Long-term exposure to multiple air pollutants and risk of Parkinson's disease: a population-based multipollutant model study

长期暴露于多种空气污染物与帕金森病风险:一项基于人群的多污染物模型研究

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Abstract

BACKGROUND: Recent evidence suggests brain-first Parkinson's disease (PD) may start from the olfactory system, indicating potential inhalational exposure to causal agents. We investigated the impact of long-term exposure to various air pollutants on PD incidence using both single- and multi-pollutant models to account for interactions between pollutants. METHODS: This retrospective population study used data from Taiwan's National Health Insurance Research Database (2006 and 2018) and included individuals aged 40-65 without PD. Personal exposure levels to various air pollutants, including PM(2.5), PM(10), NO(2), O(3), SO(2) and CO, were calculated using the hybrid Kriging/land-use regression method. Cox regression models were used to analyse the association between pollutants and PD incidence, adjusting for covariates. RESULTS: A total of 5 113 322 individuals without PD (mean age 50.1±6.9 years, 47.3% men) were followed for an average of 11.2±2.4 years, during which 20 694 incident cases of PD were identified. In the single-pollutant model, exposure to PM(2.5) (HR 2.65 (95% CI 2.59 to 2.72)), PM(10) (HR 3.13 (3.04 to 3.22)), NO(2) (HR 1.74 (1.68 to 1.80)) and SO(2) (HR 1.68 (1.65 to 1.71)) was associated with an increased risk of PD. These associations remained robust in the multipollutant model. A positive association between exposure to O(3) and an increased risk of PD (HR 1.29 (1.25-1.33)) was observed after adjusting for co-pollutants. CONCLUSIONS: This nationwide cohort study employing multiple-pollutant models for considering the interaction effects revealed an association between exposure to multiple air pollutants and the risk of PD, emphasising the need for early prevention strategies.

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