Association between pro-inflammatory diet and ulcerative colitis: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Emerging evidence suggests that dietary patterns can mediate intestinal inflammatory responses through immune-microbiome interactions. Diet and inflammation are important pathogenic factors for ulcerative colitis (UC). However, the existing evidence regarding the association between a pro-inflammatory diet and the risk of UC is controversial, and further clarification of this association is needed. Objective This study aimed to explore the association between pro-inflammatory diet and UC risk. Methods We systematically searched PubMed, Web of Science, Scopus, EMBASE, and Cochrane Library databases from their inception to January 15th, 2025. Two researchers independently used the Newcastle - Ottawa Scale to assess the quality of the included studies. Data analysis was performed using STATA 17 software. Results This systematic review and meta-analysis included eight studies involving approximately 758,068 participants. The meta-analysis indicated that an inflammatory or pro-inflammatory diet did not increase the risk of UC (OR = 0.97, 95% CI = 0.84–1.12). However, subgroup analyses revealed differing results: within the case–control study subgroup, a pro-inflammatory diet was associated with an increased risk of UC (OR = 2.09, 95% CI: 1.23–3.56), whereas in the cohort study subgroup, no significant association was found between a pro-inflammatory diet and UC (OR = 0.91, 95% CI: 0.78–1.06). Sensitivity analysis indicated that the study results were robust. Additionally, Begg’s test ( p = 0.174) and Egger’s test ( p = 0.085) showed no significant publication bias in this study. Conclusion The results of this study do not support a significant association between pro-inflammatory diets and UC risk. However, due to the limited level of evidence from observational studies and their heterogeneity, the association between pro-inflammatory diets and UC may be underestimated or overestimated. Therefore, larger multi-centre studies are needed to standardize the assessment of diets and adjust for microbial-related confounding factors in order to elucidate the association and mechanisms between pro-inflammatory diets and UC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".