Disparities by race in heat-related mortality in four US cities: the role of air conditioning prevalence.
Daily mortality is typically higher on hot days in urban areas, and certain population groups experience disproportionate risk. Air conditioning (AC) has been recommended to mitigate heat-related illness and death. We examined whether AC prevalence explained differing heat-related mortality effects by race. Poisson regression was used to model daily mortality in Chicago, Detroit, Minneapolis, and Pittsburgh. Predictors included natural splines of time (to control seasonal patterns); mean daily apparent temperature on the day of death, and averaged over lags 1-3; barometric pressure; day of week; and a linear term for airborne particles. Separate, city-specific models were fit to death counts stratified by race (Black or White) to derive the percent change in mortality at 29 degrees C, relative to 15 degrees C (lag 0). Next, city-specific effects were regressed on city- and race-specific AC prevalence. Combined effect estimates across all cities were calculated using inverse variance-weighted averages. Prevalence of central AC among Black households was less than half that among White households in all four cities, and deaths among Blacks were more strongly associated with hot temperatures. Central AC prevalence explained some of the differences in heat effects by race, but room-unit AC did not. Efforts to reduce disparities in heat-related mortality should consider access to AC.
O'Neill
Marie S
MS
The Robert Wood Johnson Health & Society Scholars Program, Center for Social Epidemiology and Population Health, University of Michigan, Ann Arbor, MI 48104-2548, USA. marieo@umich.edu
Zanobetti
Antonella
A
Schwartz
Joel
J
D001741:Black or African American / Q000706:statistics & numerical data*; D000389:Air Conditioning / Q000706:statistics & numerical data*; D002947:Cities; D004781:Environmental Exposure / Q000009:adverse effects; D006359:Heat Exhaustion / Q000401:mortality* / Q000517:prevention & control; D006801:Humans; D016012:Poisson Distribution; D015995:Prevalence; D012044:Regression Analysis; D012621:Seasons; D014481:United States / Q000453:epidemiology; D014505:Urban Population / Q000706:statistics & numerical data*; D044465:White People / Q000706:statistics & numerical data*