Metabolic Unhealthiness Increases the Likelihood of Having Metabolic Syndrome Components in Normoweight Young Adults

• Published in: International journal of environmental research and public health Vol. 16; no. 18; p. 3258
• Main Authors: Bintoro, Bagas, Fan, Yen-Chun, Chou, Chia-Chi, Chien, Kuo-Liong, Bai, Chyi-Huey
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 05.09.2019; MDPI
• Subjects: Adolescent; Adult; Age; Alcohol; Biomarkers; Body Mass Index; Cholesterol; Disease; Fasting; Female; Food; Health care; Humans; Hypertension; Insulin resistance; Laboratories; Likelihood Functions; Male; Metabolic syndrome; Metabolic Syndrome - epidemiology; Population; Studies; Substance abuse treatment; Taiwan; Young Adult; Young adults; Taiwan; metabolic syndrome; metabolic health; national survey; cohort; young adult; insulin resistance; cardiovascular disease prevention
• DOI: 10.3390/ijerph16183258
• ISSN: 1660-4601; 1661-7827

Findings on risk detection for having metabolic syndrome (MetS) components, each of which may individually increase the risk of disease and mortality, are limited in young adults. In this study, we aimed to calculate the likelihood of having ≥1 MetS component in normoweight young adults using two different metabolic health criteria. We recruited 1182 normoweight young adults from the Taiwan Survey on the Prevalence of Hypertension, Hyperglycemia, and Hyperlipidemia and the National Health Interview Survey (aged 16–45 years, 39% male, body mass index = 18.5–22.99, all without MetS) and followed them for 5 years. Metabolic health criteria were derived from the Harmonized criteria (unhealthy if showing abnormality in one or two MetS components) and the triglyceride-glucose index (TyG-i; unhealthy if TyG-i was in the >75th percentile). Odds ratio (OR) and 95% confidence interval (CI) estimations for having ≥1 MetS component and for having each MetS component in 5 years were assessed using multivariable-adjusted logistic regression. We observed a significantly increased likelihood of the presence of ≥1 MetS component in the unhealthy group by using the Harmonized criteria and TyG-i (adjusted OR (aOR); 95%CI: 2.64; 2.02-3.45 and 2.1; 1.57–2.82, respectively). The areas under the receiver-operating characteristics curves were 0.679 and 0.652 for the final models using Harmonized and TyG-i criteria, respectively. These findings support the recommendation of treating any metabolic component abnormality, even in young adults without a MetS diagnosis.