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BACKGROUND The health effects of heat are well documented; however, limited information is available regarding the health risks of hot nights. Hot nights have become more common, increasing at a faster rate than hot days, making it urgent to understand the characteristics of the hot night risk. OBJECTIVES We estimated the effects of hot nights on the cause- and location-specific mortality in a nationwide assessment over 43 y (1973-2015) using a unified analytical framework in the 47 prefectures of Japan. METHODS Hot nights were defined as days with a) minimum temperature () and b) minimum temperature percentile () for the prefecture. We conducted a time-series analysis using a two-stage approach during the hot night occurrence season (April-November). For each prefecture, we estimated associations between hot nights and mortality controlling for potential confounders including daily mean temperature. We then used a random-effects meta-analytic model to estimate the pooled cumulative association. RESULTS Overall, 24,721,226 deaths were included in this study. Nationally, all-cause mortality increased by 9%-10% [ relative risk , 95% confidence interval (CI): 1.08, 1.10; , 95% CI: 1.09, 1.11] during hot nights in comparison with nonhot nights. All 11 cause-specific mortalities were strongly associated with hot nights, and the corresponding associations appeared to be acute and lasted a few weeks, depending on the cause of death. The strength of the association between hot nights and mortality varied among prefectures. We found a higher mortality risk from hot nights in early summer in comparison with the late summer in all regions. CONCLUSIONS Our findings support the evidence of mortality impacts from hot nights in excess of that explicable by daily mean temperature and have implications useful for establishing public health policy and research efforts estimating the health effects of climate change. https://doi.org/10.1289/EHP11444.

We assessed the impact of increasing long-term exposure to particulate matter ≤2.5 microns in diameter (PM2.5) on either SARS-CoV-2 susceptibility or COVID-19 severity on projected infections and hospitalisations over two years.

Defining health-based thresholds for effective heat warnings is crucial for climate change adaptation strategies. Translating the non-linear function between heat and health effects into an effective threshold for heat warnings to protect the population is a challenge. We present a systematic analysis of heat indicators in relation to mortality. We applied distributed lag non-linear models in an individual-level case-crossover design to assess the effects of heat on mortality in Switzerland during the warm season from 2003 to 2016 for three temperature metrics (daily mean, maximum, and minimum temperature), and various threshold temperatures and heatwave definitions. Individual death records with information on residential address from the Swiss National Cohort were linked to high-resolution temperature estimates from 100 m resolution maps. Moderate (90th percentile) to extreme thresholds (99.5th percentile) of the three temperature metrics implied a significant increase in mortality (5 to 38%) in respect of the median warm-season temperature. Effects of the threshold temperatures on mortality were similar across the seven major regions in Switzerland. Heatwave duration did not modify the effect when considering delayed effects up to 7 days. This nationally representative study, accounting for small-scale exposure variability, suggests that the national heat-warning system should focus on heatwave intensity rather than duration. While a different heat-warning indicator may be appropriate in other countries, our evaluation framework is transferable to any country.

Human-induced climate change is leading to an increase in the intensity and frequency of extreme weather events, which are severely affecting the health of the population. The exceptional heat during the summer of 2022 in Europe is an example, with record-breaking temperatures only below the infamous 2003 summer. High ambient temperatures are associated with many health outcomes, including premature mortality. However, there is limited quantitative evidence on the contribution of anthropogenic activities to the substantial heat-related mortality observed in recent times. Here we combined methods in climate epidemiology and attribution to quantify the heat-related mortality burden attributed to human-induced climate change in Switzerland during the summer of 2022. We first estimated heat-mortality association in each canton and age/sex population between 1990 and 2017 in a two-stage time-series analysis. We then calculated the mortality attributed to heat in the summer of 2022 using observed mortality, and compared it with the hypothetical heat-related burden that would have occurred in absence of human-induced climate change. This counterfactual scenario was derived by regressing the Swiss average temperature against global mean temperature in both observations and CMIP6 models. We estimate 623 deaths [95% empirical confidence interval (95% eCI): 151-1068] due to heat between June and August 2022, corresponding to 3.5% of all-cause mortality. More importantly, we find that 60% of this burden (370 deaths [95% eCI: 133-644]) could have been avoided in absence of human-induced climate change. Older women were affected the most, as well as populations in western and southern Switzerland and more urbanized areas. Our findings demonstrate that human-induced climate change was a relevant driver of the exceptional excess health burden observed in the 2022 summer in Switzerland., Environmental Research Letters, 18 (7), ISSN:1748-9326, ISSN:1748-9318

The original version of this Article contained an error in Affiliation 25, which was incorrectly given as ‘Faculty of Medicine ArqFuturo INSPER, University of São Paulo, São Paulo, Brazil’. The correct affiliation is listed below. Faculty of Medicine, University of São Paulo, São Paulo, Brazil The original Article has been corrected.

Epidemiological analyses of health risks associated with non-optimal temperature are traditionally based on ground observations from weather stations that offer limited spatial and temporal coverage. Climate reanalysis represents an alternative option that provide complete spatio-temporal exposure coverage, and yet are to be systematically explored for their suitability in assessing temperature-related health risks at a global scale. Here we provide the first comprehensive analysis over multiple regions to assess the suitability of the most recent generation of reanalysis datasets for health impact assessments and evaluate their comparative performance against traditional station-based data. Our findings show that reanalysis temperature from the last ERA5 products generally compare well to station observations, with similar non-optimal temperature-related risk estimates. However, the analysis offers some indication of lower performance in tropical regions, with a likely underestimation of heat-related excess mortality. Reanalysis data represent a valid alternative source of exposure variables in epidemiological analyses of temperature-related risk., The study was primarily supported by Grants from the European Commission’s Joint Research Centre Seville (Research Contract ID: JRC/SVQ/2020/MVP/1654), Medical Research Council-UK (Grant ID: MR/R013349/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655). The following individual Grants also supported this work: J.K and A.U were supported by the Czech Science Foundation, project 20-28560S. A.T was supported by MCIN/AEI/10.13039/501100011033, Grant CEX2018-000794-S. V.H was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant agreement No 101032087. This work was generated using Copernicus Climate Change Service (C3S) information [1985–2019].

Epidemiological analyses of health risks associated with non-optimal temperature are traditionally based on ground observations from weather stations that offer limited spatial and temporal coverage. Climate reanalysis represents an alternative option that provide complete spatio-temporal exposure coverage, and yet are to be systematically explored for their suitability in assessing temperature-related health risks at a global scale. Here we provide the first comprehensive analysis over multiple regions to assess the suitability of the most recent generation of reanalysis datasets for health impact assessments and evaluate their comparative performance against traditional station-based data. Our findings show that reanalysis temperature from the last ERA5 products generally compare well to station observations, with similar non-optimal temperature-related risk estimates. However, the analysis offers some indication of lower performance in tropical regions, with a likely underestimation of heat-related excess mortality. Reanalysis data represent a valid alternative source of exposure variables in epidemiological analyses of temperature-related risk.

Background: Air conditioning has been proposed as one of the key factors explaining reductions of heat-related mortality risks observed in the last decades. However, direct evidence is still limited. Methods: We used a multi-country, multi-city, longitudinal design to quantify the independent role of air conditioning in reported attenuation in risk. We collected daily time series of mortality, mean temperature, and yearly air conditioning prevalence for 311 locations in Canada, Japan, Spain, and the USA between 1972 and 2009. For each city and sub-period, we fitted a quasi-Poisson regression combined with distributed lag non-linear models to estimate summer-only temperature–mortality associations. At the second stage, we used a novel multilevel, multivariate spatio-temporal meta-regression model to evaluate effect modification of air conditioning on heat–mortality associations. We computed relative risks and fractions of heat-attributable excess deaths under observed and fixed air conditioning prevalences. Results: Results show an independent association between increased air conditioning prevalence and lower heat-related mortality risk. Excess deaths due to heat decreased during the study periods from 1.40% to 0.80% in Canada, 3.57% to 1.10% in Japan, 3.54% to 2.78% in Spain, and 1.70% to 0.53% in the USA. However, increased air conditioning explains only part of the observed attenuation, corresponding to 16.7% in Canada, 20.0% in Japan, 14.3% in Spain, and 16.7% in the USA. Conclusions: Our findings are consistent with the hypothesis that air conditioning represents an effective heat adaptation strategy, but suggests that other factors have played an equal or more important role in increasing the resilience of populations.

Introduction: Climate change predictions indicate that global temperatures are likely to exceed those seen in the last 200,000 years, rising by around 4°C above pre-industrial levels by 2100 (without effective mitigation of current emission rates). In regions of the world set to experience extreme temperatures, women often work outside in agriculture even during pregnancy. The implications of heat strain in pregnancy on maternal health and pregnancy outcome are not well understood. This protocol describes a study to assess the physiological response of pregnant women to environmental heat stress and the immediate effect this has on fetal wellbeing. Methods and analysis: The study will be performed in West Kiang district, The Gambia; a semi-arid zone in West Africa with daily maximum temperatures ranging from approximately 32 to 40°C. We will recruit 125 pregnant women of all ages who perform agricultural work during their pregnancy. Participants will be followed every two months until delivery. At each study visit fetal growth will be measured by ultrasound scan. During the course of their working day we will take the following measurements: continuous maternal physiological measurements (heart rate, respiratory rate, chest skin temperature and tri-axis accelerometer data); intermittent maternal tympanic core temperature, four point skin temperature, blood pressure; intermittent fetal heart rate and, if eligible, umbilical artery doppler; intermittent environmental measurements of air temperature, humidity, solar radiation and wind speed. Venous blood and urine will be collected at beginning and end of day for biomarkers of heat strain or fetal distress and hydration status.

BACKGROUND: Air conditioning has been proposed as one of the key factors explaining reductions of heat-related mortality risks observed in the last decades. However, direct evidence is still limited. METHODS: We used a multi-country, multi-city, longitudinal design to quantify the independent role of air conditioning in reported attenuation in risk. We collected daily time series of mortality, mean temperature, and yearly air conditioning prevalence for 311 locations in Canada, Japan, Spain, and the USA between 1972 and 2009. For each city and sub-period, we fitted a quasi-Poisson regression combined with distributed lag non-linear models to estimate summer-only temperature-mortality associations. At the second stage, we used a novel multilevel, multivariate spatio-temporal meta-regression model to evaluate effect modification of air conditioning on heat-mortality associations. We computed relative risks and fractions of heat-attributable excess deaths under observed and fixed air conditioning prevalences. RESULTS: Results show an independent association between increased air conditioning prevalence and lower heat-related mortality risk. Excess deaths due to heat decreased during the study periods from 1.40% to 0.80% in Canada, 3.57% to 1.10% in Japan, 3.54% to 2.78% in Spain, and 1.70% to 0.53% in the USA. However, increased air conditioning explains only part of the observed attenuation, corresponding to 16.7% in Canada, 20.0% in Japan, 14.3% in Spain, and 16.7% in the USA. CONCLUSIONS: Our findings are consistent with the hypothesis that air conditioning represents an effective heat adaptation strategy, but suggests that other factors have played an equal or more important role in increasing the resilience of populations.

Supplemental material, spub-ri-2018-0175-File005 for Heat wave–related mortality in Sweden: A case-crossover study investigating effect modification by neighbourhood deprivation by Daniel Oudin Åström, Christofer Åström, Bertil Forsberg, Ana M. Vicedo-Cabrera, Antonio Gasparrini, Anna Oudin and Kristina Sundquist in Scandinavian Journal of Public Health

Supplemental material, spub-ri-2018-0175-File004 for Heat wave–related mortality in Sweden: A case-crossover study investigating effect modification by neighbourhood deprivation by Daniel Oudin Åström, Christofer Åström, Bertil Forsberg, Ana M. Vicedo-Cabrera, Antonio Gasparrini, Anna Oudin and Kristina Sundquist in Scandinavian Journal of Public Health

Designing effective public health strategies to prevent adverse health effect of hot weather is crucial in the context of global warming. In Switzerland, the 2003 heat have caused an estimated 7% increase in all-cause mortality. As a consequence, the Swiss Federal Office of Public Health developed an information campaign to raise public awareness on heat threats. For a better understanding on how hot weather affects daily mortality in Switzerland, we assessed the effect of heat on daily mortality in eight Swiss cities and population subgroups from 1995 to 2013 using different temperature metrics (daily mean (Tmean), maximum (Tmax), minimum (Tmin) and maximum apparent temperature (Tappmax)), and aimed to evaluate variations of the heat effect after 2003 (1995-2002 versus 2004-2013). We applied conditional quasi-Poisson regression models with non-linear distributed lag functions to estimate temperature-mortality associations over all cities (1995-2013) and separately for two time periods (1995-2002, 2004-2013). Relative risks (RR) of daily mortality were estimated for increases in temperature from the median to the 98th percentile of the warm season temperature distribution. Over the whole time period, significant temperature-mortality relationships were found for all temperature indicators (RR (95% confidence interval): Tappmax: 1.12 (1.05; 1.18); Tmax: 1.15 (1.08-1.22); Tmean: 1.16 (1.09-1.23); Tmin 1.23 (1.15-1.32)). Mortality risks were higher at the beginning of the summer, especially for Tmin. In the more recent time period, we observed a non-significant reduction in the effect of high temperatures on mortality, with the age group > 74 years remaining the population at highest risk. High temperatures continue to be a considerable risk factor for human health in Switzerland after 2003. More effective public health measures targeting the elderly should be promoted with increased attention to the first heat events in summer and considering both high day-time and night-time temperatures.

BACKGROUND: During July 2012, two simultaneous wildfires devastated near 50,000 hectares of forests covering the rural area of the INMA-Valencia cohort in Spain. The wildfires produced heavy smoke ...

Epidemiological studies on the health effects of air pollution usually rely on measurements from fixed ground monitors, which provide limited spatio-temporal coverage. Data from satellites, reanalysis, and chemical transport models offer additional information used to reconstruct pollution concentrations at high spatio-temporal resolutions. This study aims to develop a multi-stage satellite-based machine learning model to estimate daily fine particulate matter (PM2.5) levels across Great Britain between 2008–2018. This high-resolution model consists of random forest (RF) algorithms applied in four stages. Stage-1 augments monitor-PM2.5 series using co-located PM10 measures. Stage-2 imputes missing satellite aerosol optical depth observations using atmospheric reanalysis models. Stage-3 integrates the output from previous stages with spatial and spatio-temporal variables to build a prediction model for PM2.5. Stage-4 applies Stage-3 models to estimate daily PM2.5 concentrations over a 1 km grid. The RF architecture performed well in all stages, with results from Stage-3 showing an average cross-validated R2 of 0.767 and minimal bias. The model performed better over the temporal scale when compared to the spatial component, but both presented good accuracy with an R2 of 0.795 and 0.658, respectively. These findings indicate that direct satellite observations must be integrated with other satellite-based products and geospatial variables to derive reliable estimates of air pollution exposure. The high spatio-temporal resolution and the relatively high precision allow these estimates (approximately 950 million points) to be used in epidemiological analyses to assess health risks associated with both short- and long-term exposure to PM2.5.