Prevalence of stunting and its correlates among children under 5 in Afghanistan: the potential impact of basic and full vaccination
Bibliographic record
Abstract
BACKGROUND: Child stunting is prevalent in low and middle-income countries (LMICs), but an information gap remains regarding its current prevalence, correlates, and the impact of vaccination against this condition in Afghanistan. This study aimed to determine the prevalence and correlates of moderate and severe stunting and the potential impact of basic and full vaccination among children under five in Afghanistan. METHODS: This is a secondary analysis of the 2022-23 Afghanistan Multiple Indicators Cluster Survey (MICS) including 32,989 children under 5. Descriptive statistics were employed to describe the distribution of independent variables and the prevalence of stunting across them. Chi-square analysis was used to examine the association between each independent variable with stunting. Multinomial logistic regression was used to examine the risk of stunting across different independent variables. RESULTS: A total of 32,989 children under 5 years old were included in this study. Of those 44.7% were stunted with 21.74% being severely stunted. Children aged 24-35 and 36-47 months faced the highest risk as compared to those aged 1-5 months. The prevalence was lower in female children and they were less likely to experience severe stunting. Stunting was more prevalent in rural areas, with children there 1.16 to 1.23 times more likely to be affected than urban counterparts. Lower wealth correlated with higher stunting. Younger maternal age at birth (≤ 18) correlated with increased stunting risks, particularly in severe cases. Parental education was inversely related to stunting; higher education levels in parents, especially fathers, were associated with lower stunting rates. Households with more than seven children showed a 25% and 44% higher risk of moderate and severe stunting, respectively, compared to families with 1-4 children. Improved sanitation, but not drinking water sources, was linked to reduced stunting in the adjusted model. Vaccination had a protective effect; in the adjusted analysis, basic and full vaccinations significantly lowered the risk of severe stunting by 46% and 41%, respectively. CONCLUSION: In this nationally representative study, the prevalence of stunting was substantial (44.7%) in Afghan children. Additionally, the findings emphasize the critical factors associated with child stunting and underscore the protective role of vaccination against this condition, which provides policymakers with directions for policy efforts and intervention strategies to reduce child stunting in Afghanistan.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".