Prevalence, symptom patterns and management of episodic diarrhoea in the community: a population‐based survey in 11 countries
Bibliographic record
Abstract
BACKGROUND: The extent of episodic diarrhoea in the community is relatively unknown. AIM: To ascertain the prevalence, symptoms and management behaviours associated with self-reported diarrhoea across 11 countries. METHODS: Community screening surveys were conducted using quota sampling of respondents to identify a nationally representative sample of individuals suffering from 'episodic' diarrhoea (occurring once a month or more often). Second-phase in-depth surveys provided data on epidemiology, symptoms, attributed causes and management of episodic diarrhoea. RESULTS: A total of 11 508 phase 1 and 6613 phase 2 surveys were completed. The prevalence of self-reported episodic diarrhoea ranged from 16% to 23% across the 11 countries. The majority of episodic diarrhoea sufferers were female (57%) and were not diagnosed with pre-existing irritable bowel syndrome (IBS); IBS diagnosis ranged from 9% in Mexico to 44% in Italy. Diarrhoea was frequently attributed to anxiety/stress, food-related causes, gastrointestinal 'sensitivity' and menstruation. Accompanying symptoms included 'stomach pain/cramping' (35-62%), 'stomach grumbling' (29-68%) and 'wind' (18-74%). The proportion of episodic sufferers who reported treating their symptoms with remedies or medications ranged between 46% in Belgium and Canada and 90% in Mexico. CONCLUSIONS: A substantial proportion of the population in middle- to high-income countries report episodic diarrhoea in the absence of a pre-existing diagnosis. These symptoms are likely to be associated with substantial social and economic costs, and have implications on how best to configure and guide self-led, pharmacist-led and primary care 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".