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Nutrition-specific and sensitive drivers of poor child nutrition in Kilte Awlaelo-Health and Demographic Surveillance Site, Tigray, Northern Ethiopia: implications for public health nutrition in resource-poor settings

Background: Child undernutrition is a prevalent health problem and poses various short and long-term consequences. Objective: This study seeks to investigate the burden of child undernutrition and its drivers in Kilte Awlaelo-Health and Demographic Surveillance Site, Tigray, northern Ethiopia. Metho...

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Detalles Bibliográficos
Autores principales: Abera, Semaw Ferede, Kantelhardt, Eva Johanna, Bezabih, Afewrok Mulugeta, Gebru, Alemseged Aregay, Ejeta, Gebisa, Lauvai, Judith, Wienke, Andreas, Scherbaum, Veronika
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6338276/
https://www.ncbi.nlm.nih.gov/pubmed/31154991
http://dx.doi.org/10.1080/16549716.2018.1556572
Descripción
Sumario:Background: Child undernutrition is a prevalent health problem and poses various short and long-term consequences. Objective: This study seeks to investigate the burden of child undernutrition and its drivers in Kilte Awlaelo-Health and Demographic Surveillance Site, Tigray, northern Ethiopia. Methods: In 2015, cross-sectional data were collected from 1,525 children aged 6–23 months. Maternal and child nutritional status was assessed using the mid upper arm circumference. Child’s dietary diversity score was calculated using 24-hours dietary recall method. Log-binomial regression and partial proportional odds model were fitted to examine the drivers of poor child nutrition and child dietary diversity (CDD), respectively. Results: The burden of undernutrition and inadequate CDD was 13.7% (95% CI: 12.1–15.5%) and 81.3% (95%CI: 79.2–83.1%), respectively. Maternal undernutrition (adjusted prevalence ratio, adjPR = 1.47; 95%CI: 1.14–1.89), low CDD (adjPR = 1.90; 95%CI: 1.22–2.97), and morbidity (adjPR = 1.83; 95%CI: 1.15–2.92) were the nutrition-specific drivers of child undernutrition. The nutrition-sensitive drivers were poverty (compared to the poorest, adjPR poor = 0.65 [95%CI:0.45–0.93], adjPR medium = 0.64 [95%CI: 0.44–0.93], adjPR wealthy = 0.46 [95%CI: 0.30–0.70], and adjPR wealthiest = 0.53 [95%CI: 0.34–0.82]), larger family size (adjPR = 1.10; 95%CI: 1.02–1.18), household head’s employment insecurity (adjPR = 2.10; 95%CI: 1.43–3.09), and residing in highlands (adjPR = 1.93; 95%CI: 1.36–2.75). The data show that higher CDD was positively associated with wealth (OR wealthy = 3.06 [95%CI: 1.88–4.99], OR wealthiest = 2.57 [95%CI: 1.53–4.31]), but it was inversely associated with lack of diverse food crops production in highlands (OR = 0.23; 95%CI: 0.10–0.57]). Conclusions: Our findings suggest that the burden of poor child nutrition is very high in the study area. Multi-sectoral collaboration and cross-disciplinary interventions between agriculture, nutrition and health sectors are recommended to address child undernutrition in resource poor and food insecure rural communities of similar settings.