Daily Mortality Analysis by Using Different Regression Models in Philadelphia County, 1973–1990

Abstract

Earlier investigators found that in the city of Philadelphia there exists an association between daily levels of particulate matter and mortality (Schwartz & Dockety, 7992a). To more fully explore this result, we analyzed the daily mortality data in Philadelphia using a host of independent variables including air quality indicators such as total suspended particulates CrSP), SO₂, and O₃, and weather factors such as temperature, humidity, barometric pressure, and precipitation for the years 1973–1990. A wide variety of appropriate statistical models was applied to the data, including Poisson, multiple, and autoregression models. Our major findings on the association between mortality and daily pollution levels are that (1) the estimates of this association are related to the selection of the type of statistical model and the variables included in the model, and (2) this relationship differs across age groups, causes of death, and seasons of the year. These results are not consistent with a unique point estimate of the association between air quality and mortality.