Assessment of risk associated with specific fatty acids and colorectal cancer among French-Canadians in Montreal: a case-control study
Bibliographic record
Abstract
BACKGROUND: Discrepancies in findings on the association between dietary fats and colorectal cancer (CRC) persist, and it is hypothesized that fatty acids (FA) may modulate CRC risk because of their physiological functions. METHODS: Between 1989 and 1993, a case-control study involving 402 cases and 668 population-based controls was conducted among French-Canadians. Dietary intake was assessed by a food frequency questionnaire. RESULTS: Oleic acid was the major FA consumed by the study population. A significant inverse association was found among females between CRC and butyrate (OR = 0.57; 95% CI: 0.34-0.96; P = 0.006), alpha-linoleic acid (ALA) (OR = 0.78; 95% CI: 0.46-1.32; P = 0.016), and w-3 FA (OR = 0.84; 95% CI: 0.50-1.41; P = 0.028), comparing the upper to the lower quartiles of intake. An increased risk was associated with arachidonic acid (AA) (OR = 2.03; 95% CI: 1.16-3.54; P = 0.001) among males, and with the w6/w3 ratio (OR = 1.47; 95% CI: 0.86-2.50; P = 0.001) among females. Arachidonic acid was linked with up to fivefold increased risk (OR = 5.33; 95% CI: 2.04-13.95; P = 0.0004 for trend) among men with high vitamin C intake. Females with low carotenoids intake were at elevated risk associated with AA (OR = 4.07; 95% CI: 1.84-8.99; P = 0.003); eicosapentaenoic acid (OR = 3.50; 95% CI: 1.59-7.71; P = 0.015), and docosahexaenoic acid (OR = 5.77; 95% CI: 2.50-13.33; P = 0.002), comparing the upper with the lower quartiles of intake. CONCLUSION: The results of this study suggest that independently of total energy intake, substituting AA by butyrate, ALA, or omega-3 FA may reduce CRC risk. The role of interactions between vitamin C, total carotenoids, and polyunsaturated FA requires further investigation.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".