Metabolic syndrome among people with HIV in central Tunisia: Prevalence and associated factors

Introduction: Metabolic abnormalities are frequently reported in HIV infection. They were mainly related to the chronic infection and the use of antiretroviral therapy. Objective: Describe the epidemiological, clinical, laboratory and treatment features of people living with HIV (PLHIV) on antiretroviral therapy and determine the prevalence of metabolic syndrome and its associated factors. Materials and methods: We conducted a cross-sectional, descriptive and analytical study in the service of Infectious Diseases of the University Hospital of Monastir. We included all PLHIV on antiretroviral therapy for at least 3 months. Biological explorations based on metabolic parameters were performed systematically for all patients after informed consent. Metabolic syndrome was assessed according to the definitions of the International Diabetes Federation (IDF) in 2005. We divided the patients into two groups: Group A: PLHIV with metabolic syndrome (n = 19) and Group B: PLHIV without metabolic syndrome (n = 51). Results: We included in this study 70 PLVIH. The metabolic syndrome was noted in 19 cases (27.1%). The average age was 43.7 years in group A and 36.7 years in group B. Gender distribution were uniform in the two groups (P = 0.4). HIV infection has been evolving for 9.7 and 5.8 years respectively in group A and B, P = 0.017. Body mass index (BMI) was significantly higher in group A (26.4 vs 23.5 kg/m2, P = 0.008). Two patients in group A (10.5%) and 14 patients in group B (27.4%) had a low CD4 count (< 200/mm3). Protease inhibitor regimens were prescribed in five cases (26.3%) in group A and 26 cases (50.9%) in group B. In multivariate models, Age over 40 (OR = 9.9, 95% CI 2.4-40.6, P = 0.001) and BMI ≥ 25 Kg/m2 (OR = 8.47, 95% CI 1.94-36.8, p = 0.004) were both independently associated with the presence of the metabolic syndrome. Conclusion: Metabolic syndrome is common among PLHIV on antiretroviral therapy. The identification of factors associated is a main parameter for early detection of metabolic risk and personalized management.