The prevalence of metabolic syndrome and the associated factors in a multiethnic upper-middle-income country in Asia: findings from a nationwide community-based study in 2023
Kim Sui Wan, Muhammad Fadhli Mohd Yusoff, Halizah Mat Rifin, Wah‐Kheong Chan, Kishwen Kanna Yoga Ratnam, Shubash Shander Ganapathy, Hamizatul Akmal Abd Hamid, Masni Mohamad, Nurain Mohd Noor, Feisul Idzwan Mustapha, Noor Ani Ahmad
Abstract
BACKGROUND: Metabolic syndrome (MetS) is a constellation of cardio-metabolic risk factors that predispose individuals to cardiovascular disease and type 2 diabetes. However, the current prevalence of MetS in Malaysia is unknown. Thus, we aimed to determine the prevalence of MetS and its associated factors among the adult population in Malaysia. METHODS: This was a nationwide community-based cross-sectional study in Malaysia with two-stage stratified random sampling in 2023. MetS was defined based on the Harmonised Joint Interim Statement that required ≥ 3 metabolic risk abnormalities: abdominal obesity, elevated blood glucose, blood pressure, triglycerides, and low HDL-cholesterol. Complex sample analyses, including multiple binary logistic regression, were used to achieve the study objectives. RESULTS: The overall response rate was 71.4%, with 1,035 participants. The prevalence of MetS was 35.9% (95% CI: 31.4-40.6), translating to 8.5 million people in Malaysia. The prevalence of abdominal obesity, elevated blood glucose, elevated blood pressure, elevated triglycerides, and low HDL-cholesterol were 52.8%, 21.5%, 43.4%, 33.4%, and 44.6%, respectively. Increasing age groups, Indian ethnicity (aOR: 2.24, 95% CI: 1.19-4.22), elevated aspartate aminotransferase (aOR: 3.09, 95% CI: 1.50-6.35), and elevated gamma glutamyl-transferase (aOR: 3.30, 95% CI: 1.84-5.92) were independent factors associated with MetS. CONCLUSIONS: MetS is highly prevalent in Malaysia and represents a pressing public health issue. Concerted multisectoral strategies are needed to manage this epidemic, and precise public health interventions can be targeted at the identified high-risk subpopulations for more effective and efficient outcomes.