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

• DOI: 10.1016/j.envres.2015.06.044
• Publication Date: 2015-07-18T00:30:16Z
• Authors: Eric Coker; Jokay Ghosh; Michael Jerrett; Virgilio Gomez-Rubio; Bernardo Beckerman; Myles Cockburn; Silvia Liverani; Jason Su; Arthur Li; Molly L Kile; Beate Ritz; John Molitor
• Keywords: Environmental epidemiology; Exposure Assessment

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 have generally assumed the exposure-response PM2.5 on TLBW be same throughout a large geographical area. Health effects related exposures, however, may not uniformly distributed spatially, creating need for explicitly investigate spatial distribution relationship between individual-level and TLBW. Here, we examine overall spatially varying urban Los Angeles (LA) County, California. We estimated from combination land use regression (LUR), aerosol optical depth remote sensing, atmospheric modeling techniques. Exposures were assigned LA County individual pregnancies identified electronic certificates years 1995-2006 (N=1,359,284) provided by California Department Public Health. used single pollutant multivariate logistic model, multilevel structured unstructured random set in Bayesian framework estimate global at census tract level. Overall, increased level was county-wide. The demonstrated uniform across County. Rather, magnitude certainty estimates log odds greatest core Central Southern tracts. These results patterned, simply estimating obscures disparities suggested patterns effects. Studies incorporate coefficients allow us identify areas where air adverse outcomes most severe policies further reduce might effective.