Confirmatory-factor-analysis-derived metabolic syndrome risk score: development, validation, and clinical utility in dual adolescent populations.

Abstract

This study developed and validated a continuous metabolic syndrome (MetS) risk score (msRS) for adolescents and evaluated its clinical utility in identifying multiple clinical cardiovascular markers (CCMs) using dual adolescent populations. Adolescents aged 12‒18 from two stratified random samples were used: the nationwide Nutrition and Health Survey in Taiwan (NAHSIT, n = 1920) for development and the Adiposity‒Cardiovascular Disease Axis study in Southern Taiwan (adiCards, n = 3295) for validation. Four sex-and-age-specific msRS were developed through confirmatory factor analysis (CFA) utilizing five MetS components-waist circumference, high-density lipoprotein cholesterol, triglycerides, fasting glucose, and mean arterial pressure. Their discriminatory ability for clinical outcomes was validated using the area under receiver operating characteristic (AU-ROC) curve. The msRS demonstrated exceptional capability in detecting MetS in NAHSIT and adiCards cohorts (AU-ROCs: 0.954‒0.969). Adjusted for covariates, msRS explained higher variability in body-fat percentage, apolipoproteins B/A1, and homeostatic model assessment of insulin resistance (HOMA-IR) than binary MetS and abnormal components count (partial R², 23.7‒26.8% vs 4.1‒20.7%) in the validation dataset. An increase in msRS was associated with a 1.9-, 2.7-, 3.4-, and 14.4-fold risk of elevated low-density lipoprotein cholesterol, hyperuricemia, high HOMA-IR, and ≥3 CCMs. The CFA-derived sex-and-age-adjusted msRS scheme provides an improving measure to assess and manage adolescent cardiometabolic health. Adolescent MetS components share a latent metabolic construct. A scoring system through confirmatory factor analysis captures sex-and-age specific metabolic heterogeneity. Continuous risk score accurately discriminates pediatric MetS. MetS risk score effectively detects pediatric cardiovascular risk. Consideration of population characteristics is essential when developing a continuous MetS score.