Projections of temperature-attributable premature deaths in 209 U.S. cities using a cluster-based Poisson approach

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.

Mapping Heat Vulnerability of a Community Mental Health Center Population

Individuals with serious mental illness are vulnerable to extreme heat due to biological, social, and place-based factors. We examine the spatial correlation of prevalence of individuals treated at a community mental health center to heat vulnerability. We applied a heat vulnerability index (HVI) to the catchment of the Connecticut Mental Health Center in New Haven, Connecticut. Geocoded addresses were mapped to correlate patient prevalence with heat vulnerability of census tracts. Census tracts closer to the city center had elevated vulnerability scores. Patient prevalence was positively correlated with HVI score (Pearson's r(44) = 0.67, p < 0.01). Statistical significance persists after correction for spatial autocorrelation (modified t-test p < 0.01). The study indicates that individuals treated at this community mental health center are more likely to live in census tracts with high heat vulnerability. Heat mapping strategies can help communicate risk and target resources at the local scale.

Hourly personal temperature exposure and heart rate variability: A multi-center panel study in populations at intermediate to high-risk of cardiovascular disease

BACKGROUND

Several studies reported temperature exposure was associated with altered cardiac automatic function, while this effect of temperature on hourly heart rate variability (HRV) among populations with cardiovascular risks was seldom addressed.

METHODS

We conducted this panel study in four Chinese cities with three repeated visits among 296 participants at intermediate to high-risk of cardiovascular disease (CVD). Real-time temperature level and 24-h ambulatory electrocardiogram were monitored during each seasonal visit. Linear mixed-effects models were used to investigate associations between individual temperature and HRV parameters, and the seasonal effects and circadian effect were also evaluated.

RESULTS

We found the overall downward trend of hourly HRV associated with acute exposure to higher temperature. For each 1 °C increment in temperature of 1-3 h prior to HRV measurements (lag 1-3 h), hourly standard deviation of normal-to-normal intervals (SDNN) decreased by 0.38% (95% confidence interval [CI]: 0.22, 0.54), 0.28% (95% CI: 0.12, 0.44), and 0.20% (95% CI: 0.04, 0.36), respectively. Similar inverse associations between temperature and HRV were observed in stratified analyses by temperature level. Inverse associations for cold and warm seasons were also observed, despite some effects gradually decreased and reversed in the warm season as lag times extended. Moreover, HRV showed a more significant reduction with increased temperature during daytime than nighttime. Percent change of hourly SDNN was -0.41% (95% CI: -0.62, -0.21) with 1 °C increment of lag 1 h during daytime, while few obvious changes were revealed during nighttime.

CONCLUSIONS

Generally, increasing temperature was significantly associated with reduced HRV. Inverse relationships for cold and warm seasons were also observed. Associations during daytime were much more prominent than nighttime. Our findings clarified the relationship of temperature with HRV and provided evidence for prevention approaches to alleviate cardiac automatic dysfunction among populations at intermediate to high-risk of CVD.

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.

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.

Variation in estimates of heat-related mortality reduction due to tree cover in U.S. cities

Heat-related mortality is one of the leading causes of weather-related deaths in the United States. With changing climates and an aging population, effective adaptive strategies to address public health and environmental justice issues associated with extreme heat will be increasingly important. One effective adaptive strategy for reducing heat-related mortality is increasing tree cover. Designing such a strategy requires decision-support tools that provide spatial and temporal information about impacts. We apply such a tool to estimate spatially and temporally explicit reductions in temperature and mortality associated with a 10% increase in tree cover in 10 U.S. cities with varying climatic, demographic, and land cover conditions. Two heat metrics were applied to represent tree impacts on moderately and extremely hot days (relative to historical conditions). Increasing tree cover by 10% reduced estimated heat-related mortality in cities significantly, with total impacts generally greatest in the most populated cities. Mortality reductions vary widely across cities, ranging from approximately 50 fewer deaths in Salt Lake City to about 3800 fewer deaths in New York City. This variation is due to differences in demographics, land cover, and local climatic conditions. In terms of per capita estimated impacts, hotter and drier cities experience higher percentage reductions in mortality due to increased tree cover across the season. Phoenix potentially benefits the most from increased tree cover, with an estimated 22% reduction in mortality from baseline levels. In cooler cities such as Minneapolis, trees can reduce mortality significantly on days that are extremely hot relative to historical conditions and therefore help mitigate impacts during heat wave conditions. Recent studies project highest increases in heat-related mortality in the cooler cities, so our findings have important implications for adaptation planning. Our estimated spatial and temporal distributions of mortality reductions for each city provide crucial information needed for promoting environmental justice and equity. More broadly, the methods and model can be applied by both urban planners and the public health community for designing targeted, effective policies to reduce heat-related mortality. Additionally, land use managers can use this information to optimize tree plantings. Public stakeholders can also use these impact estimates for advocacy.

Temperature-mortality association during and before the COVID-19 pandemic in Italy: A nationwide time-stratified case-crossover study

OBJECTIVES

To identify the associations of temperature with non-COVID-19 mortality and all-cause mortality in the pandemic 2020 in comparison with the non-COVID-19 period in Italy.

METHODS

The data on 3,189,790 all-cause deaths (including 3,134,137 non-COVID-19 deaths) and meteorological conditions in 107 Italian provinces between February 1st and November 30th in each year of 2015-2020 were collected. We employed a time-stratified case-crossover study design combined with the distributed lag non-linear model to investigate the relationships of temperature with all-cause and non-COVID-19 mortality in the pandemic and non-pandemic periods.

RESULTS

Cold temperature exposure contributed higher risks for both all-cause and non-COVID-19 mortality in the pandemic period in 2020 than in 2015-2019. However, no different change was found for the impacts of heat. The relative risk (RR) of non-COVID-19 deaths and all-cause mortality at extremely cold (2 °C) in comparison with the estimated minimum mortality temperature (19 °C) in 2020 were 1.63 (95% CI: 1.55-1.72) and 1.45 (95%CI: 1.31-1.61) respectively, which were higher than all-cause mortality risk in 2015-2019 with RR of 1.19 (95%CI: 1.17-1.21).

CONCLUSION

Cold exposure indicated stronger impacts than high temperatures on all-cause and non-COVID-19 mortality in the pandemic year 2020 compared to its counterpart period in 2015-2019 in Italy.

Factors That Influence Climate Change-Related Mortality in the United States: An Integrative Review

Global atmospheric warming leads to climate change that results in a cascade of events affecting human mortality directly and indirectly. The factors that influence climate change-related mortality within the peer-reviewed literature were examined using Whittemore and Knafl’s framework for an integrative review. Ninety-eight articles were included in the review from three databases—PubMed, Web of Science, and Scopus—with literature filtered by date, country, and keywords. Articles included in the review address human mortality related to climate change. The review yielded two broad themes in the literature that addressed the factors that influence climate change-related mortality. The broad themes are environmental changes, and social and demographic factors. The meteorological impacts of climate change yield a complex cascade of environmental and weather events that affect ambient temperatures, air quality, drought, wildfires, precipitation, and vector-, food-, and water-borne pathogens. The identified social and demographic factors were related to the social determinants of health. The environmental changes from climate change amplify the existing health determinants that influence mortality within the United States. Mortality data, national weather and natural disaster data, electronic medical records, and health care provider use of International Classification of Disease (ICD) 10 codes must be linked to identify climate change events to capture the full extent of climate change upon population health.

Health Impacts of Climate Change as Contained in Economic Models Estimating the Social Cost of Carbon Dioxide

The health impacts of climate change are substantial and represent a primary motivating factor to mitigate climate change. However, the health impacts in economic models that estimate the social cost of carbon dioxide (SC-CO2) have generally been made in isolation from health experts and have never been rigorously evaluated. Version 3.10 of the Framework for Uncertainty, Negotiation and Distribution (FUND) model was used to estimate the health-based portion of current SC-CO2 estimates across low-, middle-, and high-income regions. In addition to the base model, three additional experiments assessed the sensitivity of these estimates to changes in the socio-economic assumptions in the model. Economic impacts from adverse health outcomes represent ∼8.7% of current SC-CO2 estimates. The majority of these health impacts (74%) were attributable to diarrhea mortality (from both low- and high-income regions) followed by diarrhea morbidity (12%) and malaria mortality (11%); no other health impact makes a meaningful contribution to SC-CO2 estimates in current economic models. The results of the socio-economic experiments show that the health-based portion of SC-CO2 estimates are highly sensitive to assumptions regarding income elasticity of health effects, income growth, and use of equity weights. Improving the health-based portion of SC-CO2 estimates could have substantial impacts on magnitude of the SC-CO2. Incorporating additional health impacts not previously included in estimates of SC-CO2 will be a critical component of model updates. This effort will be most successful through coordination between economists and health researchers and should focus on updating the form and function of concentration-response functions.

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.

Effects of climate change on combined labour productivity and supply: an empirical, multi-model study

BACKGROUND

Although effects on labour is one of the most tangible and attributable climate impact, our quantification of these effects is insufficient and based on weak methodologies. Partly, this gap is due to the inability to resolve different impact channels, such as changes in time allocation (labour supply) and slowdown of work (labour productivity). Explicitly resolving those in a multi-model inter-comparison framework can help to improve estimates of the effects of climate change on labour effectiveness.

METHODS

In this empirical, multi-model study, we used a large collection of micro-survey data aggregated to subnational regions across the world to estimate new, robust global and regional temperature and wet-bulb globe temperature exposure-response functions (ERFs) for labour supply. We then assessed the uncertainty in existing labour productivity response functions and derived an augmented mean function. Finally, we combined these two dimensions of labour into a single compound metric (effective labour effects). This combined measure allowed us to estimate the effect of future climate change on both the number of hours worked and on the productivity of workers during their working hours under 1·5°C, 2·0°C, and 3·0°C of global warming. We separately analysed low-exposure (indoors or outdoors in the shade) and high-exposure (outdoor in the sun) sectors.

FINDINGS

We found differentiated empirical regional and sectoral ERF's for labour supply. Current climate conditions already negatively affect labour effectiveness, particularly in tropical countries. Future climate change will reduce global total labour in the low-exposure sectors by 18 percentage points (range -48·8 to 5·3) under a scenario of 3·0°C warming (24·8 percentage points in the high-exposure sectors). The reductions will be 25·9 percentage points (-48·8 to 2·7) in Africa, 18·6 percentage points (-33·6 to 5·3) in Asia, and 10·4 percentage points (-35·0 to 2·6) in the Americas in the low-exposure sectors. These regional effects are projected to be substantially higher for labour outdoors in full sunlight compared with indoors (or outdoors in the shade) with the average reductions in total labour projected to be 32·8 percentage points (-66·3 to 1·6) in Africa, 25·0 percentage points (-66·3 to 7·0) in Asia, and 16·7 percentage points (-45·5 to 4·4) in the Americas.

INTERPRETATION

Both labour supply and productivity are projected to decrease under future climate change in most parts of the world, and particularly in tropical regions. Parts of sub-Saharan Africa, south Asia, and southeast Asia are at highest risk under future warming scenarios. The heterogeneous regional response functions suggest that it is necessary to move away from one-size-fits-all response functions to investigate the climate effect on labour. Our findings imply income and distributional consequences in terms of increased inequality and poverty, especially in low-income countries, where the labour effects are projected to be high.

FUNDING

COST (European Cooperation in Science and Technology).

City-level vulnerability to temperature-related mortality in the USA and future projections: a geographically clustered meta-regression

BACKGROUND

Extreme heat exposure can lead to premature death. Climate change is expected to increase the frequency, intensity, and duration of extreme heat events, resulting in many additional heat-related deaths globally, as well as changing the nature of extreme cold events. At the same time, vulnerability to extreme heat has decreased over time, probably due to a combination of physiological, behavioural, infrastructural, and technological adaptations. We aimed to account for these changes in vulnerability and avoid overstated projections for temperature-related mortality. We used the historical observed decrease in vulnerability to improve future mortality estimates.

METHODS

We used historical mortality and temperature data from 208 US cities to quantify how observed changes in vulnerability from 1973 to 2013 affected projections of temperature-related mortality under various climate scenarios. We used geographically structured meta-regression to characterise the relationship between temperature and mortality for these urban populations over the specified time period. We then used the fitted relationships to project mortality under future climate conditions.

FINDINGS

Between Oct 26, 2018, and March 9, 2020, we established that differences in vulnerability to temperature were geographically structured. Vulnerability decreased over time in most areas. US mortalities projected from a 2°C increase in mean temperature decreased by more than 97% when using 2003-13 data compared with 1973-82 data. However, these benefits declined with increasing temperatures, with a 6°C increase showing only an 84% decline in projected mortality based on 2003-13 data.

INTERPRETATION

Even after accounting for adaptation, the projected effects of climate change on premature mortality constitute a substantial public health risk. Our work suggests large increases in temperature will require additional mitigation to avoid excess mortality from heat events, even in areas with high air conditioning coverage in place.

FUNDING

The US Environmental Protection Agency and Abt Associates.

Compound Climate and Infrastructure Events: How Electrical Grid Failure Alters Heat Wave Risk

The potential for critical infrastructure failures during extreme weather events is rising. Major electrical grid failure or "blackout" events in the United States, those with a duration of at least 1 h and impacting 50,000 or more utility customers, increased by more than 60% over the most recent 5 year reporting period. When such blackout events coincide in time with heat wave conditions, population exposures to extreme heat both outside and within buildings can reach dangerously high levels as mechanical air conditioning systems become inoperable. Here, we combine the Weather Research and Forecasting regional climate model with an advanced building energy model to simulate building-interior temperatures in response to concurrent heat wave and blackout conditions for more than 2.8 million residents across Atlanta, Georgia; Detroit, Michigan; and Phoenix, Arizona. Study results find simulated compound heat wave and grid failure events of recent intensity and duration to expose between 68 and 100% of the urban population to an elevated risk of heat exhaustion and/or heat stroke.

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.

Analysis of Correlation between Climate Change and Human Health Based on a Machine Learning Approach

Climate change increasingly affects every aspect of human life. Recent studies report a close correlation with human health and it is estimated that global death rates will increase by 73 per 100,000 by 2100 due to changes in temperature. In this context, the present work aims to study the correlation between climate change and human health, on a global scale, using artificial intelligence techniques. Starting from previous studies on a smaller scale, that represent climate change and which at the same time can be linked to human health, four factors were chosen. Four causes of mortality, strongly correlated with the environment and climatic variability, were subsequently selected. Various analyses were carried out, using neural networks and machine learning to find a correlation between mortality due to certain diseases and the leading causes of climate change. Our findings suggest that anthropogenic climate change is strongly correlated with human health; some diseases are mainly related to risk factors while others require a more significant number of variables to derive a correlation. In addition, a forecast of victims related to climate change was formulated. The predicted scenario confirms that a prevalently increasing trend in climate change factors corresponds to an increase in victims.

Predicted impact of increasing average ambient temperature over the coming century on mortality from cardiovascular disease and stroke in the USA

BACKGROUND AND AIMS

Future climate change may adversely impact human health. The direct effects of extreme hot temperatures on mortality are well established, and their future impact well modelled. However, less extreme changes in ambient temperature (Ta) have been previously associated with increased mortality from circulatory and metabolic diseases, but their future impact is less clear.

METHODS

We evaluated the spatial association between cardiovascular diseases (CVD) and stroke mortality with average Ta across the US mainland, and then used this relationship to model future temporal trends in mortality from CVD and stroke until the end of the century (2099), using different warming scenarios for each US county.

RESULTS

Ta was significantly associated with crude levels of CVD mortality (R² = 0.269) and stroke mortality (R² = 0.264). Moreover, there was a strong positive link between Ta and physical inactivity (PIA) (R² = 0.215). Once adjusted for PIA the associations between Ta and CVD and stroke mortality were much reduced (R² = 0.054 and R² = 0.091 respectively) but still highly significant.

CONCLUSIONS

By 2099 modelling suggests between 8844 and 25,486 extra deaths each year from CVD, and between 2,063 and 13,039 extra deaths for stroke, beyond the increases expected from population expansion. Mortality due to changes in the mean Ta may be as, or more, significant than the impacts of extreme hot weather events.

Modeling and comparing central and room air conditioning ownership and cold-season in-home thermal comfort using the American Housing Survey

Household-level information on central air conditioning (cenAC) and room air conditioning (rmAC) air conditioning and cold-weather thermal comfort are often missing from publicly available housing databases hindering research and action on climate adaptation and air pollution exposure reduction. We modeled these using information from the American Housing Survey for 2003-2013 and 140 US core-based statistical areas employing variables that would be present in publicly available parcel records. We present random-intercept logistic regression models with either cenAC, rmAC or "home was uncomfortably cold for 24 h or more" (tooCold) as outcome variables and housing value, rented vs. owned, age, and multi- vs. single-family, each interacted with cooling- or heating-degree days as predictors. The out-of-sample predicted probabilities for years 2015-2017 were compared with corresponding American Housing Survey values (0 or 1). Using a 0.5 probability threshold, the model had 63% specificity (true negative rate), and 91% sensitivity (true positive rate) for cenAC, while specificity and sensitivity for rmAC were 94% and 34%, respectively. Area-specific sensitivities and specificities varied widely. For tooCold, the overall sensitivity was effectively 0%. Future epidemiologic studies, heat vulnerability maps, and intervention screenings may reliably use these or similar AC models with parcel-level data to improve understanding of health risk and the spatial patterning of homes without AC.

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.

The Effects of Heat Exposure on Human Mortality Throughout the United States

Exposure to high ambient temperatures is an important cause of avoidable, premature death that may become more prevalent under climate change. Though extensive epidemiological data are available in the United States, they are largely limited to select large cities, and hence, most projections estimate the potential impact of future warming on a subset of the U.S. population. Here we utilize evaluations of the relative risk of premature death associated with temperature in 10 U.S. cities spanning a wide range of climate conditions to develop a generalized risk function. We first evaluate the performance of this generalized function, which introduces substantial biases at the individual city level but performs well at the large scale. We then apply this function to estimate the impacts of projected climate change on heat-related nationwide U.S. deaths under a range of scenarios. During the current decade, there are 12,000 (95% confidence interval 7,400-16,500) premature deaths annually in the contiguous United States, much larger than most estimates based on totals for select individual cities. These values increase by 97,000 (60,000-134,000) under the high-warming Representative Concentration Pathway (RCP) 8.5 scenario and by 36,000 (22,000-50,000) under the moderate RCP4.5 scenario by 2100, whereas they remain statistically unchanged under the aggressive mitigation scenario RCP2.6. These results include estimates of adaptation that reduce impacts by ~40-45% as well as population increases that roughly offset adaptation. The results suggest that the degree of climate change mitigation will have important health impacts on Americans.

Predicted temperature-increase-induced global health burden and its regional variability

An increase in the global health burden of temperature was projected for 459 locations in 28 countries worldwide under four representative concentration pathway scenarios until 2099. We determined that the amount of temperature increase for each 100 ppm increase in global CO₂ concentrations is nearly constant, regardless of climate scenarios. The overall average temperature increase during 2010-2099 is largest in Canada (1.16 °C/100 ppm) and Finland (1.14 °C/100 ppm), while it is smallest in Ireland (0.62 °C/100 ppm) and Argentina (0.63 °C/100 ppm). In addition, for each 1 °C temperature increase, the amount of excess mortality is increased largely in tropical countries such as Vietnam (10.34%p/°C) and the Philippines (8.18%p/°C), while it is decreased in Ireland (-0.92%p/°C) and Australia (-0.32%p/°C). To understand the regional variability in temperature increase and mortality, we performed a regression-based modeling. We observed that the projected temperature increase is highly correlated with daily temperature range at the location and vulnerability to temperature increase is affected by health expenditure, and proportions of obese and elderly population.

Tens of thousands additional deaths annually in cities of China between 1.5 °C and 2.0 °C warming

The increase in surface air temperature in China has been faster than the global rate, and more high temperature spells are expected to occur in future. Here we assess the annual heat-related mortality in densely populated cities of China at 1.5 °C and 2.0 °C global warming. For this, the urban population is projected under five SSPs, and 31 GCM runs as well as temperature-mortality relation curves are applied. The annual heat-related mortality is projected to increase from 32.1 per million inhabitants annually in 1986–2005 to 48.8–67.1 per million for the 1.5 °C warming and to 59.2–81.3 per million for the 2.0 °C warming, taking improved adaptation capacity into account. Without improved adaptation capacity, heat-related mortality will increase even stronger. If all 831 million urban inhabitants in China are considered, the additional warming from 1.5 °C to 2 °C will lead to more than 27.9 thousand additional heat-related deaths, annually.

Heatwaves are expected to increase under climate change, and so are the associated deaths. Here the authors determine the regional high temperature thresholds for 27 metropolises in China and analyze the changes to heat-related mortality, showing that the additional global-warming temperature increase of 0.5°C, from 1.5°C to 2.0°C, will lead to tens of thousands of additional deaths, annually.

Impacts of exposure to ambient temperature on burden of disease: a systematic review of epidemiological evidence

Ambient temperature is an important determinant of mortality and morbidity, making it necessary to assess temperature-related burden of disease (BD) for the planning of public health policies and adaptive responses. To systematically review existing epidemiological evidence on temperature-related BD, we searched three databases (PubMed, Web of Science, and Scopus) on 1 September 2018. We identified 97 studies from 56 counties for this review, of which 75 reported the fraction or number of health outcomes (include deaths and diseases) attributable to temperature, and 22 reported disability-adjusted life years (include years of life lost and years lost due to disability) related to temperature. Non-optimum temperatures (i.e., heat and cold) were responsible for > 2.5% of mortality in all included high-income countries/regions, and > 3.0% of mortality in all included middle-income countries. Cold was mostly reported to be the primary source of mortality burden from non-optimum temperatures, but the relative role of three different temperature exposures (i.e., heat, cold, and temperature variability) in affecting morbidity and mortality remains unclear so far. Under the warming climate scenario, almost all projections assuming no population adaptation suggested future increase in heat-related but decrease in cold-related BD. However, some studies emphasized the great uncertainty in future pattern of temperature-related BD, largely depending on the scenarios of climate, population adaptation, and demography. We also identified important discrepancies and limitations in current research methodologies employed to measure temperature exposures and model temperature-health relationship, and calculate the past and project future temperature-related BD. Overall, exposure to non-optimum ambient temperatures has become and will continue to be a considerable contributor to the global and national BD, but future research is still needed to develop a stronger methodological framework for assessing and comparing temperature-related BD across different settings.

Temperature-Related Summer Mortality Under Multiple Climate, Population, and Adaptation Scenarios

Projections of the magnitude and pattern of possible health risks from climate change should be based on multiple climate and development scenarios to describe the range of uncertainties, to inform effective and efficient policies. For a better understanding of climate change-related risks in seven metropolitan cities of South Korea, we estimated temperature-related summer (June to August) mortality until 2100 using projected changes in climate, population, and adaptation. In addition, we extracted the variations in the mortality estimates associated with uncertainties in climate, population, and adaptation scenarios using 25 climate models, two Representative Concentration Pathways (RCP 4.5 and 8.5), three population scenarios (high, medium and low variants), and four adaptation scenarios (absolute threshold shift, slope reduction in the temperature-mortality relationship, a combination of slope reduction and threshold shift, and a sigmoid function based on the historical trend). Compared to the baseline period (1991⁻2015), temperature-attributable mortality in South Korea during summer in the 2090s is projected to increase 5.1 times for RCP 4.5 and 12.9 times for RCP 8.5 due to climate and population changes. Estimated future mortality varies by up to +44%/-55%, -80%, -60%, and +12%/-11% associated with the choice of climate models, adaptation, climate, and population scenarios, respectively, compared to the mortality estimated for the median of the climate models, no adaptation, RCP 8.5, and medium population variant. Health system choices about adaptation are the most important determinants of future mortality after climate projections. The range of possible future mortality underscores the importance of flexible, iterative risk management.

Projected Changes in Temperature-related Morbidity and Mortality in Southern New England

BACKGROUND

Climate change is expected to result in more heat-related, but potentially fewer cold-related, emergency department visits and deaths. The net effect of projected changes in temperature on morbidity and mortality remains incompletely understood. We estimated the change in temperature-related morbidity and mortality at two sites in southern New England, United States, through the end of the 21st century.

METHODS

We used distributed lag Poisson regression models to estimate the present-day associations between daily mean temperature and all-cause emergency department visits and deaths in Rhode Island and in Boston, Massachusetts. We estimated the change in temperature-related visits and deaths in 2045-2054 and 2085-2094 (relative to 2001-2010) under two greenhouse gas emissions scenarios (RCP4.5 and RCP8.5) using downscaled projections from an ensemble of over 40 climate models, assuming all other factors remain constant.

RESULTS

We observed U-shaped relationships between temperature and morbidity and mortality in Rhode Island, with minima at 10.9°C and 22.5°C, respectively. We estimated that, if this population were exposed to the future temperatures projected under RCP8.5 for 2085-2094, there would be 5,976 (95% eCI = 1,630, 11,379) more emergency department visits but 218 (95% eCI = -551, 43) fewer deaths annually. Results were similar in Boston and similar but less pronounced in the 2050s and under RCP4.5.

CONCLUSIONS

We estimated that in the absence of further adaptation, if the current southern New England population were exposed to the higher temperatures projected for future decades, temperature-related emergency department visits would increase but temperature-related deaths would not.

Socio-geographic disparity in cardiorespiratory mortality burden attributable to ambient temperature in the United States

Compared with relative risk, attributable fraction (AF) is more informative when assessing the mortality burden due to some environmental exposures (e.g., ambient temperature). Up to date, however, available AF-based evidence linking temperature with mortality has been very sparse regionally and nationally, even for the leading mortality types such as cardiorespiratory deaths. This study aimed to quantify national and regional burden of cardiorespiratory mortality (CRM) attributable to ambient temperature in the USA, and to explore potential socioeconomic and demographic sources of spatial heterogeneity between communities. Daily CRM and weather data during 1987-2000 for 106 urban communities across the mainland of USA were acquired from the publicly available National Morbidity, Mortality and Air Pollution Study (NMMAPS). We did the data analysis using a three-stage analytic approach. We first applied quasi-Poisson regression incorporated with distributed lag nonlinear model to estimate community-specific temperature-CRM associations, then pooled these associations at the regional and national level through a multivariate meta-analysis, and finally estimated the temperature-AF of CRM and performed subgroup analyses stratified by community-level characteristics. Both low and high temperatures increased short-term CRM risk, while temperature-CRM associations varied by regions. Nationally, the fraction of cardiorespiratory deaths caused by the total non-optimum, low, and high temperatures was 7.58% (95% empirical confidence interval, 6.68-8.31%), 7.15% (6.31-7.85%), and 0.43% (0.37-0.46%), respectively. Greater temperature-AF was identified in two northern regions (i.e., Industrial Midwest and North East) and communities with lower temperature and longitude, higher latitude, and moderate humidity. Additionally, higher vulnerability appeared in locations with higher urbanization level, more aging population, less White race, and lower socioeconomic status. Ambient temperature may be responsible for a large fraction of cardiorespiratory deaths. Also, temperature-AF of CRM varied considerably by geographical and climatological factors, as well as community-level disparity in socioeconomic status.

Strengthened scientific support for the Endangerment Finding for atmospheric greenhouse gases

We assess scientific evidence that has emerged since the U.S. Environmental Protection Agency’s 2009 Endangerment Finding for six well-mixed greenhouse gases and find that this new evidence lends increased support to the conclusion that these gases pose a danger to public health and welfare. Newly available evidence about a wide range of observed and projected impacts strengthens the association between the risk of some of these impacts and anthropogenic climate change, indicates that some impacts or combinations of impacts have the potential to be more severe than previously understood, and identifies substantial risk of additional impacts through processes and pathways not considered in the Endangerment Finding.

Heat-Related Health Impacts under Scenarios of Climate and Population Change

Recent assessments have found that a warming climate, with associated increases in extreme heat events, could profoundly affect human health. This paper describes a new modeling and analysis framework, built around the Benefits Mapping and Analysis Program-Community Edition (BenMAP), for estimating heat-related mortality as a function of changes in key factors that determine the health impacts of extreme heat. This new framework has the flexibility to integrate these factors within health risk assessments, and to sample across the uncertainties in them, to provide a more comprehensive picture of total health risk from climate-driven increases in extreme heat. We illustrate the framework's potential with an updated set of projected heat-related mortality estimates for the United States. These projections combine downscaled Coupled Modeling Intercomparison Project 5 (CMIP5) climate model simulations for Representative Concentration Pathway (RCP)4.5 and RCP8.5, using the new Locating and Selecting Scenarios Online (LASSO) tool to select the most relevant downscaled climate realizations for the study, with new population projections from EPA's Integrated Climate and Land Use Scenarios (ICLUS) project. Results suggest that future changes in climate could cause approximately from 3000 to more than 16,000 heat-related deaths nationally on an annual basis. This work demonstrates that uncertainties associated with both future population and future climate strongly influence projected heat-related mortality. This framework can be used to systematically evaluate the sensitivity of projected future heat-related mortality to the key driving factors and major sources of methodological uncertainty inherent in such calculations, improving the scientific foundations of risk-based assessments of climate change and human health.

A class of semiparametric tests of treatment effect robust to confounder measurement error

When assessing the presence of an exposure causal effect on a given outcome, measurement error of a confounder can inflate the type I error rate of a treatment effect in even the simplest of settings. In this paper, we develop a large class of semiparametric test statistics of an exposure causal effect, which are completely robust to additive unbiased measurement error of a subset of confounders. A unique and appealing feature of our proposed methodology is that it requires no external information such as validation data or replicates of error-prone confounders. We present a doubly robust form of this test that requires the exposure mean model to be linear in the mismeasured confounders, and only one of two models involving error-free confounders to be correctly specified for the resulting test statistic to have correct type I error rate. We demonstrate validity within our class of test statistics through simulation studies. We apply the methods to a multi-US-city time-series data set to test for an effect of temperature on mortality while adjusting for atmospheric particulate matter with diameter of 2.5 micrometres or less, which is known to be measured with error.

Climate change and temperature extremes: A review of heat- and cold-related morbidity and mortality concerns of municipalities

Cold and hot weather are associated with mortality and morbidity. Although the burden of temperature-associated mortality may shift towards high temperatures in the future, cold temperatures may represent a greater current-day problem in temperate cities. Hot and cold temperature vulnerabilities may coincide across several personal and neighborhood characteristics, suggesting opportunities for increasing present and future resilience to extreme temperatures. We present a narrative literature review encompassing the epidemiology of cold- and heat-related mortality and morbidity, related physiologic and environmental mechanisms, and municipal responses to hot and cold weather, illustrated by Detroit, Michigan, USA, a financially burdened city in an economically diverse metropolitan area. The Detroit area experiences sharp increases in mortality and hospitalizations with extreme heat, while cold temperatures are associated with more gradual increases in mortality, with no clear threshold. Interventions such as heating and cooling centers may reduce but not eliminate temperature-associated health problems. Furthermore, direct hemodynamic responses to cold, sudden exertion, poor indoor air quality and respiratory epidemics likely contribute to cold-related mortality. Short- and long-term interventions to enhance energy and housing security and housing quality may reduce temperature-related health problems. Extreme temperatures can increase morbidity and mortality in municipalities like Detroit that experience both extreme heat and prolonged cold seasons amidst large socioeconomic disparities. The similarities in physiologic and built-environment vulnerabilities to both hot and cold weather suggest prioritization of strategies that address both present-day cold and near-future heat concerns.

Emergency Department Visits and Ambient Temperature: Evaluating the Connection and Projecting Future Outcomes

The U.S. Global Climate Change Research Program has identified climate change as a growing public health threat. We investigated the potential effects of changes in ambient daily maximum temperature on hyperthermia and cardiovascular emergency department (ED) visits using records for patients age 64 and younger from a private insurance database for the May-September period for 2005-2012. We found a strong positive relationship between daily maximum temperatures and ED visits for hyperthermia but not for cardiovascular conditions. Using the fitted relationship from 136 metropolitan areas, we calculated the number and rate of hyperthermia ED visits for climates representative of year 1995 (baseline period), as well as years 2050 and 2090 (future periods), for two climate change scenarios based on outcomes from five global climate models. Without considering potential adaptation or population growth and movement, we calculate that climate change alone will result in an additional 21,000-28,000 hyperthermia ED visits for May to September, with associated treatment costs between $6 million and $52 million (2015 U.S. dollars) by 2050; this increases to approximately 28,000-65,000 additional hyperthermia ED visits with treatment costs between $9 million and $118 million (2015 U.S. dollars) by 2090. The range in projected additional hyperthermia visits reflects the difference between alternative climate scenarios, and the additional range in valuation reflects different assumptions about per-case valuation.

Projecting future climate change impacts on heat-related mortality in large urban areas in China

Global climate change is anticipated to raise overall temperatures and has the potential to increase future mortality attributable to heat. Urban areas are particularly vulnerable to heat because of high concentrations of susceptible people. As the world's largest developing country, China has experienced noticeable changes in climate, partially evidenced by frequent occurrence of extreme heat in urban areas, which could expose millions of residents to summer heat stress that may result in increased health risk, including mortality. While there is a growing literature on future impacts of extreme temperatures on public health, projecting changes in future health outcomes associated with climate warming remains challenging and underexplored, particularly in developing countries. This is an exploratory study aimed at projecting future heat-related mortality risk in major urban areas in China. We focus on the 51 largest Chinese cities that include about one third of the total population in China, and project the potential changes in heat-related mortality based on 19 different global-scale climate models and three Representative Concentration Pathways (RCPs). City-specific risk estimates for high temperature and all-cause mortality were used to estimate annual heat-related mortality over two future twenty-year time periods. We estimated that for the 20-year period in Mid-21st century (2041-2060) relative to 1970-2000, incidence of excess heat-related mortality in the 51 cities to be approximately 37,800 (95% CI: 31,300-43,500), 31,700 (95% CI: 26,200-36,600) and 25,800 (95% CI: 21,300-29,800) deaths per year under RCP8.5, RCP4.5 and RCP2.6, respectively. Slowing climate change through the most stringent emission control scenario RCP2.6, relative to RCP8.5, was estimated to avoid 12,900 (95% CI: 10,800-14,800) deaths per year in the 51 cities in the 2050s, and 35,100 (95% CI: 29,200-40,100) deaths per year in the 2070s. The highest mortality risk is primarily in cities located in the North, East and Central regions of China. Population adaptation to heat is likely to reduce excess heat mortality, but the extent of adaptation is still unclear. Future heat mortality risk attributable to exposure to elevated warm season temperature is likely to be considerable in China's urban centers, with substantial geographic variations. Climate mitigation and heat risk management are needed to reduce such risk and produce substantial public health benefits.

Accounting for adaptation and intensity in projecting heat wave-related mortality

BACKGROUND

How adaptation and intensity of heat waves affect heat wave-related mortality is unclear, making health projections difficult.

METHODS

We estimated the effect of heat waves, the effect of the intensity of heat waves, and adaptation on mortality in 209 U.S. cities with 168 million people during 1962-2006. We improved the standard time-series models by incorporating the intensity of heat waves using excess heat factor (EHF) and estimating adaptation empirically using interactions with yearly mean summer temperature (MST). We combined the epidemiological estimates for heat wave, intensity, and adaptation with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset to project heat wave-related mortality by 2050.

RESULTS

The effect of heat waves increased with its intensity. Adaptation to heat waves occurred, which was shown by the decreasing effect of heat waves with MST. However, adaptation was lessened as MST increased. Ignoring adaptation in projections would result in a substantial overestimate of the projected heat wave-related mortality (by 277-747% in 2050). Incorporating the empirically estimated adaptation into projections would result in little change in the projected heat wave-related mortality between 2006 and 2050. This differs regionally, however, with increasing mortality over time for cities in the southern and western U.S. but decreasing mortality over time for the north.

CONCLUSIONS

Accounting for adaptation is important to reduce bias in the projections of heat wave-related mortality. The finding that the southern and western U.S. are the areas that face increasing heat-related deaths is novel, and indicates that more regional adaptation strategies are needed.

Projections of temperature-related excess mortality under climate change scenarios

BACKGROUND

Climate change can directly affect human health by varying exposure to non-optimal outdoor temperature. However, evidence on this direct impact at a global scale is limited, mainly due to issues in modelling and projecting complex and highly heterogeneous epidemiological relationships across different populations and climates.

METHODS

We collected observed daily time series of mean temperature and mortality counts for all causes or non-external causes only, in periods ranging from Jan 1, 1984, to Dec 31, 2015, from various locations across the globe through the Multi-Country Multi-City Collaborative Research Network. We estimated temperature-mortality relationships through a two-stage time series design. We generated current and future daily mean temperature series under four scenarios of climate change, determined by varying trajectories of greenhouse gas emissions, using five general circulation models. We projected excess mortality for cold and heat and their net change in 1990-2099 under each scenario of climate change, assuming no adaptation or population changes.

FINDINGS

Our dataset comprised 451 locations in 23 countries across nine regions of the world, including 85 879 895 deaths. Results indicate, on average, a net increase in temperature-related excess mortality under high-emission scenarios, although with important geographical differences. In temperate areas such as northern Europe, east Asia, and Australia, the less intense warming and large decrease in cold-related excess would induce a null or marginally negative net effect, with the net change in 2090-99 compared with 2010-19 ranging from -1·2% (empirical 95% CI -3·6 to 1·4) in Australia to -0·1% (-2·1 to 1·6) in east Asia under the highest emission scenario, although the decreasing trends would reverse during the course of the century. Conversely, warmer regions, such as the central and southern parts of America or Europe, and especially southeast Asia, would experience a sharp surge in heat-related impacts and extremely large net increases, with the net change at the end of the century ranging from 3·0% (-3·0 to 9·3) in Central America to 12·7% (-4·7 to 28·1) in southeast Asia under the highest emission scenario. Most of the health effects directly due to temperature increase could be avoided under scenarios involving mitigation strategies to limit emissions and further warming of the planet.

INTERPRETATION

This study shows the negative health impacts of climate change that, under high-emission scenarios, would disproportionately affect warmer and poorer regions of the world. Comparison with lower emission scenarios emphasises the importance of mitigation policies for limiting global warming and reducing the associated health risks.

FUNDING

UK Medical Research Council.

Projected temperature-related deaths in ten large U.S. metropolitan areas under different climate change scenarios

BACKGROUND

There is an established U-shaped association between daily temperature and mortality. Temperature changes projected through the end of century are expected to lead to higher rates of heat-related mortality but also lower rates of cold-related mortality, such that the net change in temperature-related mortality will depend on location.

OBJECTIVES

We quantified the change in heat-, cold-, and temperature-related mortality rates through the end of the century across 10 large US metropolitan areas.

METHODS

We applied location-specific projections of future temperature from over 40 downscaled climate models to exposure-response functions relating daily temperature and mortality in 10 US metropolitan areas to estimate the change in temperature-related mortality rates in 2045-2055 and 2085-2095 compared to 1992-2002, under two greenhouse gas emissions scenarios (RCP 4.5 and 8.5). We further calculated the total number of deaths attributable to temperature in 1997, 2050, and 2090 in each metropolitan area, either assuming constant population or accounting for projected population growth.

RESULTS

In each of the 10 metropolitan areas, projected future temperatures were associated with lower rates of cold-related deaths and higher rates of heat-related deaths. Under the higher-emission RCP 8.5 scenario, 8 of the 10 metropolitan areas are projected to experience a net increase in annual temperature-related deaths per million people by 2086-2095, ranging from a net increase of 627 (95% empirical confidence interval [eCI]: 239, 1018) deaths per million in Los Angeles to a net decrease of 59 (95% eCI: -485, 314) deaths per million in Boston. Applying these projected temperature-related mortality rates to projected population size underscores the large public health burden of temperature.

CONCLUSIONS

Increases in the heat-related death rate are projected to outweigh decreases in the cold-related death rate in 8 out of 10 cities studied under a high emissions scenario. Adhering to a lower greenhouse gas emissions scenario has the potential to substantially reduce future temperature-related mortality.

Adaptation to Climate Change: A Comparative Analysis of Modeling Methods for Heat-Related Mortality

BACKGROUND

Multiple methods are employed for modeling adaptation when projecting the impact of climate change on heat-related mortality. The sensitivity of impacts to each is unknown because they have never been systematically compared. In addition, little is known about the relative sensitivity of impacts to "adaptation uncertainty" (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and emissions scenarios.

OBJECTIVES

This study had three aims: a) Compare the range in projected impacts that arises from using different adaptation modeling methods; b) compare the range in impacts that arises from adaptation uncertainty with ranges from using multiple climate models and emissions scenarios; c) recommend modeling method(s) to use in future impact assessments.

METHODS

We estimated impacts for 2070-2099 for 14 European cities, applying six different methods for modeling adaptation; we also estimated impacts with five climate models run under two emissions scenarios to explore the relative effects of climate modeling and emissions uncertainty.

RESULTS

The range of the difference (percent) in impacts between including and excluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). In 13 of 14 cities, the ranges in projected impacts due to adaptation uncertainty are larger than those associated with climate modeling and emissions uncertainty.

CONCLUSIONS

Researchers should carefully consider how to model adaptation because it is a source of uncertainty that can be greater than the uncertainty in emissions and climate modeling. We recommend absolute threshold shifts and reductions in slope. https://doi.org/10.1289/EHP634.

The use of climate information to estimate future mortality from high ambient temperature: A systematic literature review

BACKGROUND AND OBJECTIVES

Heat related mortality is of great concern for public health, and estimates of future mortality under a warming climate are important for planning of resources and possible adaptation measures. Papers providing projections of future heat-related mortality were critically reviewed with a focus on the use of climate model data. Some best practice guidelines are proposed for future research.

METHODS

The electronic databases Web of Science and PubMed/Medline were searched for papers containing a quantitative estimate of future heat-related mortality. The search was limited to papers published in English in peer-reviewed journals up to the end of March 2017. Reference lists of relevant papers and the citing literature were also examined. The wide range of locations studied and climate data used prevented a meta-analysis.

RESULTS

A total of 608 articles were identified after removal of duplicate entries, of which 63 were found to contain a quantitative estimate of future mortality from hot days or heat waves. A wide range of mortality models and climate model data have been used to estimate future mortality. Temperatures in the climate simulations used in these studies were projected to increase. Consequently, all the papers indicated that mortality from high temperatures would increase under a warming climate. The spread in projections of future climate by models adds substantial uncertainty to estimates of future heat-related mortality. However, many studies either did not consider this source of uncertainty, or only used results from a small number of climate models. Other studies showed that uncertainty from changes in populations and demographics, and the methods for adaptation to warmer temperatures were at least as important as climate model uncertainty. Some inconsistencies in the use of climate data (for example, using global mean temperature changes instead of changes for specific locations) and interpretation of the effects on mortality were apparent. Some factors which have not been considered when estimating future mortality are summarised.

CONCLUSIONS

Most studies have used climate data generated using scenarios with medium and high emissions of greenhouse gases. More estimates of future mortality using climate information from the mitigation scenario RCP2.6 are needed, as this scenario is the only one under which the Paris Agreement to limit global warming to 2°C or less could be realised. Many of the methods used to combine modelled data with local climate observations are simplistic. Quantile-based methods might offer an improved approach, especially for temperatures at the ends of the distributions. The modelling of adaptation to warmer temperatures in mortality models is generally arbitrary and simplistic, and more research is needed to better quantify adaptation. Only a small number of studies included possible changes in population and demographics in their estimates of future mortality, meaning many estimates of mortality could be biased low. Uncertainty originating from establishing a mortality baseline, climate projections, adaptation and population changes is important and should be considered when estimating future mortality.

Heat-related morbidity and mortality in New England: Evidence for local policy

BACKGROUND

Heat-related morbidity and mortality is a recognized public health concern. However, public health officials need to base policy decisions on local evidence, which is often lacking for smaller communities.

OBJECTIVES

To evaluate the association between maximum daily heat index (HI) and morbidity and mortality in 15 New England communities (combined population: 2.7 million) in order to provide actionable evidence for local officials.

METHODS

We applied overdispersed Poisson nonlinear distributed lag models to evaluate the association between HI and daily (May-September) emergency department (ED) admissions and deaths in each of 15 study sites in New Hampshire, Maine, and Rhode Island, controlling for time trends, day of week, and federal holidays. Site-specific estimates were meta-analyzed to provide regional estimates.

RESULTS

Associations (sometimes non-linear) were observed between HI and each health outcome. For example, a day with a HI of 95°F vs. 75°F was associated with a cumulative 7.5% (95% confidence interval [CI]: 6.5%, 8.5%) and 5.1% (95% CI: 0.2%, 10.3%) higher rate of all-cause ED visits and deaths, respectively, with some evidence of regional heterogeneity. We estimate that in the study area, days with a HI≥95°F were associated with an annual average of 784 (95% CI: 658, 908) excess ED visits and 22 (95% CI: 3, 39) excess deaths.

CONCLUSIONS

Our results suggest the presence of adverse health impacts associated with HI below the current local guideline criteria of HI≥100°F used to issue heat advisories. We hypothesize that lowering this threshold may lead to substantially reduced heat-related morbidity and mortality in the study area.

Impact of climate change on heat-related mortality in Jiangsu Province, China

A warming climate is anticipated to increase the future heat-related total mortality in urban areas. However, little evidence has been reported for cause-specific mortality or nonurban areas. Here we assessed the impact of climate change on heat-related total and cause-specific mortality in both urban and rural counties of Jiangsu Province, China, in the next five decades. To address the potential uncertainty in projecting future heat-related mortality, we applied localized urban- and nonurban-specific exposure response functions, six population projections including a no population change scenario and five Shared Socioeconomic Pathways (SSPs), and 42 temperature projections from 21 global-scale general circulation models and two Representative Concentration Pathways (RCPs). Results showed that projected warmer temperatures in 2016-2040 and 2041-2065 will lead to higher heat-related mortality for total non-accidental, cardiovascular, respiratory, stroke, ischemic heart disease (IHD), and chronic obstructive pulmonary disease (COPD) causes occurring annually during May to September in Jiangsu Province, China. Nonurban residents in Jiangsu will suffer from more excess heat-related cause-specific mortality in 2016-2065 than urban residents. Variations across climate models and RCPs dominated the uncertainty of heat-related mortality estimation whereas population size change only had limited influence. Our findings suggest that targeted climate change mitigation and adaptation measures should be taken in both urban and nonurban areas of Jiangsu Province. Specific public health interventions should be focused on the leading causes of death (stroke, IHD, and COPD), whose health burden will be amplified by a warming climate.

Effects of extreme temperatures on cardiovascular emergency hospitalizations in a Mediterranean region: a self-controlled case series study

BACKGROUND

Cold spells and heatwaves increase mortality. However little is known about the effect of heatwaves or cold spells on cardiovascular morbidity. This study aims to assess the effect of cold spells and heatwaves on cardiovascular diseases in a Mediterranean region (Catalonia, Southern Europe).

METHODS

We conducted a population-based retrospective study. Data were obtained from the System for the Development of Research in Primary Care and from the Catalan Meteorological Service. The outcome was first emergency hospitalizations due to coronary heart disease, stroke, or heart failure. Exposures were: cold spells; cold spells and 3 or 7 subsequent days; and heatwaves. Incidence rate ratios (IRR) and 95% confidence intervals were calculated using the self-controlled case series method. We accounted for age, time trends, and air pollutants; results were shown by age groups, gender or cardiovascular event type.

RESULTS

There were 22,611 cardiovascular hospitalizations in winter and 17,017 in summer between 2006 and 2013. The overall incidence of cardiovascular hospitalizations significantly increased during cold spells (IRR = 1.120; CI 95%: 1.10-1.30) and the effect was even stronger in the 7 days subsequent to the cold spell (IRR = 1.29; CI 95%: 1.22-1.36). Conversely, cardiovascular hospitalizations did not increase during heatwaves, neither in the overall nor in the stratified analysis.

CONCLUSIONS

Cold spells but not heatwaves, increased the incidence of emergency cardiovascular hospitalizations in Catalonia. The effect of cold spells was greater when including the 7 subsequent days. Such knowledge might be useful to develop strategies to reduce the impact of extreme temperature episodes on human health.

A case for Planetary Health/GeoHealth

Concern has been spreading across scientific disciplines that the pervasive human transformation of Earth's natural systems is an urgent threat to human health. The simultaneous emergence of "GeoHealth" and "Planetary Health" signals recognition that developing a new relationship between humanity and our natural systems is becoming an urgent global health priority-if we are to prevent a backsliding from the past century's great public health gains. Achieving meaningful progress will require collaboration across a broad swath of scientific disciplines as well as with policy makers, natural resource managers, members of faith communities, and movement builders around the world in order to build a rigorous evidence base of scientific understanding as the foundation for more robust policy and resource management decisions that incorporate both environmental and human health outcomes.

Iterative management of heat early warning systems in a changing climate

Extreme heat is a leading weather-related cause of morbidity and mortality, with heat exposure becoming more widespread, frequent, and intense as climates change. The use of heat early warning and response systems (HEWSs) that integrate weather forecasts with risk assessment, communication, and reduction activities is increasingly widespread. HEWSs are frequently touted as an adaptation to climate change, but little attention has been paid to the question of how best to ensure effectiveness of HEWSs as climates change further. In this paper, we discuss findings showing that HEWSs satisfy the tenets of an intervention that facilitates adaptation, but climate change poses challenges infrequently addressed in heat action plans, particularly changes in the onset, duration, and intensity of dangerously warm temperatures, and changes over time in the relationships between temperature and health outcomes. Iterative management should be central to a HEWS, and iteration cycles should be of 5 years or less. Climate change adaptation and implementation science research frameworks can be used to identify HEWS modifications to improve their effectiveness as temperature continues to rise, incorporating scientific insights and new understanding of effective interventions. We conclude that, at a minimum, iterative management activities should involve planned reassessment at least every 5 years of hazard distribution, population-level vulnerability, and HEWS effectiveness.