Background Optimal antenatal care (ANC4+) needs to be used throughout pregnancy to reduce pregnancy complications and maternal mortality. The World Health Organization (WHO) recommends eight ANC contacts, while Ethiopia has the lowest coverage of at least four ANC visits. Therefore, this study aimed to identify factors associated with optimal ANC visits among pregnant women in Ethiopia. Methods This study is a secondary data analysis of the 2019 Ethiopian Mini Demographic and Health Survey (EMDHS). A multilevel logistic regression model is set up to identify factors associated with optimal ANC visits. Adjusted odds ratios (AOR) with 95% confidence intervals (CI) were calculated to estimate the strength of the association between the outcome and the predictor variables. Results Overall, 43% of women had optimal ANC visits during their last pregnancy. Higher educated women are 3.99 times more likely (AOR = 3.99; 95% CI: 2.62–6.02) to have optimal ANC visits than women with no formal education. The wealthiest women are 2.09 times more likely (AOR = 2.09; 95% CI: 1.56–2.82) to have optimal ANC visits than women in the poorest quintile. The odds of optimal ANC visit is 42 percent lower in rural women (AOR = 0.58, 95% CI: 0.41–0.83) compared to women living in urban areas. Conclusion Women's educational status, wealth status, mass media exposure, place of residence and region are factors that are significantly associated with optimal ANC visit. These findings help health care programmers and policymakers to introduce appropriate policies and programs to ensure optimal ANC coverage. Priority should be given to addressing economic and educational interventions.

Background: Optimal antenatal care (ANC4 +) needs to be used throughout pregnancy to reduce pregnancy complications and maternal mortality. The World Health Organization (WHO) recommends eight ANC contacts, while Ethiopia has the lowest coverage of at least four ANC visits. Therefore, this study aimed to identify factors associated with optimal ANC visits among pregnant women in Ethiopia. Methods: This study is a secondary data analysis of the 2019 Ethiopian Mini Demographic and Health Survey (EMDHS). A multilevel logistic regression model is set up to identify factors associated with optimal ANC visits. Adjusted odds ratios (AOR) with 95% confidence intervals (CI) were calculated to estimate the strength of the association between the outcome and the predictor variables. Results: Overall, 43% of women had optimal ANC visits during their last pregnancy. Higher educated women are 3.99 times more likely (AOR = 3.99; 95% CI: 2.62-6.02) to have optimal ANC visits than women with no formal education. The wealthiest women are 2.09 times more likely (AOR = 2.09; 95% CI: 1.56-2.82) to have optimal ANC visits than women in the poorest quintile. The odds of optimal ANC visit is 42 percent lower in rural women (AOR = 0.58, 95% CI: 0.41-0.83) compared to women living in urban areas. Conclusion: Women's educational status, wealth status, mass media exposure, place of residence and region are factors that are significantly associated with optimal ANC visit. These findings help health care programmers and policymakers to introduce appropriate policies and programs to ensure optimal ANC coverage. Priority should be given to addressing economic and educational interventions.

Introduction: Violence against women particularly that is commited by an intimate partner is becoming a social and public health problem across the world. Studies from different countries shows that the spatial variation in distribution of domestic violence was commonly attributed by neighborhood level predictors. Despite the importance of spatial techniques, studies that employ it in Ethiopia are limited. Therefore, the aim of this study is to determine the spatial distribution and predictors of domestic violence among women aged 15-49 in Ethiopia by using EDHS 2016 dataset. Methods: Secondary data from EDHS 2016 was used to determine the spatial distribution of domestic violence in Ethiopia. Spatial auto-correlation statistics (both Global and Local Moran’s I) was used to assess the spatial distribution of domestic violence cases in Ethiopia. Spatial locations of significant clusters were identified by using Kuldorff’s Sat Scan version 9.4 software. Finally, binary logistic regression and generalized linear mixed model were fitted to identify predictors of domestic violence. Result: The study found that spatial clustering of domestic violence cases in Ethiopia with Moran’s I value of 0.26, Z score of 8.26, and P-value < 0.01. The Sat Scan analysis find out 24 significant locations of domestic violence clusters. Among this, 10 are primary clusters with RR 2.18, LLR of 39.55, and P-value < 0.01. The output from regression analysis identifies low economic status, husband/partner alcohol use, witnessing family violence as a child, marital controlling behaviors, and community acceptance of wife-beating as significant predictors of domestic violence.Conclusion and Recommendation: There is spatial clustering of d domestic violence cases in Ethiopia. Areas with a high burden of the problem should get priority for intervention. Comprehensive and collaborative action should be taken by involving stakeholders at different levels. Specific activities may include Organizing media on awareness creation and continuous education on how to maintain a stable relationship between couples and employing long term and intensive effort for transforming culture and social norms that encourage violence against woman are among the major ones.

Background Violence against women particularly that is committed by an intimate partner is becoming a social and public health problem across the world. Studies show that the spatial variation in the distribution of domestic violence was commonly attributed to neighborhood-level predictors. Despite the prominent benefits of spatial techniques, research findings are limited. Therefore, the current study intends to determine the spatial distribution and predictors of domestic violence among women aged 15–49 in Ethiopia. Methods Data from the Ethiopian demographic health survey 2016 were used to determine the spatial distribution of domestic violence in Ethiopia. Spatial auto-correlation statistics (both Global and Local Moran’s I) were used to assess the spatial distribution of domestic violence cases in Ethiopia. Spatial locations of significant clusters were identified by using Kuldorff’s Sat Scan version 9.4 software. Finally, binary logistic regression and a generalized linear mixed model were fitted to identify predictors of domestic violence. Result The study found that spatial clustering of domestic violence cases in Ethiopia with Moran’s I value of 0.26, Z score of 8.26, and P value < 0.01. The Sat Scan analysis identifies the primary most likely cluster in Oromia, SNNP regions, and secondary cluster in the Amhara region. The output from regression analysis identifies low economic status, partner alcohol use, witnessing family violence, marital controlling behaviors, and community acceptance of wife-beating as significant predictors of domestic violence. Conclusion There is spatial clustering of IPV cases in Ethiopia. The output from regression analysis shows that individual, relationship, and community-level predictors were strongly associated with IPV. Based upon our findings, we give the following recommendation: The government should give prior concern for controlling factors such as high alcohol consumption, improper parenting, and community norm that encourage IPV that were responsible for IPV in the identified hot spot areas.

Background: Childhood stunting is a major challenge to the growth and development of nations by affecting millions of children across the world. Although Ethiopia has made steady progress in reducing stunting, the prevalence of stunting is still one of the highest in the world. This study aimed to assess the spatial variation and factors associated with stunting among under-five children in Ethiopia.Methods: This study is a secondary data analysis of the 2019 Ethiopian Mini Demographic and Health Survey (EMDHS). The Getis-Ord statistics tool has been used to identify areas with high and low hotspots of stunting. A multilevel logistic regression model was used to identify factors associated with stunting. Adjusted odds ratios (AOR) with its 95% confidence intervals (CI) at p-value < 0.05 were used to declare statistical significance.Results: The result of this study shows that about 37% of under-five children were stunted. Statistically significant hotspots of stunting were found in northern parts of Ethiopia. Children in the age group between 24–35 months were more likely to be stunted than children whose age was less than one year [AOR = 3.74; 95 % CI: (3.04–4.59)]. Children with mothers who had completed higher education had lower odds of being stunted compared to children whose mothers had no formal education [AOR = 0.55; 95%CI: (0.38–0.82)]. Children from the poorest wealth quintile had higher odds of being stunted compared to children from the richest wealth quintiles [AOR = 2; 95 % CI: (1.46–2.73)]. Children living in Tigray (AOR =3.64; 95 % CI: 2.17–6.11), Afar (AOR 2.02; 95 % CI 1.19-3.39), Amhara (AOR =2.29; 95 % CI: 1.37–3.86), Benishangul Gumz (AOR=1.87; 95% CI: 1.10-3.17) and Harari (AOR=1.95; 95% CI: 1.17-3.25) regions were more likely to be stunted compared to children living in Addis Ababa.Conclusion: This study showed that both individual and community-level factors were significant predictors of stunting. Improving maternal education, improving the economic status of households, improving age-specific child feeding practice, and providing additional resources to regions with high hotspots of stunting are recommended.