Fine Particulate Air Pollution and the "No-Multiple-Versions-of-Treatment" Assumption: Does Particle Composition Matter for Causal Inference?

American journal of epidemiology(2023)

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摘要
Here we discuss possible violations of the "no-multiple-versions-of-treatment" assumption in studies of outdoor fine particulate air pollution (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5)) owing to differences in particle composition, which in turn influence health. This assumption is part of the potential outcomes framework for causal inference, and it is needed for well-defined potential outcomes, as multiple versions of the same treatment could lead to different health risks for the same level of treatment. Since 2 locations can have the same outdoor PM2.5 mass concentration (i.e., treatment) but different chemical compositions (i.e., versions of treatment), violations of the "no-multiple-versions-of-treatment" assumption seem likely. Importantly, violations of this assumption will not bias health risk estimates for PM2.5 mass concentrations if there are no unmeasured confounders of the "version of treatment"-outcome relationship. However, confounding can occur if these factors are not identified and controlled for in the analysis. We describe situations in which this may occur and provide simulations to estimate the magnitude and direction of this possible bias. In general, violations of the "no-multiple-versions-of-treatment" assumption could be an underappreciated source of bias in studies of outdoor PM2.5. Analysis of the health impacts of outdoor PM2.5 mass concentrations across spatial domains with similar composition could help to address this issue.
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关键词
PM2.5,air pollution,causal inference,chemical components,particulate matter
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