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Occupational complexity and risk of Parkinson's disease.

ABSTRACT: BACKGROUND: The etiology of Parkinson's disease (PD) remains unclear, and environmental risk-factors such as occupation have attracted interest. OBJECTIVE: The goal was to investigate occupational complexity in relation to PD. METHODS: We conducted a population-based cohort study based on the Swedish Twin Registry that included 28,778 twins born between 1886 and 1950. We identified 433 PD cases during the study period. Data on occupation were collected from either the 1970 or 1980 Swedish census, and occupational complexity was assessed via a job exposure matrix. Cox proportional hazard regression analyses with age as the underlying time scale were used to assess PD risk as a function of the three domains of occupational complexity: data, people, and things. Sex and smoking were included as covariates. Analyses stratified by twin pair were conducted to test for confounding by familial factors. RESULTS: High occupational complexity with data and people was associated with increased risk overall (Hazard Ratio [HR] = 1.07, 95% confidence interval [CI] 1.02-1.14, and HR = 1.10, 95% CI 1.01-1.21, respectively), and in men (HR = 1.08, 95% CI 1.01-1.16, and HR = 1.15, 95% CI 1.03-1.28, respectively). Complexity with things was not associated with risk of PD. When the analyses were stratified by twin pair, the HRs for occupational complexity with data and people were attenuated in men. CONCLUSIONS: High complexity of work with data and people is related to increased risk of PD, particularly in men. The attenuation of risk observed in the twin pair-stratified analyses suggests that the association may partly be explained by familial factors, such as inherited traits contributing to occupational selection or other factors shared by twins.

SUBMITTER: Valdes EG

PROVIDER: S-EPMC4157797 | biostudies-other | 2014

REPOSITORIES: biostudies-other

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Occupational stress and risk for Parkinson's disease: A nationwide cohort study.

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Complexity Measures of Voice Recordings as a Discriminative Tool for Parkinson's Disease.

Project description:In this paper, we have investigated the differences in the voices of Parkinson's disease (PD) and age-matched control (CO) subjects when uttering three phonemes using two complexity measures: fractal dimension (FD) and normalised mutual information (NMI). Three sustained phonetic voice recordings, /a/, /u/ and /m/, from 22 CO (mean age = 66.91) and 24 PD (mean age = 71.83) participants were analysed. FD was first computed for PD and CO voice recordings, followed by the computation of NMI between the test groups: PD-CO, PD-PD and CO-CO. Four features reported in the literature-normalised pitch period entropy (Norm. PPE), glottal-to-noise excitation ratio (GNE), detrended fluctuation analysis (DFA) and glottal closing quotient (ClQ)-were also computed for comparison with the proposed complexity measures. The statistical significance of the features was tested using a one-way ANOVA test. Support vector machine (SVM) with a linear kernel was used to classify the test groups, using a leave-one-out validation method. The results showed that PD voice recordings had lower FD compared to CO (p < 0.008). It was also observed that the average NMI between CO voice recordings was significantly lower compared with the CO-PD and PD-PD groups (p < 0.036) for the three phonetic sounds. The average NMI and FD demonstrated higher accuracy (>80%) in differentiating the test groups compared with other speech feature-based classifications. This study has demonstrated that the voices of PD patients has reduced FD, and NMI between voice recordings of PD-CO and PD-PD is higher compared with CO-CO. This suggests that the use of NMI obtained from the sample voice, when paired with known groups of CO and PD, can be used to identify PD voices. These findings could have applications for population screening.

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Occupational pesticide use and Parkinson's disease in the Parkinson Environment Gene (PEG) study.

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