Abstract

AbstractBackgroundGrowing studies link long‐term fine particle (PM2.5) exposures to increased risk of Alzheimer’s disease and related dementias (ADRD), but these findings have been disputed citing traditional approaches do not guarantee evidence of causality.MethodWe constructed two national U.S. population‐based cohorts of enrollees aged ≥65 from the Medicare Chronic Conditions Warehouse (2000‐2018), combined with high‐resolution air pollution datasets, to estimate the effect of long‐term exposure to PM2.5 on dementia and AD incidence, respectively. We applied multiple distinct causal inference approaches, i.e., under a set of causal inference assumptions, to compare the health estimates. We first considered three causal inference modelling approaches that rely on the potential outcomes framework and generalized propensity scores (GPS). These approaches adjust for measured confounding using 1) matching by GPS; 2) weighting by GPS; and 3) including GPS as a covariate in the health outcome model. Then we further applied the difference‐in‐differences approach that controls for unmeasured confounders by design to add robustness to any causal conclusions.ResultFor the period 2000‐2018, we found that all statistical approaches provide consistent results, suggesting that long‐term exposure to PM2.5 is causally linked to increased incidence of ADRD.ConclusionUsing a large nationwide cohort and robust epidemiologic analyses, we provide strong evidence of the causal link between long‐term PM2.5 exposure and increased incidence of dementia and AD. Our results support the importance of continued assessment the impact of air pollution exposure on neurological disorders among the older adults.

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