Early childhood development and its associated factors among children aged 36–59 months in Afghanistan: evidence from the national survey 2022–2023
Bibliographic record
Abstract
BACKGROUND: Understanding the status of early childhood development (ECD) and its associated factors could serve as the basis for future policy efforts and interventions. Therefore, this study aimed to determine the status of ECD and its associated factors among children aged 36-59 months in Afghanistan. METHODS: We used data from the Afghanistan Multiple Indicator Cluster Survey 2022-2023 (MICS) to assess ECD status. The outcome variable was a binary measure, indicating whether a child was developmentally on track or not. To explore the associations between ECD status and various explanatory variables, we applied binary logistic regression models, presenting both univariate and multivariate analyses. RESULTS: Among the 13,866 children aged 36 to 59 months included in the analysis, 29.95% (95% CI: 29.19-30.72%) were found to be developmentally on track. The likelihood of being developmentally on track was higher in children whose mothers had secondary [adjusted odds ratio (AOR) 1.36 (95%CI 1.04-1.77)] and higher education [1.73 (1.08-2.76)], in children whose fathers had primary [1.32 (1.05-1.67)], secondary [1.40 (1.10-1.79) and higher education [1.60 (1.21-2.11)], and in children belonging to the higher household wealth status [1.46 (1.18-1.82)]. On the other hand, the likelihood of being developmentally on track was lower in children aged 48-59 months [0.35 (0.30-0.40)], in children living in rural areas [0.77 (0.62-0.96)], in children with stunting [0.77 (0.61-0.96)], and in underweight children [0.61 (0.52-0.72)]. CONCLUSION: Our findings indicate that 29.95% of children aged 36-59 months in Afghanistan are developmentally on track. Positive associations were found between ECD and higher parental education and household wealth status. However, living in rural areas, underweight and stunted growth were negatively associated with ECD. To improve early childhood development programs in Afghanistan, targeted interventions are needed to address the factors identified in this study.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".