Vegetarian diets and the risk of gastrointestinal cancers: a meta-analysis of observational studies
Bibliographic record
Abstract
The systematic review aimed to assess the association between vegetarian diet and the risk of gastrointestinal tumorigenesis. PubMed, Embase, Cochrane Library, and Web of Science were searched from inception to August 2022 for observational studies on vegetarian diets and the risk of gastrointestinal tumorigenesis. The primary outcome was morbidity due to gastrointestinal cancer. The Newcastle-Ottawa Scale was used to assess the quality of included studies. Pooled effects were analyzed using a random-effects model. The study protocol was registered in PROSPERO (no. CRD42022310187). Eight original studies (seven cohorts and one case-control), involving 686 691 participants, were included. Meta-analysis showed a negative correlation between vegetarian diets and gastrointestinal tumorigenesis risk [relative risk (RR) equals 0.77, 95% confidence interval (CI) is (0.65-0.90)], compared with non-vegetarian diets. Subgroup analysis indicated that vegetarian diets were negatively correlated with the risks of gastric cancer [RR = 0.41, 95% CI (0.28-0.61)] and colorectal cancer [RR = 0.85, 95% CI (0.76-0.95)], but not with that of upper gastrointestinal cancer (excluding stomach) [RR = 0.93, 95% CI (0.61-1.42)]. Vegetarian diets were negatively correlated with the risk of gastrointestinal tumorigenesis in men [RR = 0.57, 95% CI (0.36-0.91)], but were uncorrelated in women [RR = 0.89, 95% CI (0.71-1.11)]. Vegetarian diets were negatively correlated with the risk of gastrointestinal tumorigenesis in North American [RR = 0.76, 95% CI (0.61-0.95)] and Asian populations [RR = 0.43, 95% CI (0.26-0.72)] and were uncorrelated in the European population [RR = 0.83, 95% CI (0.68-1.01)]. Adhering to vegetarian diets reduces the risk of gastrointestinal tumorigenesis. More data from well-conducted cohort and other studies are needed.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.039 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".