Physical Activity as a Modifiable Risk Factor for Gastroesophageal Reflux Disease in Saudi Arabia: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Gastroesophageal reflux disease (GERD) is one of the most common disorders, significantly impacting patients' quality of life. Research suggests that physical activity (PA) can substantially reduce the occurrence of GERD. This systematic review and meta-analysis aim to investigate the association between PA and GERD in Saudi Arabia. The databases searched included Google Scholar, PubMed, Web of Science, Cochrane Library, Medline, Embase, NCBI, Scopus, and regional sources such as the Saudi Digital Library and Index Medicus for the Eastern Mediterranean Region. Cross-sectional and quasi-experimental studies conducted in Saudi Arabia between 2015 and 2024 were included to explore the relationship between PA and GERD. The quality of the included studies was assessed using the Newcastle-Ottawa Scale. A meta-analysis was conducted using MetaXL version 5.3 (EpiGear International Pty Ltd., Queensland, Australia), employing a random-effects model to estimate the overall prevalence of GERD. The OR was used to assess the relationship between PA and GERD. Heterogeneity was evaluated using the Higgins I² statistic and tested with the Cochran Q test. A total of 250 studies were included, comprising 6,183 participants. The pooled prevalence of GERD was estimated at 35% (95% CI: 24-47%). Individuals with lower levels of physical activity were 22% more likely to develop GERD compared to those with higher activity levels (pooled OR = 1.22, 95% CI: 1.05-1.42). The analysis revealed a high level of heterogeneity among the studies (I² = 99%, p < 0.001). Five studies were rated as high quality, while two were of medium quality. In conclusion, low physical activity increases the risk of GERD in Saudi Arabia. PA appears to be an effective primary prevention strategy to reduce the incidence of GERD. Further research is needed to confirm these findings and clarify the underlying mechanisms.
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.032 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".