EXPLORATORY SPATIAL ANALYSIS OF UNDERNUTRITION AND ITS DETERMINANTS AMONG UNDERFIVE CHILDREN IN ETHIOPIA: A MULTI_LEVEL ANALYSIS

Abstract

Background: Undernutrition has been a public health problem in both developed and developing countries. According to the World Health Organization (WHO), children under 5 years of age, 155 million are stunted, 52 million are wasted, 17 million are severely wasted and 41 million are overweight and/or obese. Malnutrition is not just a health issue but also affects the global burden of malnutrition socially, economically, developmentally and medically, affecting individuals, their families and communities with serious and long lasting consequences. Identification of spatial variations and individual and contextual level determinant factors of child undernutrition is essential to deliver targeted, efficient and sustainable solutions to the problems. Objectives: This study determined exploratory spatial variations and its determinants of undernutrition among underfive children. Methods ad Result: This study uses Ethiopian Mini_Demographic Health Survey 2019 data set. Spatial and multilevel analysis was used to analyses the data set. Spatial analysis was carried out by using Geographic information system (GIS) (i.e., Arc Map 10.7). Multilevel logistic regression was used to identify determinant factors of undernutrition. The result shows that undernutrition (stunted, wasted, or underweight) affects approximately 38.25% of children in Ethiopia. The proportions of undernourished children in urban and rural areas were 26.5 % and 41.6 %, respectively. The result from Global Moran‘s I and local indicators of spatial autocorrelation reveal that the distribution of undernutrition is clustered or not random in Ethiopia. The highest prevalence of undernutrition among underfive (U5C) children was identified in the entire Tigray, Northern Amhara, Somalia, and Afar regions. The SaTScan analysis identified a total of 110 significant hotspot areas of children undernutrition with three significant spatial windows of which 100 clusters were primary (most likely clusters) while 10 were secondary clusters. Determinant factors such as regions, diet diversity, the number of household members, and the age of the child in month, the age of the mother at first birth, the partner's education level, the preceding birth interval, and the ANC visit have statistically significant roles in the odds of undernutrition in Ethiopia. Conclusion and Recommendation: The overall magnitude of childhood stunting, underweight and wasting among underfive children were found to be very high with geographical variations across different region. The study showed heterogeneity in the magnitude of child undernutrition xi | P a g e after adjusting for both individual and community level determinant factors in the multilevel analysis. It is recommended that a geographic and context specific intervention should be launched by Ethiopia government and respective local administrators supported by small area estimation researches done by academia.