Abstract
Background
Undernutrition and anemia are significant public health issues among under-5 children, with potential long-term consequences for growth, development, and overall health. Thus, this study aims to conduct a bivariate binary logistic regression model by accounting for the possible dependency of childhood undernutrition and anemia.
Methods
The data came from the DHS program’s measurement. A total of 3,206 under-five children were involved in this study. A single composite index measure was calculated for stunting, wasting, and underweight using principal component analysis. A bivariate binary logistic regression model is used to assess the association between undernutrition and anemia given the effect of other predictors.
Results
Among 3,206 under-five children considered in this study, 1482 (46.2%) and 658 (20.5%) children were agonized by anemia and undernutrition, respectively. In bivariate binary logistic regression model; Urban children [AOR = 0.751, 96% CI: 0.573–0.984; AOR = 0.663, 95% CI: 0.456–0.995] and anemic mothers [AOR = 1.160, 95% CI: 1.104–1.218; AOR = 1.663, 95% CI: 1.242–2.225] were significantly associated with both childhood anemia and undernutrition, respectively. Improved water sources [AOR = 0.681, 95% CI: 0.446–0.996], average-sized children [AOR = 0.567, 95% CI: 0.462–0.696], and diarrhea [AOR = 1.134, 95% CI: 1.120–2.792] were significantly associated with childhood anemia. Large-sized children [AOR = 0.882, 95% CI: 0.791–0.853] and those with fever [AOR = 1.152, 95% CI: 1.312–2.981] were significantly associated with under-five children’s undernutrition.
Conclusion
The prevalence of both undernutrition and anemia among under-five-year-old children was high in Rwanda. The following determinants are statistically associated with both childhood undernutrition and anemia: place of residence; source of drinking water; maternal anemia; being a twin; birth size of children; diarrhea; fever; and child age. Anemia and nutritional deficiencies must be treated concurrently under one program, with evidence-based policies aimed at vulnerable populations.
Publisher
Public Library of Science (PLoS)
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