IntroductionObstructive sleep apnea is a sleep complaint among type 2 diabetes mellitus patients that has a deleterious effect on health with immediate and long-term impacts. Despite its impacts, data on the magnitude and predictors of obstructive sleep apnea among type 2 diabetes mellitus patients in Ethiopia is still limited. Thus, this study was conducted to determine how common a high risk of obstructive sleep apnea is and its predictors among type 2 diabetes mellitus patients receiving follow-up care at the chronic illness follow-up clinic at the University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia, 2022.MethodsAn institution-based cross-sectional study was conducted. Interviewer-administered questionnaires and physical measurements with standard instruments were used to collect the required data. The collected data were entered into EpiData 4.6 and exported into STATA 14. Both Bivariable and multivariable binary logistic regression analyses were done to identify factors associated with a high risk of obstructive sleep apnea. Variables with a p-value ≤0.05 in the multivariable logistic regression analysis were declared as significantly associated with a high risk of obstructive sleep apnea.ResultsA total of 319 type 2 diabetes mellitus patients with a median age of 58 years participated in our current study. The overall prevalence of a high risk of obstructive sleep apnea among the study participants was 31.97% (95%CI: 27.06, 37.32). On multivariable logistic analysis, a neck circumference of ≥40 cm (AOR=4.33, 95%CI 1.37, 13.72), physical inactivity (AOR=2.29, 95%CI 1.15, 4.53), comorbid hypertension (AOR=4.52, 95%CI 2.30, 9.18), and male sex (AOR=8.01, 95%CI 3.02, 21.24) were associated with a high risk of obstructive sleep apnea.Conclusion and recommendationThe prevalence of a high risk of obstructive sleep apnea among type 2 diabetes mellitus patients remains high. A neck circumference of ≥40 cm, physical inactivity, comorbid hypertension, and male sex were significantly associated with a high risk of obstructive sleep apnea among type 2 diabetes mellitus patients. Screening and evaluation of type 2 diabetes mellitus patients for obstructive sleep apnea are recommended to avoid the negative impacts.

BackgroundPoor glycemic control is one of the most determinant factors for type 2 diabetes-related morbidity and mortality. The proportion of type 2 diabetes mellitus patients with poor glycemic control remains high. Yet evidence on factors contributing to poor glycemic control remains scarce. The aim of this study is to identify determinants of poor glycemic control among type 2 diabetes mellitus patients at a diabetes mellitus clinic in University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia Determinants of Poor Glycemic Control among Type 2 Diabetes mellitus Patients at University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia: Unmatched Case-Control StudyMethodsA hospital-based case-control study was conducted from June to September 2020. Using convenience sampling techniques, a total of 90 cases and 90 controls with type 2 diabetes were recruited. The data were entered into Epidata version 4.6.0.2 and analyzed by Stata version 14. A multivariable logistic regression analysis was performed to assess the association between independent variables and glycemic control. Both 95% CI and p-value<0.05 were used to determine the level and significance, respectively.ResultsThe mean age ( ± standard deviations) for the cases and controls were 57.55± 10.42 and 61.03± 8.93% respectively. The determinants of poor glycemic control were age (Adjusted odd ratio (AOR)= 0.08; 95% CI= 0.02-0.33), inadequate physical exercise (AOR = 5.05; 95% CI = 1.99-11.98), presence of comorbidities (AOR = 5.50; 95% CI = 2.06-14.66), non-adherence to anti-diabetes medications (AOR= 2.76; 95% CI= 1.19-6.40), persistent proteinuria (AOR=4.95; 95% CI=1.83-13.36) and high-density lipoprotein less than 40 mg/dl (AOR=3.08; 95% CI= 1.30-7.31).ConclusionsAge less than 65 years, inadequate physical exercise, presence of comorbidities, non-adherence to anti-diabetes medications, persistent proteinuria, and high-density lipoprotein less than 40 mg/dl were the determinants of poor glycemic control. Therefore, targeted educational and behavioral modification programs on adequate exercise and medication adherence should be routinely practiced. Furthermore, early guideline-based screening and treatment of comorbidities and complications is required to effectively manage diabetes mellitus.

Background: Due to a single infectious pathogen, tuberculosis (TB) is the world's second-greatest cause of mortality. The majority of TB deaths happen during the intensive phase of treatment. The purpose of this study is to determine the incidence and predictors of in-hospital mortality in adult TB patients. Method: A 4 year retrospective follow-up study was conducted among 200 admitted adult TB patients at the university of Gondar hospital from September 1, 2017 to September 30, 202l. The Cox proportional hazards model was used to calculate the hazard ratios (HR). The Kaplan-Meier method was used to compute survival rates. Cox regression models were used to determine the predictors of mortality. Results: This study enrolled 200 adult TB patients. Among these 60 (30%) died, 140 (70%) censored with overall incidence of death rate of 165 (95 percent CI: 128, 213)/10,000 days of observation. A multivariate Cox regression analysis revealed that patients with a low WBC count at baseline (AHR=3.16, 95% CI: 1.55, 6.41) and bedridden patients (AHR=3.49, 95% CI: 1.83, 6.66) independent predictors of in-hospital mortality among adult TB patients. Conclusions: This retrospective study found that hospital mortality among adult TB patients is high in public hospitals in northwest Ethiopia. Patients with a low WBC count and who were bedridden at the time of presentation were independent predictors of in-hospital mortality.

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BackgroundVitamin A deficiency is among the leading preventable causes of childhood morbidity and mortality that might be attributable to the low uptake of vitamin A supplementation (VAS). Factors contributing to its low utilization are not researched at the national level and with the appropriate model. Therefore, this study aimed at identifying the magnitude and the individual- and community-level factors associated with vitamin A supplementation among children aged 6–35 months in Ethiopia.MethodsWe have used the Ethiopian mini demographic and health survey data, which was conducted from 21 March to 28 June 2019. A weighted sum of 2,362 mothers having children aged 6–35 was extracted. Considering the hierarchical nature of the data, we fitted the multilevel multivariable logistic regression model. Adjusted odds ratio (AOR) with a 95% confidence interval (CI) was reported and variables with a p-value of < 0.05 were declared to be significantly associated factors.ResultsIn this study, 43.4% (95% CI: 41.4–45.4%) of children have taken the VAS. Moreover, the 12–23 age of the child (AOR = 2.64; 95% CI: 1.88–3.72), 30–34 age of the mother (AOR = 3.34; 95% CI: 1.21–9.20), middle household wealth status (AOR = 1.75; 95% CI: 1.06–2.90), and four and above antenatal care (AOR = 2.90; 95% CI: 1.90–4.43) are the individual-level factors associated with VAS whereas being from Amhara (AOR = 2.20; 95% CI: 1.29–3.76) and Tigray (AOR = 2.16; 95% CI: 1.17–3.98) regions is a community-level factor significantly associated with the uptake of VAS.ConclusionOverall, a low proportion of children have taken the VAS in Ethiopia. The higher age of the child and mother, full antenatal care, and improved wealth status positively influence VAS. Moreover, a child from the Tigray or Amhara regions was more likely to get VAS. Therefore, an intervention has to be designed to address the VAS uptake among young mothers, and working to improve the wealth status of the household would be helpful. Moreover, the advocacy of antenatal care and minimizing the regional disparity through encouraging the uptake in the rest of the regions would help increase the national-level uptake of VAS.