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Activity Number: 116
Type: Invited
Date/Time: Monday, August 4, 2008 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract - #300265
Title: Health Effects of Chemical Constituents and Sources of Fine Particulate Matter
Author(s): Francesca Dominici*+
Companies: Johns Hopkins University
Address: Department of Biostatistics, Baltimore, MD, 21205,
Keywords: particulate matter ; chemical mixture ; Bayesian hierarchical models
Abstract:

Optimal regulatory control of particulate matter (PM) is hindered by an insufficient understanding of the chemical characteristics of the PM mixture that determine its toxicity. Approximately 50 correlated chemical components of PM2.5 are monitored almost daily for several hundred monitoring stations in the US. A critical question is whether a small subset of these chemical constituents, alone or through their interactions, are responsible for the estimated harmful effects of PM. To estimate the toxicity of the PM mixture we have assembled a national data set on health outcomes, PM chemical constituents, and all the important confounders. In this talk, we will present Bayesian hierarchical regression models for analyses of these large and complex national data sets. Our modeling approaches will have the ultimate goal of estimating the health effects of PM size and chemical composition.

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Revised September, 2008