Heat-related Excess Mortality Research Articles

Twenty-first-century demographic and social inequalities of heat-related deaths in Brazilian urban areas.

Population exposure to heat waves (HWs) is increasing worldwide due to climate change, significantly affecting society, including public health. Despite its significant vulnerabilities and limited adaptation resources to rising temperatures, South America, particularly Brazil, lacks research on the health impacts of temperature extremes, especially on the role played by socioeconomic factors in the risk of heat-related illness. Here, we present a comprehensive analysis of the effects of HWs on mortality rates in the 14 most populous urban areas, comprising approximately 35% of the country's population. Excess mortality during HWs was estimated through the observed-to-expected ratio (O/E) for total deaths during the events identified. Moreover, the interplay of intersectionality and vulnerability to heat considering demographics and socioeconomic heterogeneities, using gender, age, race, and educational level as proxies, as well as the leading causes of heat-related excess death, were assessed. A significant increase in the frequency was observed from the 1970s (0-3 HWs year-1) to the 2010s (3-11 HWs year-1), with higher tendencies in the northern, northeastern, and central-western regions. Over the 2000-2018 period, 48,075 (40,448-55,279) excessive deaths were attributed to the growing number of HWs (>20 times the number of landslides-related deaths for the same period). Nevertheless, our event-based surveillance analysis did not detect the HW-mortality nexus, reinforcing that extreme heat events are a neglected disaster in Brazil. Among the leading causes of death, diseases of the circulatory and respiratory systems and neoplasms were the most frequent. Critical regional differences were observed, which can be linked to the sharp North-South inequalities in terms of socioeconomic and health indicators, such as life expectancy. Higher heat-related excess mortality was observed for low-educational level people, blacks and browns, older adults, and females. Such findings highlight that the strengthening of primary health care combined with reducing socioeconomic, racial, and gender inequalities represents a crucial step to reducing heat-related deaths.

Long-Term Change in Heat-Related Excess Mortality in Japan

Long-Term Change in Heat-Related Excess Mortality in Japan

Projections of heat-related excess mortality in China due to climate change, population and aging

Projections of heat-related excess mortality in China due to climate change, population and aging

Comparison of weather station and climate reanalysis data for modelling temperature-related mortality

BACKGROUND: Epidemiological analyses of health risks associated with non-optimal temperature are traditionally based on ground observations from weather stations. Though generally considered representative of the actual ambient conditions and individual’s exposure, their broader application in environmental epidemiology is often constrained by inhomogeneous records and the sparse density of meteorological stations. 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. AIM: The aim of the study is to 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. METHODS: We applied the well-established time-series analyses with quasi-Poisson regression (with distributed lag non-linear models and multivariate meta-regression) to model the location specific temperature-mortality associations, across 612 cities within 39 countries over the period 1985–2019, covering a wide range of climates and including low- and middle-income countries. Briefly, we first systematically compared the correlation between daily temperature series derived from ground station observations and ERA5-Land/ERA5 reanalysis, then we evaluated differences in estimated exposure-response functions of temperature-mortality relationships, and finally we compared their performance using fit statistics. RESULTS: 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. CONCLUSIONS: Reanalysis data represent a valid alternative source of exposure variables in epidemiological analyses of temperature-related risk. The consistent spatio-temporal coverage also makes it attractive for quantifying population attributable fractions, an indicator important for health planners and policy makers. KEYWORDS: mortality, temperature, reanalysis, ERA5-Land, distributed lag models.

Evidence of rapid adaptation integrated into projections of temperature-related excess mortality

Few studies have used empirical evidence of past adaptation to project temperature-related excess mortality under climate change. Here, we assess adaptation in future projections of temperature-related excess mortality by employing evidence of shifting minimum mortality temperatures (MMTs) concurrent with climate warming of recent decades. The study is based on daily non-external mortality and daily mean temperature time-series from 11 Spanish cities covering four decades (1978–2017). It employs distributed lag non-linear models (DLNMs) to describe temperature-mortality associations, and multivariate mixed-effect meta-regression models to derive city- and subperiod-specific MMTs, and subsequently MMT associations with climatic indicators. We use temperature projections for one low- and one high-emission scenario (ssp126, ssp370) derived from five global climate models. Our results show that MMTs have closely tracked mean summer temperatures (MSTs) over time and space, with meta-regression models suggesting that the MMTs increased by 0.73 °C (95%CI: 0.65, 0.80) per 1 °C rise in MST over time, and by 0.84 °C (95%CI: 0.76, 0.92) per 1 °C rise in MST across cities. Future projections, which include adaptation by shifting MMTs according to observed temporal changes, result in 63.5% (95%CI: 50.0, 81.2) lower heat-related excess mortality, 63.7% (95%CI: 30.2, 166.7) higher cold-related excess mortality, and 11.2% (95%CI: −5.5, 39.5) lower total temperature-related excess mortality in the 2090s for ssp370 compared to estimates that do not account for adaptation. For ssp126, assumptions on adaptation have a comparatively small impact on excess mortality estimates. Elucidating the adaptive capacities of societies can motivate strengthened efforts to implement specific adaptation measures directed at reducing heat stress under climate change.

Comparison of weather station and climate reanalysis data for modelling temperature-related mortality

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.

A Comparative Analysis of the Temperature-Mortality Risks Using Different Weather Datasets Across Heterogeneous Regions.

New gridded climate datasets (GCDs) on spatially resolved modeled weather data have recently been released to explore the impacts of climate change. GCDs have been suggested as potential alternatives to weather station data in epidemiological assessments on health impacts of temperature and climate change. These can be particularly useful for assessment in regions that have remained understudied due to limited or low quality weather station data. However to date, no study has critically evaluated the application of GCDs of variable spatial resolution in temperature‐mortality assessments across regions of different orography, climate, and size. Here we explored the performance of population‐weighted daily mean temperature data from the global ERA5 reanalysis dataset in the 10 regions in the United Kingdom and the 26 cantons in Switzerland, combined with two local high‐resolution GCDs (HadUK‐grid UKPOC‐9 and MeteoSwiss‐grid‐product, respectively) and compared these to weather station data and unweighted homologous series. We applied quasi‐Poisson time series regression with distributed lag nonlinear models to obtain the GCD‐ and region‐specific temperature‐mortality associations and calculated the corresponding cold‐ and heat‐related excess mortality. Although the five exposure datasets yielded different average area‐level temperature estimates, these deviations did not result in substantial variations in the temperature‐mortality association or impacts. Moreover, local population‐weighted GCDs showed better overall performance, suggesting that they could be excellent alternatives to help advance knowledge on climate change impacts in remote regions with large climate and population distribution variability, which has remained largely unexplored in present literature due to the lack of reliable exposure data.

Projecting heat-related excess mortality under climate change scenarios in China

Recent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.

Projection of Temperature-Related Excess Mortality by Integrating Population Adaptability Under Changing Climate — China, 2050s and 2080s

What is already known about this topic?An increasing number of studies have projected temperature-related mortality, but few consider the change of population’s adaptability to future temperature and mortality burden from cold and heat effects.What is added by this report?This study offers a comprehensive characterization of human adaptability and excess mortality burden of temperature across various regions of China.What are the implications for public health practice?The temperature-related excess mortality was projected to increase in the 2050s and decrease in the 2080s. Heat adaptability was projected to increase in the future, but along with the rising temperatures, the heat-related excess mortality continuously rose, except for the low-speed rising scenario. Although the excess mortality of cold was projected to decrease in the nearer future, it might not keep declining in the long run, due to the decreasing cold-adaptability, which deserves more attention.

Event-Based Heat-Related Risk Assessment Model for South Korea Using Maximum Perceived Temperature, Wet-Bulb Globe Temperature, and Air Temperature Data.

This study aimed to assess the heat-related risk (excess mortality rate) at six cities, namely, Seoul, Incheon, Daejeon, Gwangju, Daegu, and Busan, in South Korea using the daily maximum perceived temperature (PTmax), which is a physiology-based thermal comfort index, the wet-bulb globe temperature, which is meteorology-based thermal comfort index, and air temperature. Particularly, the applicability of PTmax was evaluated using excess mortality rate modeling. An event-based heat-related risk assessment model was employed for modeling the excess mortality rate. The performances of excess mortality rate models using those variables were evaluated for two data sets that were used (training data, 2000–2016) and not used (test data, 2017–2018) for the construction of the assessment models. Additionally, the excess mortality rate was separately modeled depending on regions and ages. PTmax is a good temperature indicator that can be used to model the excess mortality rate in South Korea. The application of PTmax in modeling the total mortality rate yields the best performances for the test data set, particularly for young people. From a forecasting perspective, PTmax is the most appropriate temperature indicator for assessing the heat-related excess mortality rate in South Korea.

Climate Change and Heat-Related Excess Mortality in the Eastern USA.

Climate change will increase extreme heat-related health risks. To quantify the health impacts of mid-century climate change, we assess heat-related excess mortality across the eastern USA. Health risks are estimated using the US Environmental Protection Agency's Environmental Benefits Mapping and Analysis Program (BenMAP). Mid-century temperature estimates, downscaled using the Weather Research and Forecasting model, are compared to 2007 temperatures at 36km and 12km resolutions. Models indicate the average apparent and actual summer temperatures rise by 4.5° and 3.3° C, respectively. Warmer average apparent temperatures could cause 11,562 additional annual deaths (95% confidence interval, CI: 2641-20,095) due to cardiovascular stress in the population aged 65years and above, while higher minimum temperatures could cause 8767 (95% CI: 5030-12,475) additional deaths each year. Modeled future climate data available at both coarse (36km) and fine (12km) resolutions predict significant human health impacts from warmer climates. The findings suggest that currently available information on future climates is sufficient to guide regional planning for the protection of public health. Higher resolution climate and demographic data are still needed to inform more targeted interventions.

Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks

Abstract. The static energy content of the atmosphere is increasing on a global scale, but exhibits important subglobal and subregional scales of variability and is a useful parameter for integrating the net effect of changes in the partitioning of energy at the surface and for improving understanding of the causes of so-called warming holes (i.e., locations with decreasing daily maximum air temperatures (T) or increasing trends of lower magnitude than the global mean). Further, measures of the static energy content (herein the equivalent potential temperature, θe) are more strongly linked to excess human mortality and morbidity than air temperature alone, and have great relevance in understanding causes of past heat-related excess mortality and making projections of possible future events that are likely to be associated with negative human health and economic consequences. New nonlinear statistical models for summertime daily maximum and minimum θe are developed and used to advance understanding of drivers of historical change and variability over the eastern USA. The predictor variables are an index of the daily global mean temperature, daily indices of the synoptic-scale meteorology derived from T and specific humidity (Q) at 850 and 500 hPa geopotential heights (Z), and spatiotemporally averaged soil moisture (SM). SM is particularly important in determining the magnitude of θe over regions that have previously been identified as exhibiting warming holes, confirming the key importance of SM in dictating the partitioning of net radiation into sensible and latent heat and dictating trends in near-surface T and θe. Consistent with our a priori expectations, models built using artificial neural networks (ANNs) out-perform linear models that do not permit interaction of the predictor variables (global T, synoptic-scale meteorological conditions and SM). This is particularly marked in regions with high variability in minimum and maximum θe, where more complex models built using ANN with multiple hidden layers are better able to capture the day-to-day variability in θe and the occurrence of extreme maximum θe. Over the entire domain, the ANN with three hidden layers exhibits high accuracy in predicting maximum θe > 347 K. The median hit rate for maximum θe > 347 K is > 0.60, while the median false alarm rate is ≈ 0.08.

Modification of Heat-Related Mortality in an Elderly Urban Population by Vegetation (Urban Green) and Proximity to Water (Urban Blue): Evidence from Lisbon, Portugal.

Background:Urban populations are highly vulnerable to the adverse effects of heat, with heat-related mortality showing intra-urban variations that are likely due to differences in urban characteristics and socioeconomic status.Objectives:We investigated the influence of urban green and urban blue, that is, urban vegetation and water bodies, on heat-related excess mortality in the elderly > 65 years old in Lisbon, Portugal, between 1998 and 2008.Methods:We used remotely sensed data and geographic information to determine the amount of urban vegetation and the distance to bodies of water (the Atlantic Ocean and the Tagus Estuary). Poisson generalized additive models were fitted, allowing for the interaction between equivalent temperature [universal thermal climate index (UTCI)] and quartiles of urban greenness [classified using the Normalized Difference Vegetation Index (NDVI)] and proximity to water (≤ 4 km vs. > 4 km), while adjusting for potential confounders.Results:The association between mortality and a 1°C increase in UTCI above the 99th percentile (24.8°C) was stronger for areas in the lowest NDVI quartile (14.7% higher; 95% CI: 1.9, 17.5%) than for areas in the highest quartile (3.0%; 95% CI: 2.0, 4.0%). In areas > 4 km from water, a 1°C increase in UTCI above the 99th percentile was associated with a 7.1% increase in mortality (95% CI: 6.2, 8.1%), whereas in areas ≤ 4 km from water, the estimated increase in mortality was only 2.1% (95% CI: 1.2, 3.0%).Conclusions:Urban green and blue appeared to have a mitigating effect on heat-related mortality in the elderly population in Lisbon. Increasing the amount of vegetation may be a good strategy to counteract the adverse effects of heat in urban areas. Our findings also suggest potential benefits of urban blue that may be present several kilometers from a body of water.Citation:Burkart K, Meier F, Schneider A, Breitner S, Canário P, Alcoforado MJ, Scherer D, Endlicher W. 2016. Modification of heat-related mortality in an elderly urban population by vegetation (urban green) and proximity to water (urban blue): evidence from Lisbon, Portugal. Environ Health Perspect 124:927–934; http://dx.doi.org/10.1289/ehp.1409529

Projection Of Heat-Related Excess Mortality Using New Climate And Population Scenarios

Introduction Last year, WHO report on the health impact of climate change was published. In the report, we conducted the projection of heat-related excess mortality. However, since the climate and ...

Heat mortality in Berlin – Spatial variability at the neighborhood scale

Heat stress increasingly affects urban populations in higher geographical latitudes. Related adverse health effects are expected to increase due to urbanization, population aging, and global warming. While many studies have examined the relationship between heat and mortality, only a few have examined the intra-urban spatial variability between them. This missing research is particularly evident for northern mid-latitude cities, where populations are not prepared for heat stress. The aim of this study is therefore to investigate heat-related excess mortality in its spatial variability at the neighborhood scale (397 planning areas) for Berlin, the capital of Germany. We analyzed age-standardized mortality rates by calculating the relative heat mortality risk ratio for months with and without severe heat waves. Local indicators of spatial association were used to locate spatial clusters. The results highlighted the intra-urban variability of heat-related excess mortality, and demonstrated clustering for the planning areas of Berlin. Temporal aggregation of mortality data enabled a neighborhood-scale analysis. Resulting heat-related excess mortality maps allow urban decision makers to identify hot spots for emergency and adaptation planning, and serve as a basis for further investigations of heat stress risk on an individual level.

The effects of season and meteorology on human mortality in tropical climates: a systematic review.

Research in the field of atmospheric science and epidemiology has long recognized the health effects of seasonal and meteorological conditions. However, little scientific knowledge exists to date about the impacts of atmospheric parameters on human mortality in tropical regions. Working within the scope of this systematic review, this investigation conducted a literature search using different databases; original research articles were chosen according to pre-defined inclusion and exclusion criteria. Both seasonal and meteorological effects were considered. The findings suggest that high amounts of rainfall and increasing temperatures cause a seasonal excess in infectious disease mortality and are therefore relevant in regions and populations in which such diseases are prevalent. On the contrary, moderately low and very high temperatures exercise an adverse effect on cardio-respiratory mortality and shape the mortality pattern in areas and sub-groups in which these diseases are dominant. Atmospheric effects were subject to population-specific factors such as age and socio-economic status and differed between urban and rural areas. The consequences of climate change as well as environmental, epidemiological and social change (e.g., emerging non-communicable diseases, ageing of the population, urbanization) suggest a growing relevance of heat-related excess mortality in tropical regions.

Effect of absolute humidity on heat-mortality relation in Japan

Background: Previously, we evaluated the confounding effect of relative humidity on temperature-mortality relation in Japan using 1972-1995 dataset, and concluded that humidity did not confound the relation. Since then, we accumulated the data up to 2010. Another finding was that absolute humidity was better variable than relative humidity in evaluating the humidity effect on influenza incidence. Aims: To show the absolute humidity effect on heat-mortality relation using the extended dataset. Methods: We used daily deaths of 65+ years of age and controlled the year trend by setting each year's minimum level mortality to be the reference. As the main weather variable, we used daily maximum temperature. Using distributed lag non-linear model, we set the lag effect of daily maximum temperature up to 15 days. In conducting regression analyses, we used two models, i.e., without and with absolute humidity term along with daily maximum temperature-lag crossbasis. The temperature-mortality relation shows V-shaped pattern, and we used only "heat" part of the temperature range and calculated the excess mortality ratio, i.e.,"without" to "with." Results: The without/with ratio was between 0.90 to 1.10. In this regard, the effect of absolute humidity was not large. However, the ratio tended to exceed one in northern part and southern areas tended to have lower than unity ratios. Conclusions: The absolute humidity effect on heat-mortality relation appeared to be related to climate. If this is generalizable, we need to incorporate humidity variable in the model for future projection of heat-related excess mortality. Acknowledgements: This study was supported by the Environment Research and Technology Development Fund (S-8 & S10) of the Ministry of the Environment, Japan, and the Global Research Laboratory (grant K21004000001-10A0500-00710) through the National Research Foundation of Korea (NRF), funded by the Ministry of Education, Science and Technology, Korea.

Heat-related mortality risk model for climate change impact projection

We previously developed a model for projection of heat-related mortality attributable to climate change. The objective of this paper is to improve the fit and precision of and examine the robustness of the model. We obtained daily data for number of deaths and maximum temperature from respective governmental organizations of Japan, Korea, Taiwan, the USA, and European countries. For future projection, we used the Bergen climate model2 (BCM2) general circulation model, the Special Report on Emissions Scenarios (SRES) A1B socioeconomic scenario, and the mortality projection for the 65+-year-old age group developed by the World Health Organization (WHO). The heat-related excess mortality was defined as follows: The temperature-mortality relation forms a V-shaped curve, and the temperature at which mortality becomes lowest is called the optimum temperature (OT). The difference in mortality between the OT and a temperature beyond the OT is the excess mortality. To develop the model for projection, we used Japanese 47-prefecture data from 1972 to 2008. Using a distributed lag nonlinear model (two-dimensional nonparametric regression of temperature and its lag effect), we included the lag effect of temperature up to 15days, and created a risk function curve on which the projection is based. As an example, we perform a future projection using the above-mentioned risk function. In the projection, we used 1961-1990 temperature as the baseline, and temperatures in the 2030s and 2050s were projected using the BCM2 global circulation model, SRES A1B scenario, and WHO-provided annual mortality. Here, we used the "counterfactual method" to evaluate the climate change impact; For example, baseline temperature and 2030 mortality were used to determine the baseline excess, and compared with the 2030 excess, for which we used 2030 temperature and 2030 mortality. In terms of adaptation to warmer climate, we assumed 0% adaptation when the OT as of the current climate is used and 100% adaptation when the OT as of the future climate is used. The midpoint of the OTs of the two types of adaptation was set to be the OT for 50% adaptation. We calculated heat-related excess mortality for 2030 and 2050. Our new model is considered to be better fit, and more precise and robust compared with the previous model.

Surveillance of Heat-related Morbidity: Relation to Heat-related Excess Mortality

Deaths tend to lag extreme heat and mortality data is generally not available for timely surveillance during heat waves. We analyzed daily weather, emergency medical system (EMS) calls flagged as heat-related, emergency department (ED) visits classified as heat-related, and natural cause deaths. We observed a 10% (95% CI: 4-16) mortality increase associated with one-day lagged heat-related EMS calls and a 5% mortality increase with one-day lagged ED visits (95% CI: 2-8). We conclude heat-related illness can be tracked during heat waves using EMS and ED data which are indicators of heat associated excess natural cause mortality.

Heat-related mortality in the Florentine area (Italy) before and after the exceptional 2003 heat wave in Europe: an improved public health response?

High ambient temperatures have been associated with increased mortality across the world. Several studies suggest that timely preventive measures may reduce heat-related excess mortality. The main aim of this study was to detect the temporal modification of heat-related mortality, in older adults (aged 65-74) and in elderly ≥75 years old, in the Florentine area by comparing previous (1999-2002) and subsequent (2004-2007) periods to the summer of 2003, when a regional Heat-Health Warning System (HHWS) was set up. Mortality data from 1999 to 2007 (May-September) were provided by the Mortality Registry of the Tuscany Region (n = 21,092). Weather data were used to assess daily apparent temperatures (AT). Case-crossover time-stratified designs and constrained segmented distributed lag models were applied. No significant heat-related mortality odds ratio (OR) variations were observed among the sub-periods. Nevertheless, a general OR decrease dating from 1999-2002 (OR 1.23; lack of HHWS) to 2004-2005 (OR 1.21; experimental HHWS running only for Florence) and to 2006-2007 (OR 1.12; official HHWS extended to the whole Florentine area) was observed when the maximum AT was considered. This modification was only evident in subjects ≥75 years old. The heat effect was higher and sustained for more days (until lag 9) during the period 1999-2002 than 2004-2007. The decrease of the excessive heat effect on mortality between periods with the absence and existence of a HHWS is also probably due to the mitigation of preventive measures and the implementation of a HHWS with specific interventions for safeguarding the health of the "frail elderly".