Mother–child dyads of overnutrition and undernutrition in sub-Saharan Africa
Notice bibliographique
Résumé
BACKGROUND: Malnutrition remains one of the major public health concerns globally. To achieve the Sustainable Development Goal 2 which seeks to ensure that hunger and malnutrition are reduced by 2030, it is imperative to ascertain the factors influencing their occurrence. This study examined the prevalence and factors associated with mother-child dyads of overnutrition and undernutrition in sub-Saharan Africa. METHODS: Demographic and Health Survey data from 25 sub-Saharan African countries were used for the study. The sample was made up of 125,280 mother-child dyads. Descriptive analysis was performed to determine the prevalence of overweight or obese mother (OWOBM) with a stunted child (OWOBM-SC), OWOBM with an underweight child (OWOBM-UC), OWOBM with a wasted child (OWOBM-WC), and OWOBM with any form of child's undernutrition indicators (OWOBM-SUWC). Multilevel regression models were developed to examine the factors associated with these indicators. The results were presented using an adjusted odds ratio (AOR) with their respective 95% confidence interval (CI). RESULTS: Higher likelihood of OWOBM-SUWC was found among women aged 45-49 [AOR 2.20, 95% CI 1.70, 2.85], those with primary [AOR 1.32, 95% CI 1.21, 1.44] or secondary education [AOR 1.21, 95% CI 1.09, 1.35], and divorced women [AOR 1.32, 95% CI 1.02, 1.73]. However, lower odds of OWOBM-SUWC were observed among women who were working [AOR 0.82, 95% CI 0.76, 0.89] and those breastfeeding [AOR 0.75, 95% CI 0.70, 0.82]. The odds of OWOBM-SUWC was lower among females compared to male children [AOR 0.85, 95% CI 0.80, 0.90]. Compared to children aged <1 year, children of all other age groups were more likely to have OWOBM-SUWC. Other child characteristics significantly associated with OWOBM-SUWC were low birth weight [AOR 1.50, 95% CI 1.32, 1.71], having diarrhea [AOR 1.13, 95% CI 1.04, 1.24], and higher birth order [AOR 1.37, 95% CI 1.13, 1.66]. Children whose mothers used unimproved toilet facilities [AOR 0.90, 95% CI 0.83, 0.98], those who lived in rural areas [AOR 0.79, 95% CI 0.71, 0.87], and children from the Central [AOR 0.55, 95% CI 0.46, 0.65], Eastern [AOR 0.44, 95% CI 0.38, 0.52] and Western [AOR 0.76, 95% CI 0.65, 0.89] sub-Saharan Africa were less likely to have OWOBM-SUWC. CONCLUSION: Combination of child, maternal, and contextual factors could explain mother-child dyads of overnutrition and undernutrition in sub-Saharan Africa. Addressing this situation requires multidimensional policies and interventions that empower women through education and economic engagement. The observed sub-regional differences in policies and commitments related to addressing malnutrition suggest the need for comprehensive and coordinated efforts to implement and strengthen multisectoral comprehensive nutrition plans across sub-Saharan Africa. Sharing best practices and lessons learned can help improve the effectiveness and comprehensiveness of nutrition interventions and contribute to reducing the prevalence of malnutrition.
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 | 0,001 | 0,004 |
| 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 | 0,001 |
| 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 ».