Background: Air pollution may be related to adverse birth outcomes. Exposure information from land-based monitoring stations often suffers from limited spatial coverage. Satellite data offer an alternative data source for exposure assessment.
Methods: We used birth certificate data for births in Connecticut and Massachusetts, United States (2000–2006). Gestational exposure to PM2.5 was estimated from US Environmental Protection Agency monitoring data and from satellite data. Satellite data were processed and modeled by using two methods—denoted satellite (1) and satellite (2)—before exposure assessment. Regression models related PM2.5 exposure to birth outcomes while controlling for several confounders. Birth outcomes were mean birth weight at term birth, low birth weight at term (<2500 g), small for gestational age (SGA, <10th percentile for gestational age and sex), and preterm birth (<37 weeks).
Results: Overall, the exposure assessment method modified the magnitude of the effect estimates of PM2.5 on birth outcomes. Change in birth weight per interquartile range (2.41 μg/m3) increase in PM2.5 was −6 g (95% confidence interval = −8 to −5), −16 g (−21 to −11), and −19 g (−23 to −15), using the monitor, satellite (1), and satellite (2) methods, respectively. Adjusted odds ratios, based on the same three exposure methods, for term low birth weight were 1.01 (0.98–1.04), 1.06 (0.97–1.16), and 1.08 (1.01–1.16); for SGA, 1.03 (1.01–1.04), 1.06 (1.03–1.10), and 1.08 (1.04–1.11); and for preterm birth, 1.00 (0.99–1.02), 0.98 (0.94–1.03), and 0.99 (0.95–1.03).
Conclusions: Under exposure assessment methods, we found associations between PM2.5 exposure and adverse birth outcomes particularly for birth weight among term births and for SGA. These results add to the growing concerns that air pollution adversely affects infant health and suggest that analysis of health consequences based on satellite-based exposure assessment can provide additional useful information.
From the a School of Public Health, Yale University, New Haven, CT; bDepartment of Environmental Health, Harvard School of Public Health, Harvard University, Boston, MA; cand School of Forestry and Environmental Studies, Yale University, New Haven, CT.
This work was supported by funding from the National Institute of Environmental Health Sciences (R01ES016317 and R01ES019587).
Submitted 11 February 2013; accepted 2 August 2013; posted 14 November 2013.
The authors report no conflicts of interest.
Correspondence: Ayaz Hyder, Dalla Lana School of Public Health, University of Toronto, 155 College Street, 5th floor, Toronto, Ontario, Canada, M5T 3M7. E-mail: firstname.lastname@example.org.