Association of coffee and caffeine intake with irritable bowel syndrome in adults
Bibliographic record
Abstract
Abstract Background: The aim of this study was to investigate the association between coffee and caffeine intake and odds of IBS and its severity in adult population. Methods: In this cross-sectional study, dietary intakes of 3363 Iranian adults were examined using a validated dish-based 106-item Semi-quantitative Food Frequency Questionnaire (DS-FFQ). Coffee and caffeine intake was assessed using the DS-FFQ. IBS was assessed using a modified Persian version of Rome III questionnaire. Binary logistic regression, in which the effect of several potential confounders were controlled for, was used to examine the association between coffee and caffeine intake and prevalence of IBS and its subtypes. To identify the association with severity of IBS symptoms, we applied ordinal logistic regression. Results: After adjustment for potential confounders, we found that individuals who were taking coffee weekly or more had greater odds of IBS (OR:1.50; 95% CI: 1.07-2.11) than those who never drinking coffee. In addition, participants in the top tertile of caffeine intake had 49% greater odds of IBS compared to those in the bottom tertile (OR: 1.49; 95% CI: 1.16-1.90). By gender, this association was observed among women, but not in men (for coffee: OR: 1.50; 95% CI: 1.00-2.57 and for caffeine: OR: 1.50; 95% CI: 1.12-2.02). In addition, a significant positive association was seen between caffeine intake and odds of IBS among subjects with BMI≥25 kg/m2 (OR: 1.76; 95% CI: 1.22-2.53). There was no significant association between coffee and caffeine intake and IBS severity.Conclusion: Coffee and caffeine consumption was associated with increased odds of IBS, in particular among women and those with BMI ≥ 25 kg/m2.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".