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Objective: Globally, 8.8% of adults were estimated to have diabetes mellitus, with the low-and middle-income countries sharing the largest burden. However, the research evidence for targeted interventions is lacking in sub-Saharan Africa, particularly in Ethiopia. Therefore, this study aimed to assess the prevalence of diabetes mellitus, disaggregated by the epidemiology of diabetes mellitus morbidity and associated factors among adults in Dire Dawa town, Eastern Ethiopia. Methods: Data from a total of 872 randomly sampled adults aged 25–64 years were obtained for analysis using the World Health Organization STEPwise approach to non-communicable disease risk factors surveillance instruments. We estimated the prevalence of diabetes mellitus disaggregated by the previous diabetes mellitus diagnosis status and by the current blood sugar level control status. The bivariable and multivariable binary logistic regression model was used to identify correlates of diabetes mellitus, along with STATA version 14.2 for data management and analysis. All statistical tests were declared significant at p-value

Objectives: Diabetes mellitus is a metabolic disorder of major public health importance due to its prevalence and potential health complication. The success of long-term maintenance therapy of diabetes patients depends largely on their ability to adherence to self-care practices. Africa’s most populous country, Ethiopia, has the highest burden of diabetes mellitus. However, studies on self-care activities of diabetic patients are limited. Therefore, this study measures the level of self-care activities of diabetic patients in a follow-up clinic of public hospitals in Harar and Dire Dawa, Eastern Ethiopia. Methods: A hospital-based cross-sectional study was conducted on 320 randomly selected diabetic patients in Harar and Dire Dawa. A standard diabetic self-care activity interview tool was used to collect the data. Data were entered into Epi-data v 3.1 and STATA v 14.2 was used for analysis. Our outcome variable, self-care activities, has three ordered categories and a robust Ordinal logistic regression was used to identify predictors. All statistical tests with p-value