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

Journal Article · · International Journal of Environmental Research and Public Health
ORCiD logo [1];  [2];  [3];  [4];  [5];  [6]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Virginia Commonwealth Univ., Richmond, VA (United States)
  3. North Carolina State Univ., Raleigh, NC (United States)
  4. Univ. of North Carolina, Chapel Hill, NC (United States)
  5. Stanford Univ. School of Medicine, Stanford, CA (United States)
  6. The Climate Corp., San Francisco, CA (United States)
+ Show Author Affiliations

Evidence suggests that exposure to elevated concentrations of air pollution during pregnancy is associated with increased risks 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 distinct 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 speciated particulate matter using dynamic spatial factors. These spatial factors can then be interpolated to the pregnant women’s homes to be used to model birth defects. The birth defect model allows the impact of pollutants to vary across different weeks of the pregnancy in order to identify susceptible periods. Here, the proposed methodology is illustrated using pollutant monitoring data from the Environmental Protection Agency and birth records from the National Birth Defect Prevention Study.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1415413
Report Number(s):
LA-UR-17-25966; IJERGQ
Journal Information:
International Journal of Environmental Research and Public Health, Vol. 14, Issue 9; ISSN 1660-4601
Publisher:
MDPICopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

60 APPLIED LIFE SCIENCES
54 ENVIRONMENTAL SCIENCES
Mathematics
multivariate
spatiotemporal
birth defects
pollutants
factor analysis