Major Maternal Related Determinants of Non-Breastfeeding among Mothers in Ethiopia: A Multilevel Analysis from DHS Ethiopia 2016.

INTRODUCTION:In Ethiopia, the burden of non-breastfeeding is still high despite substantial improvements in breastfeeding. However, the determinants of non-breastfeeding were poorly understood. Therefore, the aim of this study was to identify the maternal -related factors associated with non-breastfeeding.METHODS:An in-depth analysis of data from the Ethiopian Demographic and Health Survey 2016 (EDHS 2016) was used. A total weighted sample of 11,007 children was included in the analysis. Multilevel logistic regression models were fitted to identify factors associated with non-breastfeeding. A p-value < of 0.05 was used to identify factors significantly associated with non-breastfeeding.RESULTS:The prevalence of non-breastfeeding in Ethiopia was 5.28%. The odds of not breastfeeding were 1.5 times higher among women aged 35to 49 years (AOR = 1.5 CI: 1.034, 2.267) than among women aged 15to 24 years. The odds of not breastfeeding were higher among children whose mothers had BMIs of 18.5-24.9 (AOR = 1.6 CI: 1.097, 2.368) and 25-29.9 (AOR = 2.445 CI: 1.36, 4.394) than among women with BMIs of < 18.5. In addition, not breastfeeding was also significantly associated with ANC follow-up, where mothers who had 1-3 ANC follow-up had a 54% decreased odds (AOR = 0.651 CI: 0.46,0.921) compared to mothers who had no ANC follow-up. Demographically, mothers from Somalia region were five times (AOR = 5.485 CI: 1.654, 18.183) and mothers from SNNP region were almost four times (AOR = 3.997 CI: 1.352, 11.809) more likely to not breastfeed than mothers residing in Addis Ababa.CONCLUSIONS:Although breastfeeding practices are gradually improving in Ethiopia, the number of children not breastfed remains high. Individual-level characteristics (women's age, body mass index, and ANC follow-up) and community-level characteristics (geographic region) were statistically significant determinants of non-breastfeeding. Therefore, it is good for the federal minister of Health, planners, policy and decision- makers, and other concerned child health programmers to prioritize both individual and community factors.