Global prevalence and burden of meal-related abdominal pain
Bibliographic record
Abstract
BACKGROUND: Patients with disorders of gut-brain interaction (DGBI) report meal intake to be associated with symptoms. DGBI patients with meal-related symptoms may have more severe symptoms overall and worse health outcomes, but this subgroup has not been well characterized. We aimed to describe the global prevalence of meal-related abdominal pain and characterize this subgroup. METHODS: The data analyzed originated from the Internet survey component of the population-based Rome Foundation Global Epidemiology Study, completed in 26 countries (n = 54,127). Adult subjects were asked whether they had abdominal pain and how often this was meal-related. Respondents were categorized into "no," "occasional," and "frequent" meal-related abdominal pain groups based on 0%, 10-40%, and ≥50% of the pain episodes being meal-related, respectively. DGBI diagnoses, frequency of other GI symptoms, psychological distress, non-GI somatic symptoms, quality of life, and healthcare utilization were compared between groups. Mixed linear and ordinal regression was used to assess independent associations between psychological distress, non-GI somatic symptoms, quality of life, other GI symptoms, and meal-related abdominal pain. RESULTS: Overall, 51.9% of the respondents reported abdominal pain in the last 3 months, and 11.0% belonged to the group with frequent meal-related abdominal pain, which included more females and younger subjects. DGBI diagnoses were more common in subjects with frequent meal-related abdominal pain, and the frequency of several GI symptoms was associated with having more frequent meal-related abdominal pain. Having meal-related abdominal pain more frequently was also associated with more severe psychological distress, non-GI somatic symptoms, and a poorer quality of life. The group with frequent meal-related abdominal pain also more often consulted a doctor for bowel problems compared to the other groups of meal-related abdominal pain. CONCLUSION: Reporting frequent meal-related abdominal pain is common across the globe and associated with other GI and non-GI somatic symptoms, psychological distress, healthcare utilization, and a poorer quality of life. Individuals who frequently experience meal-related abdominal pain also more frequently fulfill the diagnostic criteria for DGBI. Assessing meal-related symptoms in all DGBI patients could be of major importance to improve and individualize symptom management.
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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 | 0.002 |
| 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 | 0.001 |
| 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".