Spatial variation and determinants of childhood anemia among children aged 6 to 59 months in Ethiopia: further analysis of Ethiopian demographic and health survey 2016
BACKGROUND: The magnitude of childhood anemia was increased from time to time. Thus, Even if the Ethiopian government applied tremendous efforts, anemia in children continues as a major public health problem. There is limited evidence on the spatial variation of and determinant factors of childhood anemia at the national level. Therefore, this study aimed to explore spatial distribution and determinants of anemia among children aged 6 to 59 months in Ethiopia. METHOD: A stratified two-stage cluster sampling technique was used in Ethiopian Demographic Health Survey 2016 data. In this study 8602 children aged 6–59 months were included. Bernoulli model was used to explore the presence of purely spatial clusters of Anemia in children in age 6–59 months using Sat scan. ArcGIS version 10.3 was used to know the distribution of anemia cases across the country. A mixed-effects Logistic regression model was used to identify determinant factors of anemia. RESULTS: The finding indicates that the spatial distribution of childhood anemia was non-random in the country with Moran's I: 0.65, p < 0.001. The SaT scan analysis identified a total of 180 significant primary clusters located in the Somali and Afar regions (LLR = 14.47, P-value< 0.001, RR = 1.47). Age of child 12–23 months (AOR = 0, 68, 95%CI: 0.55, 0.85), 24–35 months (AOR = 0.38, 95%CI: 0.31, 0.47), and36–47 months (AOR = 0.25, 95%CI, 0.20, 0.31), working mother (AOR = 0.87, 95%CI: 0.76, 0.99), anemic mother (AOR = 1.53, 95%CI, 1.35, 1.73), had fever in the last 2 weeks (AOR = 1.36,95%CI:1.13, 1.65), moderate stunting (AOR = 1.31,95%CI: 1.13, 1.50),Severely stunting (AOR = 1.82,95%CI: 1.54, 2.16), religion, wealth index, and number of under-five children in the household were statistically significant associated with childhood anemia. CONCLUSION: Spatial variation of childhood anemia across the country was non-random. Age of the child, wealth index, stunting, religion, number of under-five children in the household, fever in the last 2 weeks, anemic mother, and ...