Objective. There is a dearth of relevant research on the rapidly evolving epidemic of diabetes mellitus (particularly Type 2 diabetes mellitus) in sub-Saharan Africa. To address some of these issues in the Eritrean context, we conducted a cross-sectional study on glycemic and lipid profiles and associated risk factors. Methods. A total of 309 patients with diabetes mellitus on regular follow-up at the Diabetic and Hypertensive Department at Halibet Regional Referral Hospital, Asmara, were enrolled for the study. Data on specific clinical chemistry and anthropomorphic parameters was collected. Chi-squared (χ2) test or Fischer’s exact test was used to evaluate the relationship between specific variables. Multivariate logistic regression (backward: conditional) was undertaken to identify the factors associated with increased odds of suboptimal values in glucose and specific lipid panel subfractions. Results. High proportions of patients (76.7%) had suboptimal levels of HbA1c with a mean±SD of 8.6%±1.36, respectively. In multivariate regression analysis, the likelihood of HbA1c≥7% was higher in patients with abnormal WHR (AOR=3.01, 95% CI, 3.01 (1.15–7.92=0.024)) and in patients without hypertension (AOR=1.97, 95% CI (1.06–3.56), p=0.021). A unit reduction in eGFR was also associated with HbA1c≥7% (AOR=0.99, 95% CI (0.98–1=0.031)). In a separate analysis, the data shows that 80.9% of the patients had dyslipidemia. In particular, 62.1% of the patients had TC≥200 mg/dL (risk factors: sex, hypertension, and HbA1c concentration), 81.6% had LDL‐C≥100 mg/dL (risk factors: sex and hypertension), 56.3% had TG≥150 (risk factors: sex, HbA1c, and waist circumference), 62.8% had abnormal HDL-C (risk factors: waist circumference), 78.3% had non‐HDL<130 mg/dL (risk factors: duration of disease, reduced estimated glomerular filtration rate, and HbA1c), and 45.3% had abnormal TG/HDL (risk factors: sex, age of patient, FPG, and waist circumference). Conclusions. The quality of care, as measured by glycemic and specific lipid targets, in this setting is suboptimal. Therefore, there is an urgent need for simultaneous improvements in both indicators. This will require evidence-based optimization of pharmacological and lifestyle interventions. Therefore, additional studies, preferably longitudinal studies with long follow-up, are required on multiple aspects of DM.

Background: Type 2 Diabetes Mellitus (T2DM) is an escalating problem worldwide and is frequently associated with Metabolic Syndrome (MetSyn) which, in turn, is causally associated with heightened cardiometabolic risk. Therefore, investigating the magnitude of MetSyn in T2DM patients is critical for cardiovascular disease prevention or management of specific comorbidities. Methods: This cross-sectional study was conducted among 309 previously diagnosed T2DM patients. Data on specific clinical chemistry and anthropomorphic parameters was collected. MetSyn was defined according to the IDF harmonized criteria. Pearson Chi-Square test (ꭓ2)/or Fisher’s exact test in the CROSSTAB procedure was used to evaluate the relationship between specific variables. Logistic regression models were constructed to assess risk factors associated with MetSyn. Results: According to the data, 58.1% of the patients had MetSyn. The frequency of MetSyn in females was significantly higher compared to that of males (67.8 vs 49.7%). Among individuals with MetSyn, 54.4% had hypertension; 57.9% had abnormal waist circumference; 75.4% had elevated LDL-C (≥100 mg/dL), 72.8% had raised TG (>150 mg/dl) and 61.0% had reduced HDL-C (males: ≤40 mg/dL and females: ≤50 mg/dL in females). Separately, our study demonstrates that number of MetSyn components is associated with higher averages in multiple traditional (BMI, TG, TC, WHtR, WHR, WC, HC) and non-traditional (TG/HDL-C, TC/HDL-C and LDL/HDL) CVD risk indicators. In the fitted multivariable logistic regression model, the following factors were associated with the presence of MetSyn: age (aOR=1.02, 95%CI=1.00–1.05, p=0.040); LDL-C>100 mg/dL (aOR=3.56, 95%CI=1.52–8.54, p=0.003); Non-HDL-C (aOR=1.02, 95%CI=1.02–1.03, p=0.001); BMI (aOR=1.23, 95%CI = 1.13–1.32, p=0.001). Absence of insulin injection was associated with reduced presence of MetSyn (aOR=0.37,95% CI=0.19–0.70, p=0.002). Conclusion: A comparatively high prevalence of the MetSyn was found. Therefore, there is an urgent need for improvements in the management and prevention of multiple CVD risk indicators. This will require evidence-based optimization of pharmacological and non-pharmacological interventions.