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Background: Exposure to PM_2.5 has been linked to neurodegenerative diseases, with limited understanding of constituent-specific contributions.

Objectives: To explore the associations between long-term exposure to PM_2.5 constituents and neurodegenerative diseases.

Methods: We 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 (PM_2.5 mass, black carbon (BC), organic matter (OM), ammonium (NH₄⁺), nitrate (NO₃^-) and sulfate (SO₄^2-)) 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.

Results: PM_2.5 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).

Conclusions: Long-term exposure to PM_2.5 and its constituents, particularly combustion-related BC, OM, and SO₄^2-, was significantly associated with higher prevalence of AD and PD in Chinese individuals.

Environmental implication: PM_2.5 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 PM_2.5 constituents to health effects is scarce. This study firstly investigated the association between PM_2.5 constituents and neurodegenerative diseases in the moderately to highly polluted Pearl River Delta region in China, and identified hazardous constituents within PM_2.5 that have significant impacts. This study provides important implications for the development of targeted PM_2.5 prevention and control policies to reduce specific hazardous PM_2.5 constituents.