Dietary transfatty acids and cancer risk
Bibliographic record
Abstract
This study assesses the association between dietary transfatty acid (TFA) intake and the risk of selected cancers. Mailed questionnaires were completed between 1994 and 1997 in eight Canadian provinces by 1182 incident, histologically confirmed cases of the stomach, 1727 of the colon, 1447 of the rectum, 628 of the pancreas, 3341 of the lung, 2362 of the breast, 442 of the ovary, 1799 of the prostate, 686 of the testis, 1345 of the kidney, 1029 of the bladder, 1009 of the brain, 1666 non-Hodgkin's lymphomas, 1069 leukemias, and 5039 population controls. Information on dietary habits and nutrition intake was obtained using a food frequency questionnaire, which provided data on eating habits 2 years before the study. Odds ratios (OR) and 95% confidenc530e intervals (CI) were derived by unconditional logistic regression to adjust for total energy intake and other potential confounding factors. Dietary TFA were positively associated with the risk of cancers of the colon (OR: 1.38 for the highest vs. the lowest quartile), breast in premenopause (OR: 1.60), and prostate (OR: 1.42). There were a borderline association for pancreas cancer (OR: 1.38; P=0.06). No significant association was observed for cancers of the stomach, rectum, lung, ovary, testis, kidney, bladder, brain, non-Hodgkin's lymphomas, and leukemia, although the ORs for the highest quartile were above unity for all neoplasms considered, except testis. Our findings add evidence that high TFA is associated with an increased risk of various cancers. Thus, a diet low in transfat may play a role in the prevention of several cancers.
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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 | 0.000 |
| 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 | 0.000 | 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".