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

Author

Listed:
  • Kevin P. Josey

    (Harvard T.H. Chan School of Public Health)

  • Priyanka deSouza

    (University of Colorado)

  • Xiao Wu

    (Stanford University
    Stanford University)

  • Danielle Braun

    (Harvard T.H. Chan School of Public Health
    Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute)

  • Rachel Nethery

    (Harvard T.H. Chan School of Public Health)

Abstract

Numerous studies have examined the associations between long-term exposure to fine particulate matter (PM $$_{2.5}$$ 2.5 ) and adverse health outcomes. Recently, many of these studies have begun to employ high-resolution predicted PM $$_{2.5}$$ 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 measurement error correction steps can be seamlessly integrated into a Bayesian additive regression trees (BART) estimator of the causal ERF. We also demonstrate how kernel-weighted smoothing of the posterior samples from BART can be used to create a more accurate ERF estimate. Our proposed approach also properly propagates the exposure measurement error uncertainty to yield accurate standard error estimates. We assess the robustness of our proposed approach in an extensive simulation study. We then apply our methodology to estimate the effects of PM $$_{2.5}$$ 2.5 on all-cause mortality among Medicare enrollees in New England from 2000 to 2012. Supplementary materials accompanying this paper appear on-line

Suggested Citation

  • Kevin P. Josey & Priyanka deSouza & Xiao Wu & Danielle Braun & Rachel Nethery, 2023. "Estimating a Causal Exposure Response Function with a Continuous Error-Prone Exposure: A Study of Fine Particulate Matter and All-Cause Mortality," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(1), pages 20-41, March.
  • Handle: RePEc:spr:jagbes:v:28:y:2023:i:1:d:10.1007_s13253-022-00508-z
    DOI: 10.1007/s13253-022-00508-z
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    References listed on IDEAS

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