Background: The associations of PM2.5 mass and various adverse health outcomes have been widely investigated. However, fewer studies focused on the potential health impacts of PM2.5 components, especially for dementia and Alzheimer's diseases (AD). Methods: We constructed a nationwide population-based open cohort study among Medicare beneficiaries aged 65 or older during 2000-2018. This dataset was linked with the predicted levels of 15 PM2.5 components, including 5 major mass contributors (EC, OC, NH4+, NO3-, SO42-) and 10 trace elements (Br, Ca, Cu, Fe, K, Ni, Pb, Si, V, Zn) across contiguous US territory. Data were aggregated by ZIP code, calendar year and individual level demographics. Two mixture analysis methods, weighted quantile sum regression (WQS) and quantile g-computation (qgcomp), were used with quasi-Poisson models to analyze the health effects of the total mixture of PM2.5 components on dementia and AD, as well as the relative contribution of individual components. Results: Exposure to PM2.5 components over the previous 5 years was significantly associated with increased risks of both dementia and AD, with stronger associations observed for AD. SO42-, OC, Cu were identified with large contributions to the combined positive association of the mixture from both WQS and qgcomp models. Conclusion: We found positive associations between the 15 PM2.5 components and the incidence of dementia and AD. Our findings suggest that reducing PM2.5 emissions from traffic and fossil fuel combustion could help mitigate the growing burden of dementia and Alzheimer's disease.

The authors have declared no competing interest.

This study was funded by the National Institute on Aging (NIA/NIH R01 AG074357).

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

IRB of Emory University gave ethical approval for this work

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The PM2.5 data that support the findings of this study are publicly available from https://doi.org/10.7927/0rvr-4538, NO2 and O3 data are available from https://doi.org/ 10.6084/m9.figshare.16834390. Behavioral risk factors are publicly available from https:// www.cdc.gov/brfss/annual_data/annual_data.html; SES data are publicly available from https:// www.census.gov/data/datasets/2000/dec/summary-file-3.html, https://www.census.gov/ data/datasets/2010/dec/summary-file-1.html, and https://www.census.gov/data/ developers/data-sets/acs-1year.html. Health-care capacity data are available from https:// data.hrsa.gov/topics/health-workforce/ahrf. The rules governing the main Medicare dataset used in this study prohibit any sharing of the health datasets being used here, restricted by for our Data Use Agreement with the US Centers for Medicare & Medicaid Services. Academic and non-profit researchers who are interested in using Medicare data should contact the US Centers for Medicare & Medicaid Services directly to obtain their own datasets upon completion of a Data Use Agreement.