Diet, Urate, and Parkinson's Disease Risk in Men
Bibliographic record
Abstract
The authors examined whether a diet that increases plasma urate level is also related to reduced risk of Parkinson's disease (PD). The study population comprised 47,406 men in the Health Professionals Follow-up Study. The potential effect of diet on plasma urate level was estimated by regressing plasma urate on intakes of selected foods and nutrients in a subsample of 1,387 men. Coefficients of this regression model were then used to calculate a dietary urate index for all cohort participants. Multivariate relative risks of PD were estimated by means of Cox proportional hazards models. After 14 years of follow-up (1986-2000), the authors documented 248 incident cases of PD. A higher dietary urate index was associated with a lower risk of PD (top quintile vs. bottom: relative risk = 0.47, p-trend = 0.0008), after adjustment for age, smoking, caffeine intake, and other potential confounders. This association remained strong and significant after further adjustment for each component of the index individually (p-trend < 0.02 for each). These data support urate as a potentially protective factor in PD and suggest that dietary changes expected to increase plasma urate level may contribute to lower risk of PD. These potential benefits, however, should be weighed against expected adverse effects on risk of gout and other chronic diseases.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".