Effects of physical activity on colorectal cancer risk among family history and body mass index subgroups: a systematic review and meta-analysis
Bibliographic record
Abstract
Physical activity is consistently associated with a reduced risk of colorectal cancer in epidemiologic studies. This association among higher risk subgroups, such as those with a first-degree family history of colorectal cancer or high body mass index remains unclear. We searched MEDLINE for studies examining physical activity and colorectal cancer risk among higher risk subgroups through July 11, 2017. Fifteen and three studies were eligible for inclusion for body mass index and first-degree family history of colorectal cancer subgroups, respectively. Estimates of the highest to lowest comparison of physical activity for each subgroup of risk were pooled using random-effects models. The pooled associations of physical activity and colorectal cancer risk for those without and with a first-degree family history of colorectal cancer were 0.56 (95% confidence interval (CI) = 0.39–0.80) and 0.72 (95% CI = 0.39–1.32), respectively (p heterogeneity = 0.586). The pooled associations of physical activity and colorectal cancer risk for the low and high body mass index groups were 0.74 (95% CI = 0.66–0.83) and 0.65 (95% CI = 0.53–0.79), respectively (p heterogeneity = 0.389). Overall, a stronger relative risk of physical activity on colorectal cancer risk was observed in the higher body mass index group, although the difference was not statistically significant, suggesting an added benefit of physical activity as a cancer prevention strategy in population groups with strong risk factors for colorectal cancer. Additional research among these subgroups is warranted.
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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.041 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".