Prevalence and Risk Factors of Gastroesophageal Reflux Disease Among University Students in Saudi Arabia: A Systematic Review and Meta-Analysis of Studies Up to 2025
Bibliographic record
Abstract
Gastroesophageal reflux disease (GERD) is increasingly reported among young adults, yet its burden in university populations within Saudi Arabia has not been fully characterized. This systematic review and meta-analysis assessed the prevalence of GERD and its associated risk factors among university students in Saudi Arabia. A comprehensive search of PubMed, Scopus, Web of Science, and Google Scholar was conducted from inception to October 2025. Eligible studies were observational, conducted among university or college students in Saudi Arabia, and used validated diagnostic methods such as the GERD Questionnaire (GerdQ) with a cutoff score of ≥8. Eight studies involving 7,229 students met the inclusion criteria. Study characteristics, prevalence estimates, and associated risk factors were extracted, and study quality was assessed using the Newcastle-Ottawa Scale, with most studies demonstrating high methodological quality (scores 7-9). Meta-analysis was performed using random-effects models with logit transformation. The pooled prevalence of GERD was 26% (95%CI: 21-31%), with individual study estimates ranging from 18% to 35%. Subgroup analyses showed comparable prevalence estimates among female participants (24.97%), male participants (25.50%), medical students (29.30%), and non-medical or mixed student populations (25.43%), with no statistically significant differences between subgroups. Between-study heterogeneity was substantial (I² = 93.3%). Reported risk factors included smoking, high body mass index, tea or coffee consumption, fast food intake, psychological stress, and positive family history, while regular physical activity and higher fiber intake appeared protective. These findings indicate a substantial burden of GERD among university students in Saudi Arabia and highlight the need for targeted prevention and health promotion strategies 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 | 0.017 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.034 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".