The association of dietary glycemic index and glycemic load with risk of irritable bowel syndrome
Bibliographic record
Abstract
Abstract Purpose To date, no existing research has explored the potential relationship between dietary Glycemic Index (GI) and Glycemic Load (GL) and the risk of developing Irritable Bowel Syndrome (IBS). Our objective was to examine this association within a substantial sample of Iranian adults. Method This study was conducted on 3363 general public adults in Isfahan, Iran. A validated dish-based 106-item semi-quantitative food frequency questionnaire was used to examine dietary GI and GL. The presence of IBS was explored using a modified Persian version of the ROME III questionnaire. Totally, 22.2% (n = 748) of study participants had IBS. Result Participants with the highest dietary GI, had higher odds for IBS than those in the lowest category (OR: 1.34; 95% CI: 1.03–1.75). However, the association became non-significant after controlling for potential confounders (OR: 1.14; 95% CI: 0.81–1.61). A positive significant association was found between dietary GI and odds of IBS-constipation predominant (IBS-C) (OR: 1.96; 95% CI: 1.09–3.52), but not with IBS-diarrhea predominant (IBS-D) (OR: 0.78; 95% CI: 0.43–1.40). Conclusions No substantial link was observed between dietary glycemic load (GL) and the risk of overall irritable bowel syndrome (IBS) or its subtypes. However, a positive correlation was discovered between dietary GI and IBS with constipation (IBS-C).
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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".