Prevalence and determinants of developmental delay among children in low- and middle-income countries: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Developmental delay is a public health problem in low- and middle-income countries. However, there is no summarized evidence in low- and middle-income countries on developmental delay, and primary studies on this issue show varied and inconclusive results. This systematic review and meta-analysis aimed to assess the pooled magnitude of confirmed developmental delay and its determinants among children in low- and middle-income countries. Methods We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines to write this systematic review and meta-analysis. Primary studies were searched from PubMed, PsycINFO, Hinari, Science Direct, African Journal of Online, Web of Science, and Google Scholar databases. The Newcastle–Ottawa Scale, adapted for the cross-sectional studies, was used to assess the quality of the included studies. Heterogeneity and publication bias were assessed by the I 2 and Eggers tests, respectively. Due to the high heterogeneity, the random effects model was used for analysis. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to show the association between developmental delay and its determinants. Results The pooled prevalence of confirmed developmental delay was 18.83, 95% CI (15.53–22.12). In the subgroup analysis, a high prevalence of developmental delay [26.69% (95% CI, 15.78–37.60)] was observed in studies performed in Africa. Maternal education [3.04; 95% CI (2.05, 4.52)] and low birth weight [3.61; 95% CI (1.72, 7.57)] were significant determinants of developmental delay. Conclusion The pooled prevalence of developmental delay in low- and middle-income countries was high as compared to that in high-income countries. Maternal education level and weight at birth were significantly associated with developmental delays. Therefore, strategies should be designed to decrease the rate of low birth weight and the number of illiterate mothers living in low- and middle-income countries. Systematic review registration PROSPERO, CRD42024513060.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.049 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".