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

Kimberly A Kaufeld; Montse Fuentes; Brian J Reich; Amy H Herring; Gary M Shaw; Maria A Terres

doi:10.3390/ijerph14091046

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

Journal article

Open access

Peer reviewed

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

Kimberly A Kaufeld, Montse Fuentes, Brian J Reich, Amy H Herring, Gary M Shaw and Maria A Terres

International journal of environmental research and public health, Vol.14(9), p.1046

09/11/2017

DOI: 10.3390/ijerph14091046

PMCID: PMC5615583

PMID: 28891988

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https://doi.org/10.3390/ijerph14091046View

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Abstract

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. The proposed methodology is illustrated using pollutant monitoring data from the Environmental Protection Agency and birth records from the National Birth Defect Prevention Study.

Models, Theoretical

Pregnancy

Young Adult

Air Pollutants - analysis

Multivariate Analysis

Congenital Abnormalities - epidemiology

Particulate Matter - analysis

Humans

Bayes Theorem

Adult

Female

Environmental Exposure - analysis

Details

Title: Subtitle: A Multivariate Dynamic Spatial Factor Model for Speciated Pollutants and Adverse Birth Outcomes
Creators: Kimberly A Kaufeld - Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM 87545, USA. kkaufeld@lanl.gov
Montse Fuentes - Department of Biostatistics and Statistics and Operations Research, Virginia Commonwealth University, Richmond, VA 23284, USA. mfuentes@vcu.edu
Brian J Reich - Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA. bjreich@ncsu.edu
Amy H Herring - Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. herring@unc.edu
Gary M Shaw - Division of Neonatology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA. gmshaw@stanford.edu
Maria A Terres - The Climate Corporation, San Francisco, CA 94103, USA. mterres.stat@gmail.com
Resource Type: Journal article
Publication Details: International journal of environmental research and public health, Vol.14(9), p.1046
DOI: 10.3390/ijerph14091046
PMID: 28891988
PMCID: PMC5615583
NLM abbreviation: Int J Environ Res Public Health
ISSN: 1661-7827
eISSN: 1660-4601
Publisher: Switzerland
Grant note: R01 ES027892 / NIEHS NIH HHS R01 ES014843 / NIEHS NIH HHS P2C HD050924 / NICHD NIH HHS U01 DD001033 / NCBDD CDC HHS
Language: English
Date published: 09/11/2017
Academic Unit: Statistics and Actuarial Science; President; Biostatistics
Record Identifier: 9984065881802771

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