Determinants of Stunting among Children under Five in Pakistan
Notice bibliographique
Résumé
Introduction: Child stunting remains a public health concern. It is characterized as poor cognitive and physical development in children due to inadequate nutrition during the first 1000 days of life. Across south Asia, Pakistan has the second-highest prevalence of stunting. This study assessed the most recent nationally representative data, the National Nutrition Survey (NNS) 2018, to identify the stunting prevalence and determinants among Pakistani children under five. Methods: The NNS 2018, a cross-sectional household-level survey, was used to conduct a secondary analysis. Data on malnutrition, dietary practices, and food insecurity were used to identify the prevalence of stunting among children under five years in terms of demographic, socioeconomic, and geographic characteristics. The prevalence of stunting was calculated using the World Health Organization (WHO) height for age z-score references. Univariate and multivariable logistic regressions were conducted to identify the factors associated with child stunting. Results: The analysis showed that out of 52,602 children under five, 40.0% were found to be stunted. Male children living in rural areas were more susceptible to stunting. Furthermore, stunting was more prevalent among children whose mothers had no education, were between 20 and 34, and were employed. In the multivariable logistic regression, male children (AOR = 1.08, 95% CI [1.04–1.14], p < 0.001) from rural areas (AOR = 1.07, 95% CI [1.01–1.14], p = 0.014), with the presence of diarrhea in the last two weeks (AOR = 1.15, 95% CI [1.06–1.25], p < 0.001) and mothers who had no education (AOR = 1.57, 95% CI [1.42–1.73], p < 0.001) or lower levels of education (primary: AOR = 1.35, 95% CI [1.21–1.51], p < 0.001; middle: AOR = 1.29, 95% CI [1.15–1.45], p < 0.001), had higher odds of stunting. Younger children aged < 6 months (AOR = 0.53, 95% CI [0.48–0.58], p < 0.001) and 6–23 months (AOR = 0.89, 95% CI [0.84–0.94], p < 0.001), with mothers aged 35–49 years (AOR = 0.78, 95% CI [0.66–0.92], p = 0.003), had lower odds of stunting. At the household level, the odds of child stunting were higher in lower-income households (AOR = 1.64, 95% CI [1.46–1.83], p < 0.001) with ≥ 7 members (AOR = 1.09, 95% CI [1.04–1.15], p < 0.001), with no access to improved sanitation facilities (AOR = 1.14, 95% CI [1.06–1.22], p < 0.001) and experiencing severe food insecurity (AOR = 1.07, 95% CI [1.01–1.14], p = 0.02). Conclusion: Child stunting in Pakistan is strongly associated with various factors, including gender, age, diarrhea, residence, maternal age and education, household size, food and wealth status, and access to sanitation. To address this, interventions must be introduced to make locally available food and nutritious supplements more affordable, improve access to safe water and sanitation, and promote female education for long-term reductions in stunting rates.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| 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 ».