Prevalence of Refractive Errors Among School-Age Children and Adolescents in Saudi Arabia: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Refractive errors, including myopia, hyperopia, and astigmatism, are a leading cause of visual impairment among children worldwide. In Saudi Arabia, the prevalence of these conditions among school-age children and adolescents remains poorly understood, with significant variations reported across studies. This systematic review and meta-analysis aimed to provide a comprehensive estimate of the pooled prevalence of refractive errors in this population and explored factors influencing their distribution. Methods: A systematic search of PubMed, Scopus, Web of Science, and ScienceDirect was conducted in accordance with PRISMA 2020 guidelines. Observational studies reporting the prevalence of refractive errors among Saudi school-aged children and adolescents were included. Data extraction and quality assessment were conducted using the Newcastle-Ottawa Scale. Pooled prevalence estimates with 95% confidence intervals (CIs) were calculated using a random-effects model, and heterogeneity was assessed with the I² statistic. Results: Nine studies including over 15,000 participants were analyzed. The pooled prevalence of myopia was 6.7% (95% CI: 3.0% to 14.2%), hyperopia was 3.6% (95% CI: 1.3% to 9.8%), and astigmatism was 7.7% (95% CI: 2.5% to 20.9%). Subgroup analysis revealed regional disparities, with the highest myopia prevalence reported in Taif (33.3%) and Bisha (22.5%), and the lowest in Medina (1.6%). Studies conducted after 2018 showed a significantly higher pooled myopia prevalence (16.4%, 95% CI: 8% to 30.5%) compared to those published before 2018 (3.3%, 95% CI: 1.4% to 7.5%) (p < 0.001). While studies using cycloplegic refraction reported a slightly higher myopia prevalence (7.2%, 95% CI: 4.7% to 11%) than those using non-cycloplegic methods (6.7%, 95% CI: 2.4% to 17.5%), the difference was not statistically significant (p = 0.9). No significant difference was observed between studies with smaller or larger sample sizes, although high heterogeneity persisted across all subgroups. Conclusion: Refractive errors, particularly astigmatism, represent a significant and growing public health issue among Saudi school-aged children and adolescents. The findings underscore the urgent need for standardized diagnostic protocols, including the use of cycloplegic refraction, and the implementation of school-based vision screening programs.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.024 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".