Environmental and Familial Risk Factors of Parkinsons Disease: Case-Control Study
Bibliographic record
Abstract
BACKGROUND: While the cause of Parkinson's disease (PD) remains unknown, evidence suggests certain environmental factors, such as well water drinking, herbicides, pesticides exposure and neurotoxins, may trigger the chain of oxidative reactions culminating in the death of dopaminergic neurons in substantia nigra to cause Parkinsonism. To investigate the possible impact of environmental risk factors for idiopathic PD, a case-control study was performed in the Eastern India. METHODS: During the period from January 1st, 2006 and December 10th, 2009, 175 PD patients (140 men, 35 women) and 350 non-Parkinson age-sex matched controls were included in the study. Subjects were given a structured neurological examination and completed an administered questionnaire which elicited detailed information on demographic data, pesticides, herbicides family history, occupation, dietary and smoking habits. RESULTS: The multivariate analysis revealed that family history of PD, pesticide exposure, exposure to toxins other than pesticides and herbicides, rural living and previous history of depression were associated with increased risk of PD, whereas, smoking appeared to be a protective factor. Well water drinking for at least five years, though a significant risk factor on univariate analysis (OR = 4.5, 95% CI = 2.1-9.9), could not be proved significant in multivariate analysis. Head trauma, vegetarian dietary habit, occupation involving physical exertion and exposure to domestic pets were not as significant risk factors. CONCLUSION: Results of our study support the hypothesis of multifactorial etiology of PD with environmental factors acting on a genetically susceptible host.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".