Dexter Tadiwanashe Chiveto,1,2 Cuthbert Musarurwa,3 Herbert T Mapira,3 Farayi Kaseke,4 Tawanda Nyengerai,5 Timothy Kaseke,6 Elizabeth Gori7 1Department of Laboratory Diagnostic and Investigative Sciences - Chemical Pathology Unit, Faculty of Medicine and Health Sciences, University of Zimbabwe, Harare, Zimbabwe; 2Department of Immunology, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa; 3Department of Biomedical Laboratory Sciences, School of Health Sciences, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda; 4Department of Physiotherapy, School of Health Sciences, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda; 5The Best Health Solutions, Johannesburg, Gauteng, South Africa; 6Zimbabwe Aids Prevention Project, ZAPP, Harare, Zimbabwe; 7Department of Medical Biochemistry, Molecular Biology and Genetics, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, Huye, RwandaCorrespondence: Elizabeth Gori, Department of Medical Biochemistry, Molecular Biology & Genetics, College of Medicine and Health Sciences-School of Medicine and Pharmacy, University of Rwanda, P.O. Box 117-Butare, Huye, Rwanda, Tel +250 7920 47482, Email e.gori@ur.ac.rwPurpose: Type 2 diabetes mellitus (T2DM) frequently presents with modified cardiometabolic risk profiles, indicative of an elevated susceptibility to cardiovascular disease (CVD). Cardiometabolic risk factors such as obesity, hyperglycemia, hypertension, insulin resistance and dyslipidemia are known contributors to increased CVD hazard in individuals with T2DM. This study evaluated the glycemic control-based cardiometabolic risk profiles of black Zimbabweans with T2DM.Patients and Methods: A cross-sectional study of 116 T2DM patients recruited from diabetic clinics at Parirenyatwa and Sally Mugabe Hospitals, Harare, Zimbabwe, was conducted. Blood samples were collected for glycated hemoglobin (HbA1c) and lipid profile assessment. The Framingham risk scores (FRS) based on body mass index (BMI) and lipid profile were used to determine CVD risk. Parametric variables were analyzed using one-way analysis of variance (ANOVA) with post hoc Bonferroni correction, while non-parametric variables were compared using the Kruskal–Wallis test with post hoc Dunn test for multiple comparisons.Results: The overall frequency of dyslipidemia was 83.6% (n=97) and hypoalphalipoproteinemia was the most prevalent dyslipidemia (79.3%). Median HDLC levels were significantly lower in participants with poor glycemic control (1.12 mmol/L) compared to those with good glycemic control group (1.37 mmol/L) (p=0.011). Despite lack of significant variations in Framingham Risk Scores, there was a trend towards lower FRS-BMI in the good control group (29.8%) compared to the inadequate control (35.4%) and poor control (32.7%) groups (p=0.078).Conclusion: Duration since DM diagnosis was observed to be an important risk factor for poor glycemic control being significantly shorter in those with good glycemic control compared to those with inadequate and poor control. Overall, there was no significant difference in HbA1c status by age but individuals with poor glycemic control were significantly older than those with good control. The most prevalent dyslipidemia among the study participants was hypoalphalipoproteinemia which is reportedly associated with genetic predisposition, warranting further investigations.Keywords: glycated hemoglobin, dyslipidemia, hypoalphalipoproteinemia, Framingham risk score