Spatial Distribution and Modeling of Malnutrition Among Under-Five Children in Ethiopia

Abstract

Background Majority of this world is concerned by malnutrition. Ethiopia is one of the Sub Saharan Africancountries known by poverty, childhood diseases, high mortality and poor infrastructures and technology. The study aimed to examine differences within individuals and between clusters in nutritional status of under-five children and to identify socioeconomic factors using adequate nutrition of children in Ethiopia. Method: Data was obtained from Ethiopian 2019 Mini Demographic and Health Survey surveyed by Ethiopian Public Health Institute. A weighted sub- sample of 8768 under-five children was drawn from the dataset. Spatial statistics was used to analysis spatial variations of malnutrition of children in clusters of regional areas of Ethiopia. Multilevel modeling was used to look at demographic, socioeconomic factors at individuals and clusters levels. Result At national level the proportion of stunting, underweight and wasting among under-five children were 39.5 percent, 29.8 percent and 15.4 percent respectively. The Global Moran Index’s value for children malnutrition result in Ethiopia was (for stunting I = 0.204, P-value = < 0.0001, for underweight I = 0.195, P-value = < 0.0001 and for wasting I = 0.152, P-value = < 0.0001). Spatial variability of malnutrition of under-five children across the clusters of Ethiopia observed. Result of heterogeneity between clusters obtained was \({X}^{2}=147.25, {X}^{2}=211.43 and {X}^{2}=201.43\)respectively for stunting, underweight and wasting with P = < 0.0001 providing evidences of variation among regional clusters with respect to the status of nutrition of under-five children.Multilevel model result revealed that high differences of malnutritionin individual households and regional clusters in the under-five children in Ethiopia. Conclusion The model showed that there were spatial variations in malnutrition among clusters in Ethiopia. Child age in month, breast feeding, family educational level, wealth index, place of residence, media access and region were highly significantly associated with childhood malnutrition. Inclusion of explanatory variables in multilevel model has shown that a significant impact on variation in malnutrition among individual households and regional clusters. Accessible resources, promoting education,use media to expand activities regarding nutritional and health services and through health workers and health institutions in Ethiopia is significant.

Spatial distribution and determinants of stunting, wasting and underweight in children under-five in Ethiopia

“…The spatial distribution of underweight was also clustered across the region and varies within the zones in the specific region. The similar findings was reported by a study conducted in Ethiopia that has detected that the Afar and Somali regions were the hotspot areas for underweight [41]. But, the previous study has reported that Fanti Rasu zone of Afar region, Metekel zone and Assosa administrative zones of Benishangul-gumuz region were identified as cold spot area for underweight in children under-five [42].…”

Using geographically weighted regression analysis to cluster under-nutrition and its predictors among under-five children in Ethiopia: Evidence from demographic and health survey

“…But it was higher than studies conducted in Tanzania [56], in Kenya [54], in Ghana [57], and in Senegal [58]. This finding was also in line with studies conducted in different parts of Ethiopia previously [27]. This finding for wasting is lower when compared with studies conducted in Ethiopia [59], in Senegal [58], and Cameroon [55].…”

“…A study conducted previously reported that significant clustering of wasting across regions. Thus, Afar and Somali regions were identified as hot spot areas for wasting [27]. A study conducted on spatial clustering of stunting…”

“…A study conducted previously found a significant clustering of underweight across Ethiopia regions. Since Afar and Somali regions were identified as hot spot areas for underweight [27]. A study conducted in India also identified clusters of underweight, 146 districts (23% of all the districts) were observed as of high underweight [67].…”

“…Consecutively, previous studies revealed that spatial variation of under-nutrition among under-five children [24][25][26]. Similarly, studies conducted in Ethiopia have also showed the spatial variation of childhood stunting [27][28][29]. However, spatial studies on under-nutrition status of children are limited and lack modeling of spatial relationships between the identified clusters of under-nutrition and its predictors.…”