Nutrients and Risk of Prostate Cancer
Bibliographic record
Abstract
This study assesses the association between intake of protein, fats, cholesterol, and carbohydrates and the risk of prostate cancer (PCa). Between 1994 and 1997, in 8 Canadian provinces, mailed questionnaires were completed by 1,797 incident, histologically confirmed cases of PCa and 2,547 population controls. Information was collected on socioeconomic status, lifestyle habits, and diet. A 69-item food frequency questionnaire provided data on eating habits 2 yr before the study. Odds ratios (ORs) and 95% confidence intervals (CIs) were computed using unconditional logistic regression, including terms for sociodemographic factors, body mass index, alcohol, and total energy intake. Intake of trans fat was associated with the risk of PCa; the OR for the highest vs. the lowest quartile was 1.45 (95% CI = 1.16-1.81); the association was apparently stronger in subjects aged less than 65, normal weight men, and ever smokers. An increased risk was also observed with increasing intake of sucrose and disaccharides. In contrast, men in the highest quartile of cholesterol intake were at lower risk of PCa. No association was found with intake of total proteins, total fat, monounsaturated fats, polyunsaturated fats, monosaccharides, and total carbohydrates. The findings provide evidence that a diet low in trans fat could reduce PCa risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".