Accounting for Exposure Measurement Error in Gridded Air Pollution Estimates in Assessing the Association of PM_2.5 Exposures with Health Outcomes in Cohort Studies.

ABSTRACT: There is increasing interest in addressing measurement error in gridded exposure estimates. Here, we provide a framework to account for exposure measurement error in gridded air pollution estimates used for health effects estimation, i.e., when numerical air quality models or satellite-derived data are the principal source of exposure data. We employed a two-stage Bayesian hierarchical modeling framework consisting of an exposure measurement error model and a health model, linking the unobserved true ambient exposure at the residential address for each participant in the cohort to health outcomes. In sensitivity analysis, we considered different health models, spatial smoothing parameters, and spatial resolutions (1.33 and 4 km grid cells) for observation-fused CMAQ output. In an example a

SUBMITTER: Park ES 

PROVIDER: S-EPMC12801408 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature