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Background: Childhood anaemia is a major public health issue necessitating rapid attention due to its debilitating consequences on the child, family, and society. Previous studies have assessed the prevalence and contributing factors to childhood anaemia in many developing countries. Yet, little is known about the factors that contribute to childhood anaemia in Ethiopia. The study examined the factors associated with inequalities of childhood anaemia in Ethiopia. Methods: Data for the study were extracted from the 2016 Demographic and Health Survey of Ethiopia. A total of 7960 children were considered in the final study. Bivariate and multilevel ordinal logistic regression analyses were used to estimate determinants of inequalities of childhood anaemia status. Results: Overall, the prevalence of mild, moderate, and severe anaemia among the children were 24.5%, 28.4%, and 2.2%, respectively. The child's age (in months), sex of the child, preceding birth interval (in months), mother's educational level, antenatal care visit, wealth index of mothers, source of drinking water, type of toilet facility, place of residence, and region were significantly associated with childhood anaemia. The multilevel random coefficient model found that there is a variation of childhood anaemia among women (intra-cluster correlation [ICC] = 15.06%), households (ICC = 15.6%), and communities (ICC = 14.22%) in Ethiopia. Conclusions: This study showed that anaemia is common among Ethiopian children. Factors found to be associated with childhood anaemia were the sociodemographic characteristics of the child and their mothers. We recommend that existing programs and interventions to prevent and reduce childhood anaemia be strengthened. Moreover, a targeted intervention includes deworming, intensified year-round behavior change communication campaigns and testing using digital methods, and point-of-care treatment.

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Individual, Maternal, Household, and Community Level Variability in Determining Inequalities in Childhood Anaemia within Ethiopia: Four-Level Multilevel Analysis Approach