期刊
BIOSTATISTICS
卷 12, 期 4, 页码 637-652出版社
OXFORD UNIV PRESS
DOI: 10.1093/biostatistics/kxr002
关键词
Air pollution; Coarse particulate matter; Exposure measurement error; Multisite time series analysis
资金
- United States Environmental Protection Agency [R83622, RD-83241701]
- National Institute for Environmental Health Sciences [ES012054-03]
- National Institute for Environmental Health Sciences Center in Urban Environmental Health [P30 ES 03819]
In air pollution epidemiology, there is a growing interest in estimating the health effects of coarse particulate matter (PM) with aerodynamic diameter between 2.5 and 10 mu m. Coarse PM concentrations can exhibit considerable spatial heterogeneity because the particles travel shorter distances and do not remain suspended in the atmosphere for an extended period of time. In this paper, we develop a modeling approach for estimating the short-term effects of air pollution in time series analysis when the ambient concentrations vary spatially within the study region. Specifically, our approach quantifies the error in the exposure variable by characterizing, on any given day, the disagreement in ambient concentrations measured across monitoring stations. This is accomplished by viewing monitor-level measurements as error-prone repeated measurements of the unobserved population average exposure. Inference is carried out in a Bayesian framework to fully account for uncertainty in the estimation of model parameters. Finally, by using different exposure indicators, we investigate the sensitivity of the association between coarse PM and daily hospital admissions based on a recent national multisite time series analysis. Among Medicare enrollees from 59 US counties between the period 1999 and 2005, we find a consistent positive association between coarse PM and same-day admission for cardiovascular diseases.
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