Research Article Advance Publication
An Empirical Assessment of Exposure Measurement Error and Effect Attenuation in Bipollutant Epidemiologic Models
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Citation: Dionisio KL, Baxter LK, Chang HH. An Empirical Assessment of Exposure Measurement Error and Effect Attenuation in Bipollutant Epidemiologic Models. Environ Health Perspect; http://dx.doi.org/10.1289/ehp.1307772.
Received: 21 October 2013
Accepted: 3 July 2014
Advance Publication: 8 July 2014
Background: Using multipollutant models to understand combined health effects of exposure to multiple pollutants is becoming more common. However, complex relationships between pollutants and differing degrees of exposure error across pollutants can make health effect estimates from multipollutant models difficult to interpret.
Objectives: To quantify relationships between multiple pollutants and their associated exposure errors across metrics of exposure, and use empirical values to evaluate potential attenuation of coefficients in epidemiologic models.
Methods: We used three daily exposure metrics (central-site measurements, air quality model estimates, population exposure model estimates) for 193 ZIP codes in the Atlanta, Georgia metropolitan area, from 1999-2002, for PM2.5 and its components (EC, SO4), O3, CO, and NOx, to construct three types of exposure error: δspatial (comparing air quality model estimates to central-site measurements), δpopulation (comparing population exposure model estimates to air quality model estimates), and δtotal (comparing population exposure model estimates to central-site measurements). We compared exposure metrics and exposure errors within and across pollutants, and present derived attenuation factors (ratio of observed to true coefficient for pollutant of interest) for single and bipollutant model coefficients.
Results: Pollutant concentrations and their exposure errors were moderately to highly correlated (typically > 0.5), especially for CO, NOx, and EC (i.e., “local” pollutants); correlations differed across exposure metrics and types of exposure error. Spatial variability was evident, with variance of exposure error for local pollutants ranging from 0.25–0.83 for δspatial and δtotal. The attenuation of model coefficients in single and bipollutant epidemiologic models relative to the true value differed across types of exposure error, pollutants, and space.
Conclusions: Under a classical exposure error framework, attenuation may be substantial for local pollutants due to δspatial and δtotal, with true coefficients reduced by a factor typically < 0.6 (results vary for δpopulation and regional pollutants).
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