Multi-pollutant exposure profiles associated with term low birth weight in Los Angeles County

• DOI: 10.1016/j.envint.2016.02.011
• Publication Date: 2016-02-16T18:07:10Z
• Authors: Eric Coker; Silvia Liverani; Jo Kay Ghosh; Michael Jerrett; Bernardo Beckerman; Arthur Li; Beate Ritz; John Molitor
• Keywords: Odds

Research indicates that multiple outdoor air pollutants and adverse neighborhood conditions are spatially correlated. Yet health risks associated with concurrent exposure to pollution mixtures clustered factors remain underexplored. Statistical models assess the effects from pollutant limited, due problems of collinearity between area-level covariates, increases in covariate dimensionality. Here we identify profiles contextual within Los Angeles (LA) County. We then relate these term low birth weight (TLBW). used land use regression estimate NO2, NO, PM2.5 concentrations averaged over census block groups generate profile clusters group-level clusters, using a Bayesian method. Pollutant cluster risk estimation was implemented multilevel hierarchical model, adjusting for individual-level random effects, modeling structured unstructured residual error. Our analysis found 13 profiles. Correlations study varied widely across clusters. elevated exhibited increased log odds TLBW, those PM2.5, NO showed lower TLBW. The spatial patterning on combined between-pollutant correlations imply traffic-related primary influence TLBW risks. Furthermore, greatest had more socioeconomic, demographic, housing conditions. data indicate that, while high-risk largely overlaps cluster, both contribute controlling other.