Change in prevalence of metabolic syndrome and its components over twenty-four months post-HAART among human immunodeficiency virus positive patients in North-Western Nigeria

Abstract

Metabolic Syndrome (MetS) serves as an important epidemiologic tool for identifying people at risk for developing cardiovascular disease (CVD) and type 2 diabetes. Antiretroviral drugs have reduced mortality and increased longevity among patients living with HIV disease. We aimed to determine the prevalence and change in MetS among HIV-positive patients pre- and post-HAART over 2 years.

This was a prospective study conducted at the Institute of Human Virology of Nigeria (IHVN) Centers of Usmanu Danfodiyo University Teaching Hospital (UDUTH) and Specialist Hospital Sokoto (SHS) in Sokoto metropolis for two years. Eighty-six (86) HIV seropositive HAART-naïve patients were recruited at entry before commencing them on HAART and eighty-six (86) healthy controls for comparison at the baseline. The data were checked, entered into an Excel spreadsheet, and exported into Statistical Package for Social Sciences (SPSS) version 23 for analysis. Descriptive statistics were used to describe the study population with MetS, and an independent t-test was used to determine the characteristics of MetS components among the study population. A one-way ANOVA was used to determine the mean difference of components of MetS among patients with and without MetS. Chi-square methods were used to assess the association of MetS with gender. P values <0.05 were taken as statistically significant. 

Out of one hundred and seventy-two (172) subjects recruited, eighty-six cases and controls were diagnosed with MetS, 15 (17.4%) and 16 (18.6%) of cases at baseline and controls, respectively. The prevalence of MetS at six months through twenty-four months was 34 (40.5%), 31 (36.9%), 28 (33.3%), and 33 (39.3%), respectively.

The prevalence of MetS has significantly increased after commencing HAART from six months through twenty-four months. MetS is associated with TG, HDL-C, FBG, blood pressure, and anthropometric parameters.