Obesity and colorectal cancer risk in women
Bibliographic record
Abstract
BACKGROUND: Several large studies of obesity and colorectal cancer risk have found no association among women but a reasonably consistent positive association among men. In women, a positive association that is stronger among, or limited to, those who are premenopausal has been suggested by studies that stratified analyses by age, although no previous study has examined the association by menopausal status. METHODS: We used proportional hazards analyses to estimate hazard ratios relating obesity to colorectal cancer risk among 89,835 women aged 40-59 years at recruitment into the Canadian National Breast Screening Study, a multicentre randomised controlled trial of mammography screening for breast cancer. During an average 10.6 years of follow up (936,433 person years), a total of 527 women were diagnosed with incident colorectal cancer (363 colon and 164 rectal). RESULTS: We found that obesity (body mass index > or = 30 kg/m(2)) was associated with an approximately twofold increased risk of colorectal cancer among women who were premenopausal at baseline (hazard ratio 1.88, 95% confidence interval 1.24-2.86). There was no association among postmenopausal women (p for interaction=0.01), and there was only a weak positive association in the entire cohort. CONCLUSIONS: Our data suggest that obesity is associated with a twofold increased risk of colorectal cancer in premenopausal women but is not associated with altered risk in postmenopausal women. Effect modification by menopausal status may better explain the inconsistent or weak findings in previous studies than the presumed lack of an association among women.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".