Prevalence of stunting and its correlates among children under 5 in Afghanistan: the potential impact of basic and full vaccination
Notice bibliographique
Résumé
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.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».