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Activity Number:
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406
- Spatio-Temporal Methods in Ecology and Epidemiology
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Type:
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Contributed
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Date/Time:
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Tuesday, August 1, 2017 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics and the Environment
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Abstract #324992
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Title:
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A Multivariate Dynamic Spatial Factor Model for Speciated Pollutants and Adverse Birth Outcomes
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Author(s):
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Kimberly Kaufeld*
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Companies:
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Los Alamos National Laboratory
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Keywords:
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spatio-temporal ;
Bayesian ;
factor analysis ;
multivariate ;
air pollution
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Abstract:
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Evidence suggests that exposure to high concentrations of air pollution during pregnancy may signi ficantly increase the risk of birth defects and other adverse birth outcomes. While current regulations put limits on total PM2:5 concentrations, there are many speciated pollutants within this size class that likely have varying eff ects on perinatal health. However, due to correlations between these speciated pollutants it can be dicult to de- cipher their eff ects in a model for birth outcomes. To combat this difficulty we develop a multivariate spatio-temporal Bayesian model for the speciated particulate matter using dynamic spatial factors. These spatial factors can then be interpolated to the pregnant mothers homes to be used in a birth outcomes model. The model for birth outcomes allows the impacts of pollutants to vary across di fferent weeks of the pregnancy in order to identify susceptible periods. The proposed methodology is illustrated using pollutant monitoring data from the Environmental Protection Agency and birth records from the National Birth Defect Prevention Study.
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Authors who are presenting talks have a * after their name.
