Identification of metabolic syndrome using phenotypes consisting of triglyceride levels with anthropometric indices in Korean adults

BACKGROUND: The metabolic syndrome (MetS) has shown strong associations with the hypertriglyceridemic waist (HW) phenotype. The best anthropometric indicator of MetS remains controversial. Furthermore, no studies have investigated alternative indices that could replace waist circumference in the HW phenotype. The objectives of this study were to find the best indicator of MetS among anthropometric indices and to examine the predictive power of phenotypes consisting of triglyceride levels with anthropometric indices. METHODS: A total of 12,025 subjects participated in this retrospective cross-sectional study. All subjects were recruited between November 2016 and August 2007 from hospitals in 28 urban and rural regions in South Korea. The data analyzed in this study were obtained from the Korean Health and Genome Epidemiology Study database and the Korea Institute of Oriental Medicine. RESULTS: The proportion of patients with MetS ranged from 9 to 57% according to age and gender groups. Waist circumference (WC) was best indicator of MetS in men of all age groups. However, in women aged 40–49 years, the waist-to-height ratio (WHtR) was the best indicator of MetS. Rib circumference and chest circumference were the strongest indicators in women aged 50–59 years and 70–79 years, respectively. The combination of WC and triglyceride (TG) was the best indicator of MetS in men and women overall. However, interestingly, the best indicator was TG + WHtR in women aged 40–49 years and TG + forehead-to-waist ratio in women aged 70–79 years. CONCLUSIONS: The best indicator of MetS in terms of individual anthropometric indices and the various phenotypes combining a single anthropometric index with TG may differ subtly according to age group in women, but not in men. Our findings provide insight into a simple and inexpensive method that could be used to identify MetS in initial health screening efforts in epidemiology and public health.