Risk factors for early-onset colorectal cancer: a population-based case–control study in Ontario, Canada
Bibliographic record
Abstract
PURPOSE: There has been an alarming increase in colorectal cancer (CRC) incidence among young adults aged < 50 years, and factors driving this upward trend are unknown. This study investigated associations between various medical, lifestyle, and dietary factors and risk of early-onset CRC (EO-CRC). METHODS: A population-based case-control study was conducted in Ontario, Canada during 2018-2019. EO-CRC cases aged 20-49 years (n = 175) were identified from the Ontario Cancer Registry; sex- and age group-matched controls (n = 253) were recruited through random digit dialing. Data on potential a priori risk factors were collected using a web-based self-reported questionnaire. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using multivariable logistic regression. RESULTS: Family history of CRC in a first- or second-degree relative (OR 2.37; 95% CI 1.47-3.84), longer sedentary time (≥ 10 vs. < 5 h/day, OR 1.93; 95% CI 1.02-3.65), greater consumption of sugary drinks (≥ 7 vs. < 1 drinks/week, OR 2.99; 95% CI 1.57-5.68), and a more Westernized dietary pattern (quartile 4 vs. 1, OR 1.92; 95% CI 1.01-3.66) were each associated with an increased risk of EO-CRC. Conversely, calcium supplement use (OR 0.53; 95% CI 0.31-0.92), history of allergy or asthma (OR 0.62; 95% CI 0.39-0.98), and greater parity in females (≥ 3 vs. nulliparity, OR 0.29; 95% CI 0.11-0.76) were each associated with a reduced risk. CONCLUSION: Modifiable factors, particularly sedentary behavior and unhealthy diet including sugary drink consumption, may be associated with EO-CRC risk. Our findings, if replicated, may help inform prevention strategies targeted at younger persons.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".