Am J Epidemiol 2003; 157:1055-1065.
Copyright © 2003 by Johns
Hopkins Bloomberg School of Public Health
ORIGINAL CONTRIBUTIONS |
Airborne Particulate Matter and Mortality: Timescale Effects in Four US Cities
1 Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
2 Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
While time-series studies have consistently provided evidence for an effect of particulate air pollution on mortality, uncertainty remains as to the extent of the life-shortening implied by those associations. In this paper, the authors estimate the association between air pollution and mortality using different timescales of variation in the air pollution time series to gain further insight into this question. The authors’ method is based on a Fourier decomposition of air pollution time series into a set of independent exposure variables, each representing a different timescale. The authors then use this set of variables as predictors in a Poisson regression model to estimate a separate relative rate of mortality for each exposure timescale. The method is applied to a database containing information on daily mortality, particulate air pollution, and weather in four US cities (Pittsburgh, Pennsylvania; Minneapolis, Minnesota; Seattle, Washington; and Chicago, Illinois) from the period 1987–1994. The authors found larger relative rates of mortality associated with particulate air pollution at longer timescale variations (14 days–2 months) than at shorter timescales (1–4 days). These analyses provide additional evidence that associations between particle indexes and mortality do not imply only an advance in the timing of death by a few days for frail individuals.
air pollution; Fourier analysis; hierarchical model; mortality; Poisson distribution; time factors; time series
Abbreviations: Abbreviations: CI, confidence interval; PM10, particulate matter with an aerodynamic diameter ≤10 µg/m3.
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