Evidence Hub

Burden of metabolic syndrome in the global adult HIV-infected population: a systematic review and meta-analysis

D. Trachunthong, M. Tipayamongkholgul, S. Chumseng, Worrayot Darasawang, K. Bundhamcharoen

BMC Public Health, 2024

35 citations

Abstract

Metabolic syndrome (MetS) elevates the risk of heart disease and stroke. In recent decades, the escalating prevalence of MetS among people living with HIV/AIDS (PLWHA) has garnered global attention. Despite MetS development being associated with both traditional and HIV-related factors, evidence from prior studies has shown variability across geographical regions. This study aimed to conduct a systematic review and meta-analysis of MetS burdens in adult PLWHA at the regional and global levels, focusing on the common effect size of HIV infection and antiretroviral therapy (ART) on MetS. This review followed the PRISMA 2020 guidelines. A comprehensive search and review of original articles related to MetS and HIV published in peer-reviewed journals between January 2000 and December 2023 were conducted. A random effects model was used to calculate the pooled prevalence/incidence of MetS and the common effect size of HIV infection and ART exposure on MetS. A total of 102 studies from five continents comprising 78,700 HIV-infected participants were included. The overall pooled prevalence of MetS was 25.3%, 25.6% for PLWHA on ART, and 18.5% for those not receiving treatment. The pooled incidence of MetS, calculated from five studies, was 9.19 per 100 person-years. The highest pooled prevalence of MetS was observed in the Americas (30.4%), followed by the Southeast Asia/Western Pacific regions (26.7%). HIV-infected individuals had 1.6 times greater odds of having MetS than…

How strong is the evidence?

Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free