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Fine Particulate Air Pollution and Birthweight

Differences in Associations Along the Birthweight Distribution

Fong, Kelvin C.a; Kosheleva, Annaa; Kloog, Itaib; Koutrakis, Petrosa; Laden, Francinea,c; Coull, Brent A.d; Schwartz, Joel D.a,c

doi: 10.1097/EDE.0000000000001039
Air Pollution

Background: Maternal exposure to fine particulate air pollution (PM2.5) during pregnancy is associated with lower newborn birthweight, which is a risk factor for chronic disease. Existing studies typically report the average association related with PM2.5 increase, which does not offer information about potentially varying associations at different points of the birthweight distribution.

Methods: We retrieved all birth records in Massachusetts between 2001 and 2013 then restricted our analysis to full-term live singletons (n = 775,768). Using the birthdate, gestational age, and residential address reported at time of birth, we estimated the average maternal PM2.5 exposure during pregnancy of each birth. PM2.5 predictions came from a model that incorporates satellite, land use, and meteorologic data. We applied quantile regression to quantify the association between PM2.5 and birthweight at each decile of birthweight, adjusted for individual and neighborhood covariates. We considered effect modification by indicators of individual and neighborhood socioeconomic status (SES).

Results: PM2.5 was negatively associated with birthweight. An interquartile range increase in PM2.5 was associated with a 16 g [95% confidence interval (CI) = 13, 19] lower birthweight on average, 19 g (95% CI = 15, 23) lower birthweight at the lowest decile of birthweight, and 14 g (95% CI = 9, 19) lower birthweight at the highest decile. In general, the magnitudes of negative associations were larger at lower deciles. We did not find evidence of effect modification by individual or neighborhood SES.

Conclusions: In full-term live births, PM2.5 and birthweight were negatively associated with more severe associations at lower quantiles of birthweight.

From the aDepartment of Environmental Health, Harvard T. H. Chan School of Public Health Boston, MA

bDepartment of Geography and Environmental Development, Ben-Gurion University of the Negev, Beer-Sheva, Israel

cDepartment of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA

dDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA.

Editor’s Note: A related commentary appears on p. 633.

Submitted June 18, 2018; accepted May 15, 2019.

Supported by USEPA grants RD-834798, RD-835872, RD-83615601, and NIH/NIMHD grants P50MD010428 and R00CA201542. Its contents are solely the responsibility of the grantee and do not necessarily represent the official views of the USEPA or the NIH. Further, USEPA and NIH do not endorse the purchase of any commercial products or services mentioned in the publication.

The authors report no conflicts of interest.

Data source and computer code: The fine particulate air pollution exposure data were based on publicly available remote sensing, land use, and meteorologic variables. Details on these data have previously been published and are referenced in the main text. The births outcome data can be requested from the Massachusetts Department of Public Health. The statistical analysis was based on publicly available statistical software referenced in the main text.

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Correspondence: Kelvin Fong, 401 Park Drive, Landmark Center 4th Floor West, Boston, MA 02215. E-mail:

Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.