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

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

DISCUSSION

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

Simulating desegregation through affordable housing development: An environmental health impact assessment of Connecticut zoning law

Residential segregation drives exposure and health inequities. We projected the mortality impacts among low-income residents of leveraging an existing 10% affordable housing target as a case study of desegregation policy. We simulated movement into newly allocated housing, quantified changes in six ambient environmental exposures, and used exposure-response functions to estimate deaths averted. Across 1000 simulations, in one year, we found on average 169 (95% CI: 84, 255) deaths averted from changes in greenness, 71 (49, 94) deaths averted from NO2, 9 (4, 14) deaths averted from noise, 1 (1, 2) excess death from O3, and 2 (1, 2) excess deaths from PM2.5, with rates of deaths averted highest among non-Hispanic Black and non-Hispanic White residents. Strengthening desegregation policy may advance environmental health equity.

Simulating desegregation through affordable housing development: an environmental health impact assessment of Connecticut zoning law

Residential segregation shapes access to health-promoting resources and drives health inequities in the United States. Connecticut's Section 8-30g incentivizes municipalities to develop a housing stock that is at least 10% affordable housing. We used this implicit target to project the impact of increasing affordable housing across all 169 Connecticut municipalities on all-cause mortality among low-income residents. We modeled six ambient environmental exposures: fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), summertime daily maximum heat index, greenness, and road traffic noise. We allocated new affordable housing to reach the 10% target in each town and simulated random movement of low-income households into new units using an inverse distance weighting penalty. We then quantified exposure changes and used established exposure-response functions to estimate deaths averted stratified by four ethnoracial groups: Asian, Hispanic or Latino, non-Hispanic Black, and non-Hispanic White. We quantified racialized segregation by computing a multi-group index of dissimilarity at baseline and post-simulation. Across 1,000 simulations, in one year (2019) we found on average 169 (95% CI: 84, 255) deaths averted from changes in greenness, 71 (95% CI: 49, 94) deaths averted from NO2, 9 (95% CI: 4, 14) deaths averted from noise, and marginal impacts from other exposures, with the highest rates of deaths averted observed among non-Hispanic Black and non-Hispanic White residents. Multi-group index of dissimilarity declined on average in all eight Connecticut counties post-simulation. Sensitivity analyses simulating a different population movement strategy and modeling a different year (2018) yielded consistent results. Strengthening desegregation policy may reduce deaths from environmental exposures among low-income residents. Further research should explore non-mortality impacts and additional mechanisms by which desegregation may advance health equity.

Does choice of outdoor heat metric affect heat-related epidemiologic analyses in the US Medicare population?

Outdoor air temperature is associated with increased morbidity and mortality. Other thermal indices theoretically confer greater physiological relevance by incorporating additional meteorological variables. However, the optimal metric for predicting excess deaths or hospitalizations owing to extreme heat among US Medicare beneficiaries remains unknown.

Methods

We calculated daily maximum, minimum, and mean outdoor air temperature (T), heat index (HI), wet-bulb globe temperature (WBGT), and Universal Thermal Climate Index (UTCI) for populous US counties and linked estimates with daily all-cause mortality and heat-related hospitalizations among Medicare beneficiaries (2006-2016). We fit distributed-lag nonlinear models for each metric and compared relative risks (RRs) at the 99th percentile.

Results

Across all heat metrics, extreme heat was statistically significantly associated with elevated risks of morbidity and mortality. Associations were more pronounced for maximum daily values versus the corresponding minimum for the same metric. The starkest example was between HImax (RR = 1.14; 95% confidence interval [CI] = 1.12, 1.15) and HImin (RR = 1.10; 95% CI = 1.09, 1.11) for hospitalizations. When comparing RRs across heat metrics, we found no statistically significant differences within the minimum and maximum heat values (i.e., no significant differences between Tmax/HImax/WBGTmax/UTCImax or between Tmin/HImin/WBGTmin/UTCImin). We found similar relationships across the National Climate Assessment regions.

Conclusion

Among Medicare beneficiaries in populous US counties, daily maximum and mean values of outdoor heat are associated with greater RRs of heat-related morbidity and all-cause mortality versus minimum values of the same metric. The choice of heat metric (e.g., temperature versus HI) does not appear to substantively affect risk calculations in this population.

Reimagining the Role of Health Departments and Their Partners in Addressing Climate Change: Revising the Building Resilience against Climate Effects (BRACE) Framework

Public health departments have important roles to play in addressing the local health impacts of climate change, yet are often not well prepared to do so. The Climate and Health Program (CHP) at the Centers for Disease Control and Prevention (CDC) created the Building Resilience Against Climate Effects (BRACE) framework in 2012 as a five-step planning framework to support public health departments and their partners to respond to the health impacts of climate change. CHP has initiated a process to revise the framework to address learnings from a decade of experience with BRACE and advances in the science and practice of addressing climate and health. The aim of this manuscript is to describe the methodology for revising the BRACE framework and the expected outputs of this process. Development of the revised framework and associated guidance and tools will be guided by a multi-sector expert panel, and finalization will be informed by usability testing. Planned revisions to BRACE will (1) be consistent with the vision of Public Health 3.0 and position health departments as "chief health strategists" in their communities, who are responsible for facilitating the establishment and maintenance of cross-sector collaborations with community organizations, other partners, and other government agencies to address local climate impacts and prevent further harm to historically underserved communities; (2) place health equity as a central, guiding tenet; (3) incorporate greenhouse gas mitigation strategies, in addition to its previous focus on climate adaptation; and (4) feature a new set of tools to support BRACE implementation among a diverse set of users. The revised BRACE framework and the associated tools will support public health departments and their partners as they strive to prevent and reduce the negative health impacts of climate change for everyone, while focusing on improving health equity.

Heat-mortality relationship in North Carolina: Comparison using different exposure methods

BACKGROUND

Many studies have explored the heat-mortality relationship; however, comparability of results is hindered by the studies' use of different exposure methods.

OBJECTIVE

This study evaluated different methods for estimating exposure to temperature using individual-level data and examined the impacts on the heat-mortality relationship.

METHODS

We calculated different temperature exposures for each individual death by using a modeled, gridded temperature dataset and a monitoring station dataset in North Carolina for 2000-2016. We considered individual-level vs. county-level averages and measured vs. modeled temperature data. A case-crossover analysis was conducted to examine the heat-mortality risk under different exposure methods.

RESULTS

The minimum mortality temperature (MMT) (i.e., the temperature with the lowest mortality rate) for the monitoring station dataset was 23.87 °C and 22.67 °C (individual monitor and county average, respectively), whereas for the modeled temperature dataset the MMT was 19.46 °C and 19.61 °C (individual and county, respectively). We found higher heat-mortality risk while using temperature exposure estimated from monitoring stations compared to risk based on exposure using the modeled temperature dataset. Individual-aggregated monitoring station temperature exposure resulted in higher heat mortality risk (odds ratio (95% CI): 2.24 (95% CI: 2.21, 2.27)) for a relative temperature change comparing the 99th and 90th temperature percentiles, while modeled temperature exposure resulted in lower odds ratio of 1.27 (95% CI: 1.25, 1.29).

SIGNIFICANCE

Our findings indicate that using different temperature exposure methods can result in different temperature-mortality risk. The impact of using various exposure methods should be considered in planning health policies related to high temperatures, including under climate change. IMPACT STATEMENT: (1) We estimated the heat-mortality association using different methods to estimate exposure to temperature. (2) The mean temperature value among different exposure methods were similar although lower for the modeled data, however, use of the monitoring station temperature dataset resulted in higher heat-mortality risk than the modeled temperature dataset. (3) Differences in mortality risk from heat by urbanicity varies depending on the method used to estimate temperature exposure.

Planning to Reduce the Health Impacts of Extreme Heat: A Content Analysis of Heat Action Plans in Local United States Jurisdictions

Objectives. To examine commonalities and gaps in the content of local US heat action plans (HAPs) designed to decrease the adverse health effects of extreme heat. Methods. We used content analysis to identify common strategies and gaps in extreme heat preparedness among written HAPs in the United States from jurisdictions that serve municipalities with more than 200 000 residents. We reviewed, coded, and analyzed plans to assess the prevalence of key components and strategies. Results. All 21 plans evaluated incorporated data on activation triggers, heat health messaging and risk communication, cooling centers, surveillance activities, and agency coordination, and 95% incorporated information on outreach to at-risk populations. Gaps existed in the specific applications of these broad strategies. Conclusions. Practice-based recommendations as well as future areas of research should focus on increasing targeted strategies for at-risk individuals and expanding the use of surveillance data outside of situational awareness. (Am J Public Health. 2023;113(5):559-567. https://doi.org/10.2105/AJPH.2022.307217).

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

BACKGROUND

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

METHODS

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

FINDINGS

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

INTERPRETATION

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

FUNDING

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

Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions

Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions (HWDs) could change across health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 28 HWDs associated with HRI emergency department visits over five summer seasons (2011−2016), stratified by two physiographic regions (Coastal and Piedmont) in North Carolina. The HRI rate ratios associated with heat waves were estimated using the generalized linear regression framework assuming a negative binomial distribution. We compared the Akaike Information Criterion (AIC) values across the HWDs to identify an optimal HWD. In the Coastal region, HWDs based on daily maximum temperature with a threshold > 90th percentile for two or more consecutive days had the optimal model fit. In the Piedmont region, HWD based on the daily minimum temperature with a threshold value > 90th percentile for two or more consecutive days was optimal. The HWDs with optimal model performance included in this study captured moderate and frequent heat episodes compared to the National Weather Service (NWS) heat products. This study compared the HRI morbidity risk associated with epidemiologic-based HWDs and with NWS heat products. Our findings could be used for public health education and suggest recalibrating NWS heat products.

Wet-Bulb Globe Temperature, Universal Thermal Climate Index, and Other Heat Metrics for US Counties, 2000-2020

Epidemiologic research on extreme heat consistently finds significant impacts on human morbidity and mortality. However, most of these analyses do not use spatially explicit measures of heat (typically assessing exposures at major cities using the nearest weather station), and they frequently consider only ambient temperature or heat index. The field is moving toward more expansive analyses that use spatially resolved gridded meteorological datasets and alternative assessments of heat, such as wet-bulb globe temperature (WBGT) and universal thermal climate index (UTCI), both of which require technical geoscientific skills that may be inaccessible to many public health researchers. To facilitate research in this domain, we created a database of population-weighted, spatially explicit daily heat metrics - including WBGT, UTCI, heat index, dewpoint temperature, net effective temperature, and humidex - for counties in the conterminous United States derived from the ERA5-Land gridded data set and using previously validated equations and algorithms. We also provide an R package to calculate these metrics, including gold-standard algorithms for estimating WBGT and UTCI, to facilitate replication.

Heat exposure and cardiovascular health outcomes: a systematic review and meta-analysis

BACKGROUND

Heat exposure is an important but underappreciated risk factor contributing to cardiovascular disease. Warming temperatures might therefore pose substantial challenges to population health, especially in a rapidly aging population. To address a potential increase in the burden of cardiovascular disease, a better understanding of the effects of ambient heat on different types of cardiovascular disease and factors contributing to vulnerability is required, especially in the context of climate change. This study reviews the current epidemiological evidence linking heat exposures (both high temperatures and heatwaves) with cardiovascular disease outcomes, including mortality and morbidity.

METHODS

In this systematic review and meta-analysis, we searched PubMed, Embase, and Scopus for literature published between Jan 1, 1990, and March 10, 2022, and evaluated the quality of the evidence following the Navigation Guide Criteria. We included original research on independent study populations in which the exposure metric was high temperatures or heatwaves, and observational studies using ecological time series, case crossover, or case series study designs comparing risks over different exposures or time periods. Reviews, commentaries, grey literature, and studies that examined only seasonal effects without explicitly considering temperature were excluded. The risk estimates were derived from included articles and if insufficient data were available we contacted the authors to provide clarification. We did a random-effects meta-analysis to pool the relative risk (RR) of the association between high temperatures and heatwaves and cardiovascular disease outcomes. The study protocol was registered with PROSPERO (CRD42021232601).

FINDINGS

In total, 7360 results were returned from our search of which we included 282 articles in the systematic review, and of which 266 were eligible for the meta-analysis. There was substantial heterogeneity for both mortality (high temperatures: I²=93·6%, p<0·0001; heatwaves: I²=98·9%, p<0·0001) and morbidity (high temperatures: I²=98·8%, p<0·0001; heatwaves: I²=83·5%, p<0·0001). Despite the heterogeneity in environmental conditions and population dynamics among the reviewed studies, results showed that a 1°C increase in temperature was positively associated with cardiovascular disease-related mortality across all considered diagnoses. The overall risk of cardiovascular disease-related mortality increased by 2·1% (RR 1·021 [95%CI 1·020-1·023]), with the highest specific disease risk being for stroke and coronary heart disease. A 1°C temperature rise was also associated with a significant increase in morbidity due to arrhythmias and cardiac arrest and coronary heart disease. Our findings suggest heat exposure leads to elevated risk of morbidity and mortality for women, people 65 years and older, individuals living in tropical climates, and those in countries of lower-middle income. Heatwaves were also significantly associated with a 17% increase in risk of mortality (RR 1·117 [95% CI 1·093-1·141]), and increasing heatwave intensity with an increasing risk (RR 1·067 [95% CI 1·056-1·078] for low intensity, 1·088 [1·058-1·119] for middle intensity, and 1·189 [1·109-1·269] for high intensity settings).

INTERPRETATION

This review strengthens the evidence on the increase in cardiovascular disease risk due to ambient heat exposures in different climate zones. The widespread prevalence of exposure to hot temperatures, in conjunction with an increase in the proportion of older people in the population, might result in a rise in poor cardiovascular disease health outcomes associated with a warming climate. Evidence-based prevention measures are needed to attenuate peaks in cardiovascular events during hot spells, thereby lowering the worldwide total heat-related burden of cardiovascular disease-related morbidity and death.

FUNDING

Australian Research Council Discovery Program.

Effect of coconut water and milk on heat stress-induced gastrointestinal tract dysmotility in rats: Role of oxidative stress and inflammatory response

The potential effects of coconut water (CCW) and milk (CCM) on gastrointestinal motility {intestinal transit (IT), intestinal fluid accumulation (IFA) and colonic motility}, tissue oxidative, and inflammatory responses in heat-stressed rats were investigated. There were four (4) temperature exposure groups; (i) Control at 30°C, (CON), (ii) heat-stressed (HS) group exposed to the ambiance of 40°C, (iii) heat-stressed pre-treated with coconut water (HS+ CCW), and (iv) coconut milk (HS + CCM). Skin temperatures (ST) and rectal temperatures (RT) were taken daily, before and after 2 hr heat exposure. GE, IT, and IFA were assessed using standard methods while colonic motility was assessed by colonic bead expulsion (CBE) time after the 14-day exposure. Serum cortisol and lipid peroxidation, antioxidant enzyme activities, inflammatory cytokines in intestinal samples were assessed. Stomach and intestinal morphology were equally examined on histomorphometry. Increased GE, IT, IFA, and colonic motility were observed in HS. CCW and CCM reversed the increases in GE, IT, IFA, and colonic motility in the heat-stressed rats (p < .05). Elevated serum cortisol level and intestinal MDA were significantly reduced in the CCW and CCM treated. Tissue GPx, T-AOC, and T-SOD were all enhanced in HS + CCW and HS + CCM. While tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) were suppressed in the HS group, interleukin-4 (IL-4) and interleukin-10 (IL-10) were enhanced with CCW and CCM. Altered intestinal morphology in the HS was also significantly mitigated by CCW and CCM. We showed that coconut water and milk could ameliorate intestinal dysmotility associated with heat stress via oxidative stress reduction and suppression of inflammatory responses. PRACTICAL APPLICATIONS: Heat stress impacts negatively on intestinal health and integrity in both humans and animals via oxidative stress and inflammation. Conversely, coconut has demonstrated anti-oxidative and anti-inflammatory properties in health and medicinal applications. From the findings of this study, coconut water and milk display beneficial potentials against the untoward heat stress effect on gastrointestinal health.

Fluctuating temperature modifies heat-mortality association in the globe

Studies have investigated the effects of heat and temperature variability (TV) on mortality. However, few assessed whether TV modifies the heat-mortality association. Data on daily temperature and mortality in the warm season were collected from 717 locations across 36 countries. TV was calculated as the standard deviation of the average of the same and previous days’ minimum and maximum temperatures. We used location-specific quasi-Poisson regression models with an interaction term between the cross-basis term for mean temperature and quartiles of TV to obtain heat-mortality associations under each quartile of TV, and then pooled estimates at the country, regional, and global levels. Results show the increased risk in heat-related mortality with increments in TV, accounting for 0.70% (95% confidence interval [CI]: −0.33 to 1.69), 1.34% (95% CI: −0.14 to 2.73), 1.99% (95% CI: 0.29–3.57), and 2.73% (95% CI: 0.76–4.50) of total deaths for Q1–Q4 (first quartile–fourth quartile) of TV. The modification effects of TV varied geographically. Central Europe had the highest attributable fractions (AFs), corresponding to 7.68% (95% CI: 5.25–9.89) of total deaths for Q4 of TV, while the lowest AFs were observed in North America, with the values for Q4 of 1.74% (95% CI: −0.09 to 3.39). TV had a significant modification effect on the heat-mortality association, causing a higher heat-related mortality burden with increments of TV. Implementing targeted strategies against heat exposure and fluctuant temperatures simultaneously would benefit public health.

•

Increased temperature variability (TV) poses a greater mortality risk due to heat

•

TV has a more profound modification effect on extreme heat-mortality association

•

Strategies against heat and TV simultaneously would benefit public health

Nationwide Analysis of the Heat- and Cold-Related Mortality Trends in Switzerland between 1969 and 2017: The Role of Population Aging

BACKGROUND

Because older adults are particularly vulnerable to nonoptimal temperatures, it is expected that the progressive population aging will amplify the health burden attributable to heat and cold due to climate change in future decades. However, limited evidence exists on the contribution of population aging on historical temperature-mortality trends.

OBJECTIVES

We aimed to a) assess trends in heat- and cold-related mortality in Switzerland between 1969 and 2017 and b) to quantify the contribution of population aging to the observed patterns.

METHODS

We collected daily time series of all-cause mortality by age group (<65, 65-79, and 80 y and older) and mean temperature for each Swiss municipality (1969-2017). We performed a two-stage time-series analysis with distributed lag nonlinear models and multivariate longitudinal meta-regression to obtain temperature-mortality associations by canton, decade, and age group. We then calculated the corresponding excess mortality attributable to nonoptimal temperatures and compared it to the estimates obtained in a hypothetical scenario of no population aging.

RESULTS

Between 1969 and 2017, heat- and cold-related mortality represented 0.28% [95% confidence interval (CI): 0.18, 0.37] and 8.91% (95% CI: 7.46, 10.21) of total mortality, which corresponded to 2.4 and 77 deaths per 100,000 people annually, respectively. Although mortality rates for heat slightly increased over time, annual number of deaths substantially raised up from 74 (12;125) to 181 (39;307) between 1969-78 and 2009-17, mostly driven by the ≥80-y-old age group. Cold-related mortality rates decreased across all ages, but annual cold-related deaths still increased among the ≥80, due to the increase in the population at risk. We estimated that heat- and cold-related deaths would have been 52.7% and 44.6% lower, respectively, in the most recent decade in the absence of population aging.

DISCUSSION

Our findings suggest that a substantial proportion of historical temperature-related impacts can be attributed to population aging. We found that population aging has attenuated the decrease in cold-related mortality and amplified heat-related mortality. https://doi.org/10.1289/EHP9835.

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.

Heat warnings, mortality, and hospital admissions among older adults in the United States

BACKGROUND

Heat warnings are issued in advance of forecast extreme heat events, yet little evidence is available regarding their effectiveness in reducing heat-related illness and death. We estimated the association of heat warnings and advisories (collectively, "alerts") issued by the United States National Weather Service with all-cause mortality and cause-specific hospitalizations among Medicare beneficiaries aged 65 years and older in 2,817 counties, 2006-2016.

METHODS

In each county, we compared days with heat alerts to days without heat alerts, matched on daily maximum heat index and month. We used conditional Poisson regression models stratified on county, adjusting for year, day of week, federal holidays, and lagged daily maximum heat index.

RESULTS

We identified a matched non-heat alert day for 92,029 heat alert days in 2,817 counties, or 54.6% of all heat alert days during the study period. Contrary to expectations, heat alerts were not associated with lower risk of mortality (RR: 1.005 [95% CI: 0.997, 1.013]). However, heat alerts were associated with higher risk of hospitalization for fluid and electrolyte disorders (RR: 1.040 [95% CI: 1.015, 1.065]) and heat stroke (RR: 1.094 [95% CI: 1.038, 1.152]). Results were similar in sensitivity analyses additionally adjusting for same-day heat index, ozone, and PM2.5.

CONCLUSIONS

Our results suggest that heat alerts are not associated with lower risk of mortality but may be associated with higher rates of hospitalization for fluid and electrolyte disorders and heat stroke, potentially suggesting that heat alerts lead more individuals to seek or access care.

A Satellite-Based Model for Estimating Latent Heat Flux From Urban Vegetation

The impacts of extreme heat events are amplified in cities due to unique urban thermal properties. Urban greenspace mitigates high temperatures through evapotranspiration and shading; however, quantification of vegetative cooling potential in cities is often limited to simple remote sensing greenness indices or sparse, in situ measurements. Here, we develop a spatially explicit, high-resolution model of urban latent heat flux from vegetation. The model iterates through three core equations that consider urban climatological and physiological characteristics, producing estimates of latent heat flux at 30-m spatial resolution and hourly temporal resolution. We find strong agreement between field observations and model estimates of latent heat flux across a range of ecosystem types, including cities. This model introduces a valuable tool to quantify the spatial heterogeneity of vegetation cooling benefits across the complex landscape of cities at an adequate resolution to inform policies addressing the effects of extreme heat events.

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

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

Ten questions concerning occupant health in buildings during normal operations and extreme events including the COVID-19 pandemic

Even before the COVID-19 pandemic, people spent on average around 90% of their time indoors. Now more than ever, with work-from-home orders in place, it is crucial that we radically rethink the design and operation of buildings. Indoor Environmental Quality (IEQ) directly affects the comfort and well-being of occupants. When IEQ is compromised, occupants are at increased risk for many diseases that are exacerbated by both social and economic forces. In the U.S. alone, the annual cost attributed to sick building syndrome in commercial workplaces is estimated to be between $10 billion to $70 billion. It is imperative to understand how parameters that drive IEQ can be designed properly and how buildings can be operated to provide ideal IEQ to safeguard health. While IEQ is a fertile area of scholarship, there is a pressing need for a systematic understanding of how IEQ factors impact occupant health. During extreme events, such as a global pandemic, designers, facility managers, and occupants need pragmatic guidance on reducing health risks in buildings. This paper answers ten questions that explore the effects of buildings on the health of occupants. The study establishes a foundation for future work and provides insights for new research directions and discoveries.

Dwelling Characteristics Influence Indoor Temperature and May Pose Health Threats in LMICs

Background:

Shelter and safe housing is a basic human need that brings about a sense of ownership, self-sufficiency, and citizenship. Millions of people around the world live in inadequate dwellings in unhealthy areas, such as urban slums. These dwellings may experience indoor temperatures that impact inhabitants’ health. Indoor dwelling temperatures vary depending on many factors including geographic location, such as inland versus coastal. In an era of climate change, understanding how dwelling characteristics influence indoor temperature is important, especially in low- and middle-income countries, to protect health.

Objective:

To assess indoor temperature in low-cost dwellings located in a coastal setting in relation to dwelling characteristics.

Methods:

Indoor temperature and relative humidity loggers were installed from 1 June 2017 to 15 May 2018 in 50 dwellings in two settlements in a coastal town on the east coast of South Africa. Ambient outdoor temperature data were obtained from the national weather service, indoor temperature data were converted into apparent temperature, and heat index calculations were made to consider possible heat-health risks. A household questionnaire and dwelling observation assessment were administered. A mixed-effects linear regression model was constructed to consider the impact of dwelling characteristics on indoor apparent temperature.

Findings:

Among 17 dwellings with all data sets, indoor temperatures were consistently higher than, and well correlated (r = 0.92) with outdoor temperatures. Average differences in indoor and outdoor temperatures were about 4°C, with statistically significant differences in percentage difference of indoor/outdoor between seasons (p < 0.001). Heat indices for indoor temperatures were exceeded mostly in summer, thereby posing possible health risks. Dwellings with cement floors were statistically significantly cooler than any other floor type across all seasons.

Conclusions:

Low-cost dwellings experienced temperatures indoors higher than outdoor temperatures in part due to floor type. These results help inform interventions that consider housing and human health (n = 289).

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 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.

Spatial patterns of recent US summertime heat trends: Implications for heat sensitivity and health adaptations

Heat is known to cause illness and death not only at extreme temperatures, but also at moderate levels. Although substantial research has shown how summer time temperature distributions have changed over recent decades in the United States, less is known about how the heat index-a potentially more health-applicable metric of heat-has similarly evolved over this period. Moreover, the extent to which these distributional changes have overlapped with indicators of social vulnerability has not been established, despite the applicability of co-varying climatic and sociodemographic characteristics to heat-related health adaptations. Presented here is an analysis of trends in the median, 95th percentile, and 'warm-tail spread' (i.e., intra-seasonal range between the upper extreme and median) of warm-season (May-September) maximum heat index between 1979and 2018 across the conterminous US. Using40 years of data from the North American Regional Reanalysis dataset, it is shown that most of the US has experienced statistically significant positive trends in summertime heat, and that both the magnitude of trends and the shape of the frequency distributions of these measures vary regionally. Comparisons with data from the Social Vulnerability Index show that the most socially vulnerable counties appear to be warming faster than the least vulnerable, but that opposite patterns hold for trends in warm-tail spread. These findings may be applicable to further studies on climate change, heat adaptations, and environmental justice in the US.

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.

A Preliminary Study of the Effect of Dousing and Foot Immersion on Cardiovascular and Thermal Responses to Extreme Heat

This study assesses the effects of self-dousing and foot immersion on heart rate, core temperature, and thermal discomfort of healthy volunteers randomized to simulated hot and humid vs nonhumid conditions.

A Preliminary Study of the Effect of Dousing and Foot Immersion on Cardiovascular and Thermal Responses to Extreme Heat

This study assesses the effects of self-dousing and foot immersion on heart rate, core temperature, and thermal discomfort of healthy volunteers randomized to simulated hot and humid vs nonhumid conditions.

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.

The range of normative surface skin temperature changes in adolescents: prospective multicenter study

AIM

We aimed to establish a normative range of surface skin temperature (SST) changes due to blood redistribution in adolescents and to register the time needed for complete postural change-related blood redistribution.

METHODS

The healthy volunteers (age 15-18, n = 500, M 217, F 283) were recruited for this prospective multicenter study. The volunteers were asked to keep one extremity down and another extremity up in supine rest, sitting with straight legs, and upright rest. We obtained temperature readings being taken from the tips of the middle fingers and temperature readings from the tips of the first toes at the ambient temperature of 25 °C and 30 °C. The control group consisted of a 100 of adult volunteers.

RESULTS

The resting temperature of the middle fingers for a sitting participant was 28.6 ± 0.8 °C. The physiological change of this temperature during body position changes was 4.5 ± 1.1 °C and for most of the participants remained within the 26.5-31.5 °C range at 25 °C. For the toe, physiological skin temperature range was 25.5-33 °C. At 30 °C, these ranges were 27-33 °C for the fingers and 27-34 °C for the toes. On average, 2-3 min were needed for such temperature changes.

CONCLUSION

At normal room temperature, the SST of thermoneutral adolescents may vary within a range of approximately 5 °C only due to the blood redistribution in the body. This range is specific for each person due to individual peculiarities of the vasomotor activity. This normative range of SSTs should be taken into account during investigations of thermoregulation.

Ambient temperature and preterm birth: A retrospective study of 32 million US singleton births

BACKGROUND

Days of extreme temperature may be associated with transiently higher risk of preterm birth, but prior studies have been limited and results have been heterogeneous.

OBJECTIVES

To evaluate the association between days of extreme heat and cold and risk of preterm birth among ~32 million live singleton births between 1989 and 2002 across 403 counties in the contiguous United States (US).

METHODS

We used a distributed lag nonlinear model to estimate the association between population-weighted daily mean temperature and risk of preterm birth in each county and then pooled results across geographic regions and climate zones. We defined extreme heat and cold as the 95th and 5th percentile of the county-specific temperatures, respectively.

RESULTS

Preterm birth accounted for 9.3% of deliveries. There was a monotonic association between ambient temperature and risk of preterm birth. Days of extreme heat and cold were associated with a relative risk of preterm birth of 1.025 (95% CI: 1.015, 1.036) and 0.985 (95% CI: 0.976, 0.993) over the subsequent four days, respectively, relative to the county-specific median temperature. If causal, the fraction of preterm births attributable to extreme heat was 0.17% (empirical 95% CI: 0.14%, 0.19%), corresponding to 154 (empirical 95% CI: 127, 173) preterm births per million births. Extreme heat was more strongly associated with preterm birth in regions with colder and drier climates, and among younger women. Days of extreme cold temperature were associated with lower rather than higher risk of preterm birth.

CONCLUSIONS

Days of extreme heat, but not extreme cold, are associated with higher risk of preterm birth in the contiguous US. If causal, these results may have important implications for the management of pregnant women during forecasted periods of extreme heat.

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.

Estimating policy-relevant health effects of ambient heat exposures using spatially contiguous reanalysis data

BACKGROUND

Regional National Weather Service (NWS) heat advisory criteria in New York State (NYS) were based on frequency of heat events estimated by sparse monitoring data. These may not accurately reflect temperatures at which specific health risks occur in large geographic regions. The objectives of the study were to use spatially resolved temperature data to characterize health risks related to summertime heat exposure and estimate the temperatures at which excessive risk of heat-related adverse health occurs in NYS. We also evaluated the need to adjust current heat advisory threshold and messaging based on threshold temperatures of multiple health outcomes.

METHODS

We assessed the effect of multi-day lag exposure for maximum near-surface air temperature (Tmax) and maximum Heat Index derived from the gridded National Land Data Assimilation System (NLDAS) reanalysis dataset on emergency department (ED) visits/ hospitalizations for heat stress, dehydration, acute kidney failure (AKF) and cardiovascular diseases (CVD) using a case-crossover analysis during summers of 2008-2012. We assessed effect modification using interaction terms and stratified analysis. Thresholds were estimated using piecewise spline regression.

RESULTS

We observed an increased risk of heat stress (Risk ratio (RR) = 1.366, 95% confidence interval (CI): 1.347, 1.386) and dehydration (RR = 1.024, 95% CI: 1.021, 1.028) for every 1 °C increase in Tmax on the day of exposure. The highest risk for AKF (RR = 1.017, 95% CI: 1.014, 1.021) and CVD (RR = 1.001, 95% CI: 1.000, 1.002) were at lag 1 and 4 respectively. The increased risk of heat-health effects persists up to 6 days. Rural areas of NYS are at as high a risk of heat-health effects as urban areas. Heat-health risks start increasing at temperatures much lower than the current NWS criteria.

CONCLUSION

Reanalysis data provide refined exposure-response functions for health research, in areas with sparse monitor observations. Based on this research, rural areas in NYS had similar risk for health effects of heat. Heat advisories in New York City (NYC) had been reviewed and lowered previously. As such, the current NWS heat advisory threshold was lowered for the upstate region of New York and surrounding areas. Enhanced outreach materials were also developed and disseminated to local health departments and the public.

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.

Assessment of extreme heat and hospitalizations to inform early warning systems

Heat early warning systems and action plans use temperature thresholds to trigger warnings and risk communication. In this study, we conduct multistate analyses, exploring associations between heat and all-cause and cause-specific hospitalizations, to inform the design and development of heat-health early warning systems. We used a two-stage analysis to estimate heat-health risk relationships between heat index and hospitalizations in 1,617 counties in the United States for 2003-2012. The first stage involved a county-level time series quasi-Poisson regression, using a distributed lag nonlinear model, to estimate heat-health associations. The second stage involved a multivariate random-effects meta-analysis to pool county-specific exposure-response associations across larger geographic scales, such as by state or climate region. Using results from this two-stage analysis, we identified heat index ranges that correspond with significant heat-attributable burden. We then compared those with the National Oceanic and Atmospheric Administration National Weather Service (NWS) heat alert criteria used during the same time period. Associations between heat index and cause-specific hospitalizations vary widely by geography and health outcome. Heat-attributable burden starts to occur at moderately hot heat index values, which in some regions are below the alert ranges used by the NWS during the study time period. Locally specific health evidence can beneficially inform and calibrate heat alert criteria. A synchronization of health findings with traditional weather forecasting efforts could be critical in the development of effective heat-health early warning systems.

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.

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.

Risks, Health Consequences, and Response Challenges for Small-Island-Based Populations: Observations From the 2017 Atlantic Hurricane Season

ABSTRACTThe intensely active 2017 Atlantic basin hurricane season provided an opportunity to examine how climate drivers, including warming oceans and rising seas, exacerbated tropical cyclone hazards. The season also highlighted the unique vulnerabilities of populations residing on Small Island Developing States (SIDS) to the catastrophic potential of these storms. During 2017, 22 of the 29 Caribbean SIDS were affected by at least one named storm, and multiple SIDS experienced extreme damage. This paper aims to review the multiplicity of storm impacts on Caribbean SIDS throughout the 2017 season, to explicate the influences of climate drivers on storm formation and intensity, to explore the propensity of SIDS to sustain severe damage and prolonged disruption of essential services, to document the spectrum of public health consequences, and to delineate the daunting hurdles that challenged emergency response and recovery operations for island-based, disaster-affected populations. (Disaster Med Public Health Preparedness. 2019;13:5-17).

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.