Research

Construct validity of a continuous metabolic syndrome score in children

Joey C Eisenmann¹ , Kelly R Laurson² , Katrina D DuBose³ , Bryan K Smith⁴ and Joseph E Donnelly⁴

¹  Departments of Kinesiology and Pediatrics & Human Development, Michigan State University, East Lansing, USA

²  Department of Kinesiology, Illinois State University, Bloomington-Normal, USA

³  Department of Exercise and Sports Science, East Carolina University, Greenville, USA

⁴  Life Span Institute, University of Kansas, Lawrence, USA

author email corresponding author email

Diabetology & Metabolic Syndrome 2010, 2:8doi:10.1186/1758-5996-2-8

Published:	28 January 2010

Abstract

Objective

The primary purpose of this study was to examine the construct validity of a continuous metabolic syndrome score (cMetS) in children. The secondary purpose was to identify a cutpoint value(s) for an adverse cMetS based on receiver operating characteristic (ROC) curve analysis.

Methods

378 children aged 7 to 9 years were assessed for the metabolic syndrome which was determined by age-modified cutpoints. High-density-lipoprotein cholesterol, triglycerides, the homeostasis assessment model of insulin resistance, mean arterial pressure, and waist circumference were used to create a cMetS for each subject.

Results

About half of the subjects did not possess any risk factors while about 5% possessed the metabolic syndrome. There was a graded relationship between the cMetS and the number of adverse risk factors. The cMetS was lowest in the group with no adverse risk factors (-1.59 ± 1.76) and highest in those possessing the metabolic syndrome (≥3 risk factors) (7.05 ± 2.73). The cutoff level yielding the maximal sensitivity and specificity for predicting the presence of the metabolic syndrome was a cMetS of 3.72 (sensitivity = 100%, specificity = 93.9%, and the area of the curve = 0.978 (0.957-0.990, 95% confidence intervals).

Conclusion

The results demonstrate the construct validity for the cMetS in children. Since there are several drawbacks to identifying a single cut-point value for the cMetS based on this sample, we urge researchers to use the approach herein to validate and create a cMetS that is specific to their study population.