Estimating a Causal Exposure Response Function with a Continuous Error-Prone Exposure: A Study of Fine Particulate Matter and All-Cause Mortality.

ABSTRACT: Numerous studies have examined the associations between long-term exposure to fine particulate matter (PM_2.5) and adverse health outcomes. Recently, many of these studies have begun to employ high-resolution predicted PM_2.5 concentrations, which are subject to measurement error. Previous approaches for exposure measurement error correction have either been applied in non-causal settings or have only considered a categorical exposure. Moreover, most procedures have failed to account for uncertainty induced by error correction when fitting an exposure-response function (ERF). To remedy these deficiencies, we develop a multiple imputation framework that combines regression calibration and Bayesian techniques to estimate a causal ERF. We demonstrate how the output of the

SUBMITTER: Josey KP 

PROVIDER: S-EPMC10103900 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature