Environmental Science and Pollution Research

, Volume 25, Issue 30, pp 30375–30389 | Cite as

Industrial air pollution and low birth weight: a case-control study in Texas, USA

  • Xi Gong
  • Yan Lin
  • F. Benjamin ZhanEmail author
Research Article


Many studies have investigated associations between maternal residential exposures to air pollutants and low birth weight (LBW) in offspring. However, most studies focused on the criteria air pollutants (PM2.5, PM10, O3, NO2, SO2, CO, and Pb), and only a few studies examined the potential impact of other air pollutants on LBW. This study investigated associations between maternal residential exposure to industrial air emissions of 449 toxics release inventory (TRI) chemicals and LBW in offspring using a case-control study design based on a large dataset consisting of 94,106 LBW cases and 376,424 controls in Texas from 1996 to 2008. Maternal residential exposure to chemicals was estimated using a modified version of the emission-weighted proximity model (EWPM). The model takes into account reported quantities of annual air emission from industrial facilities and the distances between the locations of industrial facilities and maternal residence locations. Binary logistic regression was used to compute odds ratios measuring the association between maternal exposure to different TRI chemicals and LBW in offspring. Odds ratios were adjusted for child’s sex, birth year, gestational length, maternal age, education, race/ethnicity, and public health region of maternal residence. Among the ten chemicals selected for a complete analysis, maternal residential exposures to five TRI chemicals were positively associated with LBW in offspring. These five chemicals include acetamide (adjusted odds ratio [aOR] 2.29, 95% confidence interval [CI] 1.24, 4.20), p-phenylenediamine (aOR 1.63, 95% CI 1.18, 2.25), 2,2-dichloro-1,1,1-trifluoroethane (aOR 1.41, 95% CI 1.20, 1.66), tributyltin methacrylate (aOR 1.20, 95% CI 1.06, 1.36), and 1,1,1-trichloroethane (aOR 1.11, 95% CI 1.03, 1.20). These findings suggest that maternal residential proximity to industrial air emissions of some chemicals during pregnancy may be associated with LBW in offspring.


Air pollution GIS Health Toxic release inventory (TRI) chemicals Low birth weight (LBW) Exposure assessment 



ambient air pollution


adjusted odds ratio


criteria air pollutant


Centers for Disease Control and Prevention


confidence interval


Texas Department of State Health Services


emission weighted proximity model


low birth weight


National Oceanic and Atmospheric Administration


odds ratio


toxic release inventory


United States Environmental Protection Agency



The research reported in this article was made possible in part by a U.S. EPA-STAR grant (#R834790). The data used in the analyses were obtained from the Center for Health Statistics in the Texas Department of State Health Services (DSHS) and United States Environmental Protection Agency (U.S. EPA). The contents are solely the responsibility of the authors and do not necessarily represent the official views of the U.S. EPA and the Texas DSHS. Furthermore, U.S. EPA, the Texas DSHS, and the authors do not endorse the purchase of any commercial products or services mentioned in this article. The authors wish to thank the support from the U.S. EPA and the Texas DSHS. Xi Gong and F. Benjamin Zhan appreciated the helpful discussions with Drs. Jean D. Brender and Peter H. Langlois about the case-control study design reported in the article. The authors greatly appreciate the helpful comments and suggestions from the editor and three anonymous reviewers.

Compliance with ethical standards

Competing interest

The authors declare that they have no competing interest.

Supplementary material

11356_2018_2941_MOESM1_ESM.docx (55 kb)
ESM 1 (DOCX 54 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Geography & Environmental StudiesUniversity of New MexicoAlbuquerqueUSA
  2. 2.Texas Center for Geographic Information Science, Department of GeographyTexas State UniversitySan MarcosUSA

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