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Activity Number: 647
Type: Contributed
Date/Time: Thursday, August 13, 2015 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract #316452
Title: Using Bayesian Hierarchical Models to Simultaneously Evaluate Multiple Pollutants Associated with Spina Bifida
Author(s): Michael Swartz* and Yi Cai and Wenyaw Chan and Elaine Symanski and Laura Mitchell and Heather Danysh and Peter Langlois and Philip Lupo
Companies: The University of Texas Health Science Center and The University of Texas at Houston and The University of Texas School of Public Health and The University of Texas Health Science Center and The University of Texas Health Science Center and Baylor College of Medicine and Texas Department of State Health Services and Baylor College of Medicine
Keywords: Bayesian Hierarchical Models ; Stochastic Search Variable Selectoin ; Environmental Epidemiology ; Air Pollution ; Birth Defects
Abstract:

Assessing the association between air pollutants and health outcomes requires multivariable models that assess multiple pollutants simultaneously. Here, we fit a Bayesian hierarchical model within a stochastic search variable selection framework to select pollutants associated with spina bifida risk, a birth defect of the spine. We simultaneously investigated 33 hazardous air pollutants (HAPS) as identified by the US Environmental Protection Agency (EPA). HAP levels were estimated for census tracts across Texas using the U.S. EPA's Assessment System for Population Exposure Nation Wide (ASPEN). Cases and controls were provided by the Texas Birth Defects Registry, and assigned to census tracts using the mother's home address at time of delivery. To model HAPs at the census tract level, and adjust for individual level covariates, we used a generalized linear model with a random intercept, and used stochastic search to select HAPs associated with spina bifida. We identified two HAPs associated with spina bifida risk: quinolone and trichloroethylene. This work is to appear in Environmental Health, 2015.


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