Abstract
BackgroundExposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typically available surrogate exposures.MethodsDaily personal and ambient PM2.5, and when available sulfate, measurements were compiled from nine cities, over 2 to 12 days. True exposure was defined as personal exposure to PM2.5 of ambient origin. Since PM2.5 of ambient origin could only be determined for five cities, personal exposure to total PM2.5 was also considered. Surrogate exposures were estimated as ambient PM2.5 at the nearest monitor or predicted outside subjects’ homes. We estimated calibration coefficients by regressing true on surrogate exposures in random effects models.ResultsWhen monthly-averaged personal PM2.5 of ambient origin was used as the true exposure, calibration coefficients equaled 0.31 (95% CI:0.14, 0.47) for nearest monitor and 0.54 (95% CI:0.42, 0.65) for outdoor home predictions. Between-city heterogeneity was not found for outdoor home PM2.5 for either true exposure. Heterogeneity was significant for nearest monitor PM2.5, for both true exposures, but not after adjusting for city-average motor vehicle number for total personal PM2.5.ConclusionsCalibration coefficients were <1, consistent with previously reported chronic health risks using nearest monitor exposures being under-estimated when ambient concentrations are the exposure of interest. Calibration coefficients were closer to 1 for outdoor home predictions, likely reflecting less spatial error. Further research is needed to determine how our findings can be incorporated in future health studies.
Highlights
Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures
Exposure measurement error is a limitation of epidemiologic studies of fine particles (PM2.5) [1,2,3], which generally assess exposures using ambient concentrations measured at centrally located monitors
By-city summary statistics are presented in Additional file 1: Table S1, and the relationship between exposure to PM2.5 of ambient origin and ambient PM2.5 concentrations is presented in Additional file 1: Figure S1
Summary
Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. For application to cohort studies, researchers have used statistical models to predict exposures outside participant residences [9,10,11,12,13,14], accounting for spatial variation in ambient concentrations. While an improvement, such models still do not account for all sources of exposure variability, such as activity patterns, which can lead to biased results [15]. That such “biases” are the result of different target parameters of interest for the health effects of ambient concentration vs. personal or ambient source exposure [16]
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