Self‐Reported Motor and Nonmotor Symptoms, Prodromal Parkinson's Disease Probability, and Incident Parkinson's Disease in US Farmers
Self‐Reported Motor and Nonmotor Symptoms, Prodromal Parkinson's Disease Probability, and Incident Parkinson's Disease in US Farmers
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Original abstract
AbstractBackgroundFew studies have assessed motor and nonmotor symptoms and the prodromal probability of Parkinson's disease (PD) among farming populations.ObjectiveThe aim was to assess self‐reported nonmotor and motor symptoms and the prodromal PD probability in relation to incident PD among US farmers.MethodsThe study included 16,059 farmers (aged 65.6 ± 10.8 years) from the Agricultural Health Study, with a median of 6.2 years of follow‐up. We assessed associations using multivariable logistic regression and presented odds ratios (OR) and 95% confidence intervals (CI).ResultsAt baseline, the prevalence of individual symptoms ranged from 2.0% for arm/leg tremor to 21.1% for excessive daytime sleepiness. We identified 127 incident PD patients during follow‐up. Except for depression, all symptoms were significantly associated with future PD diagnosis, with OR (95% CI) ranging from 1.6 (1.1–2.2) for excessive daytime sleepiness to 3.9 (2.3–6.8) for arm/leg tremor. The prodromal PD probability, calculated based on limited available self‐reported prodromal and PD risk markers, was low. Using the Movement Disorder Society's prodromal PD criteria, the median (interquartile range) at baseline was 4.4% (7.2%) for incident PD patients and 2.3% (3.4%) for participants free of PD. Further, it exhibited low sensitivity and positive predictive value in identifying incident PD patients in this farming population.ConclusionsSelf‐reported prodromal PD symptoms were relatively common in US farmers. They were associated with incident PD diagnosis but had limited values in predicting disease risk. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.