BackgroundExposure to PM2.5 has been linked to neurodegenerative diseases, with limited understanding of constituent-specific contributions. ObjectivesTo explore the associations between long-term exposure to PM2.5 constituents and neurodegenerative diseases. MethodsWe recruited 148,274 individuals aged ≥ 60 from four cities in the Pearl River Delta region, China (2020 to 2021). We calculated twenty-year average air pollutant concentrations (PM2.5 mass, black carbon (BC), organic matter (OM), ammonium (NH4+), nitrate (NO3-) and sulfate (SO42-)) at the individuals' home addresses. Neurodegenerative diseases were determined by self-reported doctor-diagnosed Alzheimer’s disease (AD) and Parkinson’s disease (PD). Generalized linear mixed models were employed to explore associations between pollutants and neurodegenerative disease prevalence. ResultsPM2.5 and all five constituents were significantly associated with a higher prevalence of AD and PD. The observed associations generally exhibited a non-linear pattern. For example, compared with the lowest quartile, higher quartiles of BC were associated with greater odds for AD prevalence (i.e., the adjusted odds ratios were 1.81; 95% CI, 1.45–2.27; 1.78; 95% CI, 1.37–2.32; and 1.99; 95% CI, 1.54–2.57 for the second, third, and fourth quartiles, respectively). ConclusionsLong-term exposure to PM2.5 and its constituents, particularly combustion-related BC, OM, and SO42-, was significantly associated with higher prevalence of AD and PD in Chinese individuals. Environmental implicationPM2.5 is a routinely regulated mixture of multiple hazardous constituents that can lead to diverse adverse health outcomes. However, current evidence on the specific contributions of PM2.5 constituents to health effects is scarce. This study firstly investigated the association between PM2.5 constituents and neurodegenerative diseases in the moderately to highly polluted Pearl River Delta region in China, and identified hazardous constituents within PM2.5 that have significant impacts. This study provides important implications for the development of targeted PM2.5 prevention and control policies to reduce specific hazardous PM2.5 constituents.
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