Risk of endometrial cancer in relation to individual nutrients from diet and supplements
Bibliographic record
Abstract
OBJECTIVE: Intake of nutrients may influence the risk of endometrial cancer (EC). We aimed to estimate the association of intake of individual nutrients from food and from food plus supplements with EC occurrence. DESIGN: A population-based case-control study conducted in Canada (2002-2006). SETTING: Nutrient intakes from food and supplements were assessed using an FFQ. Logistic regression was used to estimate EC risk within quartile levels of nutrient intakes. SUBJECTS: Incident EC cases (n 506) were identified from the Alberta Cancer Registry, and population controls were frequency- and age-matched to cases (n 981). RESULTS: There existed little evidence of an association with EC for the majority of macronutrients and micronutrients examined. We observed a statistically significant increased risk associated with the highest, compared with the lowest, quartile of intake of dietary cholesterol (multivariable-adjusted OR = 1·51, 95 % CI 1·08, 2·11; P for trend = 0·02). Age-adjusted risk at the highest level of intake was significantly reduced for Ca from food sources (OR = 0·73, 95 % CI 0·54, 0·99) but was attenuated in the multivariable model (OR = 0·82, 95 % CI 0·59, 1·13). When intake from supplements was included in Ca intake, risk was significantly reduced by 28 % with higher Ca (multivariable-adjusted OR = 0·72, 95 % CI 0·51, 0·99, P for trend = 0·04). We also observed unexpected increased risks at limited levels of intakes of dietary soluble fibre, vitamin C, thiamin, vitamin B6 and lutein/zeaxanthin, with no evidence for linear trend. CONCLUSIONS: The results of our study suggest a positive association between dietary cholesterol and EC risk and an inverse association with Ca intake from food sources and from food plus supplements.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".