Identifying the best body‐weight‐status index associated with metabolic risk in youth

Abstract

This study investigated the association of six different anthropometric markers with metabolic syndrome to find the most suited to predict children at risk. Sample comprises 1324 Portuguese youth (701 girls, 623 boys), aged 10-17 years. Six anthropometric markers were included: body mass index (BMI), BMI z-score, tri-ponderal index (TPI), waist circumference (WC), WC/height ratio (WC/H), and WC/H adjusted ratio (WC/H ). A standardized metabolic risk score (zMR) was computed by summing of standardized values for fasting glucose, triglycerides, high-density lipoprotein cholesterol, and mean arterial blood pressure. The associations between zMR and anthropometric markers were assessed using univariate and multivariate analyses. Receiver operating characteristic (ROC) curve analysis was used to identify the optimal values that best predict metabolic risk of each anthropometric marker. Among the studied predictors, BMI z-score, followed by BMI and WC, was most highly associated with zMR, while WC/H was the weakest predictor. ROC analyses showed significant AUCs for all markers, yet the discrimination was poor (AUCs from 0.60 to 0.68), with sensitivity ranging from 45.5% to 67.5% and specificity from 72.6% to 81.9%. The optimal cut-off values to predict metabolic risk were 1.62, 23.1 kg/m , 71.0 cm, 18.0 kg/m , 0.47, and 0.50, for BMI z-score, BMI, WC, TPI, WC/H, and WC/H , respectively. BMI z-score, followed by BMI and WC, were the most relevant anthropometric markers to predict metabolic risk in youth, while WC/H was the worst predictor. Results suggest that anthropometric markers should continue to be used as clinical tools to identify youth at risk.

The Relationship Between Tri-ponderal Mass Index and Metabolic Syndrome and Its Components in Youth Aged 10–20 Years

“…With regard to the relationship between BMI and cardiometabolic risk factors, a series of studies were conducted in the past few decades. BMI and BMI SDS have also been demonstrated to be significantly relevant anthropometric markers to predict metabolic risk in youth 21–23 . However, few studies have been conducted regarding the association of TMI with cardiometabolic risk factors 10 .…”

Can waist circumference provide a new “third” dimension to BMI when predicting percentage body fat in children? Insights using allometric modelling

“…Within the sample, there were a small number of 16 and 17‐year‐old children. These were combined into the 15‐year‐old group, ie, 15+; for analysis, see Gomes et al Sample 3 consisted of 1745 children (859 boys) aged 7 to 17 years old, recruited as part of the Active Vouzela project in the midlands of Portugal (see Chaves et al). Sample 4 consisted of 2365 children (1197 boys) aged 8 to 17 years old, recruited as part of the Portuguese sibling study on growth, fitness, lifestyle, and health (see Pereira et al).…”

Simple universal cutoff point of waist-height ratio for metabolic risk in Korean children and adolescents

“…Studies from many countries validated that a universal WHtR≥0.5 is a better predictor of metabolic disorder risk in adolescents, independent of sex or age [8]. Another study suggested showed that compared with BMI z score and WC, the WHtR was the worst at predicting metabolic risk in adolescents [9]. Kim et al [3] reported a WHtR cutoff point of 0.48 for abdominal obesity with metabolic disorder in 13- to 18-year-old Korean adolescents based on the Korea National Health and Nutrition Examination Survey (2005–2015) data.…”