Dietary carotenoids and risk of colon cancer: Case‐control study
Bibliographic record
Abstract
Some epidemiological studies suggest that consumption of fruits and vegetables with a high carotenoid content may protect against colon cancer (CC). The evidence, however, is not completely consistent. Given the inconsistencies in findings in previous studies and continued interest in identifying modifiable risk factors for CC, a case-control study of French-Canadian in Montreal, Canada, was undertaken to examine the possible association between dietary carotenoids and CC risk and to investigate whether this association varies in relation to lifestyle factors such as smoking or diet, and particularly the high consumption of long-chain polyunsaturated fatty acids (LCPUFA). A total of 402 colorectal cases (200 males and 202 females) and 688 population-based controls matched for age, gender and place of residence were interviewed. Dietary intake was assessed through a validated food frequency questionnaire that collected information on over 200 food items and recipes. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated in unconditional logistic regression models. After adjustment for important variables such as total energy intake, no association was found between dietary intake of carotenoids and CC risk. For women with high intakes of LCPUFA, an inverse association was found between lutein + zeaxanthin and CC risk. ORs were 0.41; 95%CI (0.19-0.91), p=0.03 for eicosapentaenoic acid, and OR=0.36, 95%CI (0.19-0.78), p=0.01 for docosahexaenoic acid, when the upper quartiles of intake were compared to the lower. Among never-smokers, a significantly reduced risk of CC was associated with intake of beta-carotene [OR=0.44, 95%CI (0.21-0.92) and p=0.02], whereas an inverse association was found between lycopene intake and CC risk [OR=0.63, 95%CI (0.40-0.98) and p=0.05] among smokers. The results of our study suggest that a diet rich in both lutein + zeaxanthin and LCPUFAs may help prevent CC in French-Canadian females.
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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 | 0.000 | 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".