Objectives: The current study aimed to determine the magnitude of home delivery and its associated factors in East Africa using data from the Demographic and Health Survey. Methods: We pooled data from the Demographic and Health Survey of the 11 East African countries and included a total weighted sample of 126,107 women in the study. The generalized linear mixed model was fitted to identify factors associated with home delivery. Variables with adjusted odds ratio with a 95% confidence interval, and p value < 0.05 in the final generalized linear mixed model were reported to declare significantly associated factors with home delivery. Result: The weighted prevalence of home delivery was 23.68% (95% confidence interval: [23.45, 23.92]) among women in East African countries. Home delivery was highest in Ethiopia (72.5%) whereas, it was lowest in Mozambique (2.8%). In generalized linear mixed model, respondent’s age group, marital status, educational status, place of residence, living country, wealth index, media exposure, and number of children ever born were shown significant association with the home delivery in the East African countries, Conclusion: Home delivery varied between countries in the East African zone. Home delivery was significantly increased among women aged 20–34 years, higher number of ever born children, rural residence, never married, or formerly married participants. On the contrary, home delivery decreased with higher educational level, media exposure, and higher wealth index. Wide-range interventions to reduce home delivery should focus on addressing inequities associated with maternal education, family wealth, increased access to the media, and narrowing the gap between rural and urban areas, poor and rich families, and married and unmarried mothers.

Background. Although the rate of diabetic nephropathy which is the leading cause of end-stage renal disease (ESRD) continues to rise, there is limited information about the problem. This study aimed to assess the incidence and predictors of diabetic nephropathy among type 2 DM patients. Methods. Institution-based retrospective follow-up study was conducted at UGCSH with 462 newly diagnosed type 2 DM patients from January 2001 to February 2016, and the data were collected by reviewing their records. The Schoenfeld residuals test was used to check proportional hazard assumption. The best model was selected by using Akaike information criteria (AIC). Hazard ratios (HR) with its respective 95 confidence interval were reported to show significance and strength of association. Results. The incidence rate of diabetic nephropathy was 14 (95 CI 10.817.7) cases per 10,000 patient-month observation. In addition, 63 (13.6) DM patients developed diabetic nephropathy. The median time to develop diabetic nephropathy was 94.9 months with interquartile range (IOR) of (64.1127.4) months. Type 2 DM patients who had coronary heart disease (AHR=2.69, 95 CI 1.425.13) and anemia (AHR=1.94, 95 CI 0.973.87) were at higher hazard for developing diabetic nephropathy. Besides this, having a long duration (>10 years) (AHR=0.24, 95 CI 0.110.56) and being female (AHR=0.44, 95 CI 0.260.73) was found to be protective against diabetic nephropathy. Conclusion. The incidence of diabetic nephropathy among type 2 diabetes patients remains a significant public health problem. Duration of diabetes >10 years and female sex reduced the risk of diabetic nephropathy. Coronary heart disease and anemia increased the risk of diabetic nephropathy among type 2 DM patients. In light of these findings, early screening for diabetes complication is needed, and health professionals should give targeted intervention for type 2 DM patients with coronary heart disease comorbidity and anemia.

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 (Burundi, Comoros, Ethiopia, Kenya, Malawi, Mozambique, Tanzania, Uganda, Zambia, and Zimbabwe) were included. STATA version 16.0 statistical software was used for data processing and analysis. In the multilevel mixed-effects generalized linear model, variables with a p-value ≤ 0.05 were declared as significant associated factors of health insurance coverage. Results: The overall health insurance coverage in East Africa was 7.56% (95% CI: 7.42%, 7.77%). The odds of health insurance coverage were high among educated, currently working, and rich RAG women whereas it was low among rural residents. Besides, RAG women who have media exposure, visited by field workers, and visited health facilities have a higher chance of health insurance coverage. Conclusion: Health insurance coverage in East Africa among RAG women was below ten percent. Educational status, working status, place of residence, wealth index, media exposure, visiting health facility within 12 months and being visited by field worker were significantly associated with health insurance coverage among RAG women in East Africa. Improving women’s access to health facilities, promoting field workers’ visit, and media exposure targeting uneducated, unemployed, and rural resident women of RAG will be a gateway to promote health insurance coverage.

Background: Various primary studies have been conducted in sub-Saharan countries on the level of health related quality of life (HRQoL) and their associated factors among diabetic patients. However, the result of these studies lacks consistency. Therefore, this systematic review and meta-analysis estimates the pooled level of HRQoL and their associated factors among diabetic patients in sub-Saharan countries. Methods: Electronic databases predominantly PubMed were searched. Databases, such as Google and Google scholar, were searched for gray literature. A funnel plot and Egger’s regression test were used to see publication bias. Heterogeneity of the studies was checked by Forest plot and I-squared statistic. Both inverse-variance fixed-effect and DerSimonian and Laird random-effects methods were applied to estimate the pooled level of HRQoL (for both WHO-QoL-BREF and SF-36) and the effect size of associated factors. Result: From a total 776 retrieved studies, 16 studies were included for systematic review and meta-analysis. The pooled mean score of physical health, psychological, social relation and environmental health domain of WHO-QoL-BREF were 43.12, 47.40, 46.60 and 45.59 respectively. Age had a significant association (pooled β = − 0.47), (pooled β = − 0.24), (pooled β = − 0.32) and (pooled β = − 0.03) with physical health, psychological health, social relation and environmental health domains respectively. Being rural residence (pooled β = − 0.32) was inversely associated with environmental health domain of WHO-QoL-BREF. Increased fasting blood sugar had a significant association (pooled β = − 0.08, 95% CI − 0.11, − 0.05), (pooled β = − 0.07) and (pooled β = − 0.004) with physical health, psychological health and environmental health domains respectively. Having Co-morbidity (pooled β = − 6.25) and diabetes related complication (pooled β = − 5.65) were contrarily related to physical health domain of WHO-QoL-BREF. Conclusion: The pooled mean of physical and environmental domains of HRQOL scores was the least compared to the psychological and social domains. Being Old age and rural residence, increased fasting blood sugar, having co-morbidity and diabetic related complications were contrarily related to level of HRQoL. Therefore, we recommend that early detection and treatment of diabetes related complication and comorbidity and control of fasting blood sugar. While doing that due attention should be given for old and rural dwellers.

Objectives: We aimed to estimate the pooled prevalence of erectile dysfunction (ED) among patients with diabetes mellitus (DM) in Ethiopia and to identify its associated factors. Methods: We performed a systematic search of scientific databases (PubMed, ScienceDirect); the grey literature was also searched (Google, Google Scholar). Data were extracted from primary studies using a data extraction format and exported for statistical analysis. I² tests were used to assess the heterogeneity of studies. Owing to heterogeneity among the included studies, we used a random-effects model to determine pooled estimates of ED. Publication bias was assessed using Egger’s and Begg’s tests. Results: The pooled prevalence of ED among patients with DM in Ethiopia was 54.3% (95% confidence interval [CI]: 28.2–80.5). Older age (OR: 4.42, 95% CI: 2.83–6.00) and duration of DM (OR: 3.2, 95% CI: 1.74–4.66) had statistically significant associations with ED. Conclusion: One in two individuals with DM in Ethiopia also had ED. This finding highlights the need to integrate assessment and management of ED into routine medical care in diabetes follow-up visits. Special attention is recommended for patients with older age and a longer duration of DM.

Background. Low- and middle-income countries of which Ethiopia is one bears the high burden of depression among human immune deficiency virus and acquired immune deficiency syndrome (HIV/AIDS) patients. Several factors have been identified as being associated with increased depression among HIV/AIDS patients including poor social support. However, studies examining the effect of poor social support on depression among HIV/AIDS patients in Ethiopia have had inconsistent findings. This systematic review and meta-analysis is therefore aimed at estimating the pooled effect of poor social support on depression among HIV/AIDS patients in Ethiopia. Methods. All relevant articles published prior to July 1, 2020, were retrieved from scientific databases: PubMed, Scopus, and Google Scholar systematically. The identified studies reporting the association of depression and poor social support among HIV patients in Ethiopia were included. tests were used to assess the heterogeneity of the studies. Subgroup analysis was done based on tools to determine how pooled estimates of depression vary across tools. The pooled estimate of association between poor social support and depression was reported. Results. The aggregated meta-analysis revealed a higher odds of depression among patients with poor social support than those who had strong social support (OR: 2.31, 95% CI: 1.69, 2.93). The pooled prevalence of depression among HIV/AIDS patients in Ethiopia was 38.93% (95%: CI: 32.01, 45.84); (%, ). The subgroup analysis was performed based on tools, and the result showed that the highest pooled prevalence (44.42%) was among primary studies that used the Hospital Anxiety and Depression Scale (HADS) tool. Conclusions. Human immune deficiency virus and acquired immune deficiency syndrome (HIV/AIDS) patients with poor social support were more likely to develop depression. The pooled prevalence of depression among HIV/AIDS patient was high in Ethiopia. The highest prevalence of depression was observed among studies that used HADS to screen depression. Therefore, we recommend integration of mental health and psychosocial support services into the HIV/AIDS care. Prevention of HIV/AIDS-related stigma for people with HIV/AIDS is also needed to reduce the impact of poor social support.