Stunting remains a major public health concern in Ethiopia. Government needs to reshape and redesign new interventions to reduce stunting among under-five children. Hence, this study identified the problem according to location and risk factor. This study is a secondary data analysis of the 2016 Ethiopian Demographic and Health Survey. A total of 9588 children aged 0–59 months were included in the study. The spatial and multilevel logistic regression analyses were used to explore spatial heterogeneity and identify individual- and household-level factors associated with stunting and severe stunting. Spatial heterogeneity of stunting and severe stunting was seen across the study setting. Male children (AOR = 1.51, CI 1.16, 1.96); multiple births (AOR = 27.6, CI 10.73, 71.18); older children (AOR = 1.04, CI 1.01, 1.05) and anemic children (AOR = 3.21, CI 2.3, 4.49) were severely stunted at individual-level factors. Children from educated and malnourished mothers (respectively, AOR = 0.18, CI 0.05, 0.71; AOR = 5.35, CI 3.45, 8.32), and from less wealthier mothers (AOR = 5.95, CI 2.58, 13.69) were severely stunted at household-level factors. Giving priority to the hotspot areas of stunting and older and anemic children, multiple births, and maternal undernutrition is important to reduce stunting. Studies are recommended to fill the gaps of this study.

Background HIV is a major public health issue, especially in developing countries. It is important to track and design successful intervention programs to explore the spatial pattern, distribution, and associated factors of HIV Seropositivity. This study therefore showed the spatial variation of HIV Seropositivity and related factors in Ethiopia. Methods A total sample of 25,774 individual data collected from the 2016 EDHS data were primarily HIV biomarkers, IR, MR, and GPS. Spatial heterogeneity analysis was used with methods such as Morans I, Interpolation, and Kulldorff ‘s scan statistic. Spatial analysis was conducted using open source tools (QGIS, GeoDa, SaTScan). Multilevel logistic regression analysis was performed using Stata14 to identify HIV-associated factors. Finally, the AOR with a 95% confidence interval was used to report the mixed-effect logistic regression result in the full model. Result The prevalence of HIV / AIDS at national level was 0.93%. The highest prevalence regions were Gambela, Addis Abeba, Harari and Diredawa, accounting for 4.79, 3.36, 2.65 and 2.6%, respectively. Higher HIV seropositive spatial clusters have been established in the Gambela and Addis Ababa regions. Multilevel analysis at the individual level being married [AOR = 2.19 95% CI: (1.11–4.31)] and previously married [AOR = 6.45, 95% CI: (3.06–13.59)], female [AOR = 1.8, 95% CI: (1.19–2.72)], first-sex at age ≤15 [AOR = 4.39, 95% CI: (1.70–11.34)], 18—19 [AOR = 2.67 95% CI: (1.05–6.8)], middle age group (25-34) [AOR = 6.53, 95% CI: (3.67–11.75)], older age group (>34) [AOR = 2.67 95% CI: (1.05–6.8)], primary school [AOR = 3.03, 95% CI: (1.92–4.79)], secondary school [AOR = 3.37, 95% CI: (1.92–5.92) were significantly associated with serropositivity. Regarding household level, place of residence [urban: AOR = 6.13 CI: (3.12, 12.06)], female-headed households (AOR = 2.24 95% CI: (1.57–3.73), media exposure [low exposure (AOR = 0.53 95% CI: (0.33–0.86), no exposure AOR = 0.39 95% CI: (0.23–0.65)] and increased household size [AOR = 0.72 95% CI: (0.65–0.8)] were associated with HIV Seropositivity. Conclusion High cluster HIV cases were found in Gambela, Addis Abeba, Harari, and Diredawa. Having a history of married, start sex at a younger age, female-headed household, urban residence, and lower household size is more affected by HIV/AIDS. So any concerned body work around this risk group and area can be effective in the reduction of transmission.

Anaemia in women of reproductive age (WRA) can be effectively addressed if supported by a better understanding of the spatial variations, magnitude, severity and distribution of anaemia. This study aimed to map the subnational spatial distribution of anaemia (any, moderate and severe forms) among WRA in Ethiopia. We identified and mapped (any, moderate and severe) anaemia hotspots in WRA (n = 14,923) at the subnational level and identified risk factors using multilevel logistic regression. Kulldorff scan statistics were used to identify hotspot regions. Ordinary kringing was used to predict the anaemia prevalence in unmeasured areas. The overall anaemia prevalence increased from 16.6% in 2011 to 23.6% in 2016, a rise that was mostly related to the widening of existing hotspot areas. The primary clusters of (any) anaemia were in Somali and Afar regions. The horn of the Somali region represented a cluster of 330 km where 10% of WRA were severely anaemic. The Oromia–Somali border represented a significant cluster covering 247 km, with 9% severe anaemia. Population‐dense areas with low anaemia prevalence had high absolute number of cases. Women education, taking iron‐folic‐acid tablets during pregnancy and birth‐delivery in health facilities reduced the risk of any anaemia (P < 0.05). The local‐level mapping of anaemia helped identify clusters that require attention but also highlighted the urgent need to study the aetiology of anaemia to improve the effectiveness and safety of interventions. Both relative and absolute anaemia estimates are critical to determine where additional attention is needed.

Zero vegetable or fruit and egg and/or flesh foods are the latest indicators for assessing infant and young child feeding practices. Understanding national and subnational heterogeneity and regional clustering in children with SSA is becoming increasingly essential for geographic targeting and policy prioritization. Geographical case identification, determinants, and impacts were all investigated. SSA children's consumption of vegetable or fruit, egg and/or flesh food, and both were low. In SSA, some portions of the Southern, South direction of the Western and Central regions have a lower weight of all bad conditions than others, although children continue to suffer in considerable numbers in all disadvantage circumstances. Children under the age of 1 year, from rural areas, uneducated families, and low income were all disadvantaged by both feeding techniques. To improve child nutrition status, multisectoral collaboration is essential. This framework allows for the tracking, planning, and implementation of nutritional treatments.

Ensuring diet quality in the first 2 years of life is critical to preventing malnutrition and instilling healthy food preferences. Children's diet quality has changed little over time and inequalities by socioeconomic status, rural–urban residence, but also by food group may exist. Using data from the 2011, 2016 and 2019 demographic and health surveys (DHS), we estimated the prevalence and inequalities in the minimum diet diversity (MDD), minimum meal frequency (MMF) and minimum acceptable diet (MAD). We further assessed food group‐level inequities. In 2019, only 13.5% of children 6–23 months of age met the MDD, 55% met the MMF and only 11% met the MAD indicator. Absolute and relative measures of inequality were calculated. Modest increases in MDD, MMF and MAD were observed over the past decade (2011–2019). These modest improvements were concentrated in limited geographical areas, among children in wealthier households, and urban residents. Unhealthy practices such as bottle‐feeding and zero fruit and vegetables have been increasing; whereas, inequities in the consumption of nutrient‐dense foods have widened. Nevertheless, children from the wealthiest quintile also failed to meet the MDD. Multisectoral efforts that span from diversifying the food supply, regulating the marketing of unhealthy foods, and promoting minimal processing of perishables (i.e., to extend shelf‐life) are needed. Context‐adapted behavioural change communication along with nutrition‐sensitive social protection schemes are also needed to equitably improve the diet quality of children in Ethiopia.