Heat-Related Mortality and Adaptation to Heat in the United States

1Heat exposure has been associated with adverse health outcomes, including higher rates of all-cause and cardiovascular mortality and emergency hospitalizations, across a range of study designs, and covering geographical regions worldwide. In the United States, extreme heat accounts for the largest cause of mortality due to severe weather, followed by hurricanes and tornadoes. Under climate change, higher average temperatures, increased summertime temperature variability, and more extreme heat events are anticipated to greatly exacerbate the health impacts of heat. However, several factors, referred to as adaptations, have the potential to reduce the extent of the impacts. Factors that may modify the population’s vulnerability to heat over time include both intrinsic biological factors, such as life stage and health status, and extrinsic factors encompassing environmental, social, and health system conditions.

2A major source of evidence on the mortality impacts of heat comes from multisite time-series studies. These studies typically estimate community-specific and national average acute heat-related mortality risks, defined as the association between day-to-day changes in summer temperature (heat exposure) and day-to-day changes in mortality, adjusted for other potential confounding factors (e.g., air pollution) that vary from day to day. These studies generally assume that heat-related mortality risk remains constant over the whole study period of several years.

3Far fewer studies have investigated how heat-related mortality might be changing slowly over time in the United States. These studies have provided some evidence that heat-related mortality risk has declined, but considerable uncertainty remains as to whether the decrease is continuing in more recent years and whether heat remains significantly associated with mortality in the present. Moreover, whether the rates of temporal change in heat-related mortality differ across communities and population subgroups and the particular factors that explain why different communities might exhibit different rates of temporal change have not been identified.

4We hypothesized that the strength of the association between acute heat exposure and mortality risk is continuing to change slowly over time due to adaptation, change in vulnerability, and susceptibility. We also hypothesized that the rate of this temporal change would vary both by individual-level factors (age, cause of death) and community-level factors (geographical region, climate). Finally, we hypothesized that cities with larger increases in air conditioning (AC) prevalence over time would have larger temporal declines in heat-related mortality risk. To gather evidence addressing these hypotheses, we extended the standard approach for analyzing multisite time-series data in order to allow the location-specific and national average heat-related mortality risks to vary smoothly over time, and we applied this methodology to estimate city-specific, regional, and national temporal trends in heat-related mortality risk in the United States using the most recently available national data on daily mortality, weather, and air pollution.

5Data. Time-series data covering 106 million people in 105 large U.S. urban communities (see Supplemental Material, Figure S1) were obtained as part of the National Morbidity and Mortality Air Pollution Study (NMMAPS). This database, which has been updated with data from 1987 to 2005, consists of parallel time series of daily weather variables from the, daily air pollution concentrations from the U.S. Environmental Protection Agency’s (EPA) Air Quality System, and counts of the number of daily deaths from the National Center for Health Statistics. Mortality counts exclude deaths due to external causes (e.g., accidents, suicides, homicides) and are stratified by age category (< 65, 65–74, and ≥ 75 years) and cause (cardiovascular, respiratory, other). A full description of NMMAPS, along with the derivation of geographical regions, has been previously reported. Data were restricted to the summer months: June, July, and August.

6AC prevalence data from alternate years during the period 1989–2005, obtained from the U.S. Census Bureau’s American Housing Survey (AHS), were available for 79 of the 105 NMMAPS cities. The AHS is a longitudinal survey of housing characteristics, collected from a representative sample of housing units by the U.S. Census Bureau, and results are publicly available. We estimated the change in AC prevalence over time as the slopes obtained from regressing AC prevalence on year separately within each city.

7Statistical analysis. To estimate temporal changes in the relative risk of short-term mortality associated with elevated summer temperatures, we used the two-stage methodology previously developed for NMMAPS. At the first stage, we specified a Poisson regression model of the number of daily deaths Yitg for age group g on day t in city i:

8log E(Yitg) = γi0 + βi(t)xit + γi1dowt + γi2agecatg + ns(t, 2 df/3 months; γi3), [1]

9where xit is the average daily temperature, dowt is a categorical variable for day of the week, agecatg is a categorical variable for age group (comparing 65–74 and ≥ 75 to < 65 year age groups), and ns(·) denotes natural cubic splines with the specified number of degrees of freedom (df) and knots at quantiles. The smooth function of calendar time ns(t, 2 df/3 months; γi3) accounts for within-summer seasonality and long-term trends; thus, the model accounts for slowly changing factors such as demographic changes to estimate acute mortality risk associated with the same day’s heat exposure, βi(t). We allowed each year to have a different coefficient on daily temperature xit, but constrained the change in the coefficient over time to be linear by modeling βi(t) as

10βi(t) = βi0 + βi1(yeart – 1987). [2]

11Combining models 1 and 2 yields a within-city model with an interaction term between temperature and year. Here βi0 is the city-specific log relative risk of mortality associated with a 1°F increase in the same day’s summer temperature in 1987 (the first year of the study period), and βi1 is the yearly change in the log relative risk. The number of excess deaths (per 1,000 deaths) attributable to each 10°F increase in temperature on summer day t was calculated as 1,000{exp[10βi(t)]–1}.

12In the second stage, we combined the city-level estimates for βi = (βi0, βi1) across locations to estimate the national average, time-varying risk of heat-related mortality using Bayesian hierarchical models. We assumed

13β̂i |βi ~ N(βi, V̂i); independent, i = 1,…, I [3]

14βi ~ N(β*, Σ), [4]

15where β̂i are the estimated coefficients for the ith city, βi are the true city-level coefficients, V̂i is the estimated variance of β̂i, β* are the national average coefficients, and Σ is the across-cities variance of the true city-specific coefficients. Noninformative priors were placed on β* and Σ, and an independent sampling procedure was used for posterior inference.

16To estimate separate temporal trends by age group and cause of death, model 1 was expanded to include interaction terms of each variable with indicator variables for age group and mortality subtype. Regional estimates of temporal changes were obtained by expanding model 4 to include indicator variables for each U.S. region. We investigated potential effect modification by average temperature by expanding model 4 to include the city-level average of daily temperatures over the study period, and effect modification by central AC prevalence by expanding model 4 to include the city-level change in prevalence over the study period.

17Parameter estimates from the Bayesian hierarchical models (i.e., of the regional and national temporal trends, of the differences in temporal trends across age groups and regions, and of effect modification), were deemed “statistically significant” if 95% posterior credible intervals (PI) excluded zero. We conducted extensive sensitivity analyses for the model specification, which are described in the Supplemental Material.

18Figure 1 shows the change, from 1987 to 2005, in heat-related mortality risk, defined as the number of excess deaths, per 1,000 deaths, attributable to each 10°F increase in the same day’s summer temperature. Nationally, the number of excess heat-related deaths (per 1,000 deaths) declined from 51 (95% PI: 42, 61) in 1987 to 19 (95% PI: 12, 27) in 2005, for a total reduction in risk of 32 (95% PI: 18, 45) deaths, per 1,000 deaths (left-most point of Figure 1). Heat-related mortality risk decreased over the study period in 74 of the 105 cities (corresponding to the negative point estimates of change in risks in Figure 1), and for 18 of these cities the temporal decline was statistically significant. The national average temporal trend remained negative and statistically significant across different specifications of the statistical model, with larger temporal declines in the estimated risk based on a nonlinear temperature–mortality exposure–response function and under larger temperature lags (see Supplemental Material, Figure S2A). Allowing for a more flexible time-varying coefficient model (i.e., relaxing the linearity assumption) suggested that the rate of temporal change in the national trend may be slowing for years past 2000 (see Supplemental Material, Figure S2B).

19We next sought to identify whether the temporal trends varied by age group and cause of death (Figure 2B,C; see also corresponding numerical results in Supplemental Material, Table S1). Nationally, heat-related mortality risk declined for each age group, with the 65–74 and ≥ 75 year groups exhibiting a similar change over time (the oldest group had higher baseline risk in 1987), and the < 65-years age group exhibiting only a small, nonstatistically significant, decrease over time. Although the heat-related mortality risk for the ≥ 75-years age group was greater than for the < 65-years age group at the beginning of the study period, by 2005 they had converged to similar levels. Heat-related mortality risk declined for each cause of death, and the decline was statistically significant for cardiovascular and respiratory deaths. The largest rate of decline occurred for respiratory mortality, although respiratory deaths contribute less to total mortality (of the approximately 13.5 million deaths covered by our study, 8.7% were due to respiratory causes compared with 42.7% from cardiovascular causes).

20Because the risk of heat-related mortality varies across geographical regions, we posited that the temporal trends would reflect similar heterogeneity. Across regions, risks declined most in the Northeast, Northwest, and Industrial Midwest, followed by the Southeast (Figure 2D; see also Supplemental Material, Table S1). For one region (Southern California) we estimated an increase in risk over the study period, but the estimate was not statistically significant.

21Even with the decline in risk over time, heat remained associated with excess mortality through 2005 in all regions, and the association was statistically significant in the Northeast, Northwest, and Southern California regions. Allowing for separate regional trends by age group, we found that among the four regions with statistically significant temporal trends, the temporal decline in risk was driven by the decline among the ≥ 75-years age group (see Supplemental Material, Table S1). Next, having found that the largest declines occurred mostly in the northern regions, we investigated whether climate in particular modified the change in heat-related mortality risk over time. We found statistically significant effect modification, with cities with cooler climates having larger temporal declines in risk than cities with warmer climates, although these cities also generally had larger risks of heat-related mortality at the beginning of the study period (Figure 3; see also Supplemental Material, Table S2).

22One factor that has been proposed as a major contributor to reductions in heat-related mortality over time is AC use. Over our study period, central AC prevalence, defined as the percentage of homes with central AC, increased in all 79 cities with available AC data (see Supplemental Material, Figure S3). On average across cities, central AC prevalence was 48% at the beginning of the study period and increased by approximately 1% each year. Cities with larger increases in central AC prevalence over the study period tended to have slightly larger reductions in heat-related mortality risk over time, but the association was not statistically significant (Figure 4; see also Supplemental Material, Table S2). We found similar and nonstatistically significant effect modification when we considered a broader definition of AC prevalence that also included homes with window units, and also when we restricted the analysis to the 49 cities having baseline (1989) AC prevalence < 64% (which is equal to 100% minus the maximum change in AC prevalence over the study period) to account for the possibility that cities with high AC prevalence at baseline may have reached market saturation.

23This study provides strong evidence that acute (e.g., same-day) heat-related mortality risk has declined over time in the United States, even in more recent years. This evidence complements findings from U.S. studies using earlier data from the 1960s through the mid-1990s on community-specific mortality rates, as well as European studies that found temporal declines in heat-related mortality risk, and supports the hypothesis that the population is continually adapting to heat.

24Although the mortality impact of heat has declined, we found that statistically significant risks of heat-related mortality remain through 2005. Moreover, with the increase in average summertime temperature, and the greater frequency, duration, and intensity of extreme heat events due to climate change, even these lower mortality risks attributable to heat will likely continue to contribute to a large burden of adverse health effects across the population. For example, based on the most recent (2005) estimates of heat-related mortality risk, an increase in average daily temperature by 5°F [a central value across U.S. climate projections] would lead to an additional 1,907 deaths per summer across all cities in our study population (see Supplemental Material, Table S3). This would exceed the total number of severe weather fatalities that occurred across the United States in 2012 by more than a factor of three. Thus, even with the recent adaptation trends, there is continued potential for further gains in mitigating excess heat-related deaths in a changing climate.

25To gain insight into the potential for differential adaptation by location and population subgroup, we investigated variation in the temporal trends in heat-related mortality risk across age categories and geographical regions. Rates of decline differed by age group, with the temporal trends both nationally and regionally being driven by declining risks among the older (≥ 75 years of age) population. Northern regions exhibited the largest declines in risk, and, in particular, cities with cooler climates tended to have larger temporal declines in heat-related mortality risk than cities with hotter climates. However, cities with cooler climates also exhibited higher risks at the beginning of the study period, suggesting that these communities may be “catching up” to communities in hotter climates that had already adapted to some extent before our study period.

26To gain insight into the mechanisms of adaptation, we investigated whether the temporal decline in heat-related mortality risk could be attributed to the increasing prevalence of central AC over time. We focused on AC as a potential adaptation, because this factor has been widely hypothesized as a major contributor to reducing the adverse health impacts of heat. We evaluated the degree to which variation across cities in the temporal trends in heat-related mortality risk could be explained by increases in central AC prevalence, finding that declining risks from 1987 to 2005 could not be solely attributed to expanded AC prevalence during that period. One possible explanation is that, because the cost of running AC on high heat days can be prohibitive for some households, higher AC prevalence does not automatically imply higher usage. Also, without AC data for population subgroups, we could not directly evaluate whether groups that are more susceptible to heat (e.g., the elderly) may have experienced different trends in AC prevalence.

27Disentangling the set of factors that have contributed to declining heat-related mortality is challenging in part because of limited data availability (e.g., lack of AC usage data or even AC prevalence data for all years and cities) and in part because many potential adaptive factors are changing slowly over time and lack sufficient year-to-year variability. Cardiovascular deaths comprise a substantial portion of heat-related mortality, and incidence of myocardial infarction and subsequent cardiovascular mortality has decreased in recent decades. Consequently, the decline in risk of heat-related mortality may reflect the general decline in risk factors (e.g., smoking, cholesterol levels) and well-established improvements for the treatment of cardiovascular disease that have driven declines in adverse cardiovascular outcomes. Interventions specific to reduce short-term heat exposure may have also played a role. For example, extensive heat–health warning systems and public health response programs have been implemented in several U.S. cities, including Philadelphia, Pennsylvania, (introduced in 1995) and Phoenix, Arizona, (in 2002). These programs often contain specific measures targeted toward the elderly population, which could be one reason why heat-related mortality declined most rapidly for the oldest age group. The reduction in heat-related mortality could also reflect a shift from mortality to morbidity, whereby some individuals are admitted to the hospital rather than dying from heat exposure. Other possible factors include changes in activity patterns (e.g., less time spent outside), changes in the built environment (e.g., more green spaces), physiological adaptations, and greater awareness of the dangers of extreme heat.

28Our findings have important implications for studies assessing the future health impacts of heat in a changing climate. Projections of future heat-related mortality rely on numerous factors that exhibit a wide range of uncertainty, including future greenhouse gas emissions, global and regional climate models, population growth, statistical models for estimating the health effects, the degree to which baseline levels of morbidity and mortality will change over time, and the degree to which individuals and communities will adapt to changes in the distribution of heat. Most studies have used central estimates of the risks of heat averaged over an historical study period as the basis for future projections, which implicitly assumes no change in risk over time. By failing to account for the temporal decline in risk, these studies may overestimate mortality impacts of future heat, especially if the observed trends continue. Furthermore, if health impacts studies ignore differences across age groups in the temporal trends, they may not accurately characterize future vulnerability to heat, especially given anticipated changes in the population’s age structure over the course of the century. The age-group–specific estimates of the changes in risk over time presented here may be combined with projections of future population demographics in order to more accurately project future heat-related mortality under climate change.

29This work also has implications for developing targeted interventions aimed at strengthening the population’s capacity to adapt to heat. We found that mortality risks in the eldest (≥ 75 years) age group differed from the youngest (< 65 years) at baseline but were statistically indistinguishable by the end of the study period. This suggests that although the elderly have historically been more susceptible to extreme heat, interventions that are more broadly targeted to reduce vulnerability to heat over the lifespan should be considered moving forward. In addition, our finding that the decline in risk of heat-related mortality from 1987 to 2005 could not be fully attributed to increased central AC prevalence over the study period suggests that a range of other factors (e.g., declining cardiovascular mortality rates) likely explain the decline. Evidence of declining heat risks in locations in northern Europe where AC prevalence remains much lower than in the United States, also supports the causal role of other factors. Thus, sole emphasis on expanding AC prevalence as a mechanism to reduce future heat-related mortality is likely to miss key opportunities for adapting to and mitigating the effects of heat, especially if AC has already reached market saturation in certain areas. Furthermore, more sustainable adaptations, such as passive cooling systems, may be preferred over widespread adoption of AC, with its high energy requirements and contribution to poor air quality and climate change.

30Several limitations in the data should be acknowledged. First, the aggregation of mortality data into broad age categories precludes finer information on temporal trends in younger adults or children. As such, we were unable to detect whether risks among potentially vulnerable younger populations (e.g., outdoor workers, high-school athletes), may also be changing over time. In addition, because we considered data from only urban and suburban areas, our results may not be applicable to rural communities with different demographic, socioeconomic, or housing characteristics.

31We focused on acute heat exposure (same-day or few-days lag), rather than on heat waves (consecutive days of high temperatures). Temporal trends in heat wave mortality risk could be estimated similarly, by specifying a time-varying coefficient on the heat wave indicator variable. Our temporal trend estimates also did not account for the potential for short-term mortality displacement, which could occur if heat exposure causes deaths that otherwise would have occurred just a few days later in the absence of the exposure. Evidence on the contribution of mortality displacement to estimates of heat-related mortality is mixed and appears to vary based on population characteristics and other factors. Moreover, although the implication of mortality displacement on heat-related mortality risk estimates would be attenuation, its possible effects on the corresponding temporal trend estimates is less clear and warrants further study. Finally, although this study focused on heat, changing vulnerability to cold temperatures could be investigated using similar methods because climate change may also mitigate cold-related mortality.

32We have proposed a framework to study adaptation by leveraging information on the temporal trends in acute heat-related mortality risk to gain insight into which communities and subpopulations are adapting to heat, as well as into the mechanisms by which adaptation may be occurring. Our methodology to assess the role of expanded AC prevalence in reducing the risk of heat-related mortality could be applied to evaluate any potential adaptive strategy. Previously, the main way potential adaptive factors had been identified was to investigate whether differences across communities in a particular factor were associated with differences in heat risks. One challenge of that approach is that numerous factors differ across communities that could confound any results. Because the approach we propose here examines how changes in potential adaptive factors over time are associated with temporal changes in the heat risks, our approach is less prone to confounding by factors that remain constant (or nearly constant) over the period of study. Future studies could apply this methodology to systematically identify the drivers of declining heat-related health impacts, thereby informing the development of targeted interventions to mitigate the effects of heat in a changing climate.