A Dynamic Spatial Factor Model for Speciated Pollutants and Adverse Birth Outcomes

• Activity Number: 91
• Type: Invited
• Date/Time: Sunday, August 9, 2015 : 9:30 PM to 10:15 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Maria A. Terres* and Montserrat Fuentes
• Companies: North Carolina State University and North Carolina State University
• Keywords: dynamic factor model ; spatio-temporal ; multivariate ; speciated pollutants ; birth defects

Abstract

Researchers believe that exposure to high concentrations of air pollution during pregnancy may significantly 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 effects on perinatal health. However, due to correlations between these speciated pollutants it can be difficult to decipher their effects 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 coherently interpolated to provide measurements at the pregnant mothers' homes to be used in a model for birth outcomes. The model for birth outcomes allows the impacts of these factors to vary across different 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.