Risk factors of bloating and its association with common gastrointestinal disorders in a sample of Iranian adults
Bibliographic record
Abstract
BACKGROUND/AIMS: Bloating is an unpleasant but common gastrointestinal symptom that is experienced by many people at some stage in their lives. The current survey was conducted to investigate the epidemiology and risk factors of bloating and functional bloating (FB). In addition, we aimed to assess the association between bloating and functional gastrointestinal disorders (FGIDs). MATERIALS AND METHODS: In this cross-sectional study, the self-administered modified Rome III questionnaire was used to assess gastrointestinal symptoms and FGIDs. Severity of bloating, demographic and anthropometric measurements, physical activity level, psychological distress, and depression and anxiety were also assessed. RESULTS: Among the 4763 participants, 52.9% reported having experienced bloating at least occasionally in the past three months (among which 14.1% had severe or very severe symptoms); 19.7% of subjects were found to have FB. After adjusting for multiple variables, female gender, university degree, obesity, and anxiety were associated with both bloating and FB, while depression and psychological distress were only associated with bloating. The positive predictive value and negative predictive value of bloating for the diagnosis of functional bowel disorder were 92.9% and 80.1%, respectively. CONCLUSION: Bloating and FB are highly prevalent in the study population. We also identified several demographic, psychological, and lifestyle-related risk factors of bloating in this population.
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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) | 0.001 | 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".