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  • Title: Effects of exposure measurement error on particle matter epidemiology: a simulation using data from a panel study in Baltimore, MD.
    Author: Schwartz J, Sarnat JA, Coull BA, Wilson WE.
    Journal: J Expo Sci Environ Epidemiol; 2007 Dec; 17 Suppl 2():S2-10. PubMed ID: 18079760.
    Abstract:
    Ascertaining the true risk associated with exposure to particulate matter (PM) is difficult, given the fact that pollutant components are frequently correlated with each other and with other gaseous pollutants; relationships between ambient concentrations and personal exposures are often not well understood; and PM, unlike its gaseous co-pollutants, does not represent a single chemical. In order to examine differences between observed versus true health risk estimate from epidemiologic studies, we conducted a simulation using data from a recent multi-pollutant exposure assessment study in Baltimore, MD. The objectives of the simulation were twofold: (a) to estimate the distribution of personal air pollutant exposures one might expect to observe within a population, given the corresponding ambient concentrations found in that location and; (b) using an assumed true health risk with exposure to one pollutant, to estimate the distribution of health risk estimates likely to be observed in an epidemiologic study using ambient pollutant concentrations as a surrogate of exposure as compared with actual personal pollutant exposures. Results from the simulations showed that PM2.5 was the only pollutant where a true association with its total personal exposures resulted in a significant observed association with its ambient concentrations. The simulated results also showed that true health risks associated with personal exposure to O3 and NO2 would result in no significant observed associations with any of their respective ambient concentrations. Conversely, a true association with PM2.5 would result in a significant, observed association with NO2 (beta=0.0115, 95% confidence interval (CI): 0.0056, 0.0185) and a true association with exposure to SO4(2-) would result in an observed significant association with O3 (beta=0.0035, 95% CI: 0.0021, 0.0051) given the covariance of the ambient pollutant concentrations. The results provide an indication that, in Baltimore during this study period, ambient gaseous concentrations may not have been adequate surrogates for corresponding personal gaseous exposures to allow the question to be investigated using central site monitors. Alternatively, the findings may suggest that in some locations, observed associations with the gaseous pollutants should be interpreted with caution, as they may be reflecting associations with PM or one of its chemical components.
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