UVI previsto en condiciones de cielo despejado y nuboso.
Leishmaniasis is a vector-borne disease transmitted by sand flies. A dozen species have been involved in the transmission of Leishmania infantum in the Mediterranean region. Climate change may alter sand fly distribution at particular altitudes and latitudes. The objective of this study was to interrogate the existence of stable populations of sand flies in high-altitude ecosystems and evaluate if these populations are enough to support autochthonous transmission of leishmaniasis. These altitudinal conditions can be found in Sierra Nevada (southern Spain). Therefore, we have determined the sand fly population dynamics in different biotopes located at elevations above 1,300 m a.s.l. and searched for evidence of leishmaniasis transmission. Five collecting sites above 1,300 m a.s.l. containing large livestock concentrations were selected. Sand flies were caught using CDC light traps from May to November, annually from 2008 to 2013, and these were morphologically identified. Association between sand fly density or presence and temperature/humidity was estimated by linear and logistic regression, respectively. Leishmania infantum detection in female sand flies was performed by PCR. Diagnosis of canine leishmaniasis (CanL) was carried out by indirect immunofluorescence and PCR. A total of 2,973 specimens of 5 sand fly species were collected from June to October. Phlebotomus perniciosus was the most frequent (100%), abundant (80.1%) and densest species (9.8 sand flies/trap). The minimum temperature on the day of capture was the most important variable factor for sand fly presence and P. perniciosus density. An increase in altitude showed a negative effect over the sand fly diversity and activity period, driving changes in seasonal dynamics similar to those reported by latitudinal changes. CanL prevalence was 23%, a similar rate to previous surveys carried out on randomly selected dogs from towns in southern Spain. A successful host-vector-pathogen network was found at this altitude characterised by 9.9% L. infantum infection rate in non-blood fed P. perniciosus and Phlebotomus ariasi females and high CanL prevalence that entails an increase in the leishmaniasis risk area driven by sand fly colonization.
BACKGROUND: Mechanisms linking occupational heat exposure with chronic diseases have been proposed. However, evidence on occupational heat exposure and cancer risk is limited. METHODS: We evaluated occupational heat exposure and female breast cancer risk in a large Spanish case-control study. We enrolled 1,738 breast cancer cases and 1,910 frequency-matched population controls. A Spanish job-exposure matrix, MatEmEsp, was used to assign estimates of the proportion of workers exposed (P ? 25% for at least 1 year) and work time with heat stress (wet bulb globe temperature ISO 7243) for each occupation. We used three exposure indices: ever versus never exposed, lifetime cumulative exposure, and duration of exposure (years). We estimated ORs and 95% confidence intervals (CI), applying a lag period of 5 years and adjusting for potential confounders. RESULTS: Ever occupational heat exposure was associated with a moderate but statistically significant higher risk of breast cancer (OR 1.22; 95% CI, 1.01-1.46), with significant trends across categories of lifetime cumulative exposure and duration (P (trend) = 0.01 and 0.03, respectively). Stronger associations were found for hormone receptor-positive disease (OR ever exposure = 1.38; 95% CI, 1.12-1.67). We found no confounding effects from multiple other common occupational exposures; however, results attenuated with adjustment for occupational detergent exposure. CONCLUSIONS: This study provides some evidence of an association between occupational heat exposure and female breast cancer risk. IMPACT: Our results contribute substantially to the scientific literature. Further investigations are needed considering multiple occupational exposures.
The aim of this study was to compare airborne levels of Phl p 1 and Phl p 5, with Poaceae pollen concentrations inside and outside of the pollen season, and to evaluate their association with symptoms in grass allergic patients and the influence of climate and pollution. The Hirst and the Burkard Cyclone samplers were used for pollen and allergen quantification, respectively. The sampling period ran from 23 March 2009 to 27 July 2010. Twenty-three patients with seasonal allergic asthma and rhinitis used an electronic symptom card. The aerosol was extracted and quantified for Phl p 1 and Phl p 5 content. Descriptive statistics, non-parametric paired contrast of Wilcoxon, Spearman’s correlations, and a categorical principal component analysis (CatPCA) were carried out. Significant variations in pollen, aeroallergen levels, pollen allergen potency, and symptoms score were observed in this study. Phl p 5 pollen allergen potency was higher at the beginning of the 2010 grass pollen season. Presence of Phl p 1 outside the pollen season with positive O(3) correlation was clinically relevant. 45.5% of the variance was explained by two dimensions in the CatPCA analysis, showing the symptom relationships dissociated in two dimensions. In the first one, the more important relationship was with grass pollen grains concentration and Phl p 5 and to a lesser extent with Phl p 1 and levels of NO(2) and O(3), and in the second dimension, symptoms were associated with humidity and SO(2). Clinically relevant out-season Phl p 1 was found with a positive O(3) correlation. The effect of climate and pollution may have contributed to the higher seasonal allergic rhinitis symptom score recorded in 2009.
The health, economic, and social impact of COVID-19 has been significant across the world. Our objective was to evaluate the association between air pollution (through NO(2) and PM(2.5) levels) and COVID-19 mortality in Spanish provinces from February 3, 2020, to July 14, 2020, adjusting for climatic parameters. An observational and ecological study was conducted with information extracted from Datadista repository (Datadista, 2020). Air pollutants (NO(2) and PM(2.5) levels) were analyzed as potential determinants of COVID-19 mortality. Multilevel Poisson regression models were used to analyze the risk of mortality after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Models were adjusted by four climatic variables (hours of solar radiation, precipitation, daily temperature and wind speed) and population size. The mean levels of PM(2.5) and NO(2) across all provinces and time in Spain were 8.7 ?g/m(3) (SD 9.7) and 8.7 ?g/m(3) (SD 6.2), respectively. High levels of PM(2.5) (IRR?=?1.016, 95% CI: 1.007-1.026), NO(2) (IRR?=?1.066, 95% CI: 1.058-1.075) and precipitation (IRR(NO2)?=?0.989, 95% CI: 0.981-0.997) were positively associated with COVID-19 mortality, whereas temperature (IRR(PM2.5)?=?0.988, 95% CI: 0.976-1.000; and IRR(NO2)?=?0.771, 95% CI: 0.761-0.782, respectively) and wind speed (IRR(NO2)?=?1.095, 95% CI: 1.061-1.131) were negatively associated with COVID-19 mortality. Air pollution can be a key factor to understand the mortality rate for COVID-19 in Spain. Furthermore, climatic variables could be influencing COVID-19 progression. Thus, air pollution and climatology ought to be taken into consideration in order to control the pandemic. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-021-01062-2.
In this study, we use a statistical approach based on generalized additive models, linking atmospheric circulation and the number of influenza-related hospital admissions in the Spanish Iberian Peninsula during 2003-2013. The relative risks are estimated for administrative units in the Spanish territory, which is politically structured into 15 regions called autonomous communities. A catalog of atmospheric circulation types is defined for this purpose. The relationship between the exposure and response variables is modeled using a distributed lag nonlinear model (DLNM). Types from southwest and anticyclonic are significant in terms of the probability of having more influenza-related hospital admissions for all of Spain. The heterogeneity of the results is very high. The relative risk is also estimated for each autonomous community and weather type, with the maximum number of influenza-related hospital admissions associated with circulation types from the southwest and the south. We identify six specific situations where relative risk is considered extreme and twelve with a high risk of increasing influenza-related hospital admissions. The rest of the situations present a moderate risk. Atmospheric local conditions become a key factor for understanding influenza spread in each spatial unit of the Peninsula. Further research is needed to understand how different weather variables (temperature, humidity, and sun radiation) interact and promote the spread of influenza.
Since the early twentieth century, the intensity of malaria transmission has decreased sharply worldwide, although it is still an infectious disease with a yearly estimate of 228 million cases. The aim of this study was to expand our knowledge on the main drivers of malaria in Spain. In the case of autochthonous malaria, these drivers were linked to socioeconomic and hygienic and sanitary conditions, especially in rural areas due to their close proximity to the wetlands that provide an important habitat for anopheline reproduction. In the case of imported malaria, the main drivers were associated with urban areas, a high population density and international communication nodes (e.g. airports). Another relevant aspect is that the major epidemic episodes of the twentieth century were strongly influenced by war and military conflicts and overcrowding of the healthcare system due to the temporal overlap with the pandemic flu of 1918. Therefore, military conflicts and overlap with other epidemics or pandemics are considered to be drivers of malaria that can-in a temporary manner-exponentially intensify transmission of the disease. Climatic factors did not play a relevant role as drivers of malaria in Spain (at least directly). However, they did influence the seasonality of the disease and, during the epidemic outbreak of 1940-1944, the climate conditions favored or coadjuvated its spread. The results of this study provide additional knowledge on the seasonal and interannual variability of malaria that can help to develop and implement health risk control measures. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41207-021-00245-8.
A yellow fever epidemic occurred in Cadiz and other areas of southern Spain during the last months of 1800. An anonymous author attributed this disease to the contrast between the cold and rainy winter and spring, and the subsequent very hot summer. However, the physician J.M. Arejula published a report in 1806 where he refuted this conclusion after a detailed analysis of the meteorological conditions in the area. This controversy is a good example of the discussion about the relationships between meteorological conditions and public health. In this work, this “scientific” controversy is studied. Although the arguments of both authors were inspired by the neo-Hippocratic medical paradigm, the anonymous author put forth a simple cause effect hypothesis, while Arejula recognized the complexity of the problem, introducing the concept of “concause” to explain the confluence of environmental and contagious effects.
The increase in the frequency and intensity of heat waves is one of the most unquestionable effects of climate change. Therefore, the progressive increase in maximum temperatures will have a clear incidence on the increase in mortality, especially in countries that are vulnerable due to geographical location or their socioeconomic characteristics. Different research studies show that the mortality attributable to heat is decreasing globally, and research is centred on future scenarios. One way of detecting the existence of a lesser impact of heat is through the increase in the so-called temperature of minimum mortality (TMM). The objective of this study is to determine the temporal evolution of TMM in two Spanish provinces (Seville and Madrid) during the 1983-2018 period and to evaluate whether the rate of adaptation to heat is appropriate. We used the gross rate of daily mortality due to natural causes (CIEX: A00-R99) and the maximum daily temperature (°C) to determine the quinquennial TMM using dispersion diagrams and realizing fit using quadratic and cubic curvilinear estimation. The same analysis was carried out at the annual level, by fitting an equation to the line of TMM for each province, whose slope, if significant (p < 0.05) represents the annual rate of variation in TMM. The results observed in this quinquennial analysis showed that the TMM is higher in Seville than in Madrid and that it is higher among men than women in the two provinces. Furthermore, there was an increase in TMM in all of the quinquennium and a clear decrease in the final period. At the annual level, the linear fit was significant for Madrid for the whole population and corresponds to an increase in the TMM of 0.58 °C per decade. For Seville the linear fits were significant and the slopes of the fitted lines was 1.1 °C/decade. Both Madrid and Seville are adapting to the increase in temperatures observed over the past 36 years, and women are the group that is more susceptible to heat, compared to men. The implementation of improvements and evaluation of prevention plans to address the impact of heat waves should continue in order to ensure adequate adaptation in the future.
Introduction and objectives. The increase in mortality and hospital admissions associated with high and low temperatures is well established. However, less is known about the influence of extreme ambient temperature conditions on cardiovascular ambulance dispatches. This study seeks to evaluate the effects of minimum and maximum daily temperatures on cardiovascular morbidity in the cities of Vigo and A Coruña in North-West Spain, using emergency medical calls during the period 2005-2017. Methods. For the purposes of analysis, we employed a quasi-Poisson time series regression model, within a distributed non-linear lag model by exposure variable and city. The relative risks of cold- and heat-related calls were estimated for each city and temperature model. Results. A total of 70,537 calls were evaluated, most of which were associated with low maximum and minimum temperatures on cold days in both cities. At maximum temperatures, significant cold-related effects were observed at lags of 3-6 days in Vigo and 5-11 days in A Coruña. At minimum temperatures, cold-related effects registered a similar pattern in both cities, with significant relative risks at lags of 4 to 12 days in A Coruña. Heat-related effects did not display a clearly significant pattern. Conclusions. An increase in cardiovascular morbidity is observed with moderately low temperatures without extremes being required to establish an effect. Public health prevention plans and warning systems should consider including moderate temperature range in the prevention of cardiovascular morbidity.
