David M. Hondula

Fine-scale spatial variability of heat-related mortality in Philadelphia County, USA, from 1983-2008: a case-series analysis

BackgroundHigh temperature and humidity conditions are associated with short-term elevations in the mortality rate in many United States cities. Previous research has quantified this relationship in an aggregate manner over large metropolitan areas, but within these areas the response may differ based on local-scale variability in climate, population characteristics, and socio-economic factors.MethodsWe compared the mortality response for 48 Zip Code Tabulation Areas (ZCTAs) comprising Philadelphia County, PA to determine if certain areas are associated with elevated risk during high heat stress conditions. A randomization test was used to identify mortality exceedances for various apparent temperature thresholds at both the city and local scale. We then sought to identify the environmental, demographic, and social factors associated with high-risk areas via principal components regression.ResultsCitywide mortality increases by 9.3% on days following those with apparent temperatures over 34°C observed at 7:00 p.m. local time. During these conditions, elevated mortality rates were found for 10 of the 48 ZCTAs concentrated in the west-central portion of the County. Factors related to high heat mortality risk included proximity to locally high surface temperatures, low socioeconomic status, high density residential zoning, and age.ConclusionsWithin the larger Philadelphia metropolitan area, there exists statistically significant fine-scale spatial variability in the mortality response to high apparent temperatures. Future heat warning systems and mitigation and intervention measures could target these high risk areas to reduce the burden of extreme weather on summertime morbidity and mortality.

The SSC: a decade of climate–health research and future directions

This year marks the tenth anniversary of the development of the revised Spatial Synoptic Classification, the “SSC”, by Scott Sheridan. This daily weather-type classification scheme has become one of the key analytical tools implemented in a diverse range of climatological investigations, including analysis of air quality variability, human health, vegetation growth, precipitation and snowfall trends, and broader analyses of historical and future climatic variability and trends. The continued and expanding use of the SSC motivates a review and comparison of the system’s research and geographic foci to date, with the goal of identifying promising areas for future efforts, particularly within the context of human health and climate change. This review also assesses how the SSC has complemented and compares with other current environmental epidemiological studies in weather and health.

Mortality Displacement as a Function of Heat Event Strength in 7 US Cities

Mortality rates increase immediately after periods of high air temperature. In the days and weeks after heat events, time series may exhibit mortality displacement-periods of lower than expected mortality. We examined all-cause mortality and meteorological data from 1980 to 2009 in the cities of Atlanta, Georgia; Boston, Massachusetts; Minneapolis-St. Paul, Minnesota; Philadelphia, Pennsylvania; Phoenix, Arizona; Seattle, Washington; and St. Louis, Missouri. We modeled baseline mortality using a generalized additive model. Heat waves were defined as periods of 3 or more consecutive days in which the apparent temperature exceeded a variable percentile. For each heat wave, we calculated the sum of excess and deficit mortality. Mortality displacement, which is the ratio of grand sum deficit to grand sum excess mortality, decreased as a function of event strength in all cities. Displacement was close to 1.00 for the weakest events. At the highest temperatures, displacement varied from 0.35 (95% confidence interval: 0.21, 0.55) to 0.75 (95% confidence interval: 0.54, 0.97). We found strong evidence of acclimatization across cities. Without consideration of displacement effects, the net impacts of heat-wave mortality are likely to be significant overestimations. A statistically significant positive relationship between the onset temperature of nondisplaced heat mortality and mean warm-season temperature (R(2) = 0.78, P < 0.01) suggests that heat mortality thresholds may be predictable across cities.

A glossary for biometeorology

Here we present, for the first time, a glossary of biometeorological terms. The glossary aims to address the need for a reliable source of biometeorological definitions, thereby facilitating communication and mutual understanding in this rapidly expanding field. A total of 171 terms are defined, with reference to 234 citations. It is anticipated that the glossary will be revisited in coming years, updating terms and adding new terms, as appropriate. The glossary is intended to provide a useful resource to the biometeorology community, and to this end, readers are encouraged to contact the lead author to suggest additional terms for inclusion in later versions of the glossary as a result of new and emerging developments in the field.

Rising Temperatures, Human Health, and the Role of Adaptation

There is near consensus in the scientific community that humans will experience higher future temperatures due to the ongoing accumulation of greenhouse gases in the atmosphere. The human response to this climatic change, particularly if accompanied by a surge in extreme heat events, is a key topic being addressed by scientists across many disciplines. In this article, we review recent (2012–2015) research on human health impacts of observed and projected increases in summer temperature. We find that studies based on projected changes in climate indicate substantial increases in heat-related mortality and morbidity in the future, while observational studies based on historical climate and health records show a decrease in negative impacts during recent warming. The discrepancy between the two groups of studies generally involves how well and how quickly humans can adapt to changes in climate via physiological, behavioral, infrastructural, and/or technological adaptation, and how such adaptation is quantified.

Heat-Related Morbidity in Brisbane, Australia: Spatial Variation and Area-Level Predictors

Background: Extreme heat is a leading weather-related cause of illness and death in many locations across the globe, including subtropical Australia. The possibility of increasingly frequent and severe heat waves warrants continued efforts to reduce this health burden, which could be accomplished by targeting intervention measures toward the most vulnerable communities. Objectives: We sought to quantify spatial variability in heat-related morbidity in Brisbane, Australia, to highlight regions of the city with the greatest risk. We also aimed to find area-level social and environmental determinants of high risk within Brisbane. Methods: We used a series of hierarchical Bayesian models to examine city-wide and intracity associations between temperature and morbidity using a 2007–2011 time series of geographically referenced hospital admissions data. The models accounted for long-term time trends, seasonality, and day of week and holiday effects. Results: On average, a 10°C increase in daily maximum temperature during the summer was associated with a 7.2% increase in hospital admissions (95% CI: 4.7, 9.8%) on the following day. Positive statistically significant relationships between admissions and temperature were found for 16 of the city’s 158 areas; negative relationships were found for 5 areas. High-risk areas were associated with a lack of high income earners and higher population density. Conclusions: Geographically targeted public health strategies for extreme heat may be effective in Brisbane, because morbidity risk was found to be spatially variable. Emergency responders, health officials, and city planners could focus on short- and long-term intervention measures that reach communities in the city with lower incomes and higher population densities, including reduction of urban heat island effects. Citation: Hondula DM, Barnett AG. 2014. Heat-related morbidity in Brisbane, Australia: spatial variation and area-level predictors. Environ Health Perspect 122:831–836; http://dx.doi.org/10.1289/ehp.1307496

Challenges associated with projecting urbanization-induced heat-related mortality

Maricopa County, Arizona, anchor to the fastest growing megapolitan area in the United States, is located in a hot desert climate where extreme temperatures are associated with elevated risk of mortality. Continued urbanization in the region will impact atmospheric temperatures and, as a result, potentially affect human health. We aimed to quantify the number of excess deaths attributable to heat in Maricopa County based on three future urbanization and adaptation scenarios and multiple exposure variables. Two scenarios (low and high growth projections) represent the maximum possible uncertainty range associated with urbanization in central Arizona, and a third represents the adaptation of high-albedo cool roof technology. Using a Poisson regression model, we related temperature to mortality using data spanning 1983-2007. Regional climate model simulations based on 2050-projected urbanization scenarios for Maricopa County generated distributions of temperature change, and from these predicted changes future excess heat-related mortality was estimated. Subject to urbanization scenario and exposure variable utilized, projections of heat-related mortality ranged from a decrease of 46 deaths per year (-95%) to an increase of 339 deaths per year (+359%). Projections based on minimum temperature showed the greatest increase for all expansion and adaptation scenarios and were substantially higher than those for daily mean temperature. Projections based on maximum temperature were largely associated with declining mortality. Low-growth and adaptation scenarios led to the smallest increase in predicted heat-related mortality based on mean temperature projections. Use of only one exposure variable to project future heat-related deaths may therefore be misrepresentative in terms of direction of change and magnitude of effects. Because urbanization-induced impacts can vary across the diurnal cycle, projections of heat-related health outcomes that do not consider place-based, time-varying urban heat island effects are neglecting essential elements for policy relevant decision-making.

Increasing frequencies of warm and humid air masses over the conterminous United States from 1948 to 2005

Time series of individual climate variables, such as air temperature and precipitation, have been thoroughly examined to evaluate climate change, but few studies have evaluated how air masses have varied over time. We use the Spatial Synoptic Classification air mass approach to classify multivariate meteorological surface variables into discrete groups and examine trends in air mass frequencies over the period 1948-2005 for the continental United States. We observe increases in warm, moist air masses at the expense of cold, dry air masses, consistent with expectations in an atmosphere with increasing greenhouse gas concentrations. Temporal variations in the North Atlantic Oscillation, Pacific/North American teleconnection pattern, Arctic Oscillation, and El Nino-Southern Oscillation partially explain some of these observed trends in winter.

Geographic dimensions of heat-related mortality in seven U.S. cities

Spatially targeted interventions may help protect the public when extreme heat occurs. Health outcome data are increasingly being used to map intra-urban variability in heat-health risks, but there has been little effort to compare patterns and risk factors between cities. We sought to identify places within large metropolitan areas where the mortality rate is highest on hot summer days and determine if characteristics of high-risk areas are consistent from one city to another. A Poisson regression model was adapted to quantify temperature-mortality relationships at the postal code scale based on 2.1 million records of daily all-cause mortality counts from seven U.S. cities. Multivariate spatial regression models were then used to determine the demographic and environmental variables most closely associated with intra-city variability in risk. Significant mortality increases on extreme heat days were confined to 12-44% of postal codes comprising each city. Places with greater risk had more developed land, young, elderly, and minority residents, and lower income and educational attainment, but the key explanatory variables varied from one city to another. Regression models accounted for 14-34% of the spatial variability in heat-related mortality. The results emphasize the need for public health plans for heat to be locally tailored and not assume that pre-identified vulnerability indicators are universally applicable. As known risk factors accounted for no more than one third of the spatial variability in heat-health outcomes, consideration of health outcome data is important in efforts to identify and protect residents of the places where the heat-related health risks are the highest.

Multiple Trigger Points for Quantifying Heat-Health Impacts: New Evidence from a Hot Climate

Background Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events. Objectives This quantitative study was designed to link temperature with mortality and morbidity events in Maricopa County, Arizona, USA, with a focus on the summer season. Methods Using Poisson regression models that controlled for temporal confounders, we assessed daily temperature–health associations for a suite of mortality and morbidity events, diagnoses, and temperature metrics. Minimum risk temperatures, increasing risk temperatures, and excess risk temperatures were statistically identified to represent different “trigger points” at which heat-health intervention measures might be activated. Results We found significant and consistent associations of high environmental temperature with all-cause mortality, cardiovascular mortality, heat-related mortality, and mortality resulting from conditions that are consequences of heat and dehydration. Hospitalizations and emergency department visits due to heat-related conditions and conditions associated with consequences of heat and dehydration were also strongly associated with high temperatures, and there were several times more of those events than there were deaths. For each temperature metric, we observed large contrasts in trigger points (up to 22°C) across multiple health events and diagnoses. Conclusion Consideration of multiple health events and diagnoses together with a comprehensive approach to identifying threshold temperatures revealed large differences in trigger points for possible interventions related to heat. Providing an array of heat trigger points applicable for different end-users may improve the public health response to a problem that is projected to worsen in the coming decades. Citation Petitti DB, Hondula DM, Yang S, Harlan SL, Chowell G. 2016. Multiple trigger points for quantifying heat-health impacts: new evidence from a hot climate. Environ Health Perspect 124:176–183; http://dx.doi.org/10.1289/ehp.1409119