Projections of temperature-attributable mortality in Europe: a time series analysis of 147 contiguous regions in 16 countries

Impact of Ambient Temperature on Mortality Burden and Spatial Heterogeneity in 16 Prefecture-Level Cities of a Low-Latitude Plateau Area in Yunnan Province: Time-Series Study

Background

The relation between climate change and human health has become one of the major worldwide public health issues. However, the evidence for low-latitude plateau regions is limited, where the climate is unique and diverse with a complex geography and topography.

objectives

This study aimed to evaluate the effect of ambient temperature on the mortality burden of nonaccidental deaths in Yunnan Province and to further explore its spatial heterogeneity among different regions.

Methods

We collected mortality and meteorological data from all 129 counties in Yunnan Province from 2014 to 2020, and 16 prefecture-level cities were analyzed as units. A distributed lagged nonlinear model was used to estimate the effect of temperature exposure on years of life lost (YLL) for nonaccidental deaths in each prefecture-level city. The attributable fraction of YLL due to ambient temperature was calculated. A multivariate meta-analysis was used to obtain an overall aggregated estimate of effects, and spatial heterogeneity among 16 prefecture-level cities was evaluated by adjusting the city-specific geographical characteristics, demographic characteristics, economic factors, and health resources factors.

Results

The temperature-YLL association was nonlinear and followed slide-shaped curves in all regions. The cumulative cold and heat effect estimates along lag 0-21 days on YLL for nonaccidental deaths were 403.16 (95% empirical confidence interval [eCI] 148.14-615.18) and 247.83 (95% eCI 45.73-418.85), respectively. The attributable fraction for nonaccidental mortality due to daily mean temperature was 7.45% (95% eCI 3.73%-10.38%). Cold temperature was responsible for most of the mortality burden (4.61%, 95% eCI 1.70-7.04), whereas the burden due to heat was 2.84% (95% eCI 0.58-4.83). The vulnerable subpopulations include male individuals, people aged <75 years, people with education below junior college level, farmers, nonmarried individuals, and ethnic minorities. In the cause-specific subgroup analysis, the total attributable fraction (%) for mean temperature was 13.97% (95% eCI 6.70-14.02) for heart disease, 11.12% (95% eCI 2.52-16.82) for respiratory disease, 10.85% (95% eCI 6.70-14.02) for cardiovascular disease, and 10.13% (95% eCI 6.03-13.18) for stroke. The attributable risk of cold effect for cardiovascular disease was higher than that for respiratory disease cause of death (9.71% vs 4.54%). Furthermore, we found 48.2% heterogeneity in the effect of mean temperature on YLL after considering the inherent characteristics of the 16 prefecture-level cities, with urbanization rate accounting for the highest proportion of heterogeneity (15.7%) among urban characteristics.

Conclusions

This study suggests that the cold effect dominated the total effect of temperature on mortality burden in Yunnan Province, and its effect was heterogeneous among different regions, which provides a basis for spatial planning and health policy formulation for disease prevention.

A systematic review of ambient heat and sleep in a warming climate

Climate change is elevating nighttime and daytime temperatures worldwide, affecting a broad continuum of behavioral and health outcomes. Disturbed sleep is a plausible pathway linking rising ambient temperatures with several observed adverse human responses shown to increase during hot weather. This systematic review aims to provide a comprehensive overview of the literature investigating the relationship between ambient temperature and valid sleep outcomes measured in real-world settings, globally. We show that higher outdoor or indoor temperatures are generally associated with degraded sleep quality and quantity worldwide. The negative effect of heat persists across sleep measures, and is stronger during the hottest months and days, in vulnerable populations, and the warmest regions. Although we identify opportunities to strengthen the state of the science, limited evidence of fast sleep adaptation to heat suggests rising temperatures induced by climate change and urbanization pose a planetary threat to human sleep, and therefore health, performance, and wellbeing.

Spatiotemporal distribution and lag effect of extreme temperature exposure on mortality of residents in Jiangsu, China

Background

With the ever-increasing occurrence of extreme weather events as a result of global climate change, the impact of extreme temperatures on human health has become a critical area of concern. Specifically, it is imperative to investigate the impact of extreme weather conditions on the health of residents.

Methods

In this study, we analyze the daily death data from 13 prefecture-level cities in Jiangsu Province from January 2014 to September 2022, using the distributed lag nonlinear model (DLNM) to comprehensively account for factors such as relative humidity, atmospheric pressure, air pollutants, and other factors to evaluate the lag and cumulative effects of extreme low temperature and high temperature on the death of residents across different age groups. Additionally, we utilize the Geographical Detector to analyze the effects of various meteorological and environmental factors on the distribution of resident death in Jiangsu Province. This provides valuable insights that can guide health authorities in decision-making and in the protection of residents.

Results

The experimental results indicate that both extreme low and high temperatures increase the mortality of residents. We observe that the impact of extreme low temperatures has a delayed effect, peaking after 3-5 days and lasting up to 11-21 days. In contrast, the impact of extreme high temperature is greatest on the first day, and lasts only 2-4 days.

Conclusion

Both extreme high and low temperatures increase the mortality of residents, with the former being more transient and stronger and the latter being more persistent and slower. Furthermore, residents over 75 years of age are more vulnerable to the effects of extreme temperatures. Finally, we note that the spatial distribution of resident deaths is most closely associated consistent with the spatial distribution of daily mean temperature, and there is significant spatial heterogeneity in deaths among residents in Jiangsu Province.

Spatial Bayesian distributed lag non-linear models (SB-DLNM) for small-area exposure-lag-response epidemiological modelling

BACKGROUND

Distributed lag non-linear models (DLNMs) are the reference framework for modelling lagged non-linear associations. They are usually used in large-scale multi-location studies. Attempts to study these associations in small areas either did not include the lagged non-linear effects, did not allow for geographically-varying risks or downscaled risks from larger spatial units through socioeconomic and physical meta-predictors when the estimation of the risks was not feasible due to low statistical power.

METHODS

Here we proposed spatial Bayesian DLNMs (SB-DLNMs) as a new framework for the estimation of reliable small-area lagged non-linear associations, and demonstrated the methodology for the case study of the temperature-mortality relationship in the 73 neighbourhoods of the city of Barcelona. We generalized location-independent DLNMs to the Bayesian framework (B-DLNMs), and extended them to SB-DLNMs by incorporating spatial models in a single-stage approach that accounts for the spatial dependence between risks.

RESULTS

The results of the case study highlighted the benefits of incorporating the spatial component for small-area analysis. Estimates obtained from independent B-DLNMs were unstable and unreliable, particularly in neighbourhoods with very low numbers of deaths. SB-DLNMs addressed these instabilities by incorporating spatial dependencies, resulting in more plausible and coherent estimates and revealing hidden spatial patterns. In addition, the Bayesian framework enriches the range of estimates and tests that can be used in both large- and small-area studies.

CONCLUSIONS

SB-DLNMs account for spatial structures in the risk associations across small areas. By modelling spatial differences, SB-DLNMs facilitate the direct estimation of non-linear exposure-response lagged associations at the small-area level, even in areas with as few as 19 deaths. The manuscript includes an illustrative code to reproduce the results, and to facilitate the implementation of other case studies by other researchers.

Projection of Mortality Burden Attributable to Nonoptimum Temperature with High Spatial Resolution in China

The updated climate models provide projections at a fine scale, allowing us to estimate health risks due to future warming after accounting for spatial heterogeneity. Here, we utilized an ensemble of high-resolution (25 km) climate simulations and nationwide mortality data from 306 Chinese cities to estimate death anomalies attributable to future warming. Historical estimation (1986-2014) reveals that about 15.5% [95% empirical confidence interval (eCI):13.1%, 17.6%] of deaths are attributable to nonoptimal temperature, of which heat and cold corresponded to attributable fractions of 4.1% (eCI:2.4%, 5.5%) and 11.4% (eCI:10.7%, 12.1%), respectively. Under three climate scenarios (SSP126, SSP245, and SSP585), the national average temperature was projected to increase by 1.45, 2.57, and 4.98 °C by the 2090s, respectively. The corresponding mortality fractions attributable to heat would be 6.5% (eCI:5.2%, 7.7%), 7.9% (eCI:6.3%, 9.4%), and 11.4% (eCI:9.2%, 13.3%). More than half of the attributable deaths due to future warming would occur in north China and cardiovascular mortality would increase more drastically than respiratory mortality. Our study shows that the increased heat-attributable mortality burden would outweigh the decreased cold-attributable burden even under a moderate climate change scenario across China. The results are helpful for national or local policymakers to better address the challenges of future warming.

A scoping review of human health co-benefits of forest-based climate change mitigation in Europe

Climate change is a pressing global challenge with profound implications for human health. Forest-based climate change mitigation strategies, such as afforestation, reforestation, and sustainable forest management, offer promising solutions to mitigate climate change and simultaneously yield substantial co-benefits for human health. The objective of this scoping review was to examine research trends related to the interdisciplinary nexus between forests as carbon sinks and human health co-benefits. We developed a conceptual framework model, supporting the inclusion of exposure pathways, such as recreational opportunities or aesthetic experiences, in the co-benefit context. We used a scoping review methodology to identify the proportion of European research on forest-based mitigation strategies that acknowledge the interconnection between mitigation strategies and human impacts. We also aimed to assess whether synergies and trade-offs between forest-based carbon sink capacity and human co-benefits has been analysed and quantified. From the initial 4,062 records retrieved, 349 reports analysed European forest management principles and factors related to climate change mitigation capacity. Of those, 97 studies acknowledged human co-benefits and 13 studies quantified the impacts on exposure pathways or health co-benefits and were included for full review. Our analysis demonstrates that there is potential for synergies related to optimising carbon sink capacity together with human co-benefits, but there is currently a lack of holistic research approaches assessing these interrelationships. We suggest enhanced interdisciplinary efforts, using for example multideterminant modelling approaches, to advance evidence and understanding of the forest and health nexus in the context of climate change mitigation.

Contribution of Cold Versus Climate Change to Mortality in London, UK, 1976-2019

Objectives. To quantify past reductions in cold-related mortality attributable to anthropogenic climate change. Methods. We performed a daily time-series regression analysis employing distributed lag nonlinear models of 1 203 981 deaths in Greater London, United Kingdom, in winter months (November-March) during 1976 to 2019. We made attribution assessment by comparing differential cold-related mortality impacts associated with observed temperatures to those using counterfactual temperatures representing no climate change. Results. Over the past decade, the average number of cold days (below 8 °C) per year was 120 in the observed series and 158 in the counterfactual series. Since 1976, we estimate 447 (95% confidence interval = 330, 559) annual cold-related all-cause deaths have been avoided because of milder temperatures associated with climate change. Annually, 241 cardiovascular and 73 respiratory disease deaths have been avoided. Conclusions. Anthropogenic climate change made some contribution to reducing previous cold-related deaths in London; however, cold remains an important public health risk factor. Public Health Implications. Better adaptation to both heat and cold should be promoted in public health measures to protect against climate change. In England, this has been addressed by the development of a new year-round Adverse Weather and Health Plan. (Am J Public Health. 2024;114(4):398-402. https://doi.org/10.2105/AJPH.2023.307552).

Countrywide analysis of heat- and cold-related mortality trends in the Czech Republic: growing inequalities under recent climate warming

BACKGROUND

Only little is known about trends in temperature-mortality associations among the most vulnerable subgroups, especially in the areas of central and eastern Europe, which are considered major climatic hotspots in terms of heatwave exposure. Thus, we aimed to assess trends in temperature-related mortality in the Czech Republic by sex, age and cause of death, and to quantify the temporal evolution of possible inequalities.

METHODS

We collected daily time series of all-cause (1987-2019) and cause-specific (1994-2019) mortality by sex and age category, and population-weighted daily mean 2-metre temperatures for each region of the Czech Republic. We applied a quasi-Poisson regression model to estimate the trends in region-specific temperature-mortality associations, with distributed lag non-linear models and multivariate random-effects meta-analysis to derive average associations across the country. We then calculated mortality attributable to non-optimal temperatures and implemented the indicator of sex- and age-dependent inequalities.

RESULTS

We observed a similar risk of mortality due to cold temperatures for men and women. Conversely, for warm temperatures, a higher risk was observed for women. Results by age showed a clear pattern of increasing risk due to non-optimum temperatures with increasing age category. The relative risk (RR) related to cold was considerably attenuated in most of the studied subgroups during the study period, whereas an increase in the RR associated with heat was seen in the overall population, in women, in the age category 90+ years and with respect to respiratory causes. Moreover, underlying sex- and age-dependent inequalities experienced substantial growth.

CONCLUSIONS

Our findings suggest ongoing adaptation to cold temperatures. Mal/adaptation to hot temperatures occurred unequally among population subgroups and resulted in growing inequalities between the sexes and among age categories.

The methodology of quantitative risk assessment studies

Once an external factor has been deemed likely to influence human health and a dose response function is available, an assessment of its health impact or that of policies aimed at influencing this and possibly other factors in a specific population can be obtained through a quantitative risk assessment, or health impact assessment (HIA) study. The health impact is usually expressed as a number of disease cases or disability-adjusted life-years (DALYs) attributable to or expected from the exposure or policy. We review the methodology of quantitative risk assessment studies based on human data. The main steps of such studies include definition of counterfactual scenarios related to the exposure or policy, exposure(s) assessment, quantification of risks (usually relying on literature-based dose response functions), possibly economic assessment, followed by uncertainty analyses. We discuss issues and make recommendations relative to the accuracy and geographic scale at which factors are assessed, which can strongly influence the study results. If several factors are considered simultaneously, then correlation, mutual influences and possibly synergy between them should be taken into account. Gaps or issues in the methodology of quantitative risk assessment studies include 1) proposing a formal approach to the quantitative handling of the level of evidence regarding each exposure-health pair (essential to consider emerging factors); 2) contrasting risk assessment based on human dose-response functions with that relying on toxicological data; 3) clarification of terminology of health impact assessment and human-based risk assessment studies, which are actually very similar, and 4) other technical issues related to the simultaneous consideration of several factors, in particular when they are causally linked.

The effect of temporal data aggregation to assess the impact of changing temperatures in Europe: an epidemiological modelling study

Background

Daily time-series regression models are commonly used to estimate the lagged nonlinear relation between temperature and mortality. A major impediment to this type of analysis is the restricted access to daily health records. The use of weekly and monthly data represents a possible solution unexplored to date.

Methods

We temporally aggregated daily temperatures and mortality records from 147 contiguous regions in 16 European countries, representing their entire population of over 400 million people. We estimated temperature-lag-mortality relationships by using standard time-series quasi-Poisson regression models applied to daily data, and compared the results with those obtained with different degrees of temporal aggregation.

Findings

We observed progressively larger differences in the epidemiological estimates with the degree of temporal data aggregation. The daily data model estimated an annual cold and heat-related mortality of 290,104 (213,745-359,636) and 39,434 (30,782-47,084) deaths, respectively, and the weekly model underestimated these numbers by 8.56% and 21.56%. Importantly, differences were systematically smaller during extreme cold and heat periods, such as the summer of 2003, with an underestimation of only 4.62% in the weekly data model. We applied this framework to infer that the heat-related mortality burden during the year 2022 in Europe may have exceeded the 70,000 deaths.

Interpretation

The present work represents a first reference study validating the use of weekly time series as an approximation to the short-term effects of cold and heat on human mortality. This approach can be adopted to complement access-restricted data networks, and facilitate data access for research, translation and policy-making.

Funding

The study was supported by the ERC Consolidator Grant EARLY-ADAPT (https://www.early-adapt.eu/), and the ERC Proof-of-Concept Grants HHS-EWS and FORECAST-AIR.

The influence of humid heat on morbidity of megacity Shanghai in China

BACKGROUND

Increased attention has been paid to humid-heat extremes as they are projected to increase in both frequency and intensity. However, it remains unclear how compound extremes of heat and humidity affects morbidity when the climate is projected to continue warming in the future, in particular for a megacity with a large population.

METHODS

We chose the Wet-Bulb Globe Temperature (WBGT) index as the metric to characterize the humid-heat exposure. The historical associations between daily outpatient visits and daily mean WBGT was established using a Distributed Lag Non-linear Model (DLNM) during the warm season (June to September) from 2013 to 2015 in Shanghai, a prominent megacity of China. Future morbidity burden related to the combined effect of high temperature and humidity were projected under four greenhouse gases (GHGs) emission scenarios (SSP126, SSP245, SSP370 and SSP585).

RESULTS

The humid-heat weather was significantly associated with a higher risk of outpatient visits in Shanghai than the high-temperature conditions. Relative to the baseline period (2010-2019), the morbidity burden due to humid-heat weather was projected to increase 4.4 % (95 % confidence interval (CI): 1.1 %-10.1 %) even under the strict emission control scenario (SSP126) by 2100. Under the high-GHGs emission scenario (SSP585), this burden was projected to be 25.4 % (95 % CI: 15.8 %-38.4 %), which is 10.1 % (95 % CI: 6.5 %-15.8 %) more than that due to high-temperature weather. Our results also indicate that humid-hot nights could cause large morbidity risks under high-GHGs emission scenarios particularly in heat-sensible diseases such as the respiratory and cardiovascular disease by the end of this century.

CONCLUSIONS

Humid heat exposures significantly increased the all-cause morbidity risk in the megacity Shanghai, especially in humid-hot nights. Our findings suggest that the combined effect of elevated temperature and humidity is projected to have more substantial impact on health compared to high temperature alone in a warming climate.

Towards a more integrated research framework for heat-related health risks and adaptation

Advances in research on current and projected heat-related risks from climate change and the associated responses have rapidly developed over the past decade. Modelling architectures of climate impacts and heat-related health risks have become increasingly sophisticated alongside a growing number of experiments and socioeconomic studies, and possible options for heat-related health adaptation are increasingly being catalogued and assessed. However, despite this progress, these efforts often remain isolated streams of research, substantially hampering our ability to contribute to evidence-informed decision making on responding to heat-related health risks. We argue that the integration of scientific efforts towards more holistic research is urgently needed to tackle fragmented evidence and identify crucial knowledge gaps, so that health research can better anticipate and respond to heat-related health risks in the context of a changing climate. In this Personal View, we outline six building blocks, each constituting a research stream, but each needed as part of a more integrated research framework-namely, projected heat-related health risks; adaptation options; the feasibility and effectiveness of adaptation; synergies, trade-offs, and co-benefits of adaptation; adaptation limits and residual risks; and adaptation pathways. We outline their respective importance and discuss their benefits for health-related research and policy.

Impact of environmental factors on diabetes mortality: A comparison between inland and coastal areas

BACKGROUND

Diabetes mortality varies between coastal and inland areas in Shandong Province, China. However, evidence about the reasons for this disparity is limited. We assume that distinct environmental conditions may contribute to the disparities in diabetes mortality patterns between coastal and inland areas.

METHOD

Qingdao and Jinan were selected as typical coastal and inland cities in Shandong Province, respectively, with similar socioeconomic but different environmental characteristics. Data on diabetes deaths and environmental factors (i.e., temperature, relative humidity and air pollution particles with a diameter of 2.5 μm or less (PM2.5)) were collected from 2013 to 2020. Spatial kriging methods were used to estimate the aggregated diabetes mortality at the city level. A distributed lag non-linear model (DLNM) was used to quantify the possible cumulative and non-cumulative associations between environmental factors and diabetes mortality by age, sex and location.

RESULTS

In the coastal city (Qingdao), the maximum cumulative relative risks (RRs) of temperature and PM2.5 associated with diabetes deaths were 2.54 (95 % confidence interval (CI): 1.25-5.15), and 1.17 (95 % CI: 1.01-1.37) respectively, at lag 1 week. In the inland city (Jinan), only temperature exhibited significant cumulative associations with diabetes deaths (RR = 1.54, 95 % CI: 1.07-2.23 at 29 °C). Lower relative humidity (22 %-45 %) had a lag-specific association with diabetes deaths in inland areas at lag 3 weeks (RR = 1.33, 95 % CI: 1.03-1.70 at 22 %).

CONCLUSION

Despite the lower PM2.5 concentrations in the coastal location, diabetes mortality exhibited stronger links to environmental variables in the coastal city than in the inland city. These findings suggest that the control of air pollution could decrease the mortality burden of diabetes, even in the region with relatively good air quality. Additionally, the spatial estimation method is recommended to identify associations between environmental factors and diseases in studies with limited data.

Projection of extreme heat- and cold-related mortality in Sweden based on the spatial synoptic classification

BACKGROUND

Climate change is projected to result in increased heat events and decreased cold events. This will substantially impact human health, particularly when compounded with demographic change. This study employed the Spatial Synoptic Classification (SSC) to categorize daily weather into one of seven types. Here we estimated future mortality due to extremely hot and cold weather types under different climate change scenarios for one southern (Stockholm) and one northern (Jämtland) Swedish region.

METHODS

Time-series Poisson regression with distributed lags was used to assess the relationship between extremely hot and cold weather events and daily deaths in the population above 65 years, with cumulative effects (6 days in summer, 28 days in winter), 1991 to 2014. A global climate model (MPI-M-MPI-ESM-LR) and two climate change scenarios (RCP 4.5 and 8.5) were used to project the occurrence of hot and cold days from 2031 to 2070. Place-specific projected mortality was calculated to derive attributable numbers and attributable fractions (AF) of heat- and cold-related deaths.

RESULTS

In Stockholm, for the RCP 4.5 scenario, the mean number of annual deaths attributed to heat increased from 48.7 (CI 32.2-64.2; AF = 0.68%) in 2031-2040 to 90.2 (56.7-120.5; AF = 0.97%) in 2061-2070, respectively. For RCP 8.5, heat-related deaths increased more drastically from 52.1 (33.6-69.7; AF = 0.72%) to 126.4 (68.7-175.8; AF = 1.36%) between the first and the last decade. Cold-related deaths slightly increased over the projected period in both scenarios. In Jämtland, projections showed a small decrease in cold-related deaths but no change in heat-related mortality.

CONCLUSIONS

In rural northern region of Sweden, a decrease of cold-related deaths represents the dominant trend. In urban southern locations, on the other hand, an increase of heat-related mortality is to be expected. With an increasing elderly population, heat-related mortality will outweigh cold-related mortality at least under the RCP 8.5 scenario, requiring societal adaptation measures.

Temperature-related death burden of various neurodegenerative diseases under climate warming: a nationwide modelling study

Limited knowledge exists regarding the ramifications of climate warming on death burden from neurodegenerative diseases. Here, we conducted a nationwide, individual-level, case-crossover study between 2013 and 2019 to investigate the effects of non-optimal temperatures on various neurodegenerative diseases and to predict the potential death burden under different climate change scenarios. Our findings reveal that both low and high temperatures are linked to increased risks of neurodegenerative diseases death. We project that heat-related neurodegenerative disease deaths would increase, while cold-related deaths would decrease. This is characterized by a steeper slope in the high-emission scenario, but a less pronounced trend in the scenarios involving mitigation strategies. Furthermore, we predict that the net changes in attributable death would increase after the mid-21st century, especially under the unrestricted-emission scenario. These results highlight the urgent need for effective climate and public health policies to address the growing challenges of neurodegenerative diseases associated with global warming.

Ambient temperature and seasonal variation in inpatient mortality from respiratory diseases: a retrospective observational study

Background

The seasonal fluctuation in mortality and hospital admissions from respiratory diseases, with a winter peak and a summer trough, is widely recognized in extratropical countries. However, little is known about the seasonality of inpatient mortality and the role of ambient temperature remains uncertain. We aimed to analyse the association between ambient temperature and in-hospital mortality from respiratory diseases in the provinces of Madrid and Barcelona, Spain.

Methods

We used data on daily hospitalisations, weather (ie, temperature and relative humidity) and air pollutants (ie, PM2.5, PM10, NO2 and O3) for the Spanish provinces of Madrid and Barcelona during 2006-2019. We applied a daily time-series quasi-Poisson regression in combination with distributed lag non-linear models (DLNM) to assess, on the one hand, the seasonal variation in fatal hospitalisations and the contribution of ambient temperature, and on the other hand, the day-to-day association between temperature and fatal hospital admissions. The analyses were stratified by sex, age and primary diagnostic of hospitalisation.

Findings

The study analysed 1 710 012 emergency hospital admissions for respiratory diseases (mean [SD] age, 60.4 [31.0] years; 44.2% women), from which 103 845 resulted in in-hospital death (81.4 [12.3] years; 45.1%). We found a strong seasonal fluctuation in in-hospital mortality from respiratory diseases. While hospital admissions were higher during the cold season, the maximum incidence of inpatient mortality was during the summer and was strongly related to high temperatures. When analysing the day-to-day association between temperature and in-hospital mortality, we only found an effect for high temperatures. The relative risk (RR) of fatal hospitalisation at the 99th percentile of the distribution of daily temperatures vs the minimum mortality temperature (MMT) was 1.395 (95% eCI: 1.211-1.606) in Madrid and 1.612 (1.379-1.885) in Barcelona. In terms of attributable burden, summer temperatures (June-September) were responsible for 16.2% (8.8-23.3) and 22.3% (15.4-29.2) of overall fatal hospitalisations from respiratory diseases in Madrid and Barcelona, respectively. Women were more vulnerable to heat than men, whereas the results by diagnostic of admission showed heat effects for acute bronchitis and bronchiolitis, pneumonia and respiratory failure.

Interpretation

Unless effective adaptation measures are taken in hospital facilities, climate warming could exacerbate the burden of inpatient mortality from respiratory diseases during the warm season.

Funding

European Research Council Consolidator Grant EARLY-ADAPT, European Research Council Proof-of-Concept Grants HHS-EWS and FORECAST-AIR.

Projection of high temperature-related burden of kidney disease in Australia under different climate change, population and adaptation scenarios: population-based study

Background

The dual impacts of a warming climate and population ageing lead to an increasing kidney disease prevalence, highlighting the importance of quantifying the burden of kidney disease (BoKD) attributable to high temperature, yet studies on this subject are limited. The study aims to quantify the BoKD attributable to high temperatures in Australia across all states and territories, and project future BoKD under climatic, population and adaptation scenarios.

Methods

Data on disability-adjusted-life-years (DALYs) due to kidney disease, including years of life lost (YLL), and years lived with disability (YLD), were collected during 2003-2018 (baseline) across all states and territories in Australia. The temperature-response association was estimated using a meta-regression model. Future temperature projections were calculated using eight downscaled climate models to estimate changes in attributable BoKD centred around 2030s and 2050s, under two greenhouse gas emissions scenarios (RCP4.5 and RCP8.5), while considering changes in population size and age structure, and human adaptation to climate change.

Findings

Over the baseline (2003-2018), high-temperature contributed to 2.7% (Standard Deviation: 0.4%) of the observed BoKD in Australia. The future population attributable fraction and the attributable BoKD, projected using RCP4.5 and RCP8.5, showed a gradually increasing trend when assuming no human adaptation. Future projections were most strongly influenced by the population change, with the high temperature-related BoKD increasing by 18.4-67.4% compared to the baseline under constant population and by 100.2-291.2% when accounting for changes in population size and age structure. However, when human adaptation was adopted (from no to partial to full), the high temperature-related BoKD became smaller.

Interpretation

It is expected that increasing high temperature exposure will substantially contribute to higher BoKD across Australia, underscoring the urgent need for public health interventions to mitigate the negative health impacts of a warming climate on BoKD.

Funding

Australian Research Council Discovery Program.

Drivers of the time-varying heat-cold-mortality association in Spain: A longitudinal observational study

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.

Cascading climate effects in deep reservoirs: Full assessment of physical and biogeochemical dynamics under ensemble climate projections and ways towards adaptation

We coupled twenty-first century climate projections with a well-established water quality model to depict future ecological changes of Rappbode Reservoir, Germany. Our results document a chain of climate-driven effects propagating through the aquatic ecosystem and interfering with drinking water supply: intense climate warming (RCP8.5 scenario) will firstly trigger a strong increase in water temperatures, in turn leading to metalimnetic hypoxia, accelerating sediment nutrient release and finally boosting blooms of the cyanobacterium Planktothrix rubescens. Such adverse water quality developments will be suppressed under RCP2.6 and 6.0 indicating that mitigation of climate change is improving water security. Our results also suggested surface withdrawal can be an effective adaptation strategy to make the reservoir ecosystem more resilient to climate warming. The identified consequences from climate warming and adaptation strategies are relevant to many deep waters in the temperate zone, and the conclusion should provide important guidances for stakeholders to confront potential climate changes.

Projections of Temperature-Related Suicide under Climate Change Scenarios in Japan

BACKGROUND

The impact of climate change on mental health largely remains to be evaluated. Although growing evidence has reported a short-term association between suicide and temperature, future projections of temperature-attributable suicide have not been thoroughly examined.

OBJECTIVES

We aimed to project the excess temperature-related suicide mortality in Japan under three climate change scenarios until the 2090s.

METHODS

Daily time series of mean temperature and the number of suicide deaths in 1973-2015 were collected for 47 prefectures in Japan. A two-stage time-stratified case-crossover analysis was used to estimate the temperature-suicide association. We obtained the modeled daily temperature series using five general circulation models under three climate change scenarios from the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathways scenarios (SSPs): SSP1-2.6, SSP2-4.5, and SSP5-8.5. We projected the excess temperature-related suicide mortality until 2099 for each scenario and evaluated the net relative changes compared with the 2010s.

RESULTS

During 1973-2015, there was a total of 1,049,592 suicides in Japan. Net increases in temperature-related excess suicide mortality were estimated under all scenarios. The net change in 2090-2099 compared with 2010-2019 was 1.3% [95% empirical confidence interval (eCI): 0.6, 2.4] for the intermediate-emission scenario (SSP2-4.5), 0.6% (95% eCI: 0.1, 1.6) for a low-emission scenario (SSP1-2.6), and 2.4% (95% eCI: 0.7, 3.9) for the extreme scenario (SSP5-8.5). The increases were greater the more extreme the scenarios were, with the highest increase under the most extreme scenario (SSP5-8.5).

DISCUSSION

This study indicates that Japan may experience a net increase in excess temperature-related suicide mortality, especially under the intermediate and extreme scenarios. The findings underscore the importance of mitigation policies. Further investigations of the future impacts of climate change on mental health including suicide are warranted. https://doi.org/10.1289/EHP11246.

Future temperature-related excess mortality under climate change and population aging scenarios in Canada

OBJECTIVE

Climate change is expected to increase global temperatures. How temperature-related mortality risk will change is not completely understood, and how future demographic changes will affect temperature-related mortality needs to be clarified. We evaluate temperature-related mortality across Canada until 2099, accounting for age groups and scenarios of population growth.

METHODS

We used daily counts of non-accidental mortality for 2000 to 2015 for all 111 health regions across Canada, incorporating in the study both urban and rural areas. A two-part time series analysis was used to estimate associations between mean daily temperatures and mortality. First, current and future daily mean temperature time series simulations were developed from Coupled Model Inter-Comparison Project 6 (CMIP6) climate model ensembles from past and projected climate change scenarios under Shared Socioeconomic Pathways (SSPs). Next, excess mortality due to heat and cold and the net difference were projected to 2099, also accounting for different regional and population aging scenarios.

RESULTS

For 2000 to 2015, we identified 3,343,311 non-accidental deaths. On average, a net increase of 17.31% (95% eCI: 13.99, 20.62) in temperature-related excess mortality under a higher greenhouse gas emission scenario is expected for Canada in 2090-2099, which represents a greater burden than a scenario that assumed strong levels of greenhouse gas mitigation policies (net increase of 3.29%; 95% eCI: 1.41, 5.17). The highest net increase was observed among people aged 65 and over, and the largest increases in both net and heat- and cold-related mortality were observed in population scenarios that incorporated the highest rates of aging.

CONCLUSION

Canada may expect net increases in temperature-related mortality under a higher emissions climate change scenario, compared to one assuming sustainable development. Urgent action is needed to mitigate future climate change impacts.

Observational and model evidence together support wide-spread exposure to noncompensable heat under continued global warming

As our planet warms, a critical research question is when and where temperatures will exceed the limits of what the human body can tolerate. Past modeling efforts have investigated the 35°C wet-bulb threshold, proposed as a theoretical upper limit to survivability taking into account physiological and behavioral adaptation. Here, we conduct an extreme value theory analysis of weather station observations and climate model projections to investigate the emergence of an empirically supported heat compensability limit. We show that the hottest parts of the world already experience these heat extremes on a limited basis and that under moderate continued warming parts of every continent, except Antarctica, will see a rapid increase in their extent and frequency. To conclude, we discuss the consequences of the emergence of this noncompensable heat and the need for incorporating different critical thermal limits into heat adaptation planning.

The Direct and Indirect Influences of Interrelated Regional-Level Sociodemographic Factors on Heat-Attributable Mortality in Europe: Insights for Adaptation Strategies

BACKGROUND

Heat is a significant cause of mortality, but impact patterns are heterogenous. Previous studies assessing such heterogeneity focused exclusively on risk rather than heat-attributable mortality burdens and assume predictors are independent.

OBJECTIVES

We assessed how four interrelated regional-level sociodemographic predictors-education, life expectancy, the ratio of older to younger people (aging index), and relative income-influence heterogeneity in heat-attributable mortality burdens in Europe and then derived insights into adaptation strategies.

METHODS

We extracted four outcomes from a temperature-mortality study covering 16 European countries: the rate of increase in mortality risk at moderate and extreme temperatures (moderate and extreme slope, respectively), the minimum mortality temperature percentile (MMTP), and the underlying mortality rate. We used structural equation modeling with country-level random effects to quantify the direct and indirect influences of the predictors on the outcomes.

RESULTS

Higher levels of education were directly associated with lower heat-related mortality at moderate and extreme temperatures via lower slopes and higher MMTPs. A one standard deviation increase in education was associated with a - 0.46 ± 0.14 , - 0.41 ± 0.12 , and 0.41 ± 0.12 standard deviation (± standard error ) change in the moderate slope, extreme slope, and MMTP, respectively. However, education had mixed indirect influences via associations with life expectancy, the aging index, and relative income. Higher life expectancy had mixed relations with heat-related mortality, being associated with higher risk at moderate temperatures (0.33 ± 0.11 for the moderate slope; - 0.19 ± 0.097 for the MMTP) but lower underlying mortality rates (- 0.72 ± 0.097 ). A higher aging index was associated with higher burdens through higher risk at extreme temperatures (0.13 ± 0.072 for the extreme slope) and higher underlying mortality rates (0.93 ± 0.055 ). Relative income had relatively small, mixed influences.

DISCUSSION

Our novel approach provided insights into actions for reducing the health impacts of heat. First, the results show the interrelations between possible vulnerability-generating mechanisms and suggest future research directions. Second, the findings point to the need for a dual approach to adaptation, with actions that explicitly target heat exposure reduction and actions focused explicitly on the root causes of vulnerability. For the latter, the climate crisis may be leveraged to accelerate ongoing general public health programs. https://doi.org/10.1289/EHP11766.

Urban heat island impacts on heat-related cardiovascular morbidity: A time series analysis of older adults in US metropolitan areas

Many United States (US) cities are experiencing urban heat islands (UHIs) and climate change-driven temperature increases. Extreme heat increases cardiovascular disease (CVD) risk, yet little is known about how this association varies with UHI intensity (UHII) within and between cities. We aimed to identify the urban populations most at-risk of and burdened by heat-related CVD morbidity in UHI-affected areas compared to unaffected areas. ZIP code-level daily counts of CVD hospitalizations among Medicare enrollees, aged 65-114, were obtained for 120 US metropolitan statistical areas (MSAs) between 2000 and 2017. Mean ambient temperature exposure was estimated by interpolating daily weather station observations. ZIP codes were classified as low and high UHII using the first and fourth quartiles of an existing surface UHII metric, weighted to each have 25% of all CVD hospitalizations. MSA-specific associations between ambient temperature and CVD hospitalization were estimated using quasi-Poisson regression with distributed lag non-linear models and pooled via multivariate meta-analyses. Across the US, extreme heat (MSA-specific 99th percentile, on average 28.6 °C) increased the risk of CVD hospitalization by 1.5% (95% CI: 0.4%, 2.6%), with considerable variation among MSAs. Extreme heat-related CVD hospitalization risk in high UHII areas (2.4% [95% CI: 0.4%, 4.3%]) exceeded that in low UHII areas (1.0% [95% CI: -0.8%, 2.8%]), with upwards of a 10% difference in some MSAs. During the 18-year study period, there were an estimated 37,028 (95% CI: 35,741, 37,988) heat-attributable CVD admissions. High UHII areas accounted for 35% of the total heat-related CVD burden, while low UHII areas accounted for 4%. High UHII disproportionately impacted already heat-vulnerable populations; females, individuals aged 75-114, and those with chronic conditions living in high UHII areas experienced the largest heat-related CVD impacts. Overall, extreme heat increased cardiovascular morbidity risk and burden in older urban populations, with UHIs exacerbating these impacts among those with existing vulnerabilities.

Intra-urban risk assessment of occupational injuries and illnesses associated with current and projected climate: Evidence from three largest Australian cities

BACKGROUND

Increased risk of occupational injuries and illnesses (OI) is associated with ambient temperature. However, most studies have reported the average impacts within cities, states, or provinces at broader scales.

METHODS

We assessed the intra-urban risk of OI associated with ambient temperature in three Australian cities at statistical area level 3 (SA3). We collected daily workers' compensation claims data and gridded meteorological data from July 1, 2005, to June 30, 2018. Heat index was used as the primary temperature metric. We performed a two-stage time series analysis: we generated location-specific estimates using Distributed Lag Non-Linear Models (DLNM) and estimated the cumulative effects with multivariate meta-analysis. The risk was estimated at moderate heat (90th percentile) and extreme heat (99th percentile). Subgroup analyses were conducted to identify vulnerable groups of workers. Further, the OI risk in the future was estimated for two projected periods: 2016-2045 and 2036-2065.

RESULTS

The cumulative risk of OI was 3.4% in Greater Brisbane, 9.5% in Greater Melbourne, and 8.9% in Greater Sydney at extreme heat. The western inland regions in Greater Brisbane (17.4%) and Greater Sydney (32.3%) had higher risk of OI for younger workers, workers in outdoor and indoor industries, and workers reporting injury claims. The urbanized SA3 regions posed a higher risk (19.3%) for workers in Greater Melbourne. The regions were generally at high risk for young workers and illness-related claims. The projected risk of OI increased with time in climate change scenarios.

CONCLUSIONS

This study provides a comprehensive spatial profile of OI risk associated with hot weather conditions across three cities in Australia. Risk assessment at the intra-urban level revealed strong spatial patterns in OI risk distribution due to heat exposure. These findings provide much-needed scientific evidence for work, health, and safety regulators, industries, unions, and workers to design and implement location-specific preventative measures.

Heat-related mortality in Europe during the summer of 2022

Over 70,000 excess deaths occurred in Europe during the summer of 2003. The resulting societal awareness led to the design and implementation of adaptation strategies to protect at-risk populations. We aimed to quantify heat-related mortality burden during the summer of 2022, the hottest season on record in Europe. We analyzed the Eurostat mortality database, which includes 45,184,044 counts of death from 823 contiguous regions in 35 European countries, representing the whole population of over 543 million people. We estimated 61,672 (95% confidence interval (CI) = 37,643-86,807) heat-related deaths in Europe between 30 May and 4 September 2022. Italy (18,010 deaths; 95% CI = 13,793-22,225), Spain (11,324; 95% CI = 7,908-14,880) and Germany (8,173; 95% CI = 5,374-11,018) had the highest summer heat-related mortality numbers, while Italy (295 deaths per million, 95% CI = 226-364), Greece (280, 95% CI = 201-355), Spain (237, 95% CI = 166-312) and Portugal (211, 95% CI = 162-255) had the highest heat-related mortality rates. Relative to population, we estimated 56% more heat-related deaths in women than men, with higher rates in men aged 0-64 (+41%) and 65-79 (+14%) years, and in women aged 80+ years (+27%). Our results call for a reevaluation and strengthening of existing heat surveillance platforms, prevention plans and long-term adaptation strategies.

The interactive effects of extreme temperatures and PM2.5 pollution on mortalities in Jiangsu Province, China

Exposure to extreme temperatures or fine particles is associated with adverse health outcomes but their interactive effects remain unclear. We aimed to explore the interactions of extreme temperatures and PM2.5 pollution on mortalities. Based on the daily mortality data collected during 2015-2019 in Jiangsu Province, China, we conducted generalized linear models with distributed lag non-linear model to estimate the regional-level effects of cold/hot extremes and PM2.5 pollution. The relative excess risk due to interaction (RERI) was evaluated to represent the interaction. The relative risks (RRs) and cumulative relative risks (CRRs) of total and cause-specific mortalities associated with hot extremes were significantly stronger (p < 0.05) than those related to cold extremes across Jiangsu. We identified significantly higher interactions between hot extremes and PM2.5 pollution, with the RERI range of 0.00-1.15. The interactions peaked on ischaemic heart disease (RERI = 1.13 [95%CI: 0.85, 1.41]) in middle Jiangsu. For respiratory mortality, RERIs were higher in females and the less educated. The interaction pattern remained consistent when defining the extremes/pollution with different thresholds. This study provides a comprehensive picture of the interactions between extreme temperatures and PM2.5 pollution on total and cause-specific mortalities. The projected interactions call for public health actions to face the twin challenges, especially the co-appearance of hot extremes and PM pollution.

Assessing the Burden of Suicide Death Associated With Nonoptimum Temperature in a Changing Climate

Importance

Few studies have projected future suicide burden associated with daily temperatures in a warming climate.

Objectives

To assess the burden of suicide death associated with daily nonoptimal temperature and to project the change of suicide burden associated with nonoptimal temperature in different regions and seasons under various climate change scenarios.

Design, Setting, and Participants

Between January 1, 2013, and December 31, 2019, we conducted a time-stratified, case-control study among more than 430 000 individual suicide decedents from all counties in mainland China.

Exposures

Daily meteorological data were obtained from the European Centre for Medium-Range Weather Forecasts Reanalysis Fifth Generation (ERA5) reanalysis product. Historical and future temperature series were projected under 3 scenarios of greenhouse-gas emissions from 1980 to 2099, with 10 general circulation models.

Main Outcomes and Measures

The relative risk (RR) and burden of suicide death associated with nonoptimal temperature (ie, temperatures greater than or less than minimum-mortality temperature); the change of suicide burden associated with future climate warming in different regions and seasons under various climate change scenarios.

Results

Of 432 008 individuals (mean [SD] age; 57.6 [19.0] years; 253 093 male [58.6%]) who died by suicide, 85.8% (370 577) had a middle school education or less. The temperature-suicide associations were approximately linear, with increasing death risks at higher temperatures. The excess risk was more prominent among older adults (ie, ≥75 years; RR, 1.71; 95% CI, 1.46-1.99) and those with low education level (ie, middle school education or less; RR, 1.46; 95% CI, 1.36-1.57). There were 15.2% suicide deaths (95% estimated CI [eCI], 14.6%-15.6%) associated with nonoptimal temperature nationally. Consistent and drastic increases in excess suicide deaths over this century were predicted under the high-emission scenario, whereas a leveling-off trend after the mid-21st century was predicted under the medium- and low-emission scenarios. Nationally, compared with the historical period (1980-2009), excess suicide deaths were predicted to increase by 8.3% to 11.4% in the 2050s and 8.5% to 21.7% in the 2090s under the 3 scenarios. The projected percentage increments of excess suicide deaths were predicted to be greater in the South (55.0%; 95% eCI, 30.5%-85.6%) and in winter (54.5%; 95% eCI, 30.4%-77.0%) in the 2090s under the high-emission scenario.

Conclusions and Relevance

Findings of this nationwide case-control study suggest that higher temperature may be associated with the risk and burden of suicide death in China. These findings highlight the importance of implementing effective climate policies to reduce greenhouse gas emissions and tailoring public health policies to adapt to global warming.

Excess mortality attributed to heat and cold: a health impact assessment study in 854 cities in Europe

BACKGROUND

Heat and cold are established environmental risk factors for human health. However, mapping the related health burden is a difficult task due to the complexity of the associations and the differences in vulnerability and demographic distributions. In this study, we did a comprehensive mortality impact assessment due to heat and cold in European urban areas, considering geographical differences and age-specific risks.

METHODS

We included urban areas across Europe between Jan 1, 2000, and Dec 12, 2019, using the Urban Audit dataset of Eurostat and adults aged 20 years and older living in these areas. Data were extracted from Eurostat, the Multi-country Multi-city Collaborative Research Network, Moderate Resolution Imaging Spectroradiometer, and Copernicus. We applied a three-stage method to estimate risks of temperature continuously across the age and space dimensions, identifying patterns of vulnerability on the basis of city-specific characteristics and demographic structures. These risks were used to derive minimum mortality temperatures and related percentiles and raw and standardised excess mortality rates for heat and cold aggregated at various geographical levels.

FINDINGS

Across the 854 urban areas in Europe, we estimated an annual excess of 203 620 (empirical 95% CI 180 882-224 613) deaths attributed to cold and 20 173 (17 261-22 934) attributed to heat. These corresponded to age-standardised rates of 129 (empirical 95% CI 114-142) and 13 (11-14) deaths per 100 000 person-years. Results differed across Europe and age groups, with the highest effects in eastern European cities for both cold and heat.

INTERPRETATION

Maps of mortality risks and excess deaths indicate geographical differences, such as a north-south gradient and increased vulnerability in eastern Europe, as well as local variations due to urban characteristics. The modelling framework and results are crucial for the design of national and local health and climate policies and for projecting the effects of cold and heat under future climatic and socioeconomic scenarios.

FUNDING

Medical Research Council of UK, the Natural Environment Research Council UK, the EU's Horizon 2020, and the EU's Joint Research Center.

Current and future trends in heat-related mortality in the MENA region: a health impact assessment with bias-adjusted statistically downscaled CMIP6 (SSP-based) data and Bayesian inference

BACKGROUND

The Middle East and North Africa (MENA) is one of the regions that is most vulnerable to the negative effects of climate change, yet the potential public health impacts have been underexplored compared to other regions. We aimed to examine one aspect of these impacts, heat-related mortality, by quantifying the current and future burden in the MENA region and identifying the most vulnerable countries.

METHODS

We did a health impact assessment using an ensemble of bias-adjusted statistically downscaled Coupled Model Intercomparison Project phase 6 (CMIP6) data based on four Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2·6 [consistent with a 2°C global warming scenario], SSP2-4·5 [medium pathway scenario], SSP3-7·0 [pessimistic scenario], and SSP5-8·5 [high emissions scenario]) and Bayesian inference methods. Assessments were based on apparent temperature-mortality relationships specific to each climate subregion of MENA based on Koppen-Geiger climate type classification, and unique thresholds were characterised for each 50 km grid cell in the region. Future annual heat-related mortality was estimated for the period 2021-2100. Estimates were also presented with population held constant to quantify the contribution of projected demographic changes to the future heat-mortality burden.

FINDINGS

The average annual heat-related death rate across all MENA countries is currently 2·1 per 100 000 people. Under the two high emissions scenarios (SSP3-7·0 and SSP5-8·5), most of the MENA region will have experienced substantial warming by the 2060s. Annual heat-related deaths of 123·4 per 100 000 people are projected for MENA by 2100 under a high emissions scenario (SSP5-8·5), although this rate would be reduced by more than 80% (to 20·3 heat-related deaths per 100 000 people per year) if global warming could be limited to 2°C (ie, under the SSP1-2·6 scenario). Large increases are also expected by 2100 under the SSP3-7·0 scenario (89·8 heat-related deaths per 100 000 people per year) due to the high population growth projected under this pathway. Projections in MENA are far higher than previously observed in other regions, with Iran expected to be the most vulnerable country.

INTERPRETATION

Stronger climate change mitigation and adaptation policies are needed to avoid these heat-related mortality impacts. Since much of this increase will be driven by population changes, demographic policies and healthy ageing will also be key to successful adaptation.

FUNDING

National Institute for Health Research, EU Horizon 2020.

Cooling cities through urban green infrastructure: a health impact assessment of European cities

BACKGROUND

High ambient temperatures are associated with many health effects, including premature mortality. The combination of global warming due to climate change and the expansion of the global built environment mean that the intensification of urban heat islands (UHIs) is expected, accompanied by adverse effects on population health. Urban green infrastructure can reduce local temperatures. We aimed to estimate the mortality burden that could be attributed to UHIs and the mortality burden that would be prevented by increasing urban tree coverage in 93 European cities.

METHODS

We did a quantitative health impact assessment for summer (June 1-Aug 31), 2015, of the effect of UHIs on all-cause mortality for adults aged 20 years or older in 93 European cities. We also estimated the temperature reductions that would result from increasing tree coverage to 30% for each city and estimated the number of deaths that could be potentially prevented as a result. We did all analyses at a high-resolution grid-cell level (250 × 250 m). We propagated uncertainties in input analyses by using Monte Carlo simulations to obtain point estimates and 95% CIs. We also did sensitivity analyses to test the robustness of our estimates.

FINDINGS

The population-weighted mean city temperature increase due to UHI effects was 1·5°C (SD 0·5; range 0·5-3·0). Overall, 6700 (95% CI 5254-8162) premature deaths could be attributable to the effects of UHIs (corresponding to around 4·33% [95% CI 3·37-5·28] of all summer deaths). We estimated that increasing tree coverage to 30% would cool cities by a mean of 0·4°C (SD 0·2; range 0·0-1·3). We also estimated that 2644 (95% CI 2444-2824) premature deaths could be prevented by increasing city tree coverage to 30%, corresponding to 1·84% (1·69-1·97) of all summer deaths.

INTERPRETATION

Our results showed the deleterious effects of UHIs on mortality and highlighted the health benefits of increasing tree coverage to cool urban environments, which would also result in more sustainable and climate-resilient cities.

FUNDING

GoGreenRoutes, Spanish Ministry of Science and Innovation, Institute for Global Health, UK Medical Research Council, European Union's Horizon 2020 Project Exhaustion.

Temperature, cardiovascular mortality, and the role of hypertension and renin-angiotensin-aldosterone axis in seasonal adversity: a narrative review

Environmental temperature is now well known to have a U-shaped relationship with cardiovascular (CV) and all-cause mortality. Both heat and cold above and below an optimum temperature, respectively, are associated with adverse outcomes. However, cold in general and moderate cold specifically is predominantly responsible for much of temperature-attributable adversity. Importantly, hypertension-the most important CV risk factor-has seasonal variation such that BP is significantly higher in winter. Besides worsening BP control in established hypertensives, cold-induced BP increase also contributes to long-term BP variability among normotensive and pre-hypertensive patients, also a known CV risk factor. Disappointingly, despite the now well-stablished impact of temperature on BP and on CV mortality separately, direct linkage between seasonal BP change and CV outcomes remains preliminary. Proving or disproving this link is of immense clinical and public health importance because if seasonal BP variation contributes to seasonal adversity, this should be a modifiable risk. Mechanistically, existing evidence strongly suggests a central role of the sympathetic nervous system (SNS), and secondarily, the renin-angiotensin-aldosterone axis (RAAS) in mediating cold-induced BP increase. Though numerous other inflammatory, metabolic, and vascular perturbations likely also contribute, these may also well be secondary to cold-induced SNS/RAAS activation. This review aims to summarize the current evidence linking temperature, BP and CV outcomes. We also examine underlying mechanisms especially in regard to the SNS/RAAS axis, and highlight possible mitigation measures for clinicians.

Association of Daily Temperature With Suicide Mortality: A Comparison With Other Causes of Death and Characterization of Possible Attenuation Across 5 Decades

Suicide is one of the leading causes of death in young adults in many Western countries. We examined the short-term association of temperature with cause-specific mortality, comparing suicide with other causes of death and describing possible attenuation of associations with temperature across decades. We considered all deaths that occurred in France between 1968 and 2016. For each cause of death, we conducted a 2-stage meta-analysis of associations with daily temperature. We stratified the association across time periods. A total of 502,017 deaths by suicide were recorded over 49 years. Temperature was monotonically associated with suicide mortality. The strongest association was found at lag 0 days. The relative risk of suicide mortality at the 99th (compared with the 1st) temperature percentile was 1.54 (95% confidence interval, 1.46, 1.63). Among all causes of death, suicide was the only cause displaying a monotonic trend with temperature and ranked seventh for heat-related mortality; 2 other causes of death implying the nervous system ranked third and fourth. Associations with temperature attenuated between the 1968-1984 and 1985-2000 periods for all-cause mortality and suicide mortality, without clear further attenuation in the 2001-2016 period. The robust short-term monotonic association between temperature and suicide risk could be considered in heat effects- and suicide-related prevention campaigns.

Burden of diabetes and kidney disease attributable to non-optimal temperature from 1990 to 2019: A systematic analysis from the Global Burden of Disease Study 2019

INTRODUCTION

This study quantitatively described the disease burden of diabetes and kidney disease attributable to non-optimal temperatures and explored the influencing factors.

METHODS

We quantitatively described the mortality burden of diabetes and kidney disease attributable to non-optimal temperatures in six countries (China, USA, South Africa, Australia, Iraq, Portugal), and compare trends in mortality in six countries from 1990 to 2019. We used the APC model to analyse age, period, and cohort effects on mortality in six countries. We used restricted cubic splines and quantile regression to analyse the association of SDI with mortality and YLL using data from 21 regions in the world.

RESULTS

The mortality rates of diabetes and kidney disease in the six countries in 2019 were 1.72% (Australia), 1.83% (China), 2.99% (USA), 3% (Portugal), 7.45% (South Africa) and 8.71% (Iraq) attributable to non-optimal temperatures. Cold was more harmful than heat. The mortality, YLLs of diabetes and kidney disease of male were higher than females. The mortality rate showed an upwards trend with age. The period effect had little changes or showed a slight upwards trend. The cohort effect showed a downwards trend. The regions with higher mortality or YLLs rates were mainly had SDI values of 0.45-0.80.

CONCLUSIONS

Among the death burdens of diabetes and kidney disease attributed to non-optimal temperatures, cold had a greater burden than heat. The burden of death was affected by sex, age, period, cohort, and SDI.

City-level impact of extreme temperatures and mortality in Latin America

Climate change and urbanization are rapidly increasing human exposure to extreme ambient temperatures, yet few studies have examined temperature and mortality in Latin America. We conducted a nonlinear, distributed-lag, longitudinal analysis of daily ambient temperatures and mortality among 326 Latin American cities between 2002 and 2015. We observed 15,431,532 deaths among ≈2.9 billion person-years of risk. The excess death fraction of total deaths was 0.67% (95% confidence interval (CI) 0.58-0.74%) for heat-related deaths and 5.09% (95% CI 4.64-5.47%) for cold-related deaths. The relative risk of death was 1.057 (95% CI 1.046-1.067%) per 1 °C higher temperature during extreme heat and 1.034 (95% CI 1.028-1.040%) per 1 °C lower temperature during extreme cold. In Latin American cities, a substantial proportion of deaths is attributable to nonoptimal ambient temperatures. Marginal increases in observed hot temperatures are associated with steep increases in mortality risk. These risks were strongest among older adults and for cardiovascular and respiratory deaths.

Short-Term Effects of Apparent Temperature on Cause-Specific Mortality in the Urban Area of Thessaloniki, Greece

Although there is a growing interest in the association between ambient temperatures and mortality, little evidence is available for Thessaloniki, the second largest city of Greece. In this study, we present an assessment of the effects of temperature on daily mortality from 2006 to 2016 in the urban area of Thessaloniki, by describing the exposure-lag-response association between temperature and cause-specific mortality with the use of a distributed lag non-linear model (DLNM). A J-shaped relationship was found between temperature and mortality. The highest values of risk were evident for respiratory (RR > 10) and cardiovascular causes (RR > 3), probably due to the fact that health status of individuals with chronic respiratory and cardiovascular diseases rapidly deteriorates during hot periods. Cold effects had longer lags of up to 15 days, whereas heat effects were short-lived, up to 4 days. Percentage change in all- and cause-specific mortality per 1 °C change above and below Minimum Mortality Temperature showed a larger increase for all-cause mortality in heat (1.95%, 95% CI: 1.07–2.84), in contrast to a smaller increase in cold (0.54%, 95% CI: 0, 1.09). Overall, 3.51% of all-cause deaths were attributable to temperature, whereas deaths attributed to heat (2.34%) were more than deaths attributed to cold (1.34%). The findings of this study present important evidence for planning public-health interventions, to reduce the health impact of extreme temperatures.

Mortality Related to Air Temperature in European Cities, Based on Threshold Regression Models

There is a wealth of scientific literature that scrutinizes the relationship between mortality and temperature. The aim of this paper is to identify the nexus between temperature and three different causes of mortality (i.e., cardiological, respiratory, and cardiorespiratory) for three countries (Scotland, Spain, and Greece) and eleven cities (i.e., Glasgow, Edinburgh, Aberdeen, Dundee, Madrid, Barcelona, Valencia, Seville, Zaragoza, Attica, and Thessaloniki), emphasizing the differences among these cities and comparing them to gain a deeper understanding of the relationship. To quantify the association between temperature and mortality, temperature thresholds are defined for each city using a robust statistical analysis, namely threshold regression analysis. In a more detailed perspective, the threshold used is called Minimum Mortality Temperature (MMT), the temperature above or below which mortality is at minimum risk. Afterward, these thresholds are compared based on the geographical coordinates of each city. Our findings show that concerning all-causes of mortality under examination, the cities with higher latitude have lower temperature thresholds compared to the cities with lower latitude. The inclusion of the relationship between mortality and temperature in the array of upcoming climate change implications is critical since future climatic scenarios show an overall increase in the ambient temperature.

Mortality risk attributable to high and low ambient temperature in Pune city, India: A time series analysis from 2004 to 2012

BACKGROUND

Exposure to high and low ambient temperatures is associated with morbidity and mortality across the globe. Most of these studies assessing the effects of non-optimum temperatures on health and have been conducted in the developed world, whereas in India, the limited evidence on ambient temperature and health risks and has focused mostly on the effects of heat waves. Here we quantify short term association between all temperatures and mortality in urban Pune, India.

METHODS

We applied a time series regression model to derive temperature-mortality associations based on daily mean temperature and all-cause mortality records of Pune city from year January 2004 to December 2012. We estimated high and low temperature-mortality relationships by using standard time series quasi-Poisson regression in conjunction with a distributed lag non-linear model (DLNM). We calculated temperature attributable mortality fractions for total heat and total cold.

FINDINGS

The analysis provides estimates of the total mortality burden attributable to ambient temperature. Overall, 6∙5% [95%CI 1.76-11∙43] of deaths registered in the observational period were attributed to non-optimal temperatures, cold effect was greater 5.72% [95%CI 0∙70-10∙06] than heat 0∙84% [0∙35-1∙34]. The gender stratified analysis revealed that the highest burden among men both for heat and cold.

CONCLUSION

Non-optimal temperatures are associated with a substantial mortality burden. Our findings could benefit national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately due to climate change.

Taking globally consistent health impact projections to the next level

Despite intensive research activity within the area of climate change, substantial knowledge gaps still remain regarding the potential future impacts of climate change on human health. A key shortcoming in the scientific understanding of these impacts is the lack of studies that are conducted in a coordinated and consistent fashion, producing directly comparable outputs. This Viewpoint discusses and exemplifies a bottom-up initiative generating new research evidence in a more coordinated and consistent way compared with previous efforts. It describes one of the largest model comparisons of projected health impacts due to climate change, so far. Yet, the included studies constitute only a selection of health impacts in a variety of geographical locations, and are therefore not a comprehensive assessment of all possible impact pathways and potential consequences. The new findings of these studies shed light on the complex and multidirectional impacts of climate change on health, where impacts can be both adverse or beneficial. However, the adverse impacts dominate overall, especially in the scenarios with more greenhouse gas forcing. Overall, the future population at risk of disease and incidence rates are predicted to increase substantially, but in a highly location-specific and disease-specific fashion. Greenhouse gas emission mitigation can substantially reduce risk and resultant morbidity and mortality. The potential positive impact of adaptation has not been included in the models applied, and thus remains a major source of uncertainty. This bottom-up initiative lays out a research strategy that brings more meaningful research outputs and calls for greater coordination of research initiatives across the health community.