Background Tuberculosis is the oldest infectious disease and it is still the leading cause of morbidity and mortality worldwide. Even though several primary studies have been conducted on the incidence of tuberculosis among HIV-infected individuals in Ethiopia, national-level tuberculosis incidence is unknown. Therefore, this study is aimed to assess the TB incidence rate and its predictors among HIV-infected individuals after the initiation of ART in Ethiopia. Methods We conducted an extensive search of literature as indicated in the guideline of reporting systematic review and meta-analysis (PRISMA). The databases used were PubMed, Google Scholar, and HINARI literature. We used the Joanna Briggs Institute (JBI) Meta-Analysis of Statistics Assessment and Review Instrument for critical appraisal of studies. The meta-analysis and Meta regressions were conducted using STATA 14 software. Met-analysis and meta-regression were computed to present the pooled incidence rate and predictors of tuberculosis among HIV-infected patients after initiation of ART with a 95% confidence interval. Results Among a total of 189 studies, 11 studies were included in this analysis. The estimated pooled incidence rate of TB per 100-person year observation (PYO) among HIV-infected patients after initiation of ART therapy was 4.8(95% CI 3.69–5.83). In subgroup analysis, the estimated pooled incidence of tuberculosis showed a slight difference between adults and children after initiation of ART treatment, which was 4.3 (95% CI 2.96, 5.71) and 5.0 (95% CI 3.51, 6.50), respectively. Significantly pooled estimates of predictors of TB incidence by a meta-analysis were being anemic (2.30, 95% CI 1.75, 3.02); on clinical stages III and IV (2.26, 95% CI 1.70, 3.02); and not on cotrimoxazole preventive therapy (CPT) (2.16, 95% CI 1.23, 3.72). Besides, a meta-regression revealed that CD4 <200 cells/mm3 (2.12, 95% CI 1.17, 3.86) was a positive significant predictor of TB among HIV patients after the initiation of ART. Conclusions The current study showed that the pooled incidence of TB among HIV patients was found to be lower than the WHO 2018 national estimate. Being anemic, WHO stages III and IV, not on CPT, CD4<200cells/μl, and being male were significant predictors of tuberculosis. Therefore, the existing strategies to decrease TB should be strengthening. Study protocol registration CRD42020155573.

Background Undernutrition among late-adolescent girls (15–19 years) in Ethiopia is the highest among Southern and Eastern African countries. However, the spatial variation of undernutrition as a national context is not well understood in Ethiopia. This study aimed at the spatial patterns and determinants of undernutrition among late-adolescent girls in Ethiopia. Methods Secondary data analysis was conducted from women’s data of four consecutive Ethiopian Demographic and Health Surveys (EDHS) from 2000 to 2016. A total of 12,056 late-adolescent girls were included in this study. The global spatial autocorrelation was assessed using the Global Moran’s I autocorrelation to evaluate the presence of geographical clustering and variability of undernutrition. SaTScan cluster analysis by using the Bernoulli model to detect most likely SaTScan cluster areas of significant high-rate and low-rate of undernutrition was explored. A Multilevel binary logistic regression model with cluster-level random effects was fitted to determine factors associated with undernutrition among late-adolescent girls in Ethiopia. Results Undernutrition was clustered nationally during each survey (Global Moran’s I = 0.009–0.045, Z-score = 5.55–27.24, p-value < 0.001). In the final model, individual and community level factors accounted for about 31.02% of the regional variations for undernutrition. The odds of undernutrition among 18–19 years of adolescent girls, was 57% (AOR = 0.43; 95% CI: (0.35–0.53) lower than those 15–17 years old. Late-adolescent girls with higher educational status were 4.40 times (AOR = 4.40; 95% CI: (1.64–11.76) more likely to be undernourished than those with no educational status. The odds of undernutrition among late-adolescent girls, with the occupation of sales, was 40% (AOR = 0.60; 95% CI: 0.43–0.84) lower than those with not working adolescents. The odds of undernutrition, among late-adolescent girls, having an unimproved latrine type, was 1.79 times (AOR = 1.79; 95% CI: 1.15–2.79) higher than those participants with improved latrine type. The odds of undernutrition among late-adolescent girls with rural residents was 2.33 times higher (AOR = 2.33; 95% CI: 1.29–4.22) than those with urban residents. Conclusion Undernutrition among late-adolescent girls was spatially clustered in Ethiopia. The local significant clusters with high prevalence of undernutrition was observed in Northern and Eastern Ethiopia. Those regions with a high prevalence of undernutrition should design interventions to combat undernutrition.

Introduction: Under-nutrition of late adolescent girls in Ethiopia is the highest among Southern and Eastern African countries. However, the spatial and temporal variations of under-nutrition as a national context is not well understood. This study aimed the spatiotemporal patterns and determinants of under-nutrition among Late Adolescent Girls in Ethiopia.Methods: An in-depth secondary data analysis was conducted from women’s data of four consecutive Ethiopian Demographic and Health Surveys (EDHS) 2000 to 2016. A total of 12,056 late adolescent girls were included in this study. The global spatial autocorrelation was assessed using the Global Moran’s I statistic to evaluate the presence of geographical clustering and variability of undernutrition. The significant cluster scan statistics using Bernoulli model to detect local clusters of significant high rate and low rates of under-nutrition was explored. Multilevel binary logistic regression model with cluster level random effects was fitted to determine factors associated with under-nutrition among Late Adolescent girls in Ethiopia. Results: undernutrition was clustered nationally during each survey (Global Moran’s I=0.009-0.045, Z-score= 5.55-27.24, p value < 0.001). In the final model, individual and community level factors accounted about 31.67% of the variations for under-nutrition. The odds of being under-nourished girls in the age groups of 18 -19 years were 57 % (AOR = 0.43; 95 % CI: 0.35 - 0.53) less likely than those from 15-17 years old. Being in higher educational status was 4.50 times (AOR= 4.50; 95% CI: 2.33–8.69) more likely to be under-nourished compared with no educational status. Undernutrition with occupation of sales was 40% (AOR=0.60; 95% CI: 0.43 – 0.84) lower than those with not working. The odds of being undernourished adolescents were 1.77 times (AOR=1.77; 95% CI: 1.24 - 2.53) higher than participants with unimproved latrine type. Rural residents were 2. 35 times (AOR=2.35; 95% CI: 1.41 - 3.92) more likely to be under nourish compared with urban residents. Conclusion: undernutrition among late adolescent girls was spatially clustered in Ethiopia. The significant high rate of undernutrition was observed in Northern and Eastern Ethiopia. Those regions with high rates of under-nutrition should design interventions to combat under-nutrition.

IntroductionSafe and easily accessible drinking water service generates substantial benefits for public health and the economy. Approximately 10% of the global burden of disease worldwide could be prevented with improved access to drinking water. The death of ~ 30% of children younger than 5 years in developing countries is attributable to inadequate access to improved drinking water. Despite the presence of abundant water sources in Ethiopia, uneven distribution and waste pollution coupled with unprecedented population growth, rapid urbanization, and climate change are hindering the country's ability to maintain the balance between the demand and supply of accessible and improved drinking water services. The importance of up-to-date evidence for actions regarding the distribution of access to improved drinking water services is indicated by the Ethiopian Ministry of Water and Energy. Therefore, this study aimed to explore the spatial distribution and determinants of limited access to improved drinking water service among households in Ethiopia.MethodsThis study used the 2019 Ethiopian Mini Demographic and Health Survey (EMDHS). The data were weighted using sampling weight to restore the representativeness and to obtain valid statistical estimates. After excluding ineligible households, a total weighted sample of 5,760 households was included in the final analysis. The analysis was performed using STATA version 14.2, ArcGIS Pro, and SaTScan version 10.1 software. To find significant determinants with limited access to improved drinking water service, we used a multilevel logistic regression model. A P-value of &lt;0.05 was used to declare statistical significance.ResultsThis study found that in Ethiopia, 16.1% (95% CI: 15.2, 17.1) of households have limited access to improved drinking water services. The spatial distribution of households with limited access was identified to be clustered across a few regions of the country (Moran's I = 0.17, p-value &lt; 0.01). The most likely significant primary clusters with highly limited access were seen in the Somali region (RR = 4.16, LLR = 162.8), the border between Amhara and Afar region (RR = 4.74, LLR = 41.6), the border between Oromia and Afar region (RR = 5.21, LLR = 13.23), and the northeastern Tigray region (RR = 2.52, LLR = 9.87). The wealth index, the age of household head, residence, and region were significantly associated with limited access to improved drinking water service. A high rate of limited access to improved drinking water service is predicted in the southwestern part of Gambella, the northeastern part of Oromia, the southwestern part of South Nation Nationalities and Peoples' region, and part of the Oromia region that surrounds Addis Ababa.ConclusionLimited access to improved drinking water service in Ethiopia varies across regions, and inequality in the service provision exists in the country. Prioritization and extra level of efforts should be made by concerned government and non-government organizations as well as other stakeholders for those underprivileged areas and groups of the population as they are found in the study.