2

Temperature-Related Death and Illness

2.1 Introduction

  • Marcus C. Sarofim
    U.S. Environmental Protection Agency
  • Shubhayu Saha
    Centers for Disease Control and Prevention
  • Michelle D. Hawkins
    National Oceanic and Atmospheric Administration
  • David M. Mills
    Abt Associates, Inc.
  • Jeremy Hess
    University of Washington Seattle
  • Radley Horton
    Columbia University
  • Patrick L. Kinney
    Columbia University
  • Joel D. Schwartz
    Harvard University
  • Alexis St. Juliana
    Abt Associates, Inc.

The Earth is warming due to elevated concentrations of greenhouse gases, and will continue to warm in the future. U.S. average temperatures have increased by 1.3°F to 1.9°F since record keeping began in 1895, heat waves have become more frequent and intense, and cold waves have become less frequent across the nation (see Ch. 1: Introduction). Annual average U.S. temperatures are projected to increase by 3°F to 10°F by the end of this century, depending on future emissions of greenhouse gases and other factors.1 These temperature changes will have direct effects on human health.

Days that are hotter than the average seasonal temperature in the summer or colder than the average seasonal temperature in the winter cause increased levels of illness and death by compromising the body’s ability to regulate its temperature or by inducing direct or indirect health complications. Figure 2.1 provides a conceptual model of the various climate drivers, social factors, and environmental and institutional factors that can interact to result in changes in illness and deaths as a result of extreme heat. Increasing concentrations of greenhouse gases lead to an increase of both average and extreme temperatures, leading to an increase in deaths and illness from heat and a potential decrease in deaths from cold. Challenges involved in determining the temperature–death relationship include a lack of consistent diagnoses on death certificates and the fact that the health implications of extreme temperatures are not absolute, differing from location to location and changing over time. Both of these issues can be partially addressed through the use of statistical methods. Climate model projections of future temperatures can be combined with the estimated relationships between temperatures and health in order to assess how deaths and illnesses resulting from temperature could change in the future. The impact of a warming climate on deaths and illnesses will not be realized equally as a number of populations, such as children, the elderly, and economically disadvantaged groups, are especially vulnerable to temperature.

 

Figure 2.1: Climate Change and Health—Extreme Heat

Figure 2.1: Climate Change and Health—Extreme Heat
This conceptual diagram illustrates the key pathways by which climate change influences human health during an extreme heat event, and potential resulting health outcomes (center boxes). These exposure pathways exist within the context of other factors that positively or negatively influence health outcomes (gray side boxes). Key factors that influence vulnerability for individuals are shown in the right box, and include social determinants of health and behavioral choices. Key factors that influence vulnerability at larger scales, such as natural and built environments, governance and management, and institutions, are shown in the left box. All of these influencing factors can affect an individual’s or a community’s vulnerability through changes in exposure, sensitivity, and adaptive capacity and may also be affected by climate change. See Chapter 1: Introduction for more information.

2.2 Contribution of Extreme Temperatures to Death and Illness

Temperature extremes most directly affect health by compromising the body’s ability to regulate its internal temperature. Loss of internal temperature control can result in a cascade of illnesses, including heat cramps, heat exhaustion, heatstroke, and hyperthermia in the presence of extreme heat, and hypothermia and frostbite in the presence of extreme cold. Temperature extremes can also worsen chronic conditions such as cardiovascular disease, respiratory disease, cerebrovascular disease, and diabetes-related conditions. Prolonged exposure to high temperatures is associated with increased hospital admissions for cardiovascular, kidney, and respiratory disorders. Exposures to high minimum temperatures may also reduce the ability of the human body to recover from high daily maximum temperatures.


2.3 Defining Temperature Exposures

Extreme temperatures are typically defined by some measure, for example, an ambient temperature, heat index (a combination of temperature and humidity), or wind chill (a combination of temperature and wind speed), exceeding predefined thresholds over a number of days.2,3,4,5,6,7,8 Extremes can be defined by average, minimum, or maximum daily temperatures, by nighttime temperatures, or by daytime temperatures. However, there is no standard method for defining a heat wave or cold wave. There are dramatic differences in the observed relationships between temperature, death, and illness across different regions and seasons; these relationships vary based on average temperatures in those locations and the timing of the heat or cold event. For example, a 95°F day in Vermont will have different implications for health than a 95°F day in Texas, and similarly, a 95°F day in May will have different implications than one in August9,10,11,12 (this is further discussed in Section 2.5.2). Therefore, in some cases, temperature extremes are defined by comparison to some local average (for example, the top 1% of warmest days recorded in a particular location) rather than to some absolute temperature (such as 95°F). While temperature extremes are generally determined based on weather station records, the exposure of individuals will depend on their location: urban heat islands, microclimates, and differences between indoor and outdoor temperatures can all lead to differences between weather station data and actual exposure. The indoor environment is particularly important as most people spend the majority of their time inside.

One exception to using relative measures of temperature is that there are some critical physical and weather condition thresholds that are absolute. For example, one combined measure of humidity and temperature is known as the wet bulb temperature. As the wet bulb temperature reaches or exceeds the threshold of 35°C (95°F), the human body can no longer cool through perspiration, and recent evidence suggest that there is a physical heat tolerance limit in humans to sustained temperatures above 35°C that is similar across diverse climates.13 The combined effects of temperature and humidity have been incorporated in tools such as heat index tables, which reflect how combinations of heat and relative humidity “feel.” The heat index in these tools is often presented with notes about the potential nature and type of health risks different combinations of temperature and humidity may pose, along with confounding conditions such as exposure to direct sunlight or strong winds. 

Variations in heat wave definitions make it challenging to compare results across studies or determine the most appropriate public health warning systems.8,14 This is important as the associations between deaths and illnesses and extreme heat conditions vary depending on the methods used for defining the extreme conditions.2,15,16


2.4 Measuring the Health Impact of Temperature

Two broad approaches are used to study the relationship between temperatures and illness and death: direct attribution and statistical methods.17,18

Direct Attribution Studies

With direct attribution, researchers link health outcomes to temperatures based on assigned diagnosis codes in medical records such as hospital admissions and death certificates. For example, the International Classification of Diseases (ICD-10) contains specific codes for attributing deaths to exposure to excessive natural heat (X30) and excessive natural cold (X31).19 However, medical records will not include information on the weather conditions at the time of the event or preceding the event. It is generally accepted that direct attribution underestimates the number of people who die from temperature extremes. Reasons for this include difficulties in diagnosing heat-related and cold-related deaths, lack of consistent diagnostic criteria, and difficulty in identifying, or lack of reporting, heat or cold as a factor that worsened a preexisting medical condition.9,17 Heat-related deaths are often not reported as such if another cause of death exists and there is no well-publicized heat wave. An additional challenging factor in deaths classified as X31 (cold) deaths is that a number of these deaths result from situations involving substance use/abuse and/or contact with water, both of which can contribute to hypothermia.20,21  

Statistical Studies

Statistical studies measure the impact of temperature on death and illness using methods that relate the number of cases (for example, total daily deaths in a city) to observed weather conditions and other socio-demographic factors. These statistical methods determine whether the temperature conditions were associated with increased deaths or illness above longer-term average levels. These associations establish the relationship between temperature and premature deaths and illness. In some cases, particularly with extreme temperature conditions, the increase in premature deaths and illness can be quite dramatic and the health impact may be referred to in terms of excess deaths or illnesses. Methods for evaluating the impact of temperature in these models vary.

Many studies include all the days in the study period, which makes it possible to capture changes in deaths resulting from small variations of temperatures from their seasonal averages. Other methods restrict the analysis to days that exceed some threshold for extreme heat or cold conditions.22 Some studies incorporate methods that determine different health relationships for wind, air pressure, and cloud cover as well as the more common temperature and humidity measures.15 Another approach is to identify a heat event and compare observed illness and deaths during the event with a carefully chosen comparison period.23,24,25 Many of these methods also incorporate socio-demographic factors (for example, age, race, and poverty) that may affect the temperature–death relationship.

Comparing Results of Direct Attribution and Statistical Studies

Comparing death estimates across studies is therefore complicated by the use of different criteria for temperature extremes, different analytical methods, varying time periods, and different affected populations. Further, it is widely accepted that characteristics of extreme temperature events such as duration, intensity, and timing in season directly affect actual death totals.2,12 Estimates of the average number of deaths attributable to heat and cold considering all temperatures, rather than just those associated with extreme events, provide an alternative for considering the mortality impact of climate change.26,27 Statistical studies can also offer insights into what aspects of a temperature extreme are most important. For example, there are indications that the relationship between high nighttime temperatures and mortality is more pronounced than the relationship for daytime temperatures.12,16

These two methods (direct attribution and statistical approaches) yield very different results for several reasons. First, statistical approaches generally suggest that the actual number of deaths associated with temperature is far greater than those recorded as temperature-related in medical records. Medical records often do not capture the role of heat in exacerbating the cause of death, only recording the ultimate cause, such as a stroke or a heart attack (see, for example, Figure 2.2, where the excess deaths during the 1995 Chicago heat wave clearly exceeded the number of deaths recorded as heat-related on death certificates). Statistical methods focus on determining how temperature contributes to premature deaths and illness and therefore are not susceptible to this kind of undercount, though they face potential biases due to time-varying factors like seasonality. Both methods depend on temperatures measured at weather stations, though the actual temperature exposure of individuals may differ. In short, while the focus on temperature is consistent in both methods, the methods potentially evaluate very different combinations of deaths and weather conditions.


2.5 Observed Impact of Temperature on Deaths

A number of extreme temperature events in the United States have led to dramatic increases in deaths, including events in Kansas City and St. Louis in 1980, Philadelphia in 1993, Chicago in 1995, and California in 2006. (See Figure 2.2 for more on the July 1995 heat wave in Chicago).28,29,30,31,32

Recent U.S. studies in specific communities and for specific extreme temperature events continue to conclude that extreme temperatures, particularly extreme heat, result in premature deaths.7,30,33,34 This finding is further reinforced by a growing suite of regional- and national-scale studies documenting an increase in deaths following extreme temperature conditions, using both direct attribution17 and statistical approaches.9,10,12,15,35 The connection between heat events and deaths is also evident internationally. The European heat wave of 2003 is an especially notable example, as it is estimated to have been responsible for between 30,000 and 70,000 premature deaths.36 However, statistical approaches find that elevated death rates are seen even for less extreme temperatures. These approaches find an optimal temperature, and show that there are more deaths at any temperatures that are higher or lower than that optimal temperature.11,37 Even though the increase in deaths per degree are smaller near the optimum than at more extreme temperatures, because the percentage of days that do not qualify as extreme are large,38 it can be important to address the changes in deaths that occur for these smaller temperature differences.  

A recent analysis of U.S. deaths from temperature extremes based on death records found an average of approximately 1,300 deaths per year from 2006 to 2010 coded as resulting from extreme cold exposures, and 670 deaths per year coded as resulting from exposure to extreme heat.17 These results, and those from all similar studies that rely solely on coding within medical records to determine cause of deaths, will underestimate the actual number of deaths due to extreme temperatures.17,39 For example, some statistical approaches estimate that more than 1,300 deaths per year in the United States are due to extreme heat.15,40 Different approaches to attributing cause of death lead to differences in the relative number of deaths attributed to heat and cold.41 Studies based on statistical approaches have found that, despite a larger number of deaths being coded as related to extreme cold rather than extreme heat, and a larger mortality rate in winter overall, the relationship between mortality and an additional day of extreme heat is generally much larger than the relationship between mortality and an additional day of extreme cold.12

Confounding Factors and Effect Modifiers 

While the direct attribution approach underestimates the number of deaths resulting from extreme temperature events, there are a few ways in which the statistical approach may lead to an overestimation. However, any overestimation due to these potential confounding factors and effect modifiers is thought to be much smaller than the direct attribution underestimation.12

The first potential overestimation results from the connection between elevated temperatures and other variables that correlate with temperature, such as poor air quality. This connection involves a combination of factors, including stagnant air masses and changes in the atmospheric chemistry that affect the concentrations of air pollutants such as ozone or particulate matter (see Ch. 3: Air Quality Impacts). If some portion of the deaths during extreme heat events are actually a result of the higher levels of atmospheric pollution that are correlated with these events, then including those deaths in a statistical analysis to determine the relationship of increased heat on human health would result in double counting deaths.10,42,43,44 However, this issue is often addressed by including air pollution and other correlated variables in statistical modeling.26

Snowstorm

The relationship between mortality and an additional day of extreme heat is generally much larger than the relationship between mortality and an additional day of extreme cold.

A second consideration when using statistical approaches to determine the relationship between temperature and deaths is whether some of the individuals who died during the temperature event were already near death, and therefore the temperature event could be considered to have “displaced” the death by a matter of days rather than having killed a person not otherwise expected to die. This effect is referred to as mortality displacement. There is still no consensus regarding the influence of mortality displacement on premature death estimates, but this effect generally accounts for a smaller portion of premature deaths as events become more extreme.7,12,45,46,47

Evidence of Adaptation to Temperature Extremes 

The impact on human health of a given temperature event (for example, a 95°F day) can depend on where and when it occurs. The evidence also shows larger changes in deaths and hospitalizations in response to elevated temperatures in cities where temperatures are typically cooler as compared with warmer cities.9,11,37,48,49 This suggests that people can adapt, at least partially, to the average temperature that they are used to experiencing. Some of this effect can be explained by differences in infrastructure. For example, locations with higher average temperature, such as the Southeast, will generally have greater prevalence and use of air conditioning. However, there is also evidence that there is a physiological acclimatization (the ability to gradually adapt to heat), with changes in sweat volume and timing, blood flow and heat transfer to the skin, and kidney function and water conservation occurring over the course of weeks to months of exposure to a hot climate.50 For example, as a result of this type of adaptation, heat events later in the summer have less of an impact on deaths than those earlier in the summer, all else being equal,15 although some of  this effect is also due to the deaths of some of the most vulnerable earlier in the season. However, children and older adults remain vulnerable given their reduced ability to regulate their internal temperature and limited acclimatization capacities.50

An increased tolerance to extreme temperatures has also been observed over multiyear and multidecadal periods.9,10,51,52,53 This improvement is likely due to some combination of physiological acclimatization, increased prevalence and use of air conditioning,10 and general improvements in public health over time,9,51 but the relative importance of each is not yet clear.53

Recent changes in urban planning and development programs reflect an adaptive trend implemented partially in response to the anticipated temperature health risks of climate change. For example, because urban areas tend to be warmer than surrounding rural areas (the “urban heat island” effect), there is an increased emphasis on incorporating green space and other technologies, such as cool roofs, in new development or redevelopment projects.54 Similarly, programs that provide advice and services in preparation for or response to extreme temperatures continue to increase in number and expand the scope of their activity (see for example guidance documents on responses to extreme temperature developed by the Centers for Disease Control and Prevention and the Environmental Protection Agency).55,56 Continued changes in personal behavior as a result of these efforts, for example, seeking access to air-conditioned areas during extreme heat events or limiting outside activity, may continue to change future exposure to extreme temperatures and other climate-sensitive health stressors, such as outdoor air pollutants and vectors for disease such as ticks or mosquitoes.

Observed Trends in Heat Deaths

As discussed in Chapter 1, U.S. average temperature has increased by 1.3°F to 1.9°F since 1895, with much of that increase occurring since 1970, though this temperature increase has not been uniform geographically and some regions, such as the Southeast, have seen little increase in temperature and extreme heat over time.1,15 This warming is attributable to elevated concentrations of greenhouse gases and it has been estimated that three-quarters of moderately hot extremes are already a result of this historical warming.57 As discussed in the previous section, there have also been changes in the tolerance of populations within the United States to extreme temperatures. Changes in mortality due to high temperatures are therefore a result of the combination of higher temperatures and higher heat tolerance. Use of the direct attribution approach, based on diagnosis codes in medical records, to examine national trends in heat mortality over time is challenging because of changes in classification methods over time.58 The few studies using statistical methods that have presented total mortality estimates over time suggest that, over the last several decades, reductions in mortality due to increases in tolerance have outweighed increases in mortality due to increased temperatures.15,59


2.6 Observed Impact of Temperature on Illness

Temperature extremes are linked to a range of illnesses reported at emergency rooms and hospitals. However, estimates for the national burden of illness associated with extreme temperatures are limited.

Using a direct attribution approach, an analysis of a nationally representative database from the Healthcare Utilization Project (HCUP) produced an annual average estimate of 65,299 emergency visits for acute heat illness during the summer months (May through September)—an average rate of 21.5 visits for every 100,000 people each year.62 This result was based only on recorded diagnosis codes for hyperthermia and probably underestimates the true number of heat-related healthcare visits, as a wider range of health outcomes is potentially affected by extreme heat. For example, hyperthermia is not the only complication from extreme heat, and not every individual that suffers from a heat illness visits an emergency department. In a national study of Medicare patients from 2004 to 2005, an annual average of 5,004 hyperthermia cases and 4,381 hypothermia cases were reported for inpatient and outpatient visits.63 None of these studies link health episodes to observed temperature data, thus limiting the opportunity to attribute these adverse outcomes to specific heat events or conditions.

High ambient heat has been associated with adverse impacts for a wide range of illnesses.25 Examples of illnesses associated with extreme heat include cardiovascular, respiratory, and renal illnesses; diabetes; hyperthermia; mental health issues; and preterm births. Children spend more time outdoors and have insufficient ability for physiologic adaptation, and thus may be particularly vulnerable during heat waves.64 Respiratory illness among the elderly population was most commonly reported during extreme heat.65

Statistical studies examine the association between extreme heat and illness using data from various healthcare access points (such as hospital admissions, emergency department visits, and ambulance dispatches). The majority of these studies examine the association of extreme heat with cardiovascular and respiratory illnesses. For these particular health outcomes, the evidence is mixed, as many studies observed elevated risks of illness during periods of extreme heat but others found no evidence of elevated levels of illness.24,48,66,67,68,69,70 The evidence on some of the other health outcomes is more robust. Across emergency department visits and hospital admissions, high temperature have been associated with renal diseases, electrolyte imbalance, and hyperthermia.24,67,71,72 These health risks vary not only across types of illness but also for the same illness across different healthcare settings. In general, evidence for associations with morbidity outcomes, other than cardiovascular impacts, is strong.

While there is still uncertainty about how levels of heat-related illnesses are expected to change with projected increases in summer temperature from climate change,38 advances have been made in surveillance of heat-related illness. For example, monitoring of emergency ambulance calls during heat waves can be used to establish real-time surveillance systems to identify extreme heat events.73 The increase in emergency visits for a wide range of illnesses during the 2006 heat wave in California points to the potential for using this type of information in real-time health surveillance systems.24


2.7 Projected Deaths and Illness from Temperature Exposure

Climate change will increase the frequency and severity of future extreme heat events while also resulting in generally warmer summers and milder winters,1 with implications for human health. Absent further adaptation, these changes are expected to lead to an increase in illness and death from increases in heat, and reductions in illness and death resulting from decreases in cold, due to changes in outcomes such as heat stroke, cardiovascular disease, respiratory disease, cerebrovascular disease, and kidney disorders.38,74

A warmer future is projected to lead to increases in future mortality on the order of thousands to tens of thousands of additional premature deaths per year across the United States by the end of this century.22,35,51,75,76,77,78,79 Studies differ in which regions of the United States are examined and in how they account for factors such as adaptation, mortality displacement, demographic changes, definitions of heat waves and extreme cold, and air quality factors, and some studies examine only extreme events while others take into account the health effects of smaller deviations from average seasonal temperatures. Despite these differences there is reasonable agreement on the magnitude of the projected changes. Additionally, studies have projected an increase in premature deaths due to increases in temperature for Chicago, IL,36,80 Dallas, TX,18 the Northeast corridor cities of Boston, MA, New York, NY, and Philadelphia, PA,18,26,81,82 Washington State,83,84 California,85 or a group of cities including Portland, OR; Minneapolis and St. Paul, MN; Chicago, IL; Detroit, MI; Toledo, Cleveland, Columbus, and Cincinnati, OH; Pittsburgh and Philadelphia, PA; and Washington, DC.86 However, these regional projections use a variety of modeling strategies and therefore show more variability in mortality estimates than studies that are national in scope.

Less is known about how non-fatal illnesses will change in response to projected increases in heat. However, hospital admissions related to respiratory, hormonal, urinary, genital, and renal problems are generally projected to increase.72,87 Kidney stone prevalence has been linked to high temperatures, possibly due to dehydration leading to concentration of the salts that form kidney stones. In the United States, an increased rate of kidney stones is observed in southern regions of the country, especially the Southeast. An expansion of the regions where the risk of kidney stones is higher is therefore plausible in a warmer future.88,89,90 

The decrease in deaths and illness due to reductions in winter cold have not been as well studied as the health impacts of increased heat, but the reduction in premature deaths from cold are expected to be smaller than the increase in deaths from heat in the United States.22,26,35,38,75,77 While this is true nationally (with the exception of Barreca 2012),75 it may not hold for all regions within the country.27 Similarly, international studies have generally projected a net increase in deaths from a warming climate, though in some regions, decreases in cold mortality may outweigh increases in heat mortality.91 The projected net increase in deaths is based in part on historical studies that show that an additional extreme hot day leads to more deaths than an additional extreme cold day, and in part on the fact that the decrease in extreme cold deaths is limited as the total number of cold deaths approaches zero in a given location.

It is important to distinguish between generally higher wintertime mortality rates that are not strongly associated with daily temperatures—such as respiratory infections and some cardiovascular disease 12,92—from mortality that is more directly related to the magnitude of the cold temperatures. Some recent studies have suggested that factors leading to higher wintertime mortality rates may not be sensitive to climate warming, and that deaths due to these factors are expected to occur with or without climate change. Considering this, some estimates of wintertime mortality may overstate the benefit of climate change in reducing wintertime deaths.46,93,94

The U.S. population has become less sensitive to heat over time. Factors that have contributed to this change include infrastructure improvements, including increased access and use of air conditioning in homes and businesses, and improved societal responses, including increased access to public health programs and healthcare.15,51,59,95,96,97 Projecting these trends into the future is challenging, but this trend of increasing tolerance is projected to continue, with future changes in adaptive capacity expected to reduce the future increase in mortality.53 However, there are limits to adaptation, whether physiological50 or sociotechnical (for example, air conditioning, awareness programs, or cooling centers). While historically adaptation has outpaced warming, most studies project a future increase in mortality even when including assumptions regarding adaptation.18,22,81,85,91 Additionally, the occurrence of events such as power outages simultaneous with a heat wave may reduce some of these adaptive benefits. Such simultaneous events can be more common because of the additional demand on the electricity grid due to high air-conditioning usage.98 Another potential effect is that if current trends of population growth and migration into large urban areas continue, there may be an increasing urban heat island effect which will magnify the rate of warming locally, possibly leading to more heat-related deaths and fewer cold-related deaths.

Projected changes in future health outcomes associated with extreme temperatures can be difficult to quantify. Projections can depend on 1) the characterization of population sensitivity to temperature event characteristics such as magnitude, duration, and humidity; 2) differences in population sensitivity depending on the timing and location of an extreme event; 3) future changes in baseline rates of death and illness as well as human tolerance and adaptive capacity; 4) the changing proportions of vulnerable populations, including the elderly, in the future; and 5) uncertainty in climate projections.


2.8 Populations of Concern for Death and Illness from Extreme Temperature

Impacts of temperature extremes are geographically varied and disproportionally affect certain populations of concern (see also Ch. 9: Populations of Concern).38  Certain populations are more at risk for experiencing detrimental consequences of exposure to extreme temperatures due to their sensitivity to hot and cold temperatures and limitations to their capacity for adapting to new climate conditions. 

Older adults are a rapidly growing population in the United States, and heat impacts are projected to occur in places where older adults are heavily concentrated and therefore most exposed.99 Older adults are at higher risk for temperature-related mortality and morbidity, particularly those who have preexisting diseases, those who take certain medications that affect thermoregulation or block nerve impulses (for example, beta-blockers, major tranquilizers, and diuretics), those who are living alone, or those with limited mobility (see also Ch. 9: Populations of Concern).17,24,39,42,100 The relationship between increased temperatures and death in older adults is well-understood with strong evidence of heat-related vulnerability for adults over 65 and 75 years old.101 An increased risk for respiratory and cardiovascular death is observed in older adults during temperature extremes due to reduced thermoregulation.17,39,42,65 Morbidity studies have also identified links between increased temperatures and respiratory and cardiovascular hospitalizations in older adults.65

Young baseball catcher

Physiological factors and participation in vigorous outdoor activities make children particularly vulnerable to extreme heat.

Children are particularly vulnerable because they must rely on others to help keep them safe. This is especially true in environments that may lack air conditioning, including homes, schools, or cars (see also Ch. 9: Populations of Concern).102 The primary health complications observed in children exposed to extreme heat include dehydration, electrolyte imbalance, fever, renal disease, heat stress, and hyperthermia.64 Infectious and respiratory diseases in children are affected by both hot and cold temperatures.64 Inefficient thermoregulation, reduced cardiovascular output, and heightened metabolic rate are physiological factors driving vulnerability in children to extreme heat. Children also spend a considerable amount of time outdoors and participating in vigorous physical activities.17,39,64,103 High-school football players are especially vulnerable to heat illness (see also Ch. 9: Populations of Concern).104 A limited number of studies show evidence of cold-related mortality in children. However, no study has examined the relationship between cold temperature and cause-specific mortality.64 Pregnant women are also vulnerable to temperature extremes as preterm birth has been associated with extreme heat.39,105,106 Elevated heat exposure can increase dehydration, leading to the release of labor-inducing hormones.107 Extreme heat events are also associated with adverse birth outcomes, such as low birth weight and infant mortality (see Ch. 9: Populations of Concern).

Where a person lives, works, or goes to school can also make them more vulnerable to health impacts from extreme temperatures. Of particular concern for densely populated cities is the urban heat island effect, where manmade surfaces absorb sunlight during the day and then radiate the stored energy at night as heat. This process will exacerbate any warming from climate change and limit the potential relief of cooler nighttime temperatures in urban areas.81 In addition to the urban heat island effect, land cover characteristics and poor air quality combine to increase the impacts of high ambient temperatures for city dwellers and further increase the burden on populations of concern within the urban area.12,17,42,108 The homeless are often more exposed to heat and cold extremes, while also sharing many risk factors with other populations of concern such as social isolation, psychiatric illness, and other health issues.109

Race, ethnicity, and socioeconomic status can affect vulnerability to temperature extremes. Non-Hispanic Black persons have been identified as being more vulnerable than other racial and ethnic groups to detrimental consequences of exposure to temperature extremes.17,39,42,103,110,111 One study found that non-Hispanic Blacks were 2.5 times more likely to experience heat-related mortality compared to non-Hispanic Whites, and non-Hispanic Blacks had a two-fold risk of dying from a heat-related event compared to Hispanics.17 Evidence of racial differences in heat tolerance due to genetic differences is inconclusive.110 However, other factors may contribute to increased vulnerability of Black populations, including comorbidities (co-existing chronic conditions) that increase susceptibility to higher temperatures, disparities in the availability and use of air conditioning and in heat risk-related land cover characteristics (for example, living in urban areas prone to heat-island effects), and environmental justice issues.17,39,108,110,112 Overall, the link between temperature extremes, race, ethnicity, and socioeconomic status is multidimensional and dependent on the outcome being studied. Education level, income, safe housing, occupational risks, access to health care, and baseline health and nutrition status can further distort the association between temperature extremes, race, and ethnicity.42,110

Construction worker

Certain occupational groups such as agricultural workers, construction workers, and electricity and pipeline utility workers are at increased risk for heat- and cold-related illness, especially where jobs involve heavy exertion.

Outdoor workers spend a great deal of time exposed to temperature extremes, often while performing vigorous activities. Certain occupational groups such as agricultural workers, construction workers, and electricity and pipeline utility workers are at increased risk for heat- and cold-related illness, especially where jobs involve heavy exertion.100,113,114 One study found failure of employers to provide for acclimatization to be the factor most clearly associated with heat-related death in workers.113

Mental, behavioral, and cognitive disorders can be triggered or exacerbated by heat waves. Specific illnesses impacted by heat include dementia, mood disorders, neurosis and stress, and substance abuse.100,115,116,117 Some medications interfere with thermoregulation, thereby increasing vulnerability to heat.116 One study in Australia found that hospital admissions for mental and behavioral disorders increased by 7.3% during heat waves above 80°F.115 Studies have also linked extreme heat and increased aggressive behavior. (See also Ch. 8: Mental Health).


2.9 Emerging and Cross-Cutting Issues

Emerging and cross-cutting issues include 1) disparate ways that extreme temperature and health are related, 2) urban and rural differences, 3) interactions between impacts and future changes in adaptation, and 4) projections of extreme temperature events.

The health effects addressed in this chapter are not the only ways in which heat and health are related. For example, research indicates that hotter temperatures may lead to an increase in violent crime118 and could negatively affect the labor force, especially occupational health for outdoor sectors.119,120 Extreme temperatures also interact with air quality, which can complicate estimating how extreme temperature events impact human health in the absence of air quality changes (see Section 2.5.1). In addition, increased heat may also increase vulnerability to poor air quality and allergens, leading to potential non-linear health outcome responses. Extreme temperature events, as well as other impacts from climate change, can also be associated with changes in electricity supply and distribution that can have important implications for the availability of heating and air conditioning, which are key adaptive measures.

Though the estimates of the health impact from extreme heat discussed in the “Research Highlight” were produced only for urban areas (which provided a large sample size for statistical validity), there is also emerging evidence regarding high rates of heat-related illness in rural areas.6,62Occupational exposure and a lack of access to air conditioning are some of the factors that may make rural populations particularly susceptible to extreme heat. There are quantitative challenges to using statistical methods to estimate mortality impacts of temperatures in rural areas due to lower population density and more dispersed weather stations, but rural residents have also demonstrated vulnerability to heat events.121

Other changes in human behavior will also have implications for the linkage between climate and heat-related illness. Changes in building infrastructure as a response to changes in temperature can have impacts on indoor air quality. Similarly, changes in behavior as a result of temperature changes, for example, seeking access to air conditioning, can change exposure to indoor and outdoor pollution and vector-borne diseases (see Ch. 3: Air Quality Impacts; Ch. 5: Vector-Borne Diseases).

Finally, projecting climate variability and the most extreme temperature events can be more challenging than projecting average warming. Extreme temperatures may rise faster than average temperatures,122 with the coldest days warming faster than average for much of the twentieth century, and the warmest days warming faster than average temperatures in the past 30 years.123 Extremely high temperatures in the future may also reach levels outside of past experience, in which case statistically based relationships may no longer hold for those events. There have been suggestive links between rapid recent Arctic sea ice loss124 and an increased frequency of cold125 and warm extremes,126 but this is an active area of research with conflicting results.127,128 In regions where temperature variability increases, mortality will be expected to increase; mortality is expected to decrease in regions where variability decreases.129


2.10 Research Needs

In addition to the emerging issues identified above, the authors highlight the following potential areas for additional scientific and research activity on temperature-related illness and death based on their review of the literature. Improved modeling and more robust projections of climate variability and extreme temperatures will enhance the modeling of health impacts associated with extremes of heat and cold. While the surveillance for temperature-related deaths is relatively robust, understanding the impacts of future changes in heat waves and extreme temperatures can be improved with better surveillance and documentation of non-fatal illnesses, including hospitalizations and emergency room visits, for temperature-associated reasons. With growing implementation of heat early warning systems around the country, there is also a need for the development of evaluation methods and associated collection of data to be able to assess effectiveness of such systems and other means of health adaptation.

Future assessments can benefit from research activities that:

  • further explore the associations between exposure to a range of high and low temperatures and exacerbation of illnesses across locations and healthcare settings;
  • improve understanding of how genetic factors and social determinants contribute to vulnerability to illness and death from extreme temperature exposures;
  • analyze the combined health effects of temperature and other discrete climate-sensitive stressors, such as changing air quality, smoke from wildfires, or impacts of extreme weather events;
  • attribute changes in observed mortality to a changing climate;
  • develop effective adaptive responses to reduce the potential adverse health outcomes attributable to changing temperatures; and
  • explore how future adaptive measures and behaviors can be included in quantitative models of health impacts associated with extreme temperatures

References

  1. Alessandrini, E., S. Zauli Sajani, F. Scotto, R. Miglio, S. Marchesi, and P. Lauriola, 2011: Emergency ambulance dispatches and apparent temperature: A time series analysis in Emilia–Romagna, Italy. Environmental Research, 111, 1192-1200. doi:10.1016/j.envres.2011.07.005 | Detail
  2. Analitis, A., and others, 2014: Effects of heat waves on mortality: Effect modification and confounding by air pollutants. Epidemiology, 25, 15-22. doi:10.1097/EDE.0b013e31828ac01b | Detail
  3. Anderson, B. G., and M. L. Bell, 2009: Weather-related mortality: How heat, cold, and heat waves affect mortality in the United States. Epidemiology, 20, 205-213. doi:10.1097/EDE.0b013e318190ee08 | Detail
  4. Anderson, G. B., and M. L. Bell, 2011: Heat waves in the United States: Mortality risk during heat waves and effect modification by heat wave characteristics in 43 U.S. communities. Environmental Health Perspectives, 119, 210-218. doi:10.1289/ehp.1002313 | Detail
  5. Anderson, G. B., F. Dominici, Y. Wang, M. C. McCormack, M. L. Bell, and R. D. Peng, 2013: Heat-related emergency hospitalizations for respiratory diseases in the Medicare population. American Journal of Respiratory and Critical Care Medicine, 187, 1098-1103. doi:10.1164/rccm.201211-1969OC | Detail
  6. Arbury, S., B. Jacklitsch, O. Farquah, M. Hodgson, G. Lamson, H. Martin, and A. Profitt, 2014: Heat illness and death among workers - United States, 2012-2013. Morbidity and Mortality Weekly Report, 63, 661-665. PMID: 25102413 | Detail
  7. Åström, D. O., F. Bertil, and R. Joacim, 2011: Heat wave impact on morbidity and mortality in the elderly population: A review of recent studies. Maturitas, 69, 99-105. doi:10.1016/j.maturitas.2011.03.008 | Detail
  8. Balbus, J. M., and C. Malina, 2009: Identifying vulnerable subpopulations for climate change health effects in the United States. Journal of Occupational and Environmental Medicine, 51, 33-37. doi:10.1097/JOM.0b013e318193e12e | Detail
  9. Barnes, E. A., 2013: Revisiting the evidence linking Arctic amplification to extreme weather in midlatitudes. Geophysical Research Letters, 40, 4734-4739. doi:10.1002/grl.50880 | Detail
  10. Barnett, A. G., S. Hajat, A. Gasparrini, and J. Rocklöv, 2012: Cold and heat waves in the United States. Environmental Research, 112, 218-224. doi:10.1016/j.envres.2011.12.010 | Detail
  11. Barreca, A. I., 2012: Climate change, humidity, and mortality in the United States. Journal of Environmental Economics and Management, 63, 19-34. doi:10.1016/j.jeem.2011.07.004 | Detail
  12. Basu, R., and J. M. Samet, 2002: Relation between elevated ambient temperature and mortality: A review of the epidemiologic evidence. Epidemiologic Reviews, 24, 190-202. doi:10.1093/epirev/mxf007 | Detail
  13. Basu, R., B. Malig, and B. Ostro, 2010: High ambient temperature and the risk of preterm delivery. American Journal of Epidemiology, 172, 1108-1117. doi:10.1093/aje/kwq170 | Detail
  14. Basu, R., D. Pearson, B. Malig, R. Broadwin, and R. Green, 2012: The effect of high ambient temperature on emergency room visits. Epidemiology, 23, 813-820. doi:10.1097/EDE.0b013e31826b7f97 | Detail
  15. Beltran, A. J., J. Wu, and O. Laurent, 2014: Associations of meteorology with adverse pregnancy outcomes: A systematic review of preeclampsia, preterm birth and birth weight. International Journal of Environmental Research and Public Health, 11, 91-172. doi:10.3390/ijerph110100091 | Detail
  16. Benmarhnia, T., S. Deguen, J. S. Kaufman, and A. Smargiassi, 2015: Review article: Vulnerability to heat-related mortality: A systematic review, meta-analysis, and meta-regression analysis. Epidemiology, 26, 781-793. doi:10.1097/EDE.0000000000000375 | Detail
  17. Berko, J., D. D. Ingram, S. Saha, and J. D. Parker, 2014: Deaths Attributed to Heat, Cold, and Other Weather Events in the United States, 2006–2010. 15 pp., National Center for Health Statistics, Hyattsville, MD. URL | Detail
  18. Bobb, J. F., R. D. Peng, M. L. Bell, and F. Dominici, 2014: Heat-related mortality and adaptation to heat in the United States. Environmental Health Perspectives, 122, 811-816. doi:10.1289/ehp.1307392 | Detail
  19. Brikowski, T. H., Y. Lotan, and M. S. Pearle, 2008: Climate-related increase in the prevalence of urolithiasis in the United States. Proceedings of the National Academy of Sciences of the United States of America, 105, 9841-9846. doi:10.1073/pnas.0709652105 | Detail
  20. Bustinza, R., G. Lebel, P. Gosselin, D. Bélanger, and F. Chebana, 2013: Health impacts of the July 2010 heat wave in Quebec, Canada. BMC Public Health, 13, 56. doi:10.1186/1471-2458-13-56 | Detail
  21. Carolan-Olah, M., and D. Frankowska, 2014: High environmental temperature and preterm birth: A review of the evidence. Midwifery, 30, 50-59. doi:10.1016/j.midw.2013.01.011 | Detail
  22. CDC, 2005: Extreme Cold: A Prevention Guide to Promote Your Personal Health and Safety. 13 pp., U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Atlanta, GA. URL | Detail
  23. CDC, cited 2011: Extreme Heat and Your Health: Heat and Infants and Children. Centers for Disease Control and Prevention. URL | Detail
  24. CDC, cited 2015: Emergency Preparedness and Response: Extreme Heat. Centers for Disease Control and Prevention. URL | Detail
  25. Centers for Disease Control and Prevention (CDC), 1994: Heat-related deaths--Philadelphia and United States, 1993-1994. Morbidity and Mortality Weekly Report, 43, 453-455. PMID: 8208234 | Detail
  26. Centers for Disease Control and Prevention (CDC), 1995: Heat-related mortality--Chicago, July 1995. Morbidity and Mortality Weekly Report, 44, 577-579. PMID: 7623759 | Detail
  27. Centers for Disease Control and Prevention (CDC), 2006: Hypothermia-related deaths--United States, 1999-2002 and 2005. Morbidity and Mortality Weekly Report, 55, 282-284. PMID: 16543884 | Detail
  28. Davis, R. E., P. C. Knappenberger, W. M. Novicoff, and P. J. Michaels, 2002: Decadal changes in heat-related human mortality in the eastern United States. Climate Research, 22, 175-184. doi:10.3354/cr022175 | Detail
  29. Davis, R. E., P. C. Knappenberger, W. M. Novicoff, and P. J. Michaels, 2003: Decadal changes in summer mortality in US cities. International Journal of Biometeorology, 47, 166-175. doi:10.1007/s00484-003-0160-8 | Detail
  30. Deschênes, O., and M. Greenstone, 2011: Climate change, mortality, and adaptation: Evidence from annual fluctuations in weather in the US. American Economic Journal: Applied Economics, 3, 152-185. doi:10.1257/app.3.4.152 | Detail
  31. Dixon, P. G., and others, 2005: Heat mortality versus cold mortality: A study of conflicting databases in the United States. Bulletin of the American Meteorological Society, 86, 937-943. doi:10.1175/bams-86-7-937 | Detail
  32. Dunne, J. P., R. J. Stouffer, and J. G. John, 2013: Reductions in labour capacity from heat stress under climate warming. Nature Climate Change, 3, 563-566. doi:10.1038/nclimate1827 | Detail
  33. Ebi, K. L., and D. Mills, 2013: Winter mortality in a warming climate: A reassessment. Wiley Interdisciplinary Reviews: Climate Change, 4, 203-212. doi:10.1002/wcc.211 | Detail
  34. Ebi, K. L., T. J. Teisberg, L. S. Kalkstein, L. Robinson, and R. F. Weiher, 2004: Heat watch/warning systems save lives: Estimated costs and benefits for Philadelphia 1995–98. Bulletin of the American Meteorological Society, 85, 1067-1073. doi:10.1175/bams-85-8-1067 | Detail
  35. EPA, 2012: Climate Change Indicators in the United States, 2nd Edition. 84 pp., U.S. Environmental Protection Agency, Washington, D.C. URL | Detail
  36. EPA, cited 2015: Natural Disasters: Extreme Heat. U.S. Environmental Protection Agency. URL | Detail
  37. Fakheri, R. J., and D. S. Goldfarb, 2011: Ambient temperature as a contributor to kidney stone formation: Implications of global warming. Kidney International, 79, 1178-1185. doi:10.1038/ki.2011.76 | Detail
  38. Fischer, E. M., and R. Knutti, 2015: Anthropogenic contribution to global occurrnece of heavy-precipitation and high-temperature extremes. Nature Climate Change, 5, 560-564. doi:10.1038/nclimate2617 | Detail
  39. Fletcher, B. A., S. Lin, E. F. Fitzgerald, and S. A. Hwang, 2012: Association of summer temperatures with hospital admissions for renal diseases in New York State: A case-crossover study. American Journal of Epidemiology, 175, 907-916. doi:10.1093/aje/kwr417 | Detail
  40. Francis, J. A., and S. J. Vavrus, 2012: Evidence linking Arctic amplification to extreme weather in mid-latitudes. Geophysical Research Letters, 39, L06801. doi:10.1029/2012GL051000 | Detail
  41. Gamble, J. L., B. J. Hurley, P. A. Schultz, W. S. Jaglom, N. Krishnan, and M. Harris, 2013: Climate change and older Americans: State of the science. Environmental Health Perspectives, 121, 15-22. doi:10.1289/ehp.1205223 | Detail
  42. Gasparrini, A., and others, 2015: Mortality risk attributable to high and low ambient temperature: A multicountry observational study. The Lancet, 386, 369-375. doi:10.1016/S0140-6736(14)62114-0 | Detail
  43. Gosling, S. N., G. R. McGregor, and J. A. Lowe, 2009: Climate change and heat-related mortality in six cities Part 2: Climate model evaluation and projected impacts from changes in the mean and variability of temperature with climate change. International Journal of Biometeorology, 53, 31-51. doi:10.1007/s00484-008-0189-9 | Detail
  44. Gosling, S. N., J. A. Lowe, G. R. McGregor, M. Pelling, and B. D. Malamud, 2009: Associations between elevated atmospheric temperature and human mortality: A critical review of the literature. Climatic Change, 92, 299-341. doi:10.1007/s10584-008-9441-x | Detail
  45. Graff Zivin, J., and M. Neidell, 2014: Temperature and the allocation of time: Implications for climate change. Journal of Labor Economics, 32, 1-26. doi:10.1086/671766 | Detail
  46. Greene, S., L. S. Kalkstein, D. M. Mills, and J. Samenow, 2011: An examination of climate change on extreme heat events and climate–mortality relationships in large U.S. cities. Weather, Climate, and Society, 3, 281-292. doi:10.1175/WCAS-D-11-00055.1 | Detail
  47. Green, R. S., R. Basu, B. Malig, R. Broadwin, J. J. Kim, and B. Ostro, 2010: The effect of temperature on hospital admissions in nine California counties. International Journal of Public Health, 55, 113-121. doi:10.1007/s00038-009-0076-0 | Detail
  48. Gronlund, C. J., 2014: Racial and socioeconomic disparities in heat-related health effects and their mechanisms: A review. Current Epidemiology Reports, 1, 165-173. doi:10.1007/s40471-014-0014-4 | Detail
  49. Gronlund, C. J., A. Zanobetti, J. D. Schwartz, G. A. Wellenius, and M. S. O'Neill, 2014: Heat, heat waves, and hospital admissions among the elderly in the United States, 1992–2006. Environmental Health Perspectives, 122, 1187-1192. doi:10.1289/ehp.1206132 | Detail
  50. Guo, Y., A. G. Barnett, and S. Tong, 2012: High temperatures-related elderly mortality varied greatly from year to year: Important information for heat-warning systems. Scientific Reports, 2. doi:10.1038/srep00830 | Detail
  51. Hanna, E. G., and P. W. Tait, 2015: Limitations to thermoregulation and acclimatization challenge human adaptation to global warming. International Journal of Environmental Research and Public Health, 12, 8034-8074. doi:10.3390/ijerph120708034 | Detail
  52. Hansen, A., L. Bi, A. Saniotis, and M. Nitschke, 2013: Vulnerability to extreme heat and climate change: Is ethnicity a factor? Global Health Action, 6. doi:10.3402/gha.v6i0.21364 | Detail
  53. Hansen, A., P. Bi, M. Nitschke, P. Ryan, D. Pisaniello, and G. Tucker, 2008: The effect of heat waves on mental health in a temperate Australian city. Environmental Health Perspectives, 116, 1369-1375. doi:10.1289/ehp.11339 | Detail
  54. Harlan, S. L., J. H. Declet-Barreto, W. L. Stefanov, and D. B. Petitti, 2013: Neighborhood effects on heat deaths: Social and environmental predictors of vulnerability in Maricopa County, Arizona. Environmental Health Perspectives, 121, 197-204. doi:10.1289/ehp.1104625 | Detail
  55. Hayhoe, K., S. Sheridan, L. Kalkstein, and S. Greene, 2010: Climate change, heat waves, and mortality projections for Chicago. Journal of Great Lakes Research, 36, 65-73. doi:10.1016/j.jglr.2009.12.009 | Detail
  56. Hess, J. J., S. Saha, and G. Luber, 2014: Summertime acute heat illness in U.S. emergency departments from 2006 through 2010: Analysis of a nationally representative sample. Environmental Health Perspectives, 122, 1209-1215. doi:10.1289/ehp.1306796 | Detail
  57. Honda, Y., and others, 2014: Heat-related mortality risk model for climate change impact projection. Environmental Health and Preventive Medicine, 19, 56-63. doi:10.1007/s12199-013-0354-6 | Detail
  58. Hondula, D. M., R. C. Balling, J. K. Vanos, and M. Georgescu, 2015: Rising temperatures, human health, and the role of adaptation. Current Climate Change Reports, 1, 144-154. doi:10.1007/s40641-015-0016-4 | Detail
  59. Hoshiko, S., P. English, D. Smith, and R. Trent, 2010: A simple method for estimating excess mortality due to heat waves, as applied to the 2006 California heat wave. International Journal of Public Health, 55, 133-137. doi:10.1007/s00038-009-0060-8 | Detail
  60. Huang, C., A. G. Barnett, X. Wang, P. Vaneckova, G. FitzGerald, and S. Tong, 2011: Projecting future heat-related mortality under climate change scenarios: A systematic review. Environmental Health Perspectives, 119, 1681-1690. doi:10.1289/Ehp.1103456 | Detail
  61. Isaksen, T. B., M. Yost, E. Hom, and R. Fenske, 2014: Projected health impacts of heat events in Washington State associated with climate change. Reviews on Environmental Health, 29, 119-123. doi:10.1515/reveh-2014-0029 | Detail
  62. Jackson, J. E., and others, 2010: Public health impacts of climate change in Washington State: Projected mortality risks due to heat events and air pollution. Climatic Change, 102, 159-186. doi:10.1007/s10584-010-9852-3 | Detail
  63. Jones, S., M. Griffin, A. Liang, and P. Patriarca, 1980: The Kansas City Heat Wave, July 1980: Effects of Health, Preliminary Report. Centers for Disease Control, Atlanta, GA. | Detail
  64. Jones, T. S., and others, 1982: Morbidity and mortality associated with the July 1980 heat wave in St Louis and Kansas City, Mo. JAMA: The Journal of the American Medical Association, 247, 3327-3331. doi:10.1001/jama.1982.03320490025030 | Detail
  65. Kaiser, R., A. Le Tertre, J. Schwartz, C. A. Gotway, W. R. Daley, and C. H. Rubin, 2007: The effect of the 1995 heat wave in Chicago on all-cause and cause-specific mortality. American Journal of Public Health, 97, S158-S162. doi:10.2105/ajph.2006.100081 | Detail
  66. Kalkstein, L. S., 1998: Climate and human mortality: Relationships and mitigating measures. Advances in Bioclimatology, 5, 161-177. doi:10.1007/978-3-642-80419-9_7 | Detail
  67. Kalkstein, L. S., S. Greene, D. M. Mills, and J. Samenow, 2011: An evaluation of the progress in reducing heat-related human mortality in major U.S. cities. Natural Hazards, 56, 113-129. doi:10.1007/s11069-010-9552-3 | Detail
  68. Karl, T. R., and R. W. Knight, 1997: The 1995 Chicago heat wave: How likely is a recurrence? Bulletin of the American Meteorological Society, 78, 1107-1119. doi:10.1175/1520-0477(1997)078<1107:tchwhl>2.0.co;2 | Detail
  69. Kent, S. T., L. A. McClure, B. F. Zaitchik, T. T. Smith, and J. M. Gohlke, 2014: Heat waves and health outcomes in Alabama (USA): The importance of heat wave definition. Environmental Health Perspectives, 122, 151–158. doi:10.1289/ehp.1307262 | Detail
  70. Kerr, Z. Y., D. J. Casa, S. W. Marshall, and R. D. Comstock, 2013: Epidemiology of exertional heat illness among U.S. high school athletes. American Journal of Preventive Medicine, 44, 8-14. doi:10.1016/j.amepre.2012.09.058 | Detail
  71. Kinney, P. L., J. Schwartz, M. Pascal, E. Petkova, A. Le Tertre, S. Medina, and R. Vautard, 2015: Winter season mortality: Will climate warming bring benefits? Environmental Research Letters, 10, 064016. doi:10.1088/1748-9326/10/6/064016 | Detail
  72. Kinney, P. L., M. Pascal, R. Vautard, and K. Laaidi, 2012: Winter mortality in a changing climate: Will it go down? Bulletin Epidemiologique Hebdomadaire, 12-13, 5-7. | Detail
  73. Knowlton, K., B. Lynn, R. A. Goldberg, C. Rosenzweig, C. Hogrefe, J. K. Rosenthal, and P. L. Kinney, 2007: Projecting heat-related mortality impacts under a changing climate in the New York City region. American Journal of Public Health, 97, 2028-2034. doi:10.2105/Ajph.2006.102947 | Detail
  74. Knowlton, K., M. Rotkin-Ellman, G. King, H. G. Margolis, D. Smith, G. Solomon, R. Trent, and P. English, 2009: The 2006 California heat wave: Impacts on hospitalizations and emergency department visits. Environmental Health Perspectives, 117, 61-67. doi:10.1289/ehp.11594 | Detail
  75. Kovats, R. S., and S. Hajat, 2008: Heat stress and public health: A critical review. Annual Review of Public Health, 29, 41-55. doi:10.1146/annurev.publhealth.29.020907.090843 | Detail
  76. Lavigne, E., A. Gasparrini, X. Wang, H. Chen, A. Yagouti, M. D. Fleury, and S. Cakmak, 2014: Extreme ambient temperatures and cardiorespiratory emergency room visits: Assessing risk by comorbid health conditions in a time series study. Environmental Health, 13, 5. doi:10.1186/1476-069x-13-5 | Detail
  77. Lee, M., F. Nordio, A. Zanobetti, P. Kinney, R. Vautard, and J. Schwartz, 2014: Acclimatization across space and time in the effects of temperature on mortality: A time-series analysis. Environmental Health, 13, 89. doi:10.1186/1476-069X-13-89 | Detail
  78. Le Tertre, A., and others, 2006: Impact of the 2003 heatwave on all-cause mortality in 9 French cities. Epidemiology, 17, 75-79. doi:10.1097/01.ede.0000187650.36636.1f | Detail
  79. Li, B., and others, 2012: The impact of extreme heat on morbidity in Milwaukee, Wisconsin. Climatic Change, 110, 959-976. doi:10.1007/s10584-011-0120-y | Detail
  80. Lin, S., M. Luo, R. J. Walker, X. Liu, S. A. Hwang, and R. Chinery, 2009: Extreme high temperatures and hospital admissions for respiratory and cardiovascular diseases. Epidemiology, 20, 738-746. doi:10.1097/EDE.0b013e3181ad5522 | Detail
  81. Lin, S., W. -H. Hsu, A. R. Van Zutphen, S. Saha, G. Luber, and S. -A. Hwang, 2012: Excessive heat and respiratory hospitalizations in New York State: Estimating current and future public health burden related to climate change. Environmental Health Perspectives, 120, 1571-1577. doi:10.1289/ehp.1104728 | Detail
  82. Lippmann, S. J., C. M. Fuhrmann, A. E. Waller, and D. B. Richardson, 2013: Ambient temperature and emergency department visits for heat-related illness in North Carolina, 2007-2008. Environmental Research, 124, 35-42. doi:10.1016/j.envres.2013.03.009 | Detail
  83. Li, T., R. M. Horton, and P. L. Kinney, 2013: Projections of seasonal patterns in temperature-related deaths for Manhattan, New York. Nature Climate Change, 3, 717-721. doi:10.1038/nclimate1902 | Detail
  84. Liu, J., J. A. Curry, H. Wang, M. Song, and R. M. Horton, 2012: Impact of declining Arctic sea ice on winter snowfall. Proceedings of the National Academy of Sciences of the United States of America, 109, 4074-4079. doi:10.1073/pnas.1114910109 | Detail
  85. Liu, J., M. Song, R. M. Horton, and Y. Hu, 2013: Reducing spread in climate model projections of a September ice-free Arctic. Proceedings of the National Academy of Sciences of the United States of America, 110, 12571-12576. doi:10.1073/pnas.1219716110 | Detail
  86. Luber, G., and others, 2014: Ch. 9: Human Health. Climate Change Impacts in the United States: The Third National Climate Assessment, J.M. Melillo, Richmond, T. (T.C.), and Yohe, G.W., Eds., U.S. Global Change Research Program, 220-256. doi:10.7930/J0PN93H5 | Detail
  87. Lundgren, K., K. Kuklane, C. Gao, and I. Holmer, 2013: Effects of heat stress on working populations when facing climate change. Industrial Health, 51, 3-15. doi:10.2486/indhealth.2012-0089 | Detail
  88. Madrigano, J., D. Jack, G. B. Anderson, M. L. Bell, and P. L. Kinney, 2015: Temperature, ozone, and mortality in urban and non-urban counties in the northeastern United States. Environmental Health, 14, 3. doi:10.1186/1476-069X-14-3 | Detail
  89. Madrigano, J., M. A. Mittleman, A. Baccarelli, R. Goldberg, S. Melly, S. von Klot, and J. Schwartz, 2013: Temperature, myocardial infarction, and mortality: Effect modification by individual- and area-level characteristics. Epidemiology, 24, 439-446. doi:10.1097/EDE.0b013e3182878397 | Detail
  90. Martin-Latry, K., M. P. Goumy, P. Latry, C. Gabinski, B. Bégaud, I. Faure, and H. Verdoux, 2007: Psychotropic drugs use and risk of heat-related hospitalisation. European Psychiatry, 22, 335-338. doi:10.1016/j.eurpsy.2007.03.007 | Detail
  91. Medina-Ramón, M., and J. Schwartz, 2007: Temperature, temperature extremes, and mortality: A study of acclimatisation and effect modification in 50 US cities. Occupational and Environmental Medicine, 64, 827-833. doi:10.1136/oem.2007.033175 | Detail
  92. Mercer, J. B., 2003: Cold—an underrated risk factor for health. Environmental Research, 92, 8-13. doi:10.1016/s0013-9351(02)00009-9 | Detail
  93. Mills, D., J. Schwartz, M. Lee, M. Sarofim, R. Jones, M. Lawson, M. Duckworth, and L. Deck, 2015: Climate change impacts on extreme temperature mortality in select metropolitan areas in the United States. Climatic Change, 131, 83-95. doi:10.1007/s10584-014-1154-8 | Detail
  94. Noe, R. S., J. O. Jin, and A. F. Wolkin, 2012: Exposure to natural cold and heat: Hypothermia and hyperthermia medicare claims, United States, 2004–2005. American Journal of Public Health, 102, e11-e18. doi:10.2105/ajph.2011.300557 | Detail
  95. O’Neill, M. S., A. Zanobetti, and J. Schwartz, 2005: Disparities by race in heat-related mortality in four US cities: The role of air conditioning prevalence. Journal of Urban Health, 82, 191-197. doi:10.1093/jurban/jti043 | Detail
  96. Orlowsky, B., and S. I. Seneviratne, 2012: Global changes in extreme events: Regional and seasonal dimension. Climatic Change, 110, 669-696. doi:10.1007/s10584-011-0122-9 | Detail
  97. Ostro, B., S. Rauch, and S. Green, 2011: Quantifying the health impacts of future changes in temperature in California. Environmental Research, 111, 1258-1264. doi:10.1016/j.envres.2011.08.013 | Detail
  98. Ostro, B., S. Rauch, R. Green, B. Malig, and R. Basu, 2010: The effects of temperature and use of air conditioning on hospitalizations. American Journal of Epidemiology, 172, 1053-1061. doi:10.1093/aje/kwq231 | Detail
  99. Page, L. A., S. Hajat, R. S. Kovats, and L. M. Howard, 2012: Temperature-related deaths in people with psychosis, dementia and substance misuse. The British Journal of Psychiatry, 200, 485-490. doi:10.1192/bjp.bp.111.100404 | Detail
  100. Peng, R. D., J. F. Bobb, C. Tebaldi, L. McDaniel, M. L. Bell, and F. Dominici, 2011: Toward a quantitative estimate of future heat wave mortality under global climate change. Environmental Health Perspectives, 119, 701-706. doi:10.1289/ehp.1002430 | Detail
  101. Petkova, E. P., A. Gasparrini, and P. L. Kinney, 2014: Heat and mortality in New York City since the beginning of the 20th century. Epidemiology, 25, 554-560. doi:10.1097/ede.0000000000000123 | Detail
  102. Petkova, E. P., D. A. Bader, G. B. Anderson, R. M. Horton, K. Knowlton, and P. L. Kinney, 2014: Heat-related mortality in a warming climate: Projections for 12 U.S. cities. International Journal of Environmental Research and Public Health, 11, 11371-11383. doi:10.3390/ijerph111111371 | Detail
  103. Petkova, E. P., R. M. Horton, D. A. Bader, and P. L. Kinney, 2013: Projected heat-related mortality in the U.S. urban northeast. International Journal of Environmental Research and Public Health, 10, 6734-6747. doi:10.3390/ijerph10126734 | Detail
  104. Ramin, B., and T. Svoboda, 2009: Health of the homeless and climate change. Journal of Urban Health, 86, 654-664. doi:10.1007/s11524-009-9354-7 | Detail
  105. Ranson, M., 2014: Crime, weather, and climate change. Journal of Environmental Economics and Management, 67, 274-302. doi:10.1016/j.jeem.2013.11.008 | Detail
  106. Robeson, S. M., C. J. Willmott, and P. D. Jones, 2014: Trends in hemispheric warm and cold anomalies. Geophysical Research Letters, 41, 9065-9071. doi:10.1002/2014gl062323 | Detail
  107. Saha, M. V., R. E. Davis, and D. M. Hondula, 2014: Mortality displacement as a function of heat event strength in 7 US cities. American Journal of Epidemiology, 179, 467-474. doi:10.1093/aje/kwt264 | Detail
  108. Schwartz, J. D., and others, 2015: Projections of temperature-attributable premature deaths in 209 U.S. cities using a cluster-based Poisson approach. Environmental Health, 14. doi:10.1186/s12940-015-0071-2 | Detail
  109. Schwartz, J., J. M. Samet, and J. A. Patz, 2004: Hospital admissions for heart disease: The effects of temperature and humidity. Epidemiology, 15, 755-761. doi:10.1097/01.ede.0000134875.15919.0f | Detail
  110. Sheridan, S. C., A. J. Kalkstein, and L. S. Kalkstein, 2009: Trends in heat-related mortality in the United States, 1975–2004. Natural Hazards, 50, 145-160. doi:10.1007/s11069-008-9327-2 | Detail
  111. Sheridan, S. C., and T. J. Dolney, 2003: Heat, mortality, and level of urbanization: Measuring vulnerability across Ohio, USA. Climate Research, 24, 255-265. doi:10.3354/cr024255 | Detail
  112. Sherwood, S. C., and M. Huber, 2010: An adaptability limit to climate change due to heat stress. Proceedings of the National Academy of Sciences of the United States of America, 107, 9552-9555. doi:10.1073/pnas.0913352107 | Detail
  113. Smith, T. T., B. F. Zaitchik, and J. M. Gohlke, 2013: Heat waves in the United States: Definitions, patterns and trends. Climatic Change, 118, 811-825. doi:10.1007/s10584-012-0659-2 | Detail
  114. Stone, B. J., J. Vargo, P. Liu, D. Habeeb, A. DeLucia, M. Trail, Y. Hu, and A. Russell, 2014: Avoided heat-related mortality through climate adaptation strategies in three US cities. PLoS ONE, 9, e100852. doi:10.1371/journal.pone.0100852 | Detail
  115. Tasian, G. E., J. E. Pulido, A. Gasparrini, C. S. Saigal, B. P. Horton, J. R. Landis, R. Madison, and R. Keren, 2014: Daily mean temperature and clinical kidney stone presentation in five U.S. metropolitan areas: A time-series analysis. Environmental Health Perspectives, 122, 1081-1087. doi:10.1289/ehp.1307703 | Detail
  116. Turner, L. R., A. G. Barnett, D. Connell, and S. Tong, 2012: Ambient temperature and cardiorespiratory morbidity: A systematic review and meta-analysis. Epidemiology, 23, 594-606. doi:10.1097/EDE.0b013e3182572795 | Detail
  117. Uejio, C. K., O. V. Wilhelmi, J. S. Golden, D. M. Mills, S. P. Gulino, and J. P. Samenow, 2011: Intra-urban societal vulnerability to extreme heat: The role of heat exposure and the built environment, socioeconomics, and neighborhood stability. Health & Place, 17, 498-507. doi:10.1016/j.healthplace.2010.12.005 | Detail
  118. Vanos, J. K., L. S. Kalkstein, and T. J. Sanford, 2015: Detecting synoptic warming trends across the US midwest and implications to human health and heat-related mortality. International Journal of Climatology, 35, 85-96. doi:10.1002/joc.3964 | Detail
  119. Voorhees, A. S., N. Fann, C. Fulcher, P. Dolwick, B. Hubbell, B. Bierwagen, and P. Morefield, 2011: Climate change-related temperature impacts on warm season heat mortality: A proof-of-concept methodology using BenMAP. Environmental Science & Technology, 45, 1450-1457. doi:10.1021/es102820y | Detail
  120. Wallace, J. M., I. M. Held, D. W. J. Thompson, K. E. Trenberth, and J. E. Walsh, 2014: Global warming and winter weather. Science, 343, 729-730. doi:10.1126/science.343.6172.729 | Detail
  121. Walsh, J., and others, 2014: Ch. 2: Our Changing Climate. Climate Change Impacts in the United States: The Third National Climate Assessment, J.M. Melillo, Richmond, T. (T.C.), and Yohe, G.W., Eds., U.S. Global Change Research Program, 19-67. doi:10.7930/J0KW5CXT | Detail
  122. Wasilevich, E. A., F. Rabito, J. Lefante, and E. Johnson, 2012: Short-term outdoor temperature change and emergency department visits for asthma among children: A case-crossover study. American Journal of Epidemiology, 176, S123-S130. doi:10.1093/aje/kws326 | Detail
  123. Watkiss, P., and A. Hunt, 2012: Projection of economic impacts of climate change in sectors of Europe based on bottom up analysis: Human health. Climatic Change, 112, 101-126. doi:10.1007/s10584-011-0342-z | Detail
  124. WHO, 2004: International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD–10). World Health Organization. URL | Detail
  125. Wu, J., Y. Zhou, Y. Gao, J. S. Fu, B. A. Johnson, C. Huang, Y. -M. Kim, and Y. Liu, 2014: Estimation and uncertainty analysis of impacts of future heat waves on mortality in the eastern United States. Environmental Health Perspectives, 122, 10-16. doi:10.1289/ehp.1306670 | Detail
  126. Xu, Z., R. A. Etzel, H. Su, C. Huang, Y. Guo, and S. Tong, 2012: Impact of ambient temperature on children's health: A systematic review. Environmental Research, 117, 120-131. doi:10.1016/j.envres.2012.07.002 | Detail
  127. Ye, X., R. Wolff, W. Yu, P. Vaneckova, X. Pan, and S. Tong, 2012: Ambient temperature and morbidity: A review of epidemiological evidence. Environmental Health Perspectives, 120, 19-28. doi:10.1289/ehp.1003198 | Detail
  128. Zanobetti, A., M. S. O'Neill, C. J. Gronlund, and J. D. Schwartz, 2012: Summer temperature variability and long-term survival among elderly people with chronic disease. Proceedings of the National Academy of Sciences of the United States of America, 109, 6608-6613. doi:10.1073/pnas.1113070109 | Detail
  129. Zhang, K., R. B. Rood, G. Michailidis, E. M. Oswald, J. D. Schwartz, A. Zanobetti, K. L. Ebi, and M. S. O'Neill, 2012: Comparing exposure metrics for classifying ‘dangerous heat’ in heat wave and health warning systems. Environment International, 46, 23-29. doi:10.1016/j.envint.2012.05.001 | Detail

Likelihood

Very Likely
≥9 in 10
Likely
≥2 in 3
As Likely as Not
≈ 1 in 2
Unlikely
≤ 1 in 3
Very Unikely
≤1 in 10

Confidence Level

Very High Strong evidence (established theory, multiple sources, consistent results, well documented and accepted methods, etc.), high consensus
High Moderate evidence (several sources, some consistency, methods vary and/or documentation limited, etc.), medium consensus
Medium Suggestive evidence (a few sources, limited consistency, models incomplete, methods emerging, etc.), competing schools of thought
Low Inconclusive evidence (limited sources, extrapolations, inconsistent findings, poor documentation and/or methods not tested, etc.), disagreement or lack of opinions among experts
 

Documenting Uncertainty: This assessment relies on two metrics to communicate the degree of certainty in Key Findings. See Appendix 4: Documenting Uncertainty for more on assessments of likelihood and confidence.

Key Finding 1: Future Increases in Temperature-Related Deaths

Based on present-day sensitivity to heat, an increase of thousands to tens of thousands of premature heat-related deaths in the summer [Very Likely, High Confidence] and a decrease of premature cold-related deaths in the winter [Very Likely, Medium Confidence] are projected each year as a result of climate change by the end of the century. Future adaptation will very likely reduce these impacts (see Changing Tolerance to Extreme Heat Finding). The reduction in cold-related deaths is projected to be smaller than the increase in heat-related deaths in most regions [Likely, Medium Confidence].

Key Finding 2: Even Small Differences from Seasonal Average Temperatures Result in Illness and Death

Days that are hotter than usual in the summer or colder than usual in the winter are both associated with increased illness and death [Very High Confidence]. Mortality effects are observed even for small differences from seasonal average temperatures [High Confidence]. Because small temperature differences occur much more frequently than large temperature differences, not accounting for the effect of these small differences would lead to underestimating the future impact of climate change [Likely, High Confidence].

Key Finding 3: Changing Tolerance to Extreme Heat

An increase in population tolerance to extreme heat has been observed over time [Very High Confidence]. Changes in this tolerance have been associated with increased use of air conditioning, improved social responses, and/or physiological acclimatization, among other factors [Medium Confidence]. Expected future increases in this tolerance will reduce the projected increase in deaths from heat [Very Likely, Very High Confidence].

Key Finding 4: Some Populations at Greater Risk

Older adults and children have a higher risk of dying or becoming ill due to extreme heat [Very High Confidence]. People working outdoors, the socially isolated and economically disadvantaged, those with chronic illnesses, as well as some communities of color, are also especially vulnerable to death or illness [Very High Confidence].