Dietary Patterns Are Associated With Variations in the Global Prevalence and Severity of Rome IV Irritable Bowel Syndrome
Bibliographic record
Abstract
BACKGROUND & AIMS: The relationship between regional dietary patterns and the global prevalence and severity of irritable bowel syndrome (IBS) is unclear. We aimed to determine whether dietary patterns are associated with variation in the global prevalence and severity of IBS. METHODS: A total of 54,127 participants from 26 countries completed online questionnaires including Rome IV IBS criteria and the frequency of intake of 10 foods or food groups (fruit, vegetables/legumes, milk, rice, bread, pasta, meat, fish, tofu, eggs). Latent class analysis was conducted to identify distinct dietary patterns (clusters), adjusted for country, religion, and age. Multivariable logistic regression analysis was then performed to explore the association between these clusters and IBS prevalence and severity. RESULTS: Four clusters with marked differences in dietary intake frequency of the 10 foods and IBS prevalence (P < .001) were identified. Dietary clusters A (5.6%; 95% confidence interval [CI], 5.2%-6.0%) and B (4.5%; 95% CI, 4.2%-4.8%), with the highest IBS prevalence, also had the highest IBS symptom severity scores (P < .001), and were predominantly represented by Egypt, Brazil, and Colombia in cluster A and Argentina, Germany, Poland, and the United States in cluster B. By contrast, the lower IBS prevalence clusters, cluster C (3.4%; 95% CI, 3.1%-3.7%), represented predominantly by Europe, and cluster D (2.6%; 95% CI, 2.3%-2.9%), strongly represented by Asian countries, had lower IBS symptom severity. CONCLUSIONS: Dietary patterns adjusted by age, country, and religion are associated with the global prevalence and severity of IBS. Further studies are required to investigate population-specific dietary preferences and acceptability of dietary interventions for IBS.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".