Airborne PM2.5 and Parkinson's disease: An updated meta-analysis
- VernacularTitle:大气PM2.5暴露与帕金森病关系的meta分析
- Author:
Yixian WANG
1
;
Jianjun WU
1
;
Rui HU
1
;
Jingjuan JU
1
Author Information
- Publication Type:Investigation
- Keywords: Parkinson's disease; fine particulate matter; air pollution; meta-analysis
- From: Journal of Environmental and Occupational Medicine 2024;41(2):168-174
- CountryChina
- Language:Chinese
- Abstract: Background An association between atmospheric fine particulate matter (PM2.5) exposure and Parkinson's disease (PD) has been suggested by previous studies, but the results of current epidemiological studies are still inconclusive. Objective To systematically evaluate the relationship between exposure to ambient PM2.5 and the risk of PD, as well as to explore potential influencing factors, aiming to provide scientific evidence for formulating early prevention strategies for PD. Methods Cochrane Library, PubMed, Web of Science, Medline, Embase, China National Know-ledge Infrastructure (CNKI), Wanfang Database, and VIP Chinese Science and Technology Journal Database were queried. The search terms included Parkinson's disease, particulate matter 2.5, and PM2.5 in both Chinese and English. Cohort studies examining the association between atmospheric PM2.5 exposure and the risk of PD were collected and searched from the inception of each database to June 26, 2023. The identified literature was screened, and the basic information of the included studies and their research subjects, outcome indicators, quantitative results of each study, as well as the information required by bias risk assessment were extracted. The Newcastle-Ottawa Scale was employed to assess the risk of literature bias. Meta-analysis, subgroup analysis, sensitivity analysis, and publication bias analysis were conducted in Stata 15.0 software. Results Twelve cohort studies were identified. A total of 17443136 participants with follow-up periods ranging from 3.5 to 22 years were included in the analysis. The meta-analysis, utilizing a random-effects model, revealed that PD risk was elevated by 6% after exposure to PM2.5 [HR=1.06 (95%CI: 1.02, 1.11), P=0.006]. The subgroup analysis demonstrated that exposure to PM2.5 increased PD risk by 6% in North America [HR=1.06 (95%CI: 1.00, 1.12), P=0.033] and by 17% in East Asia [HR=1.17 (95%CI: 1.02, 1.33), P=0.020]. However, the effect was not statistically significant in Europe. PD risk exhibited a 7% rise [HR=1.07 (95%CI: 1.02, 1.14), P=0.011] in individuals aged 60 years and older, which was different from that in individuals younger than 60 years. Exposure to various concentrations of PM2.5 was observed to associate with an elevated risk of PD. The inclusion of adjustments for PD-related comorbidities did not alter the conclusion that ambient PM2.5 exposure might elevate the risk of PD. The studies with a follow-up duration exceeding 5 years and reporting more than 1000 PD cases suggested a significant increase in the risk of PD due to ambient PM2.5 exposure [HR=1.06 (95%CI: 1.01, 1.12), P=0.012; HR=1.06 (95%CI: 1.01, 1.11), P=0.027, respectively]. Conversely, no significant association was identified between ambient PM2.5 exposure and the risk of PD within the cohorts with a follow-up duration of less than 5 years and reporting fewer than 1000 PD cases [HR=1.09 (95%CI: 0.95, 1.26), P=0.214; HR=1.12 (95%CI: 0.98, 1.02), P=0.092, respectively]. The sensitivity analysis showed that the results were stable. The publication bias analysis and the combined trim-and-fill method showed that the results were robust. Conclusion The risk of PD could be increased by ambient PM2.5 exposure and influenced by age and area. The research results might be affected by the duration of follow-up and the quantity of PD cases reported.
