Global Glaucoma Prevalence: Burden and Projection to 2060
Bibliographic record
Abstract
PURPOSE: To provide updated global and regional estimates of the prevalence and population burden of open-angle glaucoma (OAG), incorporating both demographic aging and the rising prevalence of myopia-a major risk factor that accelerates onset and increases OAG risk. DESIGN: Systematic review, meta-analysis, and global projection study. METHODS: A systematic review and meta-analysis (PROSPERO: CRD42024520990) of 77 population-based publications (1991-2023) were conducted to estimate current age- and region-specific OAG prevalence across Global Burden of Disease regions. OAG prevalence in 2060 was modeled based on associated risk ratios (RR: 1.9 [95% confidence interval (CI), 1.7-2.1]) and myopia trends synthesized from 57 publications. United Nations population data were integrated to estimate the affected population. Early-onset OAG (20-39 years) in 2060, attributable to high myopia, was estimated separately using projected high myopia prevalence and a pooled OAG prevalence of 4.4% (95% CI, 3.5%-5.3%) in this highly myopic younger population. RESULTS: Global OAG prevalence (≥40 years) is expected to rise from 2.8% (95% CI, 2.6%-3.0%) in 2024 to 3.5% (95% CI, 3.2%-3.8%) by 2060, with the affected population increasing from 80.5 (95% CI, 75.4-85.6) million to 186.6 (95% CI, 174.3-199.0) million. Aging and demographic changes account for an increase to 77.3 million, leaving the additional 28.9 million cases (27.2% of the total increase) attributed to the myopia epidemic. An estimated 6.1 (95% CI, 5.5-6.7) million early-onset OAG cases due to high myopia will bring the total global OAG population to 192.7 (95% CI, 180.4-205.1) million by 2060. East Asia will experience the greatest relative increase, with prevalence rising by 50.5% from 2.3% (95% CI, 1.8%-2.8%) to 3.4% (95% CI, 2.7%-4.2%). CONCLUSIONS: There is a significant, previously underestimated, increase in OAG burden globally, driven by the rising prevalence of myopia. This adds additional OAG burden, particularly to younger populations less than 40 years. Thus, myopia prevention and new targeted screening strategies are important to tackle OAG, especially in regions with a high prevalence of myopia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".