title: Modeling spatial effects of PM(2.5) on term low birth weight in Los Angeles County.
abstract: 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.
authors.affiliation: College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA. Electronic address: cokerer@onid.orst.edu.
authors.forename: Eric
authors.initials: E
authors.lastname: Coker
authors.affiliation: School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
authors.forename: Jokay
authors.initials: J
authors.lastname: Ghosh
authors.affiliation: School of Public Health, University of California, Berkeley, Berkeley, CA, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Jerrett
authors.affiliation: Department of Mathematics, Universidad De Castilla-La Mancha, Albacete, Spain.
authors.forename: Virgilio
authors.initials: V
authors.lastname: Gomez-Rubio
authors.affiliation: School of Public Health, University of California, Berkeley, Berkeley, CA, USA.
authors.forename: Bernardo
authors.initials: B
authors.lastname: Beckerman
authors.affiliation: Preventive Medicine and Spatial Sciences, University of Southern California, Los Angeles, CA, USA.
authors.forename: Myles
authors.initials: M
authors.lastname: Cockburn
authors.affiliation: Department of Mathematics, Brunel University, London, United Kingdom.
authors.forename: Silvia
authors.initials: S
authors.lastname: Liverani
authors.affiliation: School of Public Health, University of California, Berkeley, Berkeley, CA, USA.
authors.forename: Jason
authors.initials: J
authors.lastname: Su
authors.affiliation: Department of Information Science, City of Hope National Cancer Center, Duarte, CA, USA.
authors.forename: Arthur
authors.initials: A
authors.lastname: Li
authors.affiliation: College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA.
authors.forename: Molly L
authors.initials: ML
authors.lastname: Kile
authors.affiliation: School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
authors.forename: Beate
authors.initials: B
authors.lastname: Ritz
authors.affiliation: College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA.
authors.forename: John
authors.initials: J
authors.lastname: Molitor
mesh_terms: D000393:Air Pollutants / Q000009:adverse effects / Q000032:analysis*; D005260:Female; D006801:Humans; D007230:Infant, Low Birth Weight; D007231:Infant, Newborn; D015141:Los Angeles; D018811:Maternal Exposure / Q000706:statistics & numerical data; D015233:Models, Statistical; D052638:Particulate Matter / Q000009:adverse effects / Q000032:analysis*; D062206:Spatial Analysis; D014505:Urban Population / Q000706:statistics & numerical data
chemical_list: D000393:Air Pollutants; D052638:Particulate Matter
keywords: Air pollution; Multilevel modeling; PM(2.5); Spatial effects; Term low birth weight