Inequities in childhood anaemia in Mozambique: results from multilevel Bayesian analysis of 2018 National Malaria Indicator Survey
Notice bibliographique
Résumé
Abstract Introduction Childhood anaemia is a common public health problem worldwide. The geographical patterns and underlying factors of childhood anaemia have been understudied in Mozambique. The objectives of this study were to identify the child-, maternal-, household-, and community-level determinants of anaemia among children aged 6-59 months, and the contribution of these factors to the variation in childhood anaemia at the community level in Mozambique. Methods This is a cross-sectional study that utilized data of a weighted population of 4,141 children aged 6-59 months delivered by women between 15-49 years of age, from the 2018 Mozambique Malaria Indicator Survey. Multilevel Bayesian linear regressions identified key determinants of childhood anaemia. Spatial analysis was used to determine geographic variation of anaemia at the community level and areas with higher risks. Results The overall national prevalence of childhood anaemia was 78-80.3%. There was provincial variation with Cabo Delgado province (86.2%) having highest prevalence, and Maputo province (70.2%) the lowest. Children with excess risk were mostly found in communities that had proximity to provincial borders: Niassa-Cabo Delgado-Nampula tri-provincial border, Gaza-Inhambane border, Zambezia-Nampula border, and provinces of Manica and Inhambane. Children with anaemia tended to be younger, males, and at risk of having malaria because they were not sleeping under mosquito nets. In addition, children from poor families and those living in female-headed households were prone to anaemia. Conclusion This study provides evidence that anaemia among children aged 6-59 months is a severe public health threat across the provinces in Mozambique. It also identifies inequity in childhood anaemia—worse among communities living close to the provincial borders. We recommend interventions that would generate income for households, increase community-support for households headed by women, improve malaria control, build capacity of healthcare workers to manage severely anaemic children and health education for mothers. More importantly, there is need to foster collaborations between communities, districts and provinces to strengthen maternal and child health programmes for the severely affected areas. What is already known? Nearly two billion people are anaemic, affecting mostly poor women and children. Anaemia, a co-morbidity with other major health conditions, frequently is less prioritized. Sustainable Development Goals 2 and 3, formulated to tackle hunger/food insecurity and attain optimal health/wellbeing, respectively, currently have no specific target for monitoring global progress for anaemia among children. What are the new findings? Twenty-four percent of children (6-59 months) had anaemia classified as mild, 50% moderate and 7% severe. Childhood anaemia showed spatial variation across the communities—especially in the provincial border regions--and provinces in Mozambique; they were younger, males, at risk of having malaria, from poor families and lived in female-headed household. What do the new findings imply? Anaemia among children could be effectively reduced through malaria prevention, e.g. bed netting. This report of anaemia at community and district level provides baseline data and can guide targeted implementation of the 2025 Mozambique National Development Plan. Interventions needed that generate income for households, increase community-support for households headed by women, improve malaria control, build capacity of healthcare workers to manage severely anaemic children and health education for mothers.
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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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| 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) | 0,001 | 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 ».