Relationship between spicy food intake and chronic uninvestigated dyspepsia in Iranian adults
Bibliographic record
Abstract
OBJECTIVE: To assess the association between spicy food consumption and chronic uninvestigated dyspepsia (CUD) in a large sample of Iranian adults. METHODS: In this cross-sectional study we assessed the consumption of spicy foods in 4763 Iranian adults living in Isfahan Province using a dietary habit questionnaire. A modified validated version of the Rome III questionnaire was used to assess CUD-related symptoms. CUD was defined as having one or more of the following characteristics: distressing postprandial fullness, early satiation and/or epigastric pain or epigastric burning at least often during the past three months. Information on meal regularity, meal frequency, intra-meal intake of fluid as well as other potential confounders was also collected. RESULTS: CUD was prevalent in 15% of the participants. The frequent consumption of spicy foods (≥ 10 times/week) was associated with greater odds of having CUD [odds ratio (OR) 1.64, 95% confidence interval (CI) 1.09-2.49, P < 0.05). This relationship was significant even after adjusted for diet-related practices (OR 1.68, 95% CI 1.01-2.79, P < 0.05). There was a significantly positive association between spicy food consumption and postprandial fullness (OR 1.76, 95% CI 1.29-2.40, P < 0.05) and epigastric pain (OR 1.78, 95% CI 1.30-2.44, P < 0.05). However, no significant relationship was observed between the frequent consumption of spicy foods and early satiation. CONCLUSIONS: High consumption of spicy foods is associated with greater odds of CUD, frequent postprandial fullness and epigastric pain. Further studies, particularly of a prospective nature, are needed to confirm our findings.
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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 | 0.002 |
| 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".