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Background Underweight is one form of indicators of under-nutrition, which results from the poor nutrient intake and underlying health problems. Its impact is beyond an individual and extends to a country level. It has been known from the literature that underweight has a negative effect on income and development of a country. In the context of Ethiopia, factors predicting underweight remain unknown and there is a paucity of evidence on geographical distribution of underweight among individuals aged 15–49 years. Therefore, the aim of this study was to examine the geographic distribution of underweight and its associated factors among individuals aged 15–49 years in Ethiopia. Methods Secondary data analysis was done on a data set consisting of 28,450 individuals and obtained from the Ethiopian Demography and Health Survey (EDHS) 2016. The spatial distribution of underweight across the country was identified by ArcGIS software. Hotspots analysis was done using Getis-Ord Gi* statistic within ArcGIS. In SaTScan software, the Bernoulli model was fitted by Kulldorff’s methods to identify the purely spatial clusters of underweight. A binary logistic regression was applied to determine factors associated with being underweight. Result In Ethiopia, the spatial distribution of underweight was clustered with Global Moran’s I  =  0.79 at p-value < 0.0001. The highest underweight clusters were observed in Tigray, Gambella, eastern part of Amhara, and western and central part of Afar regions. Male individuals [AOR = 1.21; 95% CI: (1.15 1.28)], never married [AOR = 1.14; 95% CI: (1.05, 1.24)], rural residents [AOR = 1.32; 95% CI: (1.18, 1.47)], rich [AOR = 0.85; 95% CI: (0.76, 0.94)], cigarette smoking [AOR = 1.25; 95% CI: (1.07, 1.46)], drinking treated water [AOR = 0.91; 95% CI: (0.83, 0.99)] and open filed defecation [AOR = 1.17; 95% CI: (1.08, 1.26)] were found to have a significant association with being underweight. Conclusions There was a significant clustering of underweight among individuals aged 15–49 years. Gender, age, marital status, place of residence, wealth index, cigarette smoking, using untreated water and types of toilet were the significant factors of being underweight. Therefore, effective public health interventions like building safe and supportive environments for nutrition, providing socio-economic protection and nutrition-related education for poor and rural resident would be better to mitigate these situations and associated risk factors in hot spot areas. In addition, policymakers should strengthen and promote nutrition sensitive policies and activities in order to alleviate the underlying and basic causes of underweight.

Background: Despite improvement in access to modern healthcare services in East African countries, health-service delivery and health status of the population remained poor mainly due to the weak health-sector financing system. Therefore, the current study aimed to assess the health insurance coverage and its associated factors among reproductive-age group (RAG) women in East Africa. Methods: The most recent (between 2010 and 2018) Demographic and Health Surveys (DHS) data of the ten East African countries

Background Violence against women is a significant public health problem, and human rights abuse, and is associated with multiple adverse physical, mental, sexual, and reproductive health effects. The current study aimed to determine the magnitude of intimate partner violence (IPV) and its determinant factors in East African countries. Methods We utilized the most recent demographic and health survey data from 11 East African countries, which was comprised of a weighted sample of 55,501 ever-married women. A multilevel multivariable logistic regression analysis was applied. We used an adjusted odds ratio with a 95% CI and a p value ≤ 0.05 in the multilevel logistic model to declare significant factors associated with IPV. Results The overall prevalence of all forms of IPV in East African countries was 32.66% [95% CI 32.27, 33.05], with the highest IPV occurring in Uganda (14.93%) and the lowest IPV recorded in Comoros (0.87%). In the multivariable multilevel logistic regression model, women’s education, residence, sex of household head, current pregnancy, husband drinking alcohol, attitude towards wife-beating husband controlling behavior, and women’s decision-making autonomy were significantly associated with IPV. Conclusion The risk factors noted above increase the likelihood of a woman experiencing IPV. Therefore, we recommend establishing effective health and legal response services for IPV, raising awareness of the existing legislation service and improving its application, strengthening legislations on purchasing and selling of alcohol, strengthening joint (both husband and wife) decision-making power by empowering women, improving the educational level of women, and establishing measures to break the culture of societal tolerance towards IPV.

Background: The number of studies on the magnitude of anemia and its determinant factors among lactating mothers is limited in East African countries regardless of its multivariate consequences. Even though few studies were conducted on the magnitude of anemia and its determinants, most of them focused on the country level and different parts of countries. Therefore, the current study is aimed to determine the magnitude of anemia and determinant factors among lactating mothers in East African countries.Methods: From nine East African countries, a total weighted sample of 25,425 lactating mothers was included in the study. Determinate factors of anemia were identified using generalized linear mixed models (GLMM). Variables with a p &lt; 0.05 in the final GLMM model were stated to confirm significant association with anemia.Result: The magnitude of anemia in East African countries was found to be 36.5% [95% confidence interval (CI): 35.55%, 36.75%]. Besides, as for the generalized linear mixed-effect model, age, educational status, working status, country of residence, wealth index, antenatal care service, place of delivery, history of using family planning in a health facility, current pregnancy, and visited by fieldworker in the last 12 months were factors that have a significant association with anemia in lactating mothers.Conclusion: In East Africa, more than one-third of lactating mothers have anemia. The odds of anemia were significantly low among young mothers (15–34), who had primary education, were working, country of residence, and higher wealth index (middle and high). In addition, the likelihood of anemia was also low among lactating mothers who had antenatal care, used family planning, delivered at a health facility, were pregnant during the survey, and visited by fieldworkers. Therefore, promoting maternal care services (family planning, Antenatal Care (ANC), and delivery at health facilities) and a field visit by health extension workers are strongly recommended.