Current and Projected Heat-Related Morbidity and Mortality in Rhode Island

Heat Metrics and Maternal-Child Health Diagnoses in Emergency Departments in the United States: A Scoping Review

OBJECTIVE

To summarize current research on associations between heat metrics and emergency department discharge diagnoses for US pregnant women and children from birth to age 18 via a scoping review.

BACKGROUND

Climate change directly contributes to extreme weather conditions and environmental changes and indirectly affects health and the health care system. Pregnant women and children are believed to be more susceptible to extreme heat, but few empirical studies have been conducted evaluating effects of heat metrics on these populations.

METHODS

Ovid MEDLINE, CIHAHL, SCOPUS, Web of Science, JSTOR, and PsycINFO databases were searched using a combination of key words.

RESULTS

Twelve studies were selected for this review. In pregnant women, positive associations were found between mean daily temperature and multiple subtypes of pregnancy complications, including threatened or spontaneous abortion, renal diseases, infectious diseases, diabetes, and hypertension. In children, positive associations were found with all-cause diagnoses; asthma; dehydration; electrolyte disorders; heat-related illness; infection; endocrine, nutritional, and metabolic diseases; injury; and otitis media and external emergency department discharge diagnoses and temperature or heatwave versus non-heatwave.

CONCLUSION

By tracking associations between maternal-child emergency department discharge diagnoses and various heat metrics, researchers can contribute to better clinical practices that promote environmental justice and climate resilience.

How climate change degrades child health: A systematic review and meta-analysis

BACKGROUND

Children are more vulnerable than adults to climate-related health threats, but reviews examining how climate change affects human health have been mainly descriptive and lack an assessment of the magnitude of health effects children face. This is the first systematic review and meta-analysis that identifies which climate-health relationships pose the greatest threats to children.

OBJECTIVES

We reviewed epidemiologic studies to analyse various child health outcomes due to climate change and identify the relationships with the largest effect size. We identify population-specific risks and provide recommendations for future research.

METHODS

We searched four large online databases for observational studies published up to 5 January 2023 following PRISMA (systematic review) guidelines. We evaluated each included study individually and aggregated relevant quantitative data. We used quantitative data in our meta-analysis, where we standardised effect sizes and compared them among different groupings of climate variables and health outcomes.

RESULTS

Of 1301 articles we identified, 163 studies were eligible for analysis. We identified many relationships between climate change and child health, the strongest of which was increasing risk (60 % on average) of preterm birth from exposure to temperature extremes. Respiratory disease, mortality, and morbidity, among others, were also influenced by climate changes. The effects of different air pollutants on health outcomes were considerably smaller compared to temperature effects, but with most (16/20 = 80 %) pollutant studies indicating at least a weak effect. Most studies occurred in high-income regions, but we found no geographical clustering according to health outcome, climate variable, or magnitude of risk. The following factors were protective of climate-related child-health threats: (i) economic stability and strength, (ii) access to quality healthcare, (iii) adequate infrastructure, and (iv) food security. Threats to these services vary by local geographical, climate, and socio-economic conditions. Children will have increased prevalence of disease due to anthropogenic climate change, and our quantification of the impact of various aspects of climate change on child health can contribute to the planning of mitigation that will improve the health of current and future generations.

Prediction of climate change impacts on heatstroke cases in Japan's 47 prefectures with the effect of long-term heat adaptation

One of the negative consequences of increased air temperatures due to global warming is the associated increase in heat-related mortality and morbidity. Studies that focused on future predictions of heat-related morbidity do not consider the effect of long-term heat adaptation measures, nor do they use evidence-based methods. Therefore, this study aimed to predict the future heatstroke cases for all 47 prefectures of Japan, by considering long-term heat adaptation by translating current geographical differences in heat adaptation to future temporal heat adaptation. Predictions were conducted for age groups of 7-17, 18-64, and ≥65 years. The prediction period was set to a base period (1981-2000), mid-21st century (2031-2050), and the end of the 21st century (2081-2100). We found that the average heatstroke incidence (number of patients with heatstroke transported by ambulance per population) in Japan under five representative climate models and three greenhouse gas (GHG) emissions scenarios increased by 2.92- for 7-17 years, 3.66- for 18-64 years, and 3.26-fold for ≥65 years at the end of the 21st century without heat adaptation. The corresponding numbers were 1.57 for 7-17 years, 1.77 for 18-64 years, and 1.69 for ≥65 years with heat adaptation. Furthermore, the average number of patients with heatstroke transported by ambulance (NPHTA) under all climate models and GHG emissions scenarios increased by 1.02- for 7-17 years, 1.76- for 18-64 years, and 5.50-fold for ≥65 years at the end of 21st century without heat adaptation, where demographic changes were considered. The corresponding numbers were 0.55 for 7-17 years, 0.82 for 18-64 years, and 2.74 for ≥65 years with heat adaptation. The heatstroke incidence, as well as the NPHTA, substantially decreased when heat adaptation was considered. Our method could be applicable to other regions across the globe.

Ambient temperature and air pollution associations with suicide and homicide mortality in California: A statewide case-crossover study

BACKGROUND

Higher ambient temperature and air pollution may contribute to increased risk of behaviors harmful to oneself or to others; however, quantitative evidence is limited. We examined the relationship of deaths due to suicide and homicide with temperature and air pollution in California-a state prone to high levels of both exposures.

METHOD

California death certificates from 2014 to 2019 were used to identify deaths due to suicide and homicide. Residential data for decedents were used to assign exposure to daily temperature (maximum[Tmax], minimum[Tmin]) and daily average air pollution concentrations (particulate matter <10 μm[PM10] and < 2.5 μm[PM2.5], nitrogen dioxide[NO2], ozone[O3]). Tmin served as a surrogate for nighttime temperature. A time-stratified case-crossover study design using conditional logistic regression was used to assess the effects of daily exposure to temperature and air pollutants on suicide and homicide mortality, adjusting for relative humidity. Effect modification by sex and age was assessed.

RESULTS

We observed 24,387 deaths due to suicide and 10,767 deaths due to homicide. We found a monotonic temperature association for both outcomes. A 5 °C increase in Tmax at lag-2 and Tmin at lag-0 was associated with 3.1 % (95 % confidence interval [CI]: 1.1 %-5.2 %) and 3.8 % (95%CI: 0.9 %-6.8 %) increased odds of death due to suicide, respectively. The increased odds of homicide mortality per 5 °C increase in Tmax at lag-0 and Tmin at lag-1 were 4.9 % (95%CI: 1.6 %-8.1 %) and 6.2 % (95%CI: 1.6 %-11.0 %), respectively. No air pollutant associations were statistically significant. Temperature associations were robust after adjustment for PM2.5. Some temperature effects were larger among women for suicide and men for homicide mortality, and among those over age 65 years for both outcomes.

CONCLUSION

Risk of suicide and homicide mortality increases with increasing daily ambient temperatures. Findings have public health relevance given anticipated increases in temperatures due to global climate change.

Temperature-related mortality in China from specific injury

Injury poses heavy burden on public health, accounting for nearly 8% of all deaths globally, but little evidence on the role of climate change on injury exists. We collect data during 2013-2019 in six provinces of China to examine the effects of temperature on injury mortality, and to project future mortality burden attributable to temperature change driven by climate change based on the assumption of constant injury mortality and population scenario. The results show that a 0.50% (95% confident interval (CI): 0.13%-0.88%) increase of injury mortality risk for each 1 °C rise in daily temperature, with higher risk for intentional injury (1.13%, 0.55%-1.71%) than that for unintentional injury (0.40%, 0.04%-0.77%). Compared to the 2010s, total injury deaths attributable to temperature change in China would increase 156,586 (37,654-272,316) in the 2090 s under representative concentration pathways 8.5 scenario with the highest for transport injury (64,764, 8,517-115,743). Populations living in Western China, people aged 15-69 years, and male may suffer more injury mortality burden from increased temperature caused by climate change. Our findings may be informative for public health policy development to effectively adapt to climate change.

Emergency Department Visits and Summer Temperatures in Bologna, Northern Italy, 2010-2019: A Case-Crossover Study and Geographically Weighted Regression Methods

The aim of the study is to evaluate the association between summer temperatures and emergency department visits (EDVs) in Bologna (Italy) and assess whether this association varies across areas with different socioeconomic and microclimatic characteristics. We included all EDVs within Bologna residences during the summers of 2010-2019. Each subject is attributed a deprivation and a microclimatic discomfort index according to the residence. A time-stratified case-crossover design was conducted to estimate the risk of EDV associated with temperature and the effect modification of deprivation and microclimatic characteristics. In addition, a spatial analysis of data aggregated at the census block level was conducted by applying a Poisson and a geographically weighted Poisson regression model. For each unit increase in temperature above 26 °C, the risk of EDV increases by 0.4% (95%CI: 0.05-0.8). The temperature-EDV relationship is not modified by the microclimatic discomfort index but rather by the deprivation index. The spatial analysis shows that the EDV rate increases with deprivation homogeneously, while it diminishes with increases in median income and microclimatic discomfort, with differences across areas. In conclusion, in Bologna, the EDV risk associated with high temperatures is not very relevant overall, but it tends to increase in areas with a low socioeconomic level.

Estimating the Burden of Heat-Related Illness Morbidity Attributable to Anthropogenic Climate Change in North Carolina

Climate change is known to increase the frequency and intensity of hot days (daily maximum temperature ≥30°C), both globally and locally. Exposure to extreme heat is associated with numerous adverse human health outcomes. This study estimated the burden of heat-related illness (HRI) attributable to anthropogenic climate change in North Carolina physiographic divisions (Coastal and Piedmont) during the summer months from 2011 to 2016. Additionally, assuming intermediate and high greenhouse gas emission scenarios, future HRI morbidity burden attributable to climate change was estimated. The association between daily maximum temperature and the rate of HRI was evaluated using the Generalized Additive Model. The rate of HRI assuming natural simulations (i.e., absence of greenhouse gas emissions) and future greenhouse gas emission scenarios were predicted to estimate the HRI attributable to climate change. Over 4 years (2011, 2012, 2014, and 2015), we observed a significant decrease in the rate of HRI assuming natural simulations compared to the observed. About 3 out of 20 HRI visits are attributable to anthropogenic climate change in Coastal (13.40% [IQR: -34.90,95.52]) and Piedmont (16.39% [IQR: -35.18,148.26]) regions. During the future periods, the median rate of HRI was significantly higher (78.65%: Coastal and 65.85%: Piedmont), assuming a higher emission scenario than the intermediate emission scenario. We observed significant associations between anthropogenic climate change and adverse human health outcomes. Our findings indicate the need for evidence-based public health interventions to protect human health from climate-related exposures, like extreme heat, while minimizing greenhouse gas emissions.

Association of ambient extreme heat with pediatric morbidity: a scoping review

Global climate change is leading to higher ambient temperatures and more frequent heatwaves. To date, impacts of ambient extreme heat on childhood morbidity have been understudied, although-given children's physiologic susceptibility, with smaller body surface-to-mass ratios, and many years of increasing temperatures ahead-there is an urgent need for better information to inform public health policies and clinical approaches. In this review, we aim to (1) identify pediatric morbidity outcomes previously associated with extreme heat, (2) to identify predisposing co-morbidities which may make children more susceptible to heat-related outcomes, and (3) to map the current body of available literature. A scoping review of the current full-text literature was conducted using the Arksey and O'Malley framework Int J Soc Res Methodol 8:19-32, (2015). Search terms for (1) pediatric population, (2) heat exposures, (3) ambient conditions, and (4) adverse outcomes were combined into a comprehensive PubMed and Medline literature search. Of the 1753 publications identified, a total of 20 relevant studies were ultimately selected based on selection criteria of relevance to US urban populations. Most identified studies supported positive associations between high extreme temperature exposures and heat-related illness, dehydration/electrolyte imbalance, general symptoms, diarrhea and digestion disorders, infectious diseases/infections, asthma/wheeze, and injury. Most studies found no association with renal disease, cardiovascular diseases, or diabetes mellitus. Results were mixed for other respiratory diseases and mental health/psychological disorders. Very few of the identified studies examined susceptibility to pre-existing conditions; Cystic Fibrosis was the only co-morbidity for which we found significant evidence. Further research is needed to understand the nuances of associations between extreme heat and specific outcomes-particularly how associations may vary by child age, sex, race/ ethnicity, community characteristics, and other pre-existing conditions.

Internet searches and heat-related emergency department visits in the United States

Emerging research suggests that internet search patterns may provide timely, actionable insights into adverse health impacts from, and behavioral responses to, days of extreme heat, but few studies have evaluated this hypothesis, and none have done so across the United States. We used two-stage distributed lag nonlinear models to quantify the interrelationships between daily maximum ambient temperature, internet search activity as measured by Google Trends, and heat-related emergency department (ED) visits among adults with commercial health insurance in 30 US metropolitan areas during the warm seasons (May to September) from 2016 to 2019. Maximum daily temperature was positively associated with internet searches relevant to heat, and searches were in turn positively associated with heat-related ED visits. Moreover, models combining internet search activity and temperature had better predictive ability for heat-related ED visits compared to models with temperature alone. These results suggest that internet search patterns may be useful as a leading indicator of heat-related illness or stress.

Hot weather as a risk factor for kidney disease outcomes: A systematic review and meta-analysis of epidemiological evidence

BACKGROUND

The occurrence or exacerbation of kidney disease has been documented as a growing problem associated with hot weather. The implementation of effective prevention measures requires a better understanding of the risk factors that increase susceptibility. To fill gaps in knowledge, this study reviews the current literature on the effects of heat on kidney-disease outcomes (ICD-10 N00-N39), including morbidity and mortality.

METHODS

Databases were systematically searched for relevant literature published between 1990 and 2020 and the quality of evidence evaluated. We performed random effects meta-analysis to calculate the pooled relative risks (RRs) of the association between high temperatures (and heatwaves) and kidney disease outcomes. We further evaluated vulnerability concerning contextual population characteristics.

RESULTS

Of 2739 studies identified, 91 were reviewed and 82 of these studies met the criteria for inclusion in a meta-analysis. Findings showed that with a 1 °C increase in temperature, the risk of kidney-related morbidity increased by 1% (RR 1.010; 95% CI: 1.009-1.011), with the greatest risk for urolithiasis. Heatwaves were also associated with increased morbidity with a trend observed with heatwave intensity. During low-intensity heatwaves, there was an increase of 5.9% in morbidity, while during high-intensity heatwaves there was a 7.7% increase. There were greater RRs for males, people aged ≤64 years, and those living in temperate climate zones. Similarly, for every 1 °C temperature increase, there was a 3% (RR 1.031; 95% CI: 1.018-1.045) increase in the risk of kidney-related mortality, which also increased during heatwaves.

CONCLUSIONS

High temperatures (and heatwaves) are associated with an elevated risk of kidney disease outcomes, particularly urolithiasis. Preventive measures that may minimize risks in vulnerable individuals during hot spells are discussed.

Ambient heat and risks of emergency department visits among adults in the United States: time stratified case crossover study

OBJECTIVE

To quantify the association between ambient heat and visits to the emergency department (ED) for any cause and for cause specific conditions in the conterminous United States among adults with health insurance.

DESIGN

Time stratified case crossover analyses with distributed lag non-linear models.

SETTING

US nationwide administrative healthcare claims database.

PARTICIPANTS

All commercial and Medicare Advantage beneficiaries (74.2 million) aged 18 years and older between May and September 2010 to 2019.

MAIN OUTCOME MEASURES

Daily rates of ED visits for any cause, heat related illness, renal disease, cardiovascular disease, respiratory disease, and mental disorders based on discharge diagnosis codes.

RESULTS

21 996 670 ED visits were recorded among adults with health insurance living in 2939 US counties. Days of extreme heat-defined as the 95th centile of the local warm season (May through September) temperature distribution (at 34.4°C v 14.9°C national average level)-were associated with a 7.8% (95% confidence interval 7.3% to 8.2%) excess relative risk of ED visits for any cause, 66.3% (60.2% to 72.7%) for heat related illness, 30.4% (23.4% to 37.8%) for renal disease, and 7.9% (5.2% to 10.7%) for mental disorders. Days of extreme heat were associated with an excess absolute risk of ED visits for heat related illness of 24.3 (95% confidence interval 22.9 to 25.7) per 100 000 people at risk per day. Heat was not associated with a higher risk of ED visits for cardiovascular or respiratory diseases. Associations were more pronounced among men and in counties in the north east of the US or with a continental climate.

CONCLUSIONS

Among both younger and older adults, days of extreme heat are associated with a higher risk of ED visits for any cause, heat related illness, renal disease, and mental disorders. These results suggest that the adverse health effects of extreme heat are not limited to older adults and carry important implications for the health of adults across the age spectrum.

Heat illness data strengthens vulnerability maps

Background

Previous extreme heat and human health studies have investigated associations either over time (e.g. case-crossover or time series analysis) or across geographic areas (e.g. spatial models), which may limit the study scope and regional variation. Our study combines a case-crossover design and spatial analysis to identify: 1) the most vulnerable counties to extreme heat; and 2) demographic and socioeconomic variables that are most strongly and consistently related to heat-sensitive health outcomes (cardiovascular disease, dehydration, heat-related illness, acute renal disease, and respiratory disease) across 67 counties in the state of Florida, U. S over 2008–2012.

Methods

We first used a case-crossover design to examine the effects of air temperature on daily counts of health outcomes. We employed a time-stratified design with a 28-day comparison window. Referent periods were extracted from ±7, ±14, or ± 21 days to address seasonality. The results are expressed as odds ratios, or the change in the likelihood of each health outcome for a unit change in heat exposure. We then spatially examined the case-crossover extreme heat and health odds ratios and county level demographic and socioeconomic variables with multiple linear regression or spatial lag models.

Results

Results indicated that southwest Florida has the highest risks of cardiovascular disease, dehydration, acute renal disease, and respiratory disease. Results also suggested demographic and socioeconomic variables were significantly associated with the magnitude of heat-related health risk. The counties with larger populations working in farming, fishing, mining, forestry, construction, and extraction tended to have higher risks of dehydration and acute renal disease, whereas counties with larger populations working in installation, maintenance, and repair workers tended to have lower risks of cardiovascular, dehydration, acute renal disease, and respiratory disease. Finally, our results showed that high income counties consistently have lower health risks of dehydration, heat-related illness, acute renal disease, and respiratory disease.

Conclusions

Our study identified different relationships with demographic/socioeconomic variables for each heat-sensitive health outcome. Results should be incorporated into vulnerability or risk indices for each health outcome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-12097-6.

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.

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.

Estimation of Heat-Attributable Mortality Using the Cross-Validated Best Temperature Metric in Switzerland and South Korea

This study presents a novel method for estimating the heat-attributable fractions (HAF) based on the cross-validated best temperature metric. We analyzed the association of eight temperature metrics (mean, maximum, minimum temperature, maximum temperature during daytime, minimum temperature during nighttime, and mean, maximum, and minimum apparent temperature) with mortality and performed the cross-validation method to select the best model in selected cities of Switzerland and South Korea from May to September of 1995-2015. It was observed that HAF estimated using different metrics varied by 2.69-4.09% in eight cities of Switzerland and by 0.61-0.90% in six cities of South Korea. Based on the cross-validation method, mean temperature was estimated to be the best metric, and it revealed that the HAF of Switzerland and South Korea were 3.29% and 0.72%, respectively. Furthermore, estimates of HAF were improved by selecting the best city-specific model for each city, that is, 3.34% for Switzerland and 0.78% for South Korea. To the best of our knowledge, this study is the first to observe the uncertainty of HAF estimation originated from the selection of temperature metric and to present the HAF estimation based on the cross-validation method.

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.

Effects of weather, air pollution and Oktoberfest on ambulance-transported emergency department admissions in Munich, Germany

BACKGROUND

Climate change and increasing risks of extreme weather events affect human health and lead to changes in the emergency department (ED) admissions and the emergency medical services (EMS) operations. For a better allocation of resources in the healthcare system, it is essential to predict ED numbers based on environmental variables. This publication aims to quantify weather, air pollution and calendar-related effects on daily ED admissions.

METHODS

Analyses were based on 575,725 admissions from the web-based IVENA system recording all patients in the greater Munich area with pre-hospital emergency care in ambulance operations during 2014-2018. Linear models were used to identify statistically significant associations between daily ED admissions and calendar, meteorological and pollution factors, allowing for lag effects of one to three days. Separate analyses were performed for seasons, with additional subset analyses by sex, age and surgical versus internal department.

RESULTS

ED admissions were exceptionally high during the three-week Oktoberfest, particularly for males and on the weekends, as well as during the New Year holiday. Admissions significantly increased during the years of study, decreased in spring and summer holidays, and were lower on Sundays while higher on Mondays. In the warmer seasons, admissions were significantly associated with higher temperature, adjusting for the effects of sunshine and humidity in all age groups except for the elderly. Adverse weather conditions in non-summer seasons were either linked to increasing ED admissions (from storms, gust) or decreasing them from rain. Mostly, but not exclusively, in winter, increasing ED admissions were associated with colder minimum temperatures as well as with higher NO and PM₁₀ concentrations.

CONCLUSIONS

In addition to standard calendar-related factors, incorporating seasonal weather, air pollutant and interactions with patient demographics into resource planning models can improve the daily allocation of resources and staff of EMS operations at hospital and city levels.

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.

Characterization of the 2017 Summer Heat Waves and Their Effects on the Population of an Area of Southern Italy

Knowledge of bioclimatic comfort is paramount for improving people’s quality of life. To this purpose, several studies related to climatic comfort/discomfort have been recently published. These studies mainly focus on the analysis of temperature and relative humidity, i.e., the main variables influencing the environmental stress in the human body. In this context, the present work aims to analyze the number of visits to the hospital emergency department made by the inhabitants of the Crati River valley (Calabria region, southern Italy) during the heat waves that accompanied the African anticyclone in the summer of 2017. The analysis of the bioclimatic comfort was performed using the humidity index. Results showed that greater the index, the higher the number of accesses to the emergency department, in particular by the most vulnerable population groups, such as children and the elderly.

Emerging climate change-related public health challenges in Africa: A case study of the heat-health vulnerability of informal settlement residents in Dar es Salaam, Tanzania

Heat has the potential to become one of the most significant public health impacts of climate change in the coming decades. Increases in temperature have been linked to both increasing mortality and morbidity. Cities have been recognized as areas of particular vulnerability to heat's impacts on health, and marginalized groups, such as the poor, appear to have higher heat-related morbidity and mortality. Little research has examined the heat vulnerability of urban informal settlements residents in Africa, even though surface temperatures across Africa are projected to increase at a rate faster than the global average. This paper addresses this knowledge gap through a mixed-methods analysis of the heat-health vulnerability of informal settlement residents in Dar es Salaam, Tanzania. The heat exposure, sensitivity and adaptive capacity of informal settlement residents were assessed through a combination of climate analyses, semi-structured interviews with local government actors and informal settlement residents, unstructured interviews with health sector respondents, a health impacts literature review, and a stakeholder engagement workshop. The results suggest that increasing temperatures due to climate change will likely be a significant risk to human health in Dar es Salaam, even though the city does not reach extreme temperature conditions, because informal settlement residents have high exposure, high sensitivity and low adaptive capacity to heat, and because the heat-health relationship is currently an under-prioritized policy issue. While numerous urban planning approaches can play a key role in increasing the resilience of citizens to heat, Dar es Salaam's past and current growth and development patterns greatly complicate the implementation and enforcement of such approaches. For African cities, the findings highlight an urgent need for more research on the vulnerability and resilience of residents to heat-health impacts, because many African cities are likely to present similar characteristics to those in Dar es Salaam that increase resident's vulnerability.

Cumulative effect of indoor temperature on cardiovascular disease-related emergency department visits among older adults in Taiwan

Studies have demonstrated that exposure to extreme outdoor temperatures increases cardiovascular disease mortality and morbidity. However, people spend 80%-90% of their time indoors, and the cumulative effects of exposure to high or low temperature on the risk of cardiovascular diseases had not been considered. This study investigated the cumulative effects of high or low indoor temperature exposure on the risk of cardiovascular diseases. We estimated indoor temperatures by using a prediction model of indoor temperature from a previous study and further calculated the cumulative degree hours at different indoor temperature ranges. Samples of emergency department visits due to cardiovascular diseases were collected from the Longitudinal Health Insurance Database (LHID) from 2000 to 2014 in Taiwan. We used a distributed lag nonlinear model to analyze the data. Our data demonstrated a significant risk of emergency department visits due to cardiovascular diseases at 27, 28, 29, 30, and 31 °C when cooling cumulative degree hours exceeded 62, 43, 16, 1, and 1 during the hot season (May to October), respectively, and at 19, 20, 21, 22, and 23 °C when heating cumulative degree hours exceeded 1, 1, 1, 11, and 33 during the cold season (November to April), respectively. Cumulative degree hours were different according to gender and age groups. Policymakers should further consider the cumulative effects to prevent hot- or cold-related cardiovascular diseases for populations.

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.

The Influence of Heat on Daily Police, Medical, and Fire Dispatches in Boston, Massachusetts: Relative Risk and Time-Series Analyses

Objectives. To examine the impact of extreme heat on emergency services in Boston, MA.Methods. We conducted relative risk and time series analyses of 911 dispatches of the Boston Police Department (BPD), Boston Emergency Medical Services (BEMS), and Boston Fire Department (BFD) from November 2010 to April 2014 to assess the impact of extreme heat on emergency services.Results. During the warm season, there were 2% (95% confidence interval [CI] = 0%, 5%) more BPD dispatches, 9% (95% CI = 7%, 12%) more BEMS dispatches, and 10% (95% CI = 5%, 15%) more BFD dispatches on days when the maximum temperature was 90°F or higher, which remained consistent when we considered multiple days of heat. A 10°F increase in daily maximum temperature, from 80° to 90°F, resulted in 1.016, 1.017, and 1.002 times the expected number of daily BPD, BEMS, and BFD dispatch calls, on average, after adjustment for other predictors.Conclusions. The burden of extreme heat on local emergency medical and police services may be agency-wide, and impacts on fire departments have not been previously documented.Public Health Implications. It is important to account for the societal burden of extreme heat impacts to most effectively inform climate change adaptation strategies and planning.

The Role of Individual and Small-Area Social and Environmental Factors on Heat Vulnerability to Mortality Within and Outside of the Home in Boston, MA

Climate change is resulting in heatwaves that are more frequent, severe, and longer lasting, which is projected to double-to-triple the heat-related mortality in Boston, MA if adequate climate change mitigation and adaptation strategies are not implemented. A case-only analysis was used to examine subject and small-area neighborhood characteristics that modified the association between hot days and mortality. Deaths of Boston, Massachusetts residents that occurred from 2000–2015 were analyzed in relation to the daily temperature and heat index during the warm season as part of the case-only analysis. The modification by small-area (census tract, CT) social, and environmental (natural and built) factors was assessed. At-home mortality on hot days was driven by both social and environmental factors, differentially across the City of Boston census tracts, with a greater proportion of low-to-no income individuals or those with limited English proficiency being more highly represented among those who died during the study period; but small-area built environment features, like street trees and enhanced energy efficiency, were able to reduce the relative odds of death within and outside the home. At temperatures below current local thresholds used for heat warnings and advisories, there was increased relative odds of death from substance abuse and assault-related altercations. Geographic weighted regression analyses were used to examine these relationships spatially within a subset of at-home deaths with high-resolution temperature and humidity data. This revealed spatially heterogeneous associations between at-home mortality and social and environmental vulnerability factors.

Comparison of temperature-mortality associations estimated with different exposure metrics

Background:

Studies of the short-term association between ambient temperature and mortality often use temperature observations from a single monitoring station, frequently located at the nearest airport, to represent the exposure of individuals living across large areas. Population-weighted temperature estimates constructed from gridded meteorological data may offer an opportunity to improve exposure assessment in locations where station observations do not fully capture the average exposure of the population of interest.

Methods:

We compared the association between daily mean temperature and mortality in each of 113 United States counties using (1) temperature observations from a single weather station and (2) population-weighted temperature estimates constructed from a gridded meteorological dataset. We used distributed lag nonlinear models to estimate the 21-day cumulative association between temperature and mortality in each county, 1987–2006, adjusting for seasonal and long-term trends, day of week, and holidays.

Results:

In the majority (73.4%) of counties, the relative risk of death on extremely hot days (99th percentile of weather station temperature) versus the minimum mortality temperature was larger when generated from the population-weighted estimates. In contrast, relative risks on extremely cold days (first percentile of weather station temperature) were often larger when generated from the weather station observations. In most counties, the difference in associations estimated from the two temperature metrics was small.

Conclusions:

In a large, multi-site analysis, temperature-mortality associations were largely similar when estimated from weather station observations versus population-weighted temperature estimates. However, spatially refined exposure data may be more appropriate for analyses seeking to elucidate local health effects.

Suitability of gridded climate datasets for use in environmental epidemiology

Epidemiologic analyses of the health effects of meteorological exposures typically rely on observations from the nearest weather station to assess exposure for geographically diverse populations. Gridded climate datasets (GCD) provide spatially resolved weather data that may offer improved exposure estimates, but have not been systematically validated for use in epidemiologic evaluations. As a validation, we linearly regressed daily weather estimates from two GCDs, PRISM and Daymet, to observations from a sample of weather stations across the conterminous United States and compared spatially resolved, population-weighted county average temperatures and heat indices from PRISM to single-pixel PRISM values at the weather stations to identify differences. We found that both Daymet and PRISM accurately estimate ambient temperature and mean heat index at sampled weather stations, but PRISM outperforms Daymet for assessments of humidity and maximum daily heat index. Moreover, spatially-resolved exposure estimates differ from point-based assessments, but with substantial inter-county heterogeneity. We conclude that GCDs offer a potentially useful approach to exposure assessment of meteorological variables that may, in some locations, reduce exposure measurement error, as well as permit assessment of populations distributed far from weather stations.

Does Particulate Matter Modify the Short-Term Association between Heat Waves and Hospital Admissions for Cardiovascular Diseases in Greater Sydney, Australia?

Little is known about the potential interactive effects of heat waves and ambient particulate matter on cardiovascular morbidity. A time-stratified case-crossover design was used to examine whether particulate matter (PM₁₀) modifies the association between heat waves and emergency hospital admissions for six cardiovascular diseases in Greater Sydney, Australia during the warm season for 2001–2013. We estimated and compared the effect of heat waves on high- and low-level PM₁₀ days at lag₀–lag₂, adjusting for dew-point temperature, ambient ozone, ambient nitrogen dioxide, and public holidays. We also investigated the susceptibility of both younger (0–64 years) and older populations (65 years and above), and tested the sensitivity of three heat wave definitions. Stronger heat wave effects were observed on high- compared to low-level PM₁₀ days for emergency hospital admissions for cardiac arrest for all ages combined, 0–64 years and 65 years and above; conduction disorders for 0–64 years; and hypertensive diseases for all ages combined and 0–64 years. Overall, we found some evidence to suggest that PM₁₀ may modify the association between heat waves and hospital admissions for certain cardiovascular diseases, although our findings largely differed across disease, age group, lag, and heat wave definition.

Using web data to improve surveillance for heat sensitive health outcomes

BACKGROUND

Elevated and prolonged exposure to extreme heat is an important cause of excess summertime mortality and morbidity. To protect people from health threats, some governments are currently operating syndromic surveillance systems. However, A lack of resources to support time- and labor- intensive diagnostic and reporting processes make it difficult establishing region-specific surveillance systems. Big data created by social media and web search may improve upon the current syndromic surveillance systems by directly capturing people's individual and subjective thoughts and feelings during heat waves. This study aims to investigate the relationship between heat-related web searches, social media messages, and heat-related health outcomes.

METHODS

We collected Twitter messages that mentioned "air conditioning (AC)" and "heat" and Google search data that included weather, medical, recreational, and adaptation information from May 7 to November 3, 2014, focusing on the state of Florida, U.S. We separately associated web data against two different sources of health outcomes (emergency department (ED) and hospital admissions) and five disease categories (cardiovascular disease, dehydration, heat-related illness, renal disease, and respiratory disease). Seasonal and subseasonal temporal cycles were controlled using autoregressive moving average-generalized autoregressive conditional heteroscedasticity (ARMA-GARCH) and generalized linear model (GLM).

RESULTS

The results show that the number of heat-related illness and dehydration cases exhibited a significant positive relationship with web data. Specifically, heat-related illness cases showed positive associations with messages (heat, AC) and web searches (drink, heat stroke, park, swim, and tired). In addition, terms such as park, pool, swim, and water tended to show a consistent positive relationship with dehydration cases. However, we found inconsistent relationships between renal illness and web data. Web data also did not improve the models for cardiovascular and respiratory illness cases.

CONCLUSIONS

Our findings suggest web data created by social medias and search engines could improve the current syndromic surveillance systems. In particular, heat-related illness and dehydration cases were positively related with web data. This paper also shows that activity patterns for reducing heat stress are associated with several health outcomes. Based on the results, we believe web data could benefit both regions without the systems and persistently hot and humid climates where excess heat early warning systems may be less effective.

Temporal changes in the effects of ambient temperatures on hospital admissions in Spain

BACKGROUND

The exposure to extreme ambient temperatures has been reported to increase mortality, although less is known about its impact on morbidity. The analysis of temporal changes in temperature-health associations has also focused on mortality with no studies on hospitalizations worldwide. Studies on temporal variations can provide insights on changes in susceptibility or on effectiveness of public health interventions. We aimed to analyse the effects of temperature on cause-specific hospital admissions in Spain and assess temporal changes using two periods, the second one characterized by the introduction of a heat health prevention plan.

METHODS

Daily counts of non-scheduled hospital admissions for cardiovascular, cerebrovascular and respiratory diseases and daily maximum temperature were obtained for each Spanish province for the period 1997-2013. The relationship between temperature and hospitalizations was estimated using distributed lag non-linear models. We compared the risk of hospitalization due to temperatures (cold, heat and extreme heat) in two periods (1997-2002 and 2004-2013).

RESULTS

Cold temperatures were associated with increased risk of cardiovascular, cerebrovascular and respiratory hospital admissions. Hot temperatures were only associated with higher hospital admissions for respiratory causes while hospitalizations for cardiovascular and cerebrovascular diseases did not increase with heat. There was a small reduction in heat-related respiratory admissions in period 2. Whereas cold-related hospitalizations for cardiovascular and cerebrovascular diseases increased in period 2, a significant reduction for respiratory hospitalizations was reported.

CONCLUSIONS

Our results suggested that heat had an adverse impact on hospital admissions for respiratory diseases, while cold increased the risk of the three studied cause-specific hospitalizations. Public health interventions should also focus on morbidity effects of temperature.

Increasing mitigation ambition to meet the Paris Agreement's temperature goal avoids substantial heat-related mortality in U.S. cities

Current greenhouse gas mitigation ambition is consistent with ~3°C global mean warming above preindustrial levels. There is a clear need to strengthen mitigation ambition to stabilize the climate at the Paris Agreement goal of warming of less than 2°C. We specify the differences in city-level heat-related mortality between the 3°C trajectory and warming of 2° and 1.5°C. Focusing on 15 U.S. cities where reliable climate and health data are available, we show that ratcheting up mitigation ambition to achieve the 2°C threshold could avoid between 70 and 1980 annual heat-related deaths per city during extreme events (30-year return period). Achieving the 1.5°C threshold could avoid between 110 and 2720 annual heat-related deaths. Population changes and adaptation investments would alter these numbers. Our results provide compelling evidence for the heat-related health benefits of limiting global warming to 1.5°C in the United States.

The Future of Climate Epidemiology: Opportunities for Advancing Health Research in the Context of Climate Change

In the coming decades, climate change is expected to dramatically affect communities worldwide, altering the patterns of many ambient exposures and disasters, including extreme temperatures, heat waves, wildfires, droughts, and floods. These exposures, in turn, can affect risks for a variety of human diseases and health outcomes. Climate epidemiology plays an important role in informing policy related to climate change and its threats to public health. Climate epidemiology leverages deep, integrated collaborations between epidemiologists and climate scientists to understand the current and potential future impacts of climate-related exposures on human health. A variety of recent and ongoing developments in climate science are creating new avenues for epidemiologic contributions. Here, we discuss the contributions of climate epidemiology and describe some key current research directions, including research to better characterize uncertainty in climate health projections. We end by outlining 3 developing areas of climate science that are creating opportunities for high-impact epidemiologic advances in the near future: 1) climate attribution studies, 2) subseasonal to seasonal forecasts, and 3) decadal predictions.

Assessing the magnitude and uncertainties of the burden of selected diseases attributable to extreme heat and extreme precipitation under a climate change scenario in Michigan for the period 2041-2070

BACKGROUND

Extreme heat (EH) and extreme precipitation (EP) events are expected to increase with climate change in many parts of the world. Characterizing the potential future morbidity and mortality burden of EH and EP and associated costs, as well as uncertainties in the estimates, can identify areas for public health intervention and inform adaptation strategies. We demonstrate a burden of disease and uncertainty assessment using data from Michigan, USA, and provide approaches for deriving these estimates for locations lacking certain data inputs.

METHODS

Case-crossover analysis adapted from previous Michigan-specific modeling was used to characterize the historical EH-mortality relationship by county poverty rate and age group. Historical EH-associated hospitalization and emergency room visit risks from the literature were adapted to Michigan. In the U.S. Environmental Protection Agency's BenMAP software, we used a novel approach, with multiple spatially-varying exposures, to estimate all non-accidental mortality and morbidity occurring on EH days (EH days; days where maximum temperature 32.2-35 C or > 35 C) and EP days. We did so for two time periods: the "historical" period (1971-2000), and the "projected" period (2041-2070), by county.

RESULTS

The rate of all non-accidental mortality associated with EH days increased from 0.46/100,000 persons historically to 2.9/100,000 in the projected period, for 240 EH-attributable deaths annually. EH-associated ED visits increased from 12/100,000 persons to 68/100,000 persons, for 7800 EH-attributable emergency department visits. EP-associated ED visits increased minimally from 1.7 to 1.9/100,000 persons. Mortality and morbidity were highest among those aged 65+ (91% of all deaths). Projected health costs are dominated by EH-associated mortality ($280 million) and EH-associated emergency department visits ($14 million). A variety of sources contribute to a moderate-to-high degree of uncertainty around the point estimates, including uncertainty in the magnitude of climate change, population composition, baseline health rates, and exposure-response estimates.

CONCLUSIONS

The approach applied here showed that health burden due to climate may significantly rise for all Michigan counties by midcentury. The costs to health care and uncertainties in the estimates, given the potential for substantial attributable burden, provide additional information to guide adaptation measures for EH and EP.

Characterizing Spatial Variability of Climate-Relevant Hazards and Vulnerabilities in the New England Region of the United States

Weather and climate have substantial effects on human health. While much is known about how morbidity and mortality are affected by moderate-to-extreme heat, poor air quality, and heavy precipitation individually, less is known about the cumulative occurrence of these climatic hazards, and the extent to which they spatially overlap with community-scale vulnerabilities. Specifically, there is interest in determining whether individuals living in places with the highest exposure to multiple health hazardous climatic conditions are also more vulnerable to having negative health outcomes. Presented here is a spatial analysis of the distribution of health-relevant climatic hazards and social vulnerabilities across the New England region of the northeastern United States. We show that the frequency of excessive heat days, heavy precipitation days, and ozone (O3) and fine particulate matter (PM2.5) exceedances during the warm seasons (May-September) from 2009 to 2014 have distinct spatial distributions and are statistically significantly correlated across space with indicators of social vulnerability. We further quantify an integrated measure of the hazards and vulnerabilities to illustrate the spatial heterogeneity of overall risk, as well as to demonstrate how the choice of spatial scale influences the identification of high-risk areas. These methods are transferrable to other locations and contexts, which could be of utility not only to geographers and epidemiologists, but also to policymakers tasked with allocating public health resources to populations at greatest risk of weather- and climate-related health effects.

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.

State-of-the-art global models underestimate impacts from climate extremes

Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.

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.

Effects of ambient temperature on ambulance emergency call-outs in the subtropical city of Shenzhen, China

The associations between meteorological factors and mortality have been well documented worldwide, but limited evidence is available for the non-fatal health impacts of ambient temperature, particularly there are few population-based investigations on the impacts of emergency ambulance dispatches in Asia. In this study, based on 809,906 ambulance emergency call-outs (AECOs) for the total population from 2010-2016 in the subtropical city of Shenzhen, China, a Poisson regression combined with a distributed lag nonlinear model was used to simultaneously assess the nonlinear and lag effects of daily mean temperature on AECOs. Stratified analyses by age and sex were performed to identify vulnerable subpopulations. A U-shaped relationship was found between temperature and AECOs. Cold effects were delayed and persisted for 3-4 weeks, with a cumulative relative risk (RR) and 95% confidence interval (CI) of 1.23 (1.10-1.38) and 1.25 (1.16-1.35) over lag 0-28 when comparing the 1st and 5th percentile of the temperature distribution to the optimal (i.e. minimum AECOs) temperature, respectively. Hot effects were immediate and diminished quickly in 5 days, with an increase of 19% (RR = 1.19, 95%CI: 1.14-1.23) and 21% (RR = 1.21, 95%CI: 1.16-1.26) in AECOs over lag 0-5 when comparing the 95th and 99th percentile of temperature to the optimal temperature. Children and the elderly were more vulnerable to cold effects. The youth and middle-aged people suffered more from high temperature. The effects of temperature were similar between males and females. In summary, significant increases were observed in the frequency of AECOs during cold and hot days, and the weather-associated increases in AECOs are different among age groups. This information has valuable implications in ambulance demand prediction and service provision planning.

Threshold Evaluation of Emergency Risk Communication for Health Risks Related to Hazardous Ambient Temperature

Emergency risk communication (ERC) programs that activate when the ambient temperature is expected to cross certain extreme thresholds are widely used to manage relevant public health risks. In practice, however, the effectiveness of these thresholds has rarely been examined. The goal of this study is to test if the activation criteria based on extreme temperature thresholds, both cold and heat, capture elevated health risks for all-cause and cause-specific mortality and morbidity in the Minneapolis-St. Paul Metropolitan Area. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson generalized linear model is used to derive the exposure-response functions between daily maximum heat index and mortality (1998-2014) and morbidity (emergency department visits; 2007-2014). Specific causes considered include cardiovascular, respiratory, renal diseases, and diabetes. Six extreme temperature thresholds, corresponding to 1st-3rd and 97th-99th percentiles of local exposure history, are examined. All six extreme temperature thresholds capture significantly increased relative risks for all-cause mortality and morbidity. However, the cause-specific analyses reveal heterogeneity. Extreme cold thresholds capture increased mortality and morbidity risks for cardiovascular and respiratory diseases and extreme heat thresholds for renal disease. Percentile-based extreme temperature thresholds are appropriate for initiating ERC targeting the general population. Tailoring ERC by specific causes may protect some but not all individuals with health conditions exacerbated by hazardous ambient temperature exposure.

Escalating heat-stress mortality risk due to global warming in the Middle East and North Africa (MENA)

Climate change will substantially exacerbate extreme temperature and heatwaves. The impacts will be more intense across the Middle East and North Africa (MENA), a region mostly characterized by hot and arid climate, already intolerable for human beings in many parts. In this study, daily climate data from 17 fine-resolution Regional Climate Models (RCMs) are acquired to calculate wet-bulb temperature and investigate the mortality risk for people aged over 65 years caused by excessive heat stress across the MENA region. Spatially adaptive temperature thresholds are implemented for quantifying the mortality risk, and the analysis is conducted for the historical period of 1951-2005 and two future scenarios of RCP4.5 and RCP8.5 during the 2006-2100 period. Results show that the mortality risk will increase in distant future to 8-20 times higher than that of the historical period if no climate change mitigation is implemented. The coastal regions of the Red sea, Persian Gulf, and Mediterranean Sea indicate substantial increase in mortality risk. Nonetheless, the risk ratio will be limited to 3-7 times if global warming is limited to 2 °C. Climate change planning and adaptation is imperative for mitigating heat-related mortality risk across the region.

The Impact of Heat Waves on Emergency Department Admissions in Charlottesville, Virginia, U.S.A

Heat waves have been linked to increases in emergency-related morbidity, but more research is needed on the demographic and disease-specific aspects of these morbidities. Using a case-crossover approach, over 700,000 daily emergency department hospital admissions in Charlottesville, Virginia, U.S.A. from 2005–2016 are compared between warm season heat wave and non-heat wave periods. Heat waves are defined based on the exceedance, for at least three consecutive days, of two apparent temperature thresholds (35 °C and 37 °C) that account for 3 and 6% of the period of record. Total admissions and admissions for whites, blacks, males, females, and 20–49 years old are significantly elevated during heat waves, as are admissions related to a variety of diagnostic categories, including diabetes, pregnancy complications, and injuries and poisoning. Evidence that heat waves raise emergency department admissions across numerous demographic and disease categories suggests that heat exerts comorbidity influences that extend beyond the more well-studied direct relationships such as heat strokes and cardiac arrest.

Effectiveness of National Weather Service heat alerts in preventing mortality in 20 US cities

BACKGROUND

Extreme heat is a well-documented public health threat. The US National Weather Service (NWS) issues heat advisories and warnings (collectively, "heat alerts") in advance of forecast extreme heat events. The effectiveness of these alerts in preventing deaths remains largely unknown.

OBJECTIVES

To quantify the change in mortality rates associated with heat alerts in 20 US cities between 2001 and 2006.

METHODS

Because NWS heat alerts are issued based on forecast weather and these forecasts are imperfect, in any given location there exists a set of days of similar observed heat index in which heat alerts have been issued for some days but not others. We used a case-crossover design and conditional logistic regression to compare mortality rates on days with versus without heat alerts among such eligible days, adjusting for maximum daily heat index and temporal factors. We combined city-specific estimates into a summary measure using standard random-effects meta-analytic techniques.

RESULTS

Overall, NWS heat alerts were not associated with lower mortality rates (percent change in rate: -0.5% [95% CI: -2.8, 1.9]). In Philadelphia, heat alerts were associated with a 4.4% (95% CI: -8.3, -0.3) lower mortality rate or an estimated 45.1 (95% empirical CI: 3.1, 84.1) deaths averted per year if this association is assumed to be causal. No statistically significant beneficial association was observed in other individual cities.

CONCLUSIONS

Our results suggest that between 2001 and 2006, NWS heat alerts were not associated with lower mortality in most cities studied, potentially missing a valuable opportunity to avert a substantial number of heat-related deaths. These results highlight the need to better link alerts to effective communication and intervention strategies to reduce heat-related mortality.

Dependence of future mortality changes on global CO2 concentrations: A review

The heterogeneity among previous studies of future mortality projections due to climate change has often hindered comparisons and syntheses of resulting impacts. To address this challenge, the present study introduced a novel method to normalize the results from projection studies according to different baseline and projection periods and climate scenarios, thereby facilitating comparison and synthesis. This study reviewed the 15 previous studies involving projected climate change-related mortality under Representative Concentration Pathways. To synthesize their results, we first reviewed the important study design elements that affected the reported results in previous studies. Then, we normalized the reported results by CO₂ concentration in order to eliminate the effects of the baseline period, projection period, and climate scenario choices. For twenty-five locations worldwide, the normalized percentage changes in temperature-attributable mortality per 100 ppm increase in global CO₂ concentrations ranged between 41.9% and 330%, whereas those of total mortality ranged between 0.3% and 4.8%. The normalization methods presented in this work will guide future studies to provide their results in a normalized format and facilitate research synthesis to reinforce our understanding on the risk of climate change.

Modeling the Present and Future Incidence of Pediatric Hand, Foot, and Mouth Disease Associated with Ambient Temperature in Mainland China

BACKGROUND

There is limited evidence about the association between ambient temperature and the incidence of pediatric hand, foot, and mouth disease (HFMD) nationwide in China.

OBJECTIVES

We examined the childhood temperature-HFMD associations across mainland China, and we projected the change in HFMD cases due to projected temperature change by the 2090s.

METHODS

Data on daily HFMD (children 0-14 y old) counts and weather were collected from 362 sites during 2009-2014. Daily temperature by the 2090s was downscaled under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. Temperature-HFMD associations were quantified using a two-stage Poisson regression with a distributed lag nonlinear model. The impact of changes in temperature on the incidence of HFMD was estimated by combining the fitted temperature-HFMD associations with projected temperatures under each scenario, assuming a constant population structure. Sensitivity analyses were performed to assess the influence of primary model assumptions.

RESULTS

During 2009-2014, >11 million HFMD cases were reported. In most regions, the temperature-HFMD association had an inverted U shape with a peak at approximately 20°C, but the association leveled off or continued to increase in the Inner Mongolia and Northeast regions. When estimates were pooled across all regions and the population size was held constant, the projected incidence of HFMD increased by 3.2% [95% empirical confidence interval (eCI): −13.5%, 20.0%] and 5.3% (95% eCI: −33.3%, 44.0%) by the 2090s under the RCP 4.5 and 8.5 scenarios, respectively. However, regional projections suggest that HFMD may decrease with climate change in temperate areas of central and eastern China.

CONCLUSION

Our estimates suggest that the association between temperature and HFMD varies across China and that the future impact of climate change on HFMD incidence will vary as well. Other factors, including changes in the size of the population at risk (children 0-14 y old) will also influence future HFMD trends. https://doi.org/10.1289/EHP3062.

Changes in relative fit of human heat stress indices to cardiovascular, respiratory, and renal hospitalizations across five Australian urban populations

Various human heat stress indices have been developed to relate atmospheric measures of extreme heat to human health impacts, but the usefulness of different indices across various health impacts and in different populations is poorly understood. This paper determines which heat stress indices best fit hospital admissions for sets of cardiovascular, respiratory, and renal diseases across five Australian cities. We hypothesized that the best indices would be largely dependent on location. We fit parent models to these counts in the summers (November-March) between 2001 and 2013 using negative binomial regression. We then added 15 heat stress indices to these models, ranking their goodness of fit using the Akaike information criterion. Admissions for each health outcome were nearly always higher in hot or humid conditions. Contrary to our hypothesis that location would determine the best-fitting heat stress index, we found that the best indices were related largely by health outcome of interest, rather than location as hypothesized. In particular, heatwave and temperature indices had the best fit to cardiovascular admissions, humidity indices had the best fit to respiratory admissions, and combined heat-humidity indices had the best fit to renal admissions. With a few exceptions, the results were similar across all five cities. The best-fitting heat stress indices appear to be useful across several Australian cities with differing climates, but they may have varying usefulness depending on the outcome of interest. These findings suggest that future research on heat and health impacts, and in particular hospital demand modeling, could better reflect reality if it avoided "all-cause" health outcomes and used heat stress indices appropriate to specific diseases and disease groups.

Projected trends in high-mortality heatwaves under different scenarios of climate, population, and adaptation in 82 US communities

Some rare heatwaves have extreme daily mortality impacts; moderate heatwaves have lower daily impacts but occur much more frequently at present and so account for large aggregated impacts. We applied health-based models to project trends in high-mortality heatwaves, including proportion of all heatwaves expected to be high-mortality, using the definition that a high-mortality heatwave increases mortality risk by ≥20 %. We projected these trends in 82 US communities in 2061-2080 under two scenarios of climate change (RCP4.5, RCP8.5), two scenarios of population change (SSP3, SSP5), and three scenarios of community adaptation to heat (none, lagged, on-pace) for large- and medium-ensemble versions of the National Center for Atmospheric Research's Community Earth System Model. More high-mortality heatwaves were expected compared to present under all scenarios except on-pace adaptation, and population exposure was expected to increase under all scenarios. At least seven more high-mortality heatwaves were expected in a twenty-year period in the 82 study communities under RCP8.5 than RCP4.5 when assuming no adaptation. However, high-mortality heatwaves were expected to remain <1 % of all heatwaves and heatwave exposure under all scenarios. Projections were most strongly influenced by the adaptation scenario- going from a scenario of on-pace to lagged adaptation or from lagged to no adaptation more than doubled the projected number of and exposure to high-mortality heatwaves. Based on our results, fewer high-mortality heatwaves are expected when following RCP4.5 versus RCP8.5 and under higher levels of adaptation, but high-mortality heatwaves are expected to remain a very small proportion of total heatwave exposure.

Effects of high ambient temperature on ambulance dispatches in different age groups in Fukuoka, Japan

BACKGROUND

The elderly population has been the primary target of intervention to prevent heat-related illnesses. According to the literature, the highest risks have been observed among the elderly in the temperature-mortality relationship. However, findings regarding the temperature-morbidity relationship are inconsistent.

OBJECTIVES

This study aimed to examine the association of temperature with ambulance dispatches due to acute illnesses, stratified by age group. Specifically, we explored the optimum temperature, at which the relative health risks were found to be the lowest, and quantified the health risk associated with higher temperatures among different age groups.

METHODS

We used the data for ambulance dispatches in Fukuoka, Japan, during May and September from 2005 to 2012. The data were grouped according to age in 20-year increments. We explored the pattern of the association of ambulance dispatches with temperature using a smoothing spline curve to identify the optimum temperature for each age group. Then, we applied a distributed lag nonlinear model to estimate the risks of the 85th-95th percentile temperature relative to the overall optimum temperature, for each age group.

RESULTS

The relative risk of ambulance dispatches at the 85th and 95th percentile temperature for all ages was 1.08 [95% confidence interval (CI): 1.05, 1.12] and 1.12 (95% CI: 1.08, 1.16), respectively. In comparison, among age groups, the optimum temperature was observed as 25.0°C, 23.2°C, and 25.3°C for those aged 0-19, 60-79, and ≥80, respectively. The optimum temperature could not be determined for those aged 20-39 and 40-59. The relative risks of high temperature tended to be higher for those aged 20-39 and 40-59 than those for other age groups.

CONCLUSIONS

We did not find any definite difference in the effect of high temperature on ambulance dispatches for different age groups. However, more measures should be taken for younger and middle-aged people to avoid heat-related illnesses.

Risk characterization of hospitalizations for mental illness and/or behavioral disorders with concurrent heat-related illness

Background

Many studies have found significant associations between high ambient temperatures and increases in heat-related morbidity and mortality. Several studies have demonstrated that increases in heat-related hospitalizations are elevated among individuals with diagnosed mental illnesses and/or behavioral disorders (MBD). However, there are a limited number of studies regarding risk factors associated with specific mental illnesses that contribute, at least in part, to heat-related illnesses (HRI) in the United States.

Objective

To identify and characterize individual and environmental risk factors associated with MBD hospitalizations with a concurrent HRI diagnosis.

Methods

This study uses hospitalization data from the Nationwide Inpatient Sample (2001–2010). Descriptive analyses of primary and secondary diagnoses of MBDs with an HRI were examined. Risk ratios (RR) were calculated from multivariable models to identify risk factors for hospitalizations among patients with mental illnesses and/or behavioral disorders and HRI.

Results

Nondependent alcohol/drug abuse, dementia, and schizophrenia were among the disorders that were associated with increased frequency of HRI hospitalizations among MBD patients. Increased risk of MBD hospitalizations with HRI was observed for Males (RR, 3.06), African Americans (RR, 1.16), Native Americans (RR, 1.70), uninsured (RR, 1.92), and those 40 years and older, compared to MBD hospitalizations alone.

Conclusions

Previous studies outside the U.S. have found that dementia and schizophrenia are significant risk factors for HRI hospitalizations. Our results suggest that hospitalizations among substance abusers may also be an important risk factor associated with heat morbidity. Improved understanding of these relative risks could help inform future public health strategies.

Current and Projected Burden of Disease From High Ambient Temperature in Korea

BACKGROUND

The objective of the present study was to estimate the current and projected burden of disease from high ambient temperature using population-based data sources of nationwide mortality and morbidity in Korea.

METHODS

Disability-adjusted life years (DALY) were estimated using noninjury-related deaths, and cerebrovascular and cardiovascular diseases from recently released nationwide health and mortality databases. Years of life lost and years lost due to disability were measured based on the point prevalence and number of deaths during the study period. Future DALY attributable to heat waves were estimated from projected populations, and temperature predictions for the years 2030 and 2050 were under Representative Concentration Pathways (RCP) 4.5 and 8.5 with summertime temperatures above threshold.

RESULTS

Relative risks (RR) of total mortality and of cardiovascular disease were 1.02 (95% CI, 1.01, 1.02) and 1.08 (95% CI, 1.06, 1.09) for each 1°C increase in temperature above threshold, respectively. The morbidity of heat-related disease was RR 1.67 (95% CI, 1.64, 1.68) for each 1°C increase in temperature above threshold. DALY for all-cause death were 0.49 DALY/1000 in 2011, 0.71 (0.71) DALY/1000 in 2030 and 0.77 (1.72) DALY/1000 in 2050 based on RCP 4.5 (RCP 8.5). DALY for cardio- and cerebrovascular diseases were 1.24 DALY/1000 in 2011, 1.63 (1.82) DALY/1000 in 2030, and 1.76 (3.66) DALY/1000 in 2050 based on RCP 4.5 (RCP 8.5).

CONCLUSIONS

Future excess mortality due to high ambient temperature is expected to be profound in Korea. Efforts to mitigate climate change can provide substantial health benefits via reducing heat-related mortality.

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.