Burden and determinants of cataract among adult patients over 40 years old in Ethiopia: a systematic review and meta-analysis, 2024
Bibliographic record
Abstract
Cataract is the most prevalent cause of blindness and the second most common cause of visual impairment globally. The primary cause of blindness in Ethiopia is cataracts. However, there is no evidence of pooled prevalence. The aim of this study was to assess the burden and determinants of cataract among adult people aged 40 years and above in Ethiopia. Potential studies were chosen using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria. PubMed, scopes and web of science were searched to identify relevant studies from 2000 to 2024 GC. To examine for heterogeneity the I 2 statistic was employed. A random-effects model was applied to estimate the pooled effect size across studies. The Egger's regression test and a funnel plot were employed to look for evidence of publication bias. The quality of included studies was assessed by utilizing the Newcastle–Ottawa Scale. The pooled burden and determinants of cataract were determined using STATA 17.0. A total of 5 studies met the inclusion criteria. In 2024, the pooled overall burden of cataract in 2989 people was 36% (95%CI 14–58%). Based on subgroup analysis, in the random effect method, the frequency of cataract in males and females were 17% (95% CI 0.07, 0.42) and 20% (95% CI 0.04, 0.36), respectively. The burden of cataract also in participants aged 40–49 years and older was found to be 6% (95% CI 0.04, 0.07) and 40% (95% CI 0.04, 0.75) correspondingly. Participants with a single marital status (AOR = 4.59, 95% CI 2.01, 7.17) and individuals 70 years of age and older (AOR = 7.35, 95% CI (2.93, 11.77)) have a higher risk of having cataract. A considerable proportion of research participants were found to have cataracts. Two factors were linked to cataract development: age and single marital status. Better cataract control in Ethiopia may arise from heeding the findings of the current study and putting international policy initiatives into practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".