The Prevalence and Risk Factors of Stress Urinary Incontinence Among Women in Saudi Arabia: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Stress urinary incontinence (SUI) is a prevalent condition among women in Saudi Arabia, characterized by involuntary urine leakage during physical activities that increase abdominal pressure, such as coughing or sneezing. This systematic review and meta-analysis aimed to evaluate the prevalence of SUI and identify its key risk factors. Methods: A comprehensive search of PubMed, Scopus, and Web of Science was conducted for studies published up to July 2024, following PRISMA 2020 guidelines. Results: Ten observational studies involving 18,245 participants met the inclusion criteria, and study quality was assessed using the Newcastle–Ottawa Scale. A random-effects model was employed for meta-analysis, with subgroup and sensitivity analyses performed to address heterogeneity. The pooled prevalence of SUI was 26% (95% CI: 14–41%, I2 = 99%, p < 0.001), with rates ranging from 3.3% to 50%. Subgroup analysis showed a prevalence of 17% (95% CI: 1–42%, I2 = 99%, p < 0.001) in the general population and 33% (95% CI: 19–48%, I2 = 99%, p < 0.001) in specific groups, such as postpartum women and those with low back pain. Significant risk factors included age, obesity, high parity, and chronic conditions like diabetes. Despite high heterogeneity, sensitivity analyses confirmed the robustness of these findings. Conclusions: The findings underscore the need for public health strategies focused on weight management, pelvic floor rehabilitation, and increased awareness about SUI. Effective preventive measures could significantly reduce the burden of SUI and improve the quality of life for women in Saudi Arabia.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.034 |
| Bibliometrics | 0.008 | 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) | 0.002 | 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".