Abstract #302204

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JSM 2003 Abstract #302204
Activity Number: 81
Type: Contributed
Date/Time: Monday, August 4, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics & the Environment
Abstract - #302204
Title: A Bayesian Hierarchical Model for Human Exposure to Fine Particulate Matter in an Elderly Population
Author(s): Sandra McBride*+
Companies: Duke University
Address: 2401 Eddystone Dr., Raleigh, NC, 27612-6712,
Keywords: Bayesian hierarchical model ; human exposure ; air quality ; particulate matter
Abstract:

In 1998, the U.S. EPA conducted an epidemiology-exposure study in a retirement home in Baltimore, Maryland. For each of 28 elderly participants over a month-long period, personal concentrations of fine particulate matter, PM2.5, were measured. Extensive monitoring of PM2.5 and copollutants indoors and outdoors was conducted concurrently. We develop a Bayesian hierarchical model to explore relationships among true unobserved concentrations for each subject, individual apartment concentrations, central indoor residential concentrations, outdoor concentrations, and ambient pollutant concentrations, while accounting for important covariates. Measured concentrations are used to estimate parameters of population distributions of interest, such as the distribution of personal exposures for an individual engaging in activities throughout a day. The model incorporates missing observations through multiple data imputation. The results from this exposure model have important implications for assessing the health effects of particulate air pollution for susceptible subpopulations.

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