The Role of a Plant-Only (Vegan) Diet in Gastroesophageal Reflux Disease: Online Survey of the Italian General Population
Bibliographic record
Abstract
The relationship between food and the pathophysiological mechanisms of gastroesophageal reflux disease (GERD) is unclear. There are few data on the impact of dietary habits on GERD symptoms and on the incidence of GERD in subjects undergoing plant-based diets. In this study, we investigated the association between diet and GERD, using data collected through an online survey of the Italian general population. In total, 1077 subjects participated in the study. GERD was defined according to the Montreal Consensus. For all subjects age, gender, body mass index (BMI), marital status, education, occupation, alcohol consumption, and smoking habits were recorded. All participants also completed the SF-36 questionnaire on Quality of Life. A total of 402 subjects (37.3%) were vegans and 675 (62.7%) non-vegans. The prevalence of GERD in the total population was 9%. Subjects with GERD-related symptoms recorded a worse quality of life according to SF-36 analysis (p < 0.05 for all dimensions). In multivariate analysis, after adjusting for confounders, participants undergoing a vegan diet had a significantly lower risk of GERD (OR = 0.47, 95% CI 0.28–0.81, p = 0.006). These findings should be taken into account to inform the lifestyle management of GERD.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".