Adherence to the pro-inflammatory diet in relation to prevalence of irritable bowel syndrome
Bibliographic record
Abstract
Abstract Objective There is no prior study that examined the association between nutrient-based dietary inflammatory index (DII) and odds of Irritable Bowel Syndrome (IBS). We examined the association between DII score and odds of IBS and its severity among Iranian adults. 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). DII was calculated based on dietary intakes derived from DS-FFQ. IBS was assessed using a modified Persian version of Rome III questionnaire. Results After adjustment for potential confounders, we found that participants in the highest quintile of DII score had greater chance for IBS compared with those in the lowest quintile (OR: 1.36; 95% CI: 1.03–1.80). By gender, we found a significant association between DII score and IBS among women (OR: 1.41; 95% CI: 1.00–2.00). By BMI status, overweight or obese (BMI ≥ 25 kg/m2) individuals in top quintile of DII score had greater odds for IBS than those in the bottom quintile (OR: 1.64; 95% CI: 1.07–2.53). No significant association was observed between a pro-inflammatory diet and severity of IBS symptoms. Conclusions Consumption of a pro-inflammatory diet 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 | 0.001 | 0.003 |
| 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 | 0.001 |
| 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".