Investigating Parkinson’s disease risk across farming activities using data mining and large-scale administrative health data

Abstract The risk of Parkinson’s disease (PD) associated with farming has received considerable attention, in particular for pesticide exposure. However, data on PD risk associated with specific farming activities is lacking. We aimed to explore whether specific farming activities exhibited a higher...

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Bibliographic Details
Main Authors: Pascal Petit, François Berger, Vincent Bonneterre, Nicolas Vuillerme
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:npj Parkinson's Disease
Online Access:https://doi.org/10.1038/s41531-024-00864-2
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Summary:Abstract The risk of Parkinson’s disease (PD) associated with farming has received considerable attention, in particular for pesticide exposure. However, data on PD risk associated with specific farming activities is lacking. We aimed to explore whether specific farming activities exhibited a higher risk of PD than others among the entire French farm manager (FM) population. A secondary analysis of real-world administrative insurance claim data and electronic health/medical records (TRACTOR project) was conducted to estimate PD risk for 26 farming activities using data mining. PD cases were identified through chronic disease declarations and antiparkinsonian drug claims. There were 8845 PD cases among 1,088,561 FMs. The highest-risk group included FMs engaged in pig farming, cattle farming, truck farming, fruit arboriculture, and crop farming, with mean hazard ratios (HRs) ranging from 1.22 to 1.67. The lowest-risk group included all activities involving horses and small animals, as well as gardening, landscaping and reforestation companies (mean HRs: 0.48–0.81). Our findings represent a preliminary work that suggests the potential involvement of occupational risk factors related to farming in PD onset and development. Future research focusing on farmers engaged in high-risk farming activities will allow to uncover potential occupational factors by better characterizing the farming exposome, which could improve PD surveillance among farmers.
ISSN:2373-8057