Estimating the Combined Effects of Natural and Built Environmental Exposures on Birthweight among Urban Residents in Massachusetts

Maayan Yitshak-Sade, M. Patricia Fabian, Kevin J. Lane, Jaime E. Hart, Joel D. Schwartz, Francine Laden, Peter James, Kelvin C. Fong, Itai Kloog and Antonella Zanobetti
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Maayan Yitshak-Sade: Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
M. Patricia Fabian: Department of Environmental Health, Boston University School of Public Health, Boston, MA 02118, USA
Kevin J. Lane: Department of Environmental Health, Boston University School of Public Health, Boston, MA 02118, USA
Jaime E. Hart: Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
Joel D. Schwartz: Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
Francine Laden: Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
Peter James: Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
Kelvin C. Fong: Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
Itai Kloog: Department of Geography and Environmental Development, Faculty of Humanities and Social Sciences, Ben-Gurion University, Beer-Sheva 84105, Israel
Antonella Zanobetti: Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA

IJERPH, 2020, vol. 17, issue 23, 1-16

Abstract: Intrauterine growth has health implications both in childhood and adulthood. Birthweight is partially determined by prenatal environmental exposures. We aim to identify important predictors of birthweight out of a set of environmental, built environment exposures, and socioeconomic environment variables during pregnancy (i.e., fine particulate matter (PM 2.5 ), temperature, greenness, walkability, noise, and economic indices). We included all singleton live births of mothers who resided in urban census block-groups and delivered in Massachusetts between 2001 and 2011 ( n = 640,659). We used an elastic-net model to select important predictors of birthweight and constructed a multivariate model including the selected predictors, with adjustment for confounders. We additionally used a weighted quantile sum regression to assess the contribution of each exposure to differences in birthweight. All exposures were selected as important predictors of birthweight. In the multivariate model, lower birthweight was significantly associated with lower greenness and with higher temperature, walkability, noise, and segregation of the “high income” group. Treating the exposures individually, nighttime noise had the highest weight in its contribution to lower birthweight. In conclusion, after accounting for individual confounders, maternal environmental exposures, built environment exposures, and socioeconomic environment during pregnancy were important predictors of birthweight, emphasizing the role of these exposures in fetal growth and development.

Keywords: birthweight; exposome; air pollution; temperature; noise; greenness (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
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