Spatial-temporal modeling of the association between air pollution exposure and preterm birth: identifying critical windows of exposure

Joshua Warren; Montserrat Fuentes; Amy Herring; Peter Langlois

doi:10.1111/j.1541-0420.2012.01774.x

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Spatial-temporal modeling of the association between air pollution exposure and preterm birth: identifying critical windows of exposure

Journal article

Open access

Peer reviewed

Spatial-temporal modeling of the association between air pollution exposure and preterm birth: identifying critical windows of exposure

Joshua Warren, Montserrat Fuentes, Amy Herring and Peter Langlois

Biometrics, Vol.68(4), pp.1157-1167

12/2012

DOI: 10.1111/j.1541-0420.2012.01774.x

PMCID: PMC3422613

PMID: 22568640

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https://doi.org/10.1111/j.1541-0420.2012.01774.xView

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Abstract

Exposure to high levels of air pollution during the pregnancy is associated with increased probability of preterm birth (PTB), a major cause of infant morbidity and mortality. New statistical methodology is required to specifically determine when a particular pollutant impacts the PTB outcome, to determine the role of different pollutants, and to characterize the spatial variability in these results. We develop a new Bayesian spatial model for PTB which identifies susceptible windows throughout the pregnancy jointly for multiple pollutants (PM(2.5) , ozone) while allowing these windows to vary continuously across space and time. We geo-code vital record birth data from Texas (2002-2004) and link them with standard pollution monitoring data and a newly introduced EPA product of calibrated air pollution model output. We apply the fully spatial model to a region of 13 counties in eastern Texas consisting of highly urban as well as rural areas. Our results indicate significant signal in the first two trimesters of pregnancy with different pollutants leading to different critical windows. Introducing the spatial aspect uncovers critical windows previously unidentified when space is ignored. A proper inference procedure is introduced to correctly analyze these windows.

Air Pollution - statistics & numerical data

Prenatal Exposure Delayed Effects - epidemiology

Humans

Risk Factors

Proportional Hazards Models

Male

Models, Statistical

Premature Birth - epidemiology

Incidence

Pregnancy

Computer Simulation

Female

Environmental Exposure - statistics & numerical data

Texas - epidemiology

Details

Title: Subtitle: Spatial-temporal modeling of the association between air pollution exposure and preterm birth: identifying critical windows of exposure
Creators: Joshua Warren - Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7420, USA. joshuawa@email.unc.edu
Montserrat Fuentes
Amy Herring
Peter Langlois
Resource Type: Journal article
Publication Details: Biometrics, Vol.68(4), pp.1157-1167
DOI: 10.1111/j.1541-0420.2012.01774.x
PMID: 22568640
PMCID: PMC3422613
NLM abbreviation: Biometrics
ISSN: 0006-341X
eISSN: 1541-0420
Publisher: United States
Grant note: 5R01ES014843-02 / NIEHS NIH HHS R01 ES014843 / NIEHS NIH HHS R24 HD050924 / NICHD NIH HHS R01 ES020619 / NIEHS NIH HHS
Language: English
Date published: 12/2012
Academic Unit: Statistics and Actuarial Science; President; Biostatistics
Record Identifier: 9984065772902771

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