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Modeling spatial effects of PM₂.₅ on term low birth weight in Los Angeles County

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https://ir.library.oregonstate.edu/concern/articles/9306t121f

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  • Air pollution epidemiological studies suggest that elevated exposure to fine particulate matter (PM₂.₅) is associated with higher prevalence of term low birth weight (TLBW). Previous studies have generally assumed the exposure–response of PM₂.₅ on TLBW to be the same throughout a large geographical area. Health effects related to PM₂.₅ exposures, however, may not be uniformly distributed spatially, creating a need for studies that explicitly investigate the spatial distribution of the exposure–response relationship between individual-level exposure to PM₂.₅ and TLBW. Here, we examine the overall and spatially varying exposure–response relationship between PM₂.₅ and TLBW throughout urban Los Angeles (LA) County, California. We estimated PM₂.₅ from a combination of land use regression (LUR), aerosol optical depth from remote sensing, and atmospheric modeling techniques. Exposures were assigned to LA County individual pregnancies identified from electronic birth certificates between the years 1995-2006 (N=1,359,284) provided by the California Department of Public Health. We used a single pollutant multivariate logistic regression model, with multilevel spatially structured and unstructured random effects set in a Bayesian framework to estimate global and spatially varying pollutant effects on TLBW at the census tract level. Overall, increased PM₂.₅ level was associated with higher prevalence of TLBW county-wide. The spatial random effects model, however, demonstrated that the exposure–response for PM₂.₅ and TLBW was not uniform across urban LA County. Rather, the magnitude and certainty of the exposure–response estimates for PM₂.₅ on log odds of TLBW were greatest in the urban core of Central and Southern LA County census tracts. These results suggest that the effects may be spatially patterned, and that simply estimating global pollutant effects obscures disparities suggested by spatial patterns of effects. Studies that incorporate spatial multilevel modeling with random coefficients allow us to identify areas where air pollutant effects on adverse birth outcomes may be most severe and policies to further reduce air pollution might be most effective
  • KEYWORDS: Multilevel modeling, Term low birth weight, Air pollution, PM2.5, Spatial effects, PM₂.₅
  • This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Elsevier. The published article can be found at: http://www.journals.elsevier.com/environmental-research/
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  • Coker, E., Ghosh, J., Jerrett, M., Gomez-Rubio, V., Beckerman, B., Cockburn, M., ... & Molitor, J. (2015). Modeling spatial effects of PM₂.₅ on term low birth weight in Los Angeles County. Environmental Research, 142, 354-364. doi:10.1016/j.envres.2015.06.044
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  • 142
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  • Research described in this article was conducted under contract to the Health Effects Institute (HEI), an organization jointly funded by the United States Environmental Protection Agency (EPA) (Assistance Award No. R-82811201) and certain motor vehicle and engine manufacturers.
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