Projecting future heat-related mortality under climate change scenarios: a systematic review

Estimating the heat-related mortality and morbidity burden in the province of Quebec, Canada

BACKGROUND

As climate change increases the frequency and intensity of extreme heat events, there is an urgent need to quantify the heat-related health burden. However, most past studies have focussed on a single health outcome (mainly mortality) or on specific heatwaves, thus providing limited knowledge of the total pressure heat exerts on health services.

OBJECTIVES

This study aims to quantify the heat-related mortality and morbidity burden for five different health outcomes including all-cause mortality, hospitalizations, emergency department (ED) visits, ambulance transports and calls to a health hotline, using the province of Quebec (Canada) as a case study.

METHODS

A two-step statistical analysis was employed to estimate regional heat-health relationships using Distributed Lag Non-Linear Models (DLNM) and pooled estimates using a multivariate meta-regression. Heat burden was quantified by attributable fraction (AF) and attributable number (AN) for two temperature ranges: all heat (above the minimum mortality/morbidity temperature) and extreme heat (above the 95th percentile of temperature).

RESULTS

Higher temperatures were associated with greater risk ratios for all health outcomes studied, but at different levels. Significant AF ranging from 2 to 3% for the all heat effect and 0.4-1.0% for extreme heat were found for all health outcomes, except for hospitalizations that had an AF of 0.1% for both heat exposures. The estimated burden of all heat (and extreme heat) every summer across the province was 470 (200) deaths, 225 (170) hospitalizations, 36 000 (6 200) ED visits, 7 200 (1 500) ambulance transports and 15 000 (3 300) calls to a health hotline, all figures significant.

DISCUSSION

This new knowledge on the total heat load will help public health authorities to target appropriate actions to reduce its burden now and in the future. The proposed state-of-the-art framework can easily be applied to other regions also experiencing the adverse effects of extreme heat.

Temporal trends in temperature-related mortality and evidence for maladaptation to heat and cold in the Eastern Mediterranean region

The eastern Mediterranean region is characterized by rising temperature trends exceeding the corresponding global averages and is considered a climate change hot-spot. Although previous studies have thoroughly investigated the impact of extreme heat and cold on human mortality and morbidity, both for the current and future climate change scenarios, the temporal trends in temperature-related mortality or the potential historical adaptation to heat and cold extremes has never been studied in this region. This study focuses on cardiovascular mortality and assesses the temporal evolution of the Minimum Mortality Temperature (MMT), as well as the disease-specific cold- and heat-attributable fraction of mortality in three typical eastern Mediterranean environments (Athens, Thessaloniki and Cyprus). Data on daily cardiovascular mortality (ICD-10 code: I00-I99) and meteorological parameters were available between 1999 and 2019 for Athens, 1999 to 2018 for Thessaloniki and 2004 to 2019 for Cyprus. Estimation of cardiovascular MMT and mortality fractions relied on time-series Poisson regressions with distributed lag nonlinear models (DLNM) controlling for seasonal and long-term trends, performed over a series of rolling sub-periods at each site. The results indicated that in Athens, the MMT decreased from 23 °C (67.5th percentile) in 1999-2007 to 21.8 °C (62nd percentile) in 2011-2019, while in Cyprus the MMT decreased from 26.3 °C (79th percentile) in 2004-2012 to 23.9 °C (66.5th percentile) in 2011-2019. In Thessaloniki, the decrease in MMT was rather negligible. In all regions under study, the fractions of mortality attributed to both cold and heat followed an upward trend throughout the years. In conclusion, the demonstrated increase in cold attributable fraction and the decreasing temporal trend of MMT across the examined sites are suggestive of maladaptation to extreme temperatures in regions with warm climate and highlight the need for relevant public health policies and interventions.

Accounting for adaptation when projecting climate change impacts on health: A review of temperature-related health impacts

Exposure to high and low ambient temperatures can cause harm to human health. Due to global warming, heat-related health effects are likely to increase substantially in future unless populations adapt to living in a warmer world. Adaptation to temperature may occur through physiological acclimatisation, behavioural mechanisms, and planned adaptation. A fundamental step in informing responses to climate change is understanding how adaptation can be appropriately accounted for when estimating future health burdens. Previous studies modelling adaptation have used a variety of methods, and it is often unclear how underlying assumptions of adaptation are made and if they are based on evidence. Consequently, the most appropriate way to quantitatively model adaptation in projections of health impacts is currently unknown. With increasing interest from decisionmakers around implementation of adaptation strategies, it is important to consider the role of adaptation in anticipating future health burdens of climate change. To address this, a literature review using systematic scoping methods was conducted to document the quantitative methods employed by studies projecting future temperature-related health impacts under climate change that also consider adaptation. Approaches employed in studies were coded into methodological categories. Categories were discussed and refined between reviewers during synthesis. Fifty-nine studies were included and grouped into eight methodological categories. Methods of including adaptation in projections have changed over time with more recent studies using a combination of approaches or modelling adaptation based on specific adaptation strategies or socioeconomic conditions. The most common approaches to model adaptation are heat threshold shifts and reductions in the exposure-response slope. Just under 20% of studies were identified as using an intervention-based empirical basis for statistical assumptions. Including adaptation in projections considerably reduced the projected temperature-mortality burden in the future. Researchers should ensure that all future impact assessments include adaptation uncertainty in projections and assumptions are based on empirical evidence.

Global projections of heat exposure of older adults

The global population is aging at the same time as heat exposures are increasing due to climate change. Age structure, and its biological and socio-economic drivers, determine populations' vulnerability to high temperatures. Here we combine age-stratified demographic projections with downscaled temperature projections to mid-century and find that chronic exposure to heat doubles across all warming scenarios. Moreover, >23% of the global population aged 69+ will inhabit climates whose 95th percentile of daily maximum temperature exceeds the critical threshold of 37.5 °C, compared with 14% today, exposing an additional 177-246 million older adults to dangerous acute heat. Effects are most severe in Asia and Africa, which also have the lowest adaptive capacity. Our results facilitate regional heat risk assessments and inform public health decision-making.

Projecting heat-related cardiovascular mortality burden attributable to human-induced climate change in China

BACKGROUND

Cardiovascular disease (CVD) has been found to be particularly vulnerable to climate change and temperature variability. This study aimed to assess the extent to which human-induced climate change contributes to future heat-related CVD burdens.

METHODS

Daily data on CVD mortality and temperature were collected in 161 Chinese communities from 2007 to 2013. The association between heat and CVD mortality was established using a two-stage time-series design. Under the natural forcing, human-induced, and combined scenarios, we then separately projected excess cause-/age-/region-/education-specific mortality from future high temperature in 2010-2100, assuming no adaptation and population changes.

FINDINGS

Under shared socioeconomic pathway with natural forcing scenario (SSP2-4.5-nat), heat-related attributable fraction of CVD deaths decreased slightly from 3.3% [95% empirical confidence interval (eCI): 0.3, 5.8] in the 2010s to 2.8% (95% eCI: 0.1, 5.2) in the 2090s, with relative change of -0.4% (95% eCI: -0.8, 0.0). However, for combined natural and human-induced forcings, this estimate would surge to 8.9% (95% eCI: 1.5, 15.7), 14.4% (95% eCI: 1.5, 25.3), 21.3% (95% eCI: -0.6, 39.4), and 28.7% (95% eCI: -3.3, 48.0) in the 2090s under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. When excluding the natural forcing, the number of human-induced heat-related CVD deaths would increase from approximately eight thousand (accounting for 31% of total heat-related CVD deaths) in the 2010s to 33,052 (68%), 63,283 (80%), 101,091 (87%), and 141,948 (90%) in the 2090s under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. Individuals with stroke, females, the elderly, people living in rural areas, and those with lower education level would exhibit heightened susceptibility to future high temperature. In addition, Southern and Eastern regions of China were expected to experience a faster increase in heat-related attributable fraction of CVD deaths.

INTERPRETATION

Human activities would significantly amplify the future burden of heat-related CVD. Our study findings suggested that active adaptation and mitigation measures towards future warming could yield substantial health benefits for the patients with CVD.

FUNDING

National Natural Science Foundation of China.

Projection of future heat-related morbidity in three metropolitan prefectures of Japan based on large ensemble simulations of climate change under 2 °C global warming scenarios

Recently, global warming has become a prominent topic, including its impacts on human health. The number of heat illness cases requiring ambulance transport has been strongly linked to increasing temperature and the frequency of heat waves. Thus, a potential increase in the number of cases in the future is a concern for medical resource management. In this study, we estimated the number of heat illness cases in three prefectures of Japan under 2 °C global warming scenarios, approximately corresponding to the 2040s. Based on the population composition, a regression model was used to estimate the number of heat illness cases with an input parameter of time-dependent meteorological ambient temperature or computed thermophysiological response of test subjects in large-scale computation. We generated 504 weather patterns using 2 °C global warming scenarios. The large-scale computational results show that daily amount of sweating increased twice and the core temperature increased by maximum 0.168 °C, suggesting significant heat strain. According to the regression model, the estimated number of heat illness cases in the 2040s of the three prefectures was 1.90 (95%CI: 1.35-2.38) times higher than that in the 2010s. These computational results suggest the need to manage ambulance services and medical resource allocation, including intervention for public awareness of heat illnesses. This issue will be important in other aging societies in near future.

Heatwave 1987: the Piraeus versus Athens case

Background

Heatwaves represent the main indices of climate change, while mortality is one of the established markers of their human effects. For unknown reasons populations adapt to temperature variations/challenges differently. Thus, to allow better precision and prediction, heatwave evaluations should be enriched by historical context and local data.

Methods

The mortality data for 1987 were collected from the Piraeus municipality registry, whereas data for Athens were obtained from literature retrieved from PUBMED. Ambient characteristics were extracted from the Geronikolou's 1991 BSc thesis and the reports of national organizations. From the death events, the odds ratio and relative risk in Piraeus compared to the Athens were calculated. Finally, a simple neural network proposed the dominant ambient parameter of the heatwave effects in the city residents of each location.

Results

The 1987 heatwave was more lethal (seven-fold) in Athens than in Piraeus and dependent on atmospheric nitric oxide (NO) concentration (with probability 0.999). In the case of Piraeus in 1987, ozone characterized the phenomenon (with probability 0.993).

Conclusions

The odds of dying due to a heatwave are highly dependent on lifestyle, population sensitivity to preventive measures and public health policy, while the phenomenon was mainly moderated by ozone in Piraeus in 1987, and NO in Athens irrespective of year.

Revisiting the importance of temperature, weather and air pollution variables in heat-mortality relationships with machine learning

Extreme heat events have significant health impacts that need to be adequately quantified in the context of climate change. Traditionally, heat-health association methods have relied on statistical models using a single air temperature index, without considering other heat-related variables that may influence the relationship and their potentially complex interactions. This study aims to introduce and compare different machine learning (ML) models, which naturally consider interactions between predictors and non-linearities, to re-examine the importance of temperature, weather and air pollution predictors in modeling the heat-mortality relationship. ML approaches based on tree ensembles and neural networks, as well as non-linear statistical models, were used to model the heat-mortality relationship in the two most populated metropolitan areas of the province of Quebec, Canada. The models were calibrated using a comprehensive database of heat-related predictors including various lagged temperature indices, temperature variations, meteorological and air pollution variables. Performance was evaluated based on out-of-sample summer mortality predictions. For the two studied regions, models relying only on lagged temperature indices performed better, or equally well, than models considering more heat-related predictors such as temperature variations, weather and air pollution variables. The temperature index with the best performance differed by region, but both mean temperature and humidex were among the best indices. In terms of modeling approaches, non-linear statistical models were as competent as more advanced ML models for predicting out-of-sample summer mortality. This research validated the current use of non-linear statistical models with the appropriate lagged temperature index to model the heat-mortality relationship. Although ML models have not improved the performance of all-cause mortality modeling, these approaches should continue to be explored, particularly for other health effects that may be more directly linked to heat exposure and, in the future, when more data become available.

Temperature extremes and infectious diarrhea in China: attributable risks and effect modification of urban characteristics

Studies about the role of urban characteristics in modifying the health effect of temperature extremes are still unclear. This study is aimed at quantifying the morbidity risk of infectious diarrhea attributable to temperature extremes and the modified effect of a range of city-specific indicators. Distributed lag non-linear model and multivariate meta-regression were applied to estimate fractions of infectious diarrhea morbidity attributable to temperature extremes and to explore the effect modification of city-level characteristics. Extreme heat- and extreme cold-related infectious diarrhea amounted to 0.99% (95% CI: 0.57-1.29) and 1.05% (95% CI: 0.64-1.24) of the total cases, respectively. The attributable fraction of temperature extremes on infectious diarrhea varied between southern and northern China. Several city characteristics modified the association of extreme cold with infectious diarrhea, with a higher morbidity impact related to increased water consumption per capita and decreased latitude. Regions with higher levels of latitude or GDP per capita appeared to be more sensitive to extreme hot. In conclusion, exposure to temperature extremes was associated with increased risks of infectious diarrhea and the effect can be modified by urban characteristics. This finding can inform public health interventions to decrease the adverse effects of temperature extremes on infectious diarrhea.

Regular physical activity across the lifespan to build resilience against rising global temperatures

Population aging, high prevalence of non-communicable diseases, physical inactivity, and rising global temperatures are some of the most pressing issues in public health of the current century. Such trends suggest that individuals increasingly less equipped to tolerate heat will be increasingly exposed to it, which from a public health perspective is alarming. Nonetheless, future impacts of extreme heat events will depend not only on the magnitude of climate change, but on our ability to adapt by becoming less sensitive and vulnerable. Although physical activity's role in mitigating climate change has received attention, its potential contribution to climate change adaptation and resilience remains largely unaddressed. Accordingly, in this viewpoint, we discuss how regular physical activity throughout life could have an important contribution to adapting to rising global temperatures, allowing to be better equipped to cope with heat-related health hazards and increasing individual and community resilience. This viewpoint constitutes a call for more research into the contribution that physical activity can have in adapting to rising global temperatures and, more broadly, to climate change.

Temporal variation in the association between temperature and cause-specific mortality in 15 German cities

BACKGROUND

There is limited evidence of temporal changes in the association between air temperature and the risk of cause-specific cardiovascular [CVD] and respiratory [RD] mortality.

METHOD

We explored temporal variations in the association between short-term exposures to air temperature and non-accidental and cause-specific CVD and RD mortality in the 15 largest German cities over 24 years (1993-2016) using time-stratified time series analysis. We applied location-specific confounder-adjusted Poisson regression with distributed lag non-linear models with a lag period of 14 days to estimate the temperature-mortality associations. We then pooled the estimates by a multivariate meta-analytical model. We analysed the whole study period and the periods 1993-2004 and 2005-16, separately. We also carried out age- and sex-stratified analysis. Cold and heat effects are reported as relative risk [RR] at the 1st and the 99th temperature percentile, relative to the 25th and the 75th percentile, respectively.

RESULT

We analysed a total of 3,159,292 non-accidental, 1,063,198 CVD and 183,027 RD deaths. Cold-related RR for CVD mortality was seen to rise consistently over time from 1.04 (95% confidence interval [95% CI] 1.02, 1.06) in the period 1993-2004 to 1.10 (95% CI 1.09, 1.11) in the period 2005-16. A similar increase in cold-related RR was also observed for RD mortality with risk increasing from 0.99 (95% CI 0.96, 1.03) to 1.07 (95% CI 1.03, 1.10). Cold-related ischemic, cerebrovascular, and heart failure mortality risk were seen to be increasing over time. Similarly, COPD, the commonly speculated driver of heat-related RD mortality was found to have a constant heat-related risk over time. Males were increasingly vulnerable to cold with time for all causes of death. Females showed increasing sensitivity to cold for CVD mortality. Our results indicated a significant increased cold and heat vulnerability of the youngest age-groups (<64) to non-accidental and RD mortality, respectively. Similarly, the older age group (>65) were found to have significantly increased susceptibility to cold for CVD mortality.

CONCLUSION

We found evidence of rising population susceptibility to both heat- and cold-related CVD and RD mortality risk from 1993 to 2016. Climate change mitigation and targeted adaptation strategies might help to reduce the number of temperature-related deaths in the future.

Temporal variation of the temperature-mortality association in Spain: a nationwide analysis

BACKGROUND

Although adaptation to continuously rising ambient temperatures is an emerging topic and has been widely studied at a global scale, detailed analysis of the joint indicators for long-term adaptation in Spain are scarce. This study aims to explore temporal variations of the minimum mortality temperature and mortality burden from heat and cold between 1979 and 2018.

METHODS

We collected individual all-cause mortality and climate reanalysis data for 4 decades at a daily time step. To estimate the temperature-mortality association for each decade, we fitted a quasi-Poisson time-series regression model using a distributed lag non-linear model with 21 days of lag, controlling for trends and day of the week. We also calculated attributable mortality fractions by age and sex for heat and cold, defined as temperatures above and below the optimum temperature, which corresponds to the minimum mortality in each period.

RESULTS

We analysed over 14 million deaths registered in Spain between 1979 and 2018. The optimum temperature estimated at a nationwide scale declined from 21 °C in 1979-1988 to 16 °C in 1999-2008, and raised to 18 °C in 2009-2018. The mortality burden from moderate cold showed a 3-fold reduction down to 2.4% in 2009-2018. Since 1988-1999, the mortality risk attributable to moderate (extreme) heat reduced from 0.9% (0.8%) to 0.6% (0.5%). The mortality risk due to heat in women was almost 2 times larger than in men, and did not decrease over time.

CONCLUSION

Despite the progressively warmer temperatures in Spain, we observed a persistent flattening of the exposure-response curves, which marked an expansion of the uncertainty range of the optimal temperatures. Adaptation has been produced to some extent in a non-uniform manner with a substantial decrease in cold-related mortality, while for heat it became more apparent in the most recent decade only.

The effectiveness of social distancing in reducing transmission during influenza epidemics: A systematic review

BACKGROUND

Social distance practices are crucial for outpatient clinics during disease outbreaks and are an effective preventive measure for reducing influenza transmission during such pandemics in people with poor health.

METHODS

This study applies an evidence-based practice (EBP) approach to confirm the effectiveness of social distancing in healthy individuals during an influenza pandemic and employs the induced ordered weighted averaging model to confirm the effectiveness of EBP. The study design, validity, reliability, results, and generalizability focused on discussing three systematic reviews and two cohort studies via the Critical Appraisal Skills Programme (CASP). First, by introducing the patient, intervention, comparison, outcome (PICO) question; second, by establishing the five steps of EBP; third, by utilizing the CASP checklist for the appraisal; and finally, by presenting a conclusion.

RESULTS

According to the hierarchy of evidence, preferred reporting items for systematic reviews and meta-analyses retrieved five articles for addressing the PICO question. All the evidence demonstrates that social distancing is valuable during influenza pandemics among non-infected individuals. Precise, timely, and robust social distancing implementation can reduce the spread of infection, delay the epidemic peak, and ease the pressure on healthcare resources. Gatekeepers are responsible for guiding individuals through the implementation process for reducing influenza transmission, particularly in densely populated areas.

CONCLUSIONS

Social distance is crucial for outpatient clinics during an epidemic and effectively reduces the spread of infection, delay epidemic peaks, and eases pressure on healthcare resources.

Achievements and gaps in projection studies on the temperature-attributable health burden: Where should we be headed?

Future projection of the temperature-related health burden, including mortality and hospital admissions, is a growing field of research. These studies aim to provide crucial information for decision-makers considering existing health policies as well as integrating targeted adaptation strategies to evade the health burden. However, this field of research is still overshadowed by large uncertainties. These uncertainties exist to an extent in the future climate and population models used by such studies but largely in the disparities in underlying assumptions. Existing studies differ in the factors incorporated for projection and strategies for considering the future adaptation of the population to temperature. These differences exist to a great degree because of a lack of robust evidence as well as gaps in the field of climate epidemiology that still require extensive input from the research community. This narrative review summarizes the current status of projection studies of temperature-attributable health burden, the guiding assumptions behind them, the common grounds, as well as the differences. Overall, the review aims to highlight existing evidence and knowledge gaps as a basis for designing future studies on temperature-attributable health burden estimation. Finding a robust methodology for projecting the future health burden could be a milestone for climate epidemiologists as this would largely benefit the world when applying this technique to project the climate-attributable cause-specific health burden and adapt our existing health policies accordingly.

The burden of heat-related stroke mortality under climate change scenarios in 22 East Asian cities

BACKGROUND

Stroke is a leading cause of death and disability in East Asia. Owing to the aging population and high prevalence of stroke, East Asia might suffer a disproportionately heavy burden of stroke under the changing climate. However, the evidence relevant is still limited in this area.

OBJECTIVE

To evaluate the stroke mortality risk due to heat exposure in East Asia and predict its burden under various future climate change scenarios.

METHODS

We conducted a multi-center observational study and collected data from 22 representative cities in three main East Asian countries (i.e., China, Japan, and South Korea) from 1972 to 2015. The two-stage time-series analyses were applied to estimate the effects of heat on stroke mortality at the regional and country level. We further projected the burden of heat-related stroke mortality using 10 global climate models (GCMs) under four shared socioeconomic pathway and representative concentration pathway (SSP-RCP) scenarios, including SSP1-RCP1.9, SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5 scenarios.

RESULTS

In the present study, a total of 287,579 stroke deaths were collected during the warm season. Heat was significantly associated with an increased risk of stroke mortality. Overall, compared with the 2010 s, the heat-related attributable fraction (AF) was projected to increase in the 2090 s, with increments ranging from 0.8 % to 7.5 % across various climate change scenarios. The heat-related AF was projected to reach 11.9 % (95 % empirical confidence interval [eCI]: 6.1 %, 17.5 %) in the 2090 s under the SSP5-RCP8.5 scenario in China, while the corresponding estimates were 6.6 % (95 % eCI: 2.5 %, 11.0 %) and 5.1 % (95 % eCI: 1.2 %, 9.1 %) for Japan and South Korea, respectively.

CONCLUSIONS

Climate change will exacerbate the burden of heat-related stroke mortality but with considerable geographical heterogeneity in East Asia.

Research Note: Demographic Change on the United States Coast, 2020-2100

Prospective demographic information of the United States is limited to national-level analyses and subnational analyses of the total population. With nearly 40% of the U.S. population being residents of coastal areas, understanding the anticipated demographic changes in coastal counties is important for long-range planning purposes. In this research note, we use long-range, county-level population projections based on a simplified cohort-component method to discuss demographic changes by age, sex, and race and ethnicity for coastal counties between 2020 and the end of the century, and we compare these changes to inland counties. Presently, coastal counties are statistically significantly different from inland counties by race and ethnicity (more diverse) and sex (more women) but not by age, yet by 2025, we expect coastal counties to become significantly older than inland counties. We note several important trajectories of predicted demographic outcomes in coastal counties across the remainder of the century: (1) the non-Hispanic White population is expected to decrease, both numerically and as a percentage of the population; (2) the population older than 65 is projected to increase, both numerically and as a percentage of the population; and (3) the ratio of women to men remains constant over the century at 1.03. These trends combine to suggest that the future U.S. coastline will likely be both increasingly diverse racially and ethnically and significantly older than it is today.

Global Health Impacts for Economic Models of Climate Change: A Systematic Review and Meta-Analysis

Rationale: Avoiding excess health damages attributable to climate change is a primary motivator for policy interventions to reduce greenhouse gas emissions. However, the health benefits of climate mitigation, as included in the policy assessment process, have been estimated without much input from health experts. Objectives: In accordance with recommendations from the National Academies in a 2017 report on approaches to update the social cost of greenhouse gases (SC-GHG), an expert panel of 26 health researchers and climate economists gathered for a virtual technical workshop in May 2021 to conduct a systematic review and meta-analysis and recommend improvements to the estimation of health impacts in economic-climate models. Methods: Regionally resolved effect estimates of unit increases in temperature on net all-cause mortality risk were generated through random-effects pooling of studies identified through a systematic review. Results: Effect estimates and associated uncertainties varied by global region, but net increases in mortality risk associated with increased average annual temperatures (ranging from 0.1% to 1.1% per 1°C) were estimated for all global regions. Key recommendations for the development and utilization of health damage modules were provided by the expert panel and included the following: not relying on individual methodologies in estimating health damages; incorporating a broader range of cause-specific mortality impacts; improving the climate parameters available in economic models; accounting for socioeconomic trajectories and adaptation factors when estimating health damages; and carefully considering how air pollution impacts should be incorporated in economic-climate models. Conclusions: This work provides an example of how subject-matter experts can work alongside climate economists in making continued improvements to SC-GHG estimates.

Outdoor ambient temperatures and occupational injuries and illnesses: Are there risk differences in various regions within a city?

Increased risk of occupational injuries and illnesses (OI) is associated with hot ambient temperatures. However, the existing evidence of risk estimation is limited to large regions at the city or provincial scales. For effective and localized occupational health risk management, spatio-temporal analysis should be carried out at the intra-city level to identify high-risk areas within cities. This study examined the exposure-response relationship between ambient temperatures and OI at the intra-city scale in Greater Adelaide, Australia. Vulnerable groups of workers, in terms of workers' characteristics, the nature of their work, and workplace characteristics were identified. Further, the projected risk of OI was quantified in various climate change scenarios. The temperature-OI association was estimated using a time-series study design combined with Distributed Lag Non-linear Models. Daily workers' compensation claims (2005-2018) were merged with 5 km gridded meteorological data of maximum temperature (°C) at Statistical Area Level 3 in Greater Adelaide. Region-wise subgroup analyses were conducted to identify vulnerable groups of workers. Future projections (2006-2100) were conducted using downscaled climate projections and the risk was quantified using log-linear extrapolation. The analyses were performed in R 4.1.0. The overall OI risk was 16.7% (95%CI: 10.8-23.0) at moderate heat (90th percentile) and increased to 25.0% (95%CI: 16.4-34.2) at extreme heat (99th percentile). Northern Adelaide had a higher risk of OI for all types of workers at moderate heat, while western regions had a high risk for indoor industries. Southern and eastern regions had a higher OI risk for males, older workers, and outdoor industries at extreme heat. The projected risk of OI is estimated to increase from 20.8% (95%CI: -0.2-46.3) in 2010s to 22.9% (95%CI: -8.0-64.1) by 2050s. Spatio-temporal risk assessment at the intra-city scale can help us identify high-risk areas, where targeted interventions can be efficiently employed to reduce the socio-economic burden of OI.

Climate change and Australian general practice vocational education: a cross-sectional study

BACKGROUND

Climate change is a rapidly progressing threat to global health and well-being. For general practitioners (GPs) currently in training, the effects of climate change on public health will shape their future professional practice We aimed to establish the prevalence and associations of Australian GP registrars' (trainees') perceptions of climate change as it relates to public health, education, and workplaces.

METHODS

A cross-sectional questionnaire-based study of GP registrars of three Australian training organizations. The questionnaire assessed attitudes regarding adverse health effects of climate change (over the next 10-20 years), and agreement with statements on (i) integrating health impacts of climate change into GP vocational training, and (ii) GPs' role in making general practices environmentally sustainable.

RESULTS

Of 879 registrars who participated (response rate 91%), 50.4% (95% CI 46.8%, 54.0%) perceived a large or very large future health effect of climate change on their patients, and 61.8% (95% CI 58.6%, 65.0%) agreed that climate health impacts should be integrated within their education programme. 77.8% (95% CI 74.9%, 80.4%) agreed that GPs should have a leadership role in their practices' environmental sustainability. Multivariable associations of these attitudes included female gender, training region, and (for the latter two outcomes) perceptions of future impact of climate change on patient health.

CONCLUSIONS

GP registrars are motivated to receive climate health education and engage in environmentally sustainable practice. This may primarily reflect concern for future practice and patient care.

Projections of future temperature-related cardiovascular mortality under climate change, urbanization and population aging in Beijing, China

Climate change is causing the surface temperature to rise and the extreme weather events to increase in frequency and intensity, which will pose potential threats to the survival and health of residents. Beijing is facing multiple challenges such as coping with climate change, urbanization, and population aging, which puts huge decision-making pressure on decision maker. However, few studies that systematically consider the health effects of climate change, urbanization, and population aging for China. Based on the distributed lag nonlinear model (DLNM) and 13 global climate models in the Coupled Model Intercomparison Project Phase 6 (CMIP6), this study obtained the temporal and spatial distribution of surface temperature through statistical downscaling methods, and comprehensively explored the independent and comprehensive effects of urbanization and population aging on the projection of future temperature-related cardiovascular disease (CVD) mortality in the context of climate and population change. The results showed that only improving urbanization can reduce future temperature-related CVD mortality by 1.7-18.3%, and only intensified aging can increase future temperature-related CVD mortality by 48.8-325.9%. Taking into account the improving urbanization and intensified aging, future temperature-related CVD mortality would increase by 44.1-256.6%, and the increase was slightly lower than that of only intensified aging. Therefore, the intensified aging was the biggest disadvantage in tackling climate change, which would obviously magnify the mortality risks of temperature-related CVD in the future. Although the advancement of urbanization would alleviate the adverse effects of the intensified aging population, the mitigation effects would be limited. Even so, Urbanization should be continued to reduce health risks for residents. These findings would contribute to formulate policies related to mitigate climate change and reduce baseline mortality rate (especially the elderly) in international mega-city - Beijing. In addition, relevant departments should improve the medical health care level and optimize the allocation of social resources to better cope with and adapt to climate change.

Climate Data to Support the Adaptation of Buildings to Climate Change in Canada

Climate change will continue to bring about unprecedented climate extremes in the future, and buildings and infrastructure will be exposed to such conditions. To ensure that new and existing buildings deliver satisfactory performance over their design lives, their performance under current and future projected climates needs to be assessed by undertaking building simulations. This study prepares climate data needed for building simulations for 564 locations by bias-correcting the Canadian Regional Climate Model version 4 (CanRCM4) large ensemble (LE) simulations with reference to observations. Technical validation results show that bias-correction effectively reduces the bias associated with CanRCM4-LE simulations in terms of their marginal distributions and the inter-relationship between climate variables. To ensure that the range of projected climate change impacts are encompassed within these data sets, and to furthermore provide building moisture and energy reference years, the reference year files were prepared from bias-corrected CanRCM4-LE simulations and are comprised of a typical meteorological year for building energy applications, a typical and extreme moisture reference year, a typical downscaled year, an extreme warm year, and an extreme cold year.

Mortality risk related to heatwaves in Finland - Factors affecting vulnerability

BACKGROUND

Heatwaves are known to increase mortality. However, there is a need for more quantitative information on factors affecting sensitivity to the adverse health effects, particularly in countries with cool summer temperatures.

OBJECTIVES

We evaluated mortality risk related to heatwave days in Finland. Risk was examined by age, sex, cause of death, and place of death, including health and social care facilities and homes. Mortality was also analysed for different patient subgroups in healthcare facilities.

METHODS

Heatwaves were defined as periods when the daily average temperature exceeded the 90th percentile of that from May to August in 2000-2014 for ≥4 days. In addition to all heatwave days, risk was analysed for short (4-5 days) and long (≥10 days) heatwaves. Mortality analyses were based on linking registry data on i) daily non-accidental and cause-specific mortality and ii) admissions to a health or social care facility. Statistical analyses were conducted using generalised estimating equations for longitudinal data analysis, assuming a Poisson distribution for the daily mortality count.

RESULTS

During all heatwave days, mortality increased among those aged 65-74 years (6.7%, 95% confidence interval 2.9-10.8%) and ≥75 years (12.8%, 95% CI 9.8-15.9%). Mortality increased in both sexes, but the risk was higher in women. Positive associations were observed for deaths due to respiratory diseases, renal diseases, mental and behavioural disorders, diseases of the nervous system, and cardiovascular diseases. Overall, effects were stronger for long than short heatwaves. During all heatwave days, mortality increased in healthcare facilities in outpatients (26.9%, 95% CI 17.3-37.2%) and inpatients. Among inpatients, the risk was higher in long-term inpatients (stay in ward > 30 days, 13.1%, 95% CI 8.6-17.7%) than others (5.8%, 95% CI 2.7-9.0%). At homes, mortality increased by 8.1% (95% CI 1.9-14.6%). Elevated risk estimates were also detected for social care facilities.

CONCLUSIONS

In Finland, a cold-climate Northern country, heatwaves increase mortality risk significantly among the elderly. Women are more susceptible than men, and many chronic diseases are important risk factors. To reduce heatwave-related deaths, preparedness should be improved particularly in hospital and healthcare centre wards, where the most vulnerable are long-term inpatients. However, measures are also needed to protect the elderly at home and in social care facilities, especially during prolonged hot periods.

Temperature-mortality relationship in North Carolina, USA: Regional and urban-rural differences

BACKGROUND

Health disparities exist between urban and rural populations, yet research on rural-urban disparities in temperature-mortality relationships is limited. As inequality in the United States increases, understanding urban-rural and regional differences in the temperature-mortality association is crucial.

OBJECTIVE

We examined regional and urban-rural differences of the temperature-mortality association in North Carolina (NC), USA, and investigated potential effect modifiers.

METHODS

We applied time-series models allowing nonlinear temperature-mortality associations for 17 years (2000-2016) to generate heat and cold county-specific estimates. We used second-stage analysis to quantify the overall effects. We also explored potential effect modifiers (e.g. social associations, greenness) using stratified analysis. The analysis considered relative effects (comparing risks at 99th to 90th temperature percentiles based on county-specific temperature distributions for heat, and 1st to 10th percentiles for cold) and absolute effects (comparing risks at specific temperatures).

RESULTS

We found null effects for heat-related mortality (relative effect: 1.001 (95% CI: 0.995-1.007)). Overall cold-mortality risk for relative effects was 1.019 (1.015-1.023). All three regions had statistically significant cold-related mortality risks for relative and absolute effects (relative effect: 1.019 (1.010-1.027) for Coastal Plains, 1.021 (1.015-1.027) for Piedmont, 1.014 (1.006-1.023) for Mountains). The heat mortality risk was not statistically significant, whereas the cold mortality risk was statistically significant, showing higher cold-mortality risks in urban areas than rural areas (relative effect for heat: 1.006 (0.997-1.016) for urban, 1.002 (0.988-1.017) for rural areas; relative effect for cold: 1.023 (1.017-1.030) for urban, 1.012 (1.001-1.023) for rural areas). Findings are suggestive of higher relative cold risks in counties with the less social association, higher population density, less green-space, higher PM_2.5, lower education level, higher residential segregation, higher income inequality, and higher income (e.g., Ratio of Relative Risks 1.72 (0.68, 4.35) comparing low to high education).

CONCLUSION

Results indicate cold-mortality risks in NC, with potential differences by regional, urban-rural areas, and community characteristics.

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.

Heat-related mortality under climate change and the impact of adaptation through air conditioning: A case study from Thessaloniki, Greece

Climate change is expected to increase heat-related mortality across the world. Health Impact Assessment (HIA) studies are used to quantify the impact of higher temperatures, taking into account the effect of population adaptation. Although air-conditioning (AC) is one of the main drivers of technological adaptation to heat, the health impacts associated with AC-induced air pollution have not been examined in detail. This study uses the city of Thessaloniki, Greece as a case study and aims to estimate the future heat-related mortality, the residential cooling demand, and the adaptation trade-off between averted heat-related and increased air pollution cardiorespiratory mortality. Using temperature and population projections under different Coupled Model Intercomparison Project Phase 6 (CIMP6) Shared Socioeconomic Pathways scenarios (SSPs), a HIA model was developed for the future heat and air pollution cardiorespiratory mortality. Counterfactual scenarios of either black carbon (BC) or natural gas (NG) being the fuel source for electricity generation were included in the HIA. The results indicate that the heat-related cardiorespiratory mortality in Thessaloniki will increase and the excess of annual heat-related deaths in 2080-2099 will range from 2.4 (95% CI: 0.0-20.9) under SSP1-2.6 to 433.7 (95% CI: 66.9-1070) under SSP5-8.5. Population adaptation will attenuate the heat-related mortality, although the latter may be counterbalanced by the higher air pollution-related mortality due to increased AC, especially under moderate SSP scenarios and coal-fired power plants. Future studies examining the health effects of warmer temperatures need to account for the impact of both adaptation and increased penetration and use of AC.

The mortality cost of carbon

Many studies project that climate change can cause a significant number of excess deaths. Yet, in integrated assessment models (IAMs) that determine the social cost of carbon (SCC) and prescribe optimal climate policy, human mortality impacts are limited and not updated to the latest scientific understanding. This study extends the DICE-2016 IAM to explicitly include temperature-related mortality impacts by estimating a climate-mortality damage function. We introduce a metric, the mortality cost of carbon (MCC), that estimates the number of deaths caused by the emissions of one additional metric ton of CO2. In the baseline emissions scenario, the 2020 MCC is 2.26 × 10‒4 [low to high estimate -1.71× 10‒4 to 6.78 × 10‒4] excess deaths per metric ton of 2020 emissions. This implies that adding 4,434 metric tons of carbon dioxide in 2020-equivalent to the lifetime emissions of 3.5 average Americans-causes one excess death globally in expectation between 2020-2100. Incorporating mortality costs increases the 2020 SCC from $37 to $258 [-$69 to $545] per metric ton in the baseline emissions scenario. Optimal climate policy changes from gradual emissions reductions starting in 2050 to full decarbonization by 2050 when mortality is considered.

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

BACKGROUND

Europe has emerged as a major climate change hotspot, both in terms of an increase in seasonal averages and climate extremes. Projections of temperature-attributable mortality, however, have not been comprehensively reported for an extensive part of the continent. Therefore, we aim to estimate the future effect of climate change on temperature-attributable mortality across Europe.

METHODS

We did a time series analysis study. We derived temperature-mortality associations by collecting daily temperature and all-cause mortality records of both urban and rural areas for the observational period between 1998 and 2012 from 147 regions in 16 European countries. We estimated the location-specific temperature-mortality relationships by using standard time series quasi-Poisson regression in conjunction with a distributed lag non-linear model. These associations were used to transform the daily temperature simulations from the climate models in the historical period (1971-2005) and scenario period (2006-2099) into projections of temperature-attributable mortality. We combined the resulting risk functions with daily time series of future temperatures simulated by four climate models (ie, GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5) under three greenhouse gas emission scenarios (ie, Representative Concentration Pathway [RCP]2.6, RCP6.0, and RCP8.5), providing projections of future mortality attributable fraction due to moderate and extreme cold and heat temperatures.

FINDINGS

Overall, 7·17% (95% CI 5·81-8·50) of deaths registered in the observational period were attributed to non-optimal temperatures, cold being more harmful than heat by a factor of ten (6·51% [95% CI 5·14-7·80] vs 0·65% [0·40-0·89]), and with large regional differences across countries-eg, ranging from 4·85% (95% CI 3·75-6·00) in Germany to 9·87% (8·53-11·19) in Italy. The projection of temperature anomalies by RCP scenario depicts a progressive increase in temperatures, more exacerbated in the high-emission scenario RCP8.5 (4·54°C by 2070-2099) than in RCP6.0 (2·89°C) and RCP2.6 (1·67°C). This increase in temperatures was transformed into attributable fraction. Projections consistently indicated that the increase in heat attributable fraction will start to exceed the reduction of cold attributable fraction in the second half of the 21st century, especially in the Mediterranean and in the higher emission scenarios. The comparison between scenarios highlighted the important role of mitigation, given that the total attributable fraction will only remain stable in RCP2.6, whereas the total attributable fraction will rapidly start to increase in RCP6.0 by the end of the century and in RCP8.5 already by the middle of the century.

INTERPRETATION

The increase in heat attributable fraction will start to exceed the reduction of cold attributable fraction in the second half of the 21st century. This finding highlights the importance of implementing mitigation policies. These measures would be especially beneficial in the Mediterranean, where the high vulnerability to heat will lead to an imbalance between the decreasing cold and increasing heat-attributable mortality.

FUNDING

None.

Large model structural uncertainty in global projections of urban heat waves

Urban heat waves (UHWs) are strongly associated with socioeconomic impacts. Here, we use an urban climate emulator combined with large ensemble global climate simulations to show that, at the urban scale a large proportion of the variability results from the model structural uncertainty in projecting UHWs in the coming decades under climate change. Omission of this uncertainty would considerably underestimate the risk of UHW. Results show that, for cities in four high-stake regions - the Great Lakes of North America, Southern Europe, Central India, and North China - a virtually unlikely (0.01% probability) UHW projected by single-model ensembles is estimated by our model with probabilities of 23.73%, 4.24%, 1.56%, and 14.76% respectively in 2061-2070 under a high-emission scenario. Our findings suggest that for urban-scale extremes, policymakers and stakeholders will have to plan for larger uncertainties than what a single model predicts if decisions are informed based on urban climate simulations.

Health effects of climate change: an overview of systematic reviews

OBJECTIVES

We aimed to develop a systematic synthesis of systematic reviews of health impacts of climate change, by synthesising studies' characteristics, climate impacts, health outcomes and key findings.

DESIGN

We conducted an overview of systematic reviews of health impacts of climate change. We registered our review in PROSPERO (CRD42019145972). No ethical approval was required since we used secondary data. Additional data are not available.

DATA SOURCES

On 22 June 2019, we searched Medline, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, Cochrane and Web of Science.

ELIGIBILITY CRITERIA

We included systematic reviews that explored at least one health impact of climate change.

DATA EXTRACTION AND SYNTHESIS

We organised systematic reviews according to their key characteristics, including geographical regions, year of publication and authors' affiliations. We mapped the climate effects and health outcomes being studied and synthesised major findings. We used a modified version of A MeaSurement Tool to Assess systematic Reviews-2 (AMSTAR-2) to assess the quality of studies.

RESULTS

We included 94 systematic reviews. Most were published after 2015 and approximately one-fifth contained meta-analyses. Reviews synthesised evidence about five categories of climate impacts; the two most common were meteorological and extreme weather events. Reviews covered 10 health outcome categories; the 3 most common were (1) infectious diseases, (2) mortality and (3) respiratory, cardiovascular or neurological outcomes. Most reviews suggested a deleterious impact of climate change on multiple adverse health outcomes, although the majority also called for more research.

CONCLUSIONS

Most systematic reviews suggest that climate change is associated with worse human health. This study provides a comprehensive higher order summary of research on health impacts of climate change. Study limitations include possible missed relevant reviews, no meta-meta-analyses, and no assessment of overlap. Future research could explore the potential explanations between these associations to propose adaptation and mitigation strategies and could include broader sociopsychological health impacts of climate change.

Mapping temporal and spatial changes in land use and land surface temperature based on MODIS data

Climate change and the rapid expansion of the built environment have intensified heat stress worldwide. Due to environmental changes and urbanization, some studies show evidence of spatial and temporal changes in heat stress. The objective of this study is to apply spatial analysis to explore temporal and spatial changes in heat stress and to conduct a comparative analysis of land surface temperature (LST) and land use. The results show a significant expansion of the areas where the LST is over 35 °C or between 30 °C and 35 °C. A comparative analysis between the expansion of areas with high LSTs and changing land use types shows that LSTs were indeed higher in 2014 than the values in 2008 and that LSTs remained relatively high in areas where the LST was over 35 °C or between 30 °C and 35 °C. The temperature variation is not significant between urban and rural areas, indicating that heat stress has been extended toward particular rural areas. The cooling effect provided by open space is not significant, so city planners should exert more effort to mitigate extreme heat stress. As a whole, heat stress does change temporally and spatially, and the results of the comparative analysis could be further referenced in future efforts to improve the ability of areas to adapt to heat stress based on various land use patterns.

Understanding linkages between environmental risk factors and noncommunicable diseases-A review

Environmental factors such as climate change are now underway, which have substantial impacts on health and well-being of human kind, but still imprecisely quantified, implications for human health. At present, one of the most significant discussions among scientists worldwide is interdependency of escalating environmental risk factors and the increasing rates of noncommunicable diseases (NCDs), which are the leading cause of death and disability worldwide. Climate change also triggers the occurrence of NCDs through a variety of direct and indirect pathways. Therefore, it is likely that the interdependence of climate change, environmental risk factors, and NCDs as a whole poses great threat to global health. Hence, this paper aims to review the latest evidence on impacts of environmental risk factors on NCDs and methods used in establishing the cause or correlation of environmental risk factors and NCDs. The literature review leveraged online databases such as PubMed and Google Scholar with articles that matched keywords "climate change", "environmental risk factors," and "noncommunicable diseases". This review shows that the burden of NCDs is increasing globally and attribution of environmental risk factors such as climate change is significant. Understanding the nature of the relation between NCDs and the environment is complex and has relied on evidence generated from multiple study designs. This paper reviews eight types of study designs that can be used to identify and measure causal and correlational nature between environment and NCDs. Future projections suggest that increases in temperatures will continue and also increase the public health burden of NCDs.

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.

A System Dynamics Model to Facilitate the Development of Policy for Urban Heat Island Mitigation

This article presents a customized system dynamics model to facilitate the informed development of policy for urban heat island mitigation within the context of future climate change, and with special emphasis on the reduction of heat-related mortality. The model incorporates a variety of components (incl.: the urban heat island effect; population dynamics; climate change impacts on temperature; and heat-related mortality) and is intended to provide urban planning and related professionals with: a facilitated means of understanding the risk of heat-related mortality within the urban heat island; and location-specific information to support the development of reasoned and targeted urban heat island mitigation policy.

Heat stroke-related deaths in India: An analysis of natural causes of deaths, associated with the regional heatwave

Soaring temperatures cause deaths in large numbers in various parts of India. The number of deaths vary with region and are influenced by the demographics and socioeconomic characteristics of the region. This study tried to estimate the number of deaths associated with exposure to heat in the different states of India. Secondary data was used, which was collected from the website data.gov.in, an Open Government Data (OGD) Platform of the Indian government. Descriptive statistics were applied using Microsoft Excel-10. It was found that there 3014 men died from heat-related causes in 2001-05, which increased to 5157 in the period 2011-15. For women the number of deaths in the corresponding periods were 849 and 1254 respectively. Deaths caused by heatwaves were found to be higher than those resulting from avalanches, exposure to cold, cyclone, tornado, starvation due to natural calamity, earthquake, epidemic, flood, landslide, torrential rain and forest fire. The study revealed that there are regional variations in the number deaths due to heatstroke. From the perspective of disaster preparedness, it is important to note that deaths from heat strokes occur every year. With rising temperatures, the numbers are likely to increase. The findings of the study highlight this concern. Therefore, there is a need for targeted region-specific interventions for reducing the number of deaths due to heatwaves.

Knowledge Graph Analysis of Human Health Research Related to Climate Change

In order to explore the development status, knowledge base, research hotspots, and future research directions related to the impacts of climate change on human health, a systematic bibliometric analysis of 6719 published articles from 2003 to 2018 in the Web of Science was performed. Using data analytics tools such as HistCite and CiteSpace, the time distribution, spatial distribution, citations, and research hotspots were analyzed and visualized. The analysis revealed the development status of the research on the impacts of climate change on human health and analyzed the research hotspots and future development trends in this field, providing important knowledge support for researchers in this field.

Projections of temperature-related cause-specific mortality under climate change scenarios in a coastal city of China

BACKGROUND

Numerous studies have been conducted to project temperature-related mortality under climate change scenarios. However, most of the previous evidence has been limited to the total or non-accidental mortality, resulting in insufficient knowledge on the influence of climate change on different types of disease.

OBJECTIVES

We aimed to project future temperature impact on mortality from 16 causes under multiple climate change models in a coastal city of China.

METHODS

We first estimated the baseline exposure-response relationships between daily average temperature and cause-specific mortality during 2009-2018. Then, we acquired downscaled future temperature projections from 28 general circulation models (GCMs) under two Representative Concentration Pathway (RCP4.5 and RCP8.5). Finally, we combined these exposure-response associations with projected temperature to estimate the change in the temperature-related death burden in different future decades in comparison to the 2010 s, assuming no demographic changes and population acclimatization.

RESULTS

We found a consistently decreasing trend in cold-related mortality but a steep rise in heat-related mortality among 16 causes under climate change scenarios. Compared with the 2010 s, the net change in the fraction of total mortality attributable to temperature are projected to -0.54% (95% eCI: -1.69% to 0.71%) and -0.38% (95% eCI: -2.73% to 2.12%) at the end of the 21st century under RCP4.5 and RCP8.5, respectively. However, the magnitude of future cold and heat effects varied by different causes of death. A net reduction of future temperature-related death burden was observed among 10 out of 15 causes, with estimates ranging from -5.02% (95% eCI: -17.42% to 2.50%) in mental disorders to -1.01% (95% eCI: -5.56% to 3.28%) in chronic lower respiratory disease. Conversely, the rest diseases are projected to experience a potential net increase of temperature-related death burden, with estimates ranging from 0.44% (95% eCI: -4.40% to 6.02%) in ischemic heart disease and 4.80% (95% eCI: -0.04% to 9.84%) in external causes.

CONCLUSIONS

Our study indicates that the mortality burden of climate change varied greatly by the mortality categories. Further investigations are warranted to comprehensively understand the impacts of climate change on different types of disease across various regions.

Extreme temperatures and mortality in Kuwait: Who is vulnerable?

BACKGROUND

Previous climate change temperature-related health studies have been performed mostly in western countries with relatively cooler temperatures than the Gulf region. Regions that are inherently hot, like Kuwait, are witnessing soaring temperatures unlike ever before. Meanwhile, Kuwait and other Gulf countries are unique in their demographic profiles due to the large number of non-national migrant workers.

OBJECTIVE

To examine the associations of hot and cold temperature extremes on the risk of mortality across gender, age groups and nationality in Kuwait.

METHODS

We investigated daily variations of all-cause non-accidental and cardiovascular mortality death counts and ambient temperatures from 2010 to 2016 in a time-series design using a negative binomial distribution. The temperature lag was modeled with distributed lag non-linear models.

RESULTS

A total of 33,472 all-cause non-accidental deaths happened during the study period. For the extreme hot temperatures and over the entire lag period, comparing the 99th percentile of temperature to the minimum mortality temperature, the risk of dying among males was 2.08 (95% CI: 1.23-3.52). Among non-Kuwaitis, males and working age group (15-64 year) had relative risks of death from extreme hot temperatures of 2.90 (1.42-5.93), and 2.59 (1.20-5.59), respectively. For extreme cold temperatures and over the entire lag period, comparing the 1st percentile of temperature to the minimum mortality temperature, the relative risk of death among Kuwaitis was 2.03 (1.05-3.93). Elderly Kuwaitis (65+ year) exposed to extreme cold temperatures had a relative risk of 2.75 (1.16-6.52).

CONCLUSIONS

Certain subpopulations in Kuwait are vulnerable to extreme temperatures with doubling to tripling risk of mortality. Nationality is an important effect modifier in temperature-related mortality studies in Kuwait and possibly the Gulf region. To the best of our knowledge, we are the first study to examine specific subpopulation vulnerabilities to temperature in this region. Our findings could carry a potential for broader insight into similar hyper-arid and hot regions.

Projection of mortality attributed to heat and cold; the impact of climate change in a dry region of Iran, Kerman

BACKGROUND

Estimating the effects of climate change on human health can help health policy makers plan for the future. In Iran, there are few studies, about investigating the effects of climate change on mortality. This study aimed to project the effect of low (cold) and high (heat) temperature on mortality in a dry region of Iran, Kerman.

METHODS

Mortality attributed to temperature was projected by estimating the temperature-mortality relation for the observed data, projection of future temperatures by the statistical downscaling model (SDSM), and quantifying the attributable fraction by applying the observed temperature-mortality relation on the projected temperature. Climate change projection was done by three climate scenarios base on Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). Adaptation was considered by using different minimum mortality temperatures (MMT) and risk reduction approaches. The current decade (2010-19) was considered as the reference period.

RESULTS

All three climate change scenarios, showed that the mean of temperature will rise about 1 °C, by 2050 in Kerman. The number of deaths attributed to heat were obviously higher than cold in all periods. Assuming no adaptation, over 3700 deaths attributed to temperature will happen in each decade (2020s, 2030s and 2040s) in the future, in which over 3000 deaths will be due to heat and over 450 due to cold. In the predictions, as Minimum Mortality Temperature (MMT) went up, the contribution of heat to mortality slightly decreased, and cold temperature played a more important role. By considering the risk reduction due to adaptation, the contribution of heat in mortality slightly and insignificantly decreased.

CONCLUSION

The results showed that although low temperatures will contribute to temperature-related mortality in the future, but heat will be a stronger risk factor for mortality, especially if adaptation is low.

Temperature-related excess mortality in German cities at 2 °C and higher degrees of global warming

BACKGROUND

Investigating future changes in temperature-related mortality as a function of global mean temperature (GMT) rise allows for the evaluation of policy-relevant climate change targets. So far, only few studies have taken this approach, and, in particular, no such assessments exist for Germany, the most populated country of Europe.

METHODS

We assess temperature-related mortality in 12 major German cities based on daily time-series of all-cause mortality and daily mean temperatures in the period 1993-2015, using distributed-lag non-linear models in a two-stage design. Resulting risk functions are applied to estimate excess mortality in terms of GMT rise relative to pre-industrial levels, assuming no change in demographics or population vulnerability.

RESULTS

In the observational period, cold contributes stronger to temperature-related mortality than heat, with overall attributable fractions of 5.49% (95%CI: 3.82-7.19) and 0.81% (95%CI: 0.72-0.89), respectively. Future projections indicate that this pattern could be reversed under progressing global warming, with heat-related mortality starting to exceed cold-related mortality at 3 °C or higher GMT rise. Across cities, projected net increases in total temperature-related mortality were 0.45% (95%CI: -0.02-1.06) at 3 °C, 1.53% (95%CI: 0.96-2.06) at 4 °C, and 2.88% (95%CI: 1.60-4.10) at 5 °C, compared to today's warming level of 1 °C. By contrast, no significant difference was found between projected total temperature-related mortality at 2 °C versus 1 °C of GMT rise.

CONCLUSIONS

Our results can inform current adaptation policies aimed at buffering the health risks from increased heat exposure under climate change. They also allow for the evaluation of global mitigation efforts in terms of local health benefits in some of Germany's most populated cities.

Projections of Ambient Temperature- and Air Pollution-Related Mortality Burden Under Combined Climate Change and Population Aging Scenarios: a Review

PURPOSE OF REVIEW

Climate change will affect mortality associated with both ambient temperature and air pollution. Because older adults have elevated vulnerability to both non-optimal ambient temperature (heat and cold) and air pollution, population aging can amplify future population vulnerability to these stressors through increasing the number of vulnerable older adults. We aimed to review recent evidence on projections of temperature- or air pollution-related mortality burden (i.e., number of deaths) under combined climate change and population aging scenarios, with a focus on evaluating the role of population aging in assessing these health impacts of climate change. We included studies published between 2014 and 2019 with age-specific population projections.

RECENT FINDINGS

We reviewed 16 temperature projection studies and 15 air pollution projection studies. Nine of the temperature studies and four of the air pollution studies took population aging into account by performing age-stratified analyses that utilized age-specific relationships between temperature or air pollution exposures and mortality (i.e., age-specific exposure-response functions (ERFs)). Population aging amplifies the projected mortality burden of temperature and air pollution under a warming climate. Compared with a constant population scenario, population aging scenarios lead to less reduction or even increases in cold-related mortality burden, resulting in substantial net increases in future overall (heat and cold) temperature-related mortality burden. There is strong evidence suggesting that to accurately assess the future temperature- and air pollution-related mortality burden of climate change, investigators need to account for the amplifying effect of population aging. Thus, all future studies should incorporate age-specific population size projections and age-specific ERFs into their analyses. These studies would benefit from refinement of age-specific ERF estimates.

Future increase in elderly heat-related mortality of a rapidly growing Asian megacity

Urban dwellers are at risk of heat-related mortality in the onset of climate change. In this study, future changes in heat-related mortality of elderly citizens were estimated while considering the combined effects of spatially-varying megacity’s population growth, urbanization, and climate change. The target area is the Jakarta metropolitan area of Indonesia, a rapidly developing tropical country. 1.2 × 1.2 km² daily maximum temperatures were acquired from weather model outputs for the August months from 2006 to 2015 (present 2010s) and 2046 to 2055 (future 2050s considering pseudo-global warming of RCP2.6 and RCP8.5). The weather model considers population-induced spatial changes in urban morphology and anthropogenic heating distribution. Present and future heat-related mortality was mapped out based on the simulated daily maximum temperatures. The August total number of heat-related elderly deaths in Jakarta will drastically increase by 12~15 times in the 2050s compared to 2010s because of population aging and rising daytime temperatures under “compact city” and “business-as-usual” scenarios. Meanwhile, mitigating climate change (RCP 2.6) could reduce the August elderly mortality count by up to 17.34%. The downwind areas of the densest city core and the coastal areas of Jakarta should be avoided by elderly citizens during the daytime.

Estimation of Hourly near Surface Air Temperature Across Israel Using an Ensemble Model

Mapping of near-surface air temperature (Ta) at high spatio-temporal resolution is essential for unbiased assessment of human health exposure to temperature extremes, not least given the observed trend of urbanization and global climate change. Data constraints have led previous studies to focus merely on daily Ta metrics, rather than hourly ones, making them insufficient for intra-day assessment of health exposure. In this study, we present a three-stage machine learning-based ensemble model to estimate hourly Ta at a high spatial resolution of 1 × 1 km2, incorporating remotely sensed surface skin temperature (Ts) from geostationary satellites, reanalysis synoptic variables, and observations from weather stations, as well as auxiliary geospatial variables, which account for spatio-temporal variability of Ta. The Stage 1 model gap-fills hourly Ts at 4 × 4 km2 from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), which are subsequently fed into the Stage 2 model to estimate hourly Ta at the same spatio-temporal resolution. The Stage 3 model downscales the residuals between estimated and measured Ta to a grid of 1 × 1 km2, taking into account additionally the monthly diurnal pattern of Ts derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. In each stage, the ensemble model synergizes estimates from the constituent base learners—random forest (RF) and extreme gradient boosting (XGBoost)—by applying a geographically weighted generalized additive model (GAM), which allows the weights of results from individual models to vary over space and time. Demonstrated for Israel for the period 2004–2017, the proposed ensemble model outperformed each of the two base learners. It also attained excellent five-fold cross-validated performance, with overall root mean square error (RMSE) of 0.8 and 0.9 °C, mean absolute error (MAE) of 0.6 and 0.7 °C, and R2 of 0.95 and 0.98 in Stage 1 and Stage 2, respectively. The Stage 3 model for downscaling Ta residuals to 1 km MODIS grids achieved overall RMSE of 0.3 °C, MAE of 0.5 °C, and R2 of 0.63. The generated hourly 1 × 1 km2 Ta thus serves as a foundation for monitoring and assessing human health exposure to temperature extremes at a larger geographical scale, helping to further minimize exposure misclassification in epidemiological studies.

Temporal changes in years of life lost associated with heat waves in the Czech Republic

Seniors constitute the population group generally most at risk of mortality due to heat stress. As life expectancy increases and health conditions of elderly people improve over time, vulnerability of the population to heat changes as well. We employed the years-of-life-lost (YLL) approach, considering life expectancy at the time of each death, to investigate how population ageing affects temporal changes in heat-related mortality in the Czech Republic. Using an updated gridded meteorological database, we identified heat waves during 1994-2017, and analysed temporal changes in their impacts on YLL and mortality. The mean impact of a heat-wave day on relative excess mortality and YLL had declined by approximately 2-3% per decade. That decline abated in the current decade, however, and the decreasing trend in mean excess mortality as well as YLL vanished when the short-term mortality displacement effect was considered. Moreover, the cumulative number of excess deaths and YLL during heat waves rose due to increasing frequency and intensity of heat waves during the examined period. The results show that in studies of temporal changes it is important to differentiate between mean effects of heat waves on mortality and the overall death burden associated with heat waves. Analysis of the average ratio of excess YLL/death per heat-wave day indicated that the major heat-vulnerable population group shifted towards older age (70+ years among males and 75+ years among females). Our findings highlight the importance of focusing heat-protection measures especially upon the elderly population, which is most heat-vulnerable and whose numbers are rising.

Spatial patterns of health vulnerability to heatwaves in Vietnam

The increasing frequency and intensity of heat events have weighty impacts on public health in Vietnam, but their effects vary across regions. In this study, we have applied a vulnerability assessment framework (VAF) to systematically assess the spatial pattern of health vulnerability to heatwaves in Vietnam. The VAF was computed as the function of three dimensions: exposure, sensitivity, and adaptive capacity, with the indicators for each dimension derived from the relevant literature, consultation with experts, and available data. An analytic hierarchy process (AHP) was used to determine the weight of indicators. Each province in Vietnam's vulnerability to the health impacts of heatwaves was evaluated by applying the vulnerability index, computed using 13 indicators (sensitivity index, 9; adaptive capacity index, 3; and exposure index, 1). As a result of this analysis, this study has identified heatwave vulnerability 'hotspots', primarily in the Southeast, Central Highlands, and South Central Coast of Vietnam. However, these hotspots are not necessarily the same as the area most vulnerable to climate change, because some areas that are more sensitive to heatwaves may have a higher capacity to adapt to them due to a host of factors including their population characteristics (e.g. rates of the elderly or children), socio-economic and geographical conditions, and the availability of air-conditioners. This kind of information, provided by the vulnerability index framework, allows policymakers to determine how to more efficiently allocate resources and devise appropriate interventions to minimise the impact of heatwaves with strategies tailored to each region of Vietnam.

Flash droughts in the Pearl River Basin, China: Observed characteristics and future changes

Heat wave flash drought or precipitation deficit flash drought has devastating impacts on society and the environment. This study explored the historical changes (1960-2015) of the two categories of flash drought over the Pearl River Basin (PRB) in China, and revealed how they would change in the future (2016-2100), by coupling the variable infiltration capacity mode with the global climate model under representative concentration pathway (RCP) 2.6, 4.5, and 8.5 scenarios. Our results indicate that during 1960-2015, the mid-northern PRB has experienced heat wave flash drought frequently while the western PRB suffered from precipitation deficit flash drought. In future, heat wave flash drought under RCP2.6 and 4.5 would occur mostly in the western and eastern PRB. Specifically, heat wave flash drought would become severe under RCP8.5, especially for the eastern PRB. However, precipitation deficit flash drought would be concentrated in the western PRB. Except for the central regions, PRB generally exhibits a significant upward trend in heat wave flash drought under RCP4.5. Under RCP8.5, distinct increases in both categories of flash drought across almost the whole PRB are expected. For precipitation deficit flash drought, only a few regions show significant upward trends under RCP2.6 and 4.5.

Anomalously warm temperatures are associated with increased injury deaths

Temperatures that deviate from the long-term local norm affect human health, and are projected to become more frequent as the global climate changes1. There are limited data on how such anomalies affect deaths from injuries. In the present study, we used data on mortality and temperature over 38 years (1980-2017) in the contiguous USA and formulated a Bayesian spatio-temporal model to quantify how anomalous temperatures, defined as deviations of monthly temperature from the local average monthly temperature over the entire analysis period, affect deaths from unintentional (transport, falls and drownings) and intentional (assault and suicide) injuries, by age group and sex. We found that a 1.5 °C anomalously warm year, as envisioned under the Paris Climate Agreement2, would be associated with an estimated 1,601 (95% credible interval 1,430-1,776) additional injury deaths. Of these additional deaths, 84% would occur in males, mostly in adolescence to middle age. These would comprise increases in deaths from drownings, transport, assault and suicide, offset partly by a decline in deaths from falls in older ages. The findings demonstrate the need for targeted interventions against injuries during periods of anomalously warm temperatures, especially as these episodes are likely to increase with global climate change.

Weather patterns and all-cause mortality in England, UK

Cold- and heat-related mortality poses significant public health concerns worldwide. Although there are numerous studies dealing with the association between extreme ambient temperature and mortality, only a small number adopt a synoptic climatological approach in order to understand the nature of weather systems that precipitate increases in cold- or heat-related mortality. In this paper, the Lamb Weather Type synoptic classification is used to examine the relationship between daily mortality and weather patterns across nine regions of England. Analysis results revealed that the population in England is more susceptible to cold weather. Furthermore, it was found that the Easterly weather types are the most hazardous for public health all-year-long; however, during the cold period, the results are more evident and spatially homogenous. Nevertheless, it is noteworthy that the most dangerous weather conditions are not always associated with extreme (high or low) temperatures, a finding which points to the complexity of weather-related health effects and highlights the importance of a synoptic climatological approach in elucidating the relationship between temperature and mortality.

Projections of the effects of global warming on the disease burden of ischemic heart disease in the elderly in Tianjin, China

Background

Ischemic heart disease (IHD) is one of the leading causes of deaths worldwide and causes a tremendous disease burden. Temperature is an important environmental determinant among the many risk factors for IHD. However, the emerging temperature-related health risks of IHD in the elderly is limited because of the lack of estimates that integrate global warming and demographic change.

Methods

Data on daily IHD deaths in the elderly aged ≥65 years and meteorological conditions were collected in Tianjin, a megacity of China, from 2006 to 2011. First, the baseline relationship between the temperature and years of life lost (YLL) from IHD was established. Then, future assessments were performed in combination with temperature projections for 19 global-scale climate models (GCMs) under 3 representative concentration pathways (RCPs) for the 2050s and 2070s.

Results

Increased YLL from IHD in the elderly was found to be associated with future ambient temperatures. The annual temperature-related YLL from IHD in the 2050s and 2070s were higher than the baseline. For instance, increases of 4.5, 14.9 and 38.3% were found under the RCP2.6, RCP4.5 and RCP8.5 scenarios, respectively, in the 2070s. The most significant increases occurred in warm season months. The increase in heat-related YLL will not be completely offset, even with the 25% adaptation assumed. When considering demographic change, the temperature-related disease burden of IHD in the elderly will be exacerbated by 158.4 to 196.6% under 3 RCPs in the 2050s and 2070s relative to the baseline.

Conclusions

These findings have significant meaning for environmental and public health policy making and interventions towards the important issue of the health impacts of global warming on the elderly.

Hands-on Tutorial on a Modeling Framework for Projections of Climate Change Impacts on Health

Supplemental Digital Content is available in the text.

Reliable estimates of future health impacts due to climate change are needed to inform and contribute to the design of efficient adaptation and mitigation strategies. However, projecting health burdens associated to specific environmental stressors is a challenging task because of the complex risk patterns and inherent uncertainty of future climate scenarios. These assessments involve multidisciplinary knowledge, requiring expertise in epidemiology, statistics, and climate science, among other subjects. Here, we present a methodologic framework to estimate future health impacts under climate change scenarios based on a defined set of assumptions and advanced statistical techniques developed in time-series analysis in environmental epidemiology. The proposed methodology is illustrated through a step-by-step hands-on tutorial structured in well-defined sections that cover the main methodological steps and essential elements. Each section provides a thorough description of each step, along with a discussion on available analytical options and the rationale on the choices made in the proposed framework. The illustration is complemented with a practical example of study using real-world data and a series of R scripts included as Supplementary Digital Content; http://links.lww.com/EDE/B504, which facilitates its replication and extension on other environmental stressors, outcomes, study settings, and projection scenarios. Users should critically assess the potential modeling alternatives and modify the framework and R code to adapt them to their research on health impact projections.