On the use of a PM2.5 exposure simulator to explain birthweight

Authors


Abstract

In relating pollution to birth outcomes, maternal exposure has usually been described using monitoring data. Such characterization provides a misrepresentation of exposure as (i) it does not take into account the spatial misalignment between an individual's residence and monitoring sites, and (ii) it ignores the fact that individuals spend most of their time indoors and typically in more than one location. In this paper, we break with previous studies by using a stochastic simulator to describe personal exposure (to particulate matter) and then relate simulated exposures at the individual level to the health outcome (birthweight) rather than aggregating to a selected spatial unit. We propose a hierarchical model that, at the first stage, specifies a linear relationship between birthweight and personal exposure, adjusting for individual risk factors and introduces random spatial effects for the census tract of maternal residence. At the second stage, we specify the distribution of each individual's personal exposure using the empirical distribution yielded by the stochastic simulator as well as a model for the spatial random effects. We have applied our framework to analyze birthweight data from 14 counties in North Carolina in years 2001 and 2002. We investigate whether there are certain aspects and time windows of exposure that are more detrimental to birthweight by building different exposure metrics which we incorporate, one by one, in our hierarchical model. To assess the difference in relating ambient exposure (i.e., exposure to ambient concentration) to birthweight versus personal exposure to birthweight, we compare estimates of the effect of air pollution obtained from hierarchical models that linearly relate ambient exposure and birthweight to those obtained from our modeling framework. Our analysis does not show a significant effect of PM2.5 on birthweight for reasons which we discuss. However, our modeling framework serves as a template for general analyses of the relationship between personal exposure and longer term health endpoints. Copyright © 2011 John Wiley & Sons, Ltd.

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