Header

UZH-Logo

Maintenance Infos

A new approach to define and diagnose cardiometabolic disorder in children


Abstract

The aim of the study was to test the performance of a new definition of metabolic syndrome (MetS), which better describes metabolic dysfunction in children. Methods. 15,794 youths aged 6–18 years participated. Mean z-score for CVD risk factors was calculated. Sensitivity analyses were performed to evaluate which parameters best described the metabolic dysfunction by analysing the score against independent variables not included in the score. Results. More youth had clustering of CVD risk factors (>6.2%) compared to the number selected by existing MetS definitions (International Diabetes Federation (IDF) < 1%). Waist circumference and BMI were interchangeable, but using insulin resistance homeostasis model assessment (HOMA) instead of fasting glucose increased the score. The continuous MetS score was increased when cardiorespiratory fitness (CRF) and leptin were included. A mean z-score of 0.40–0.85 indicated borderline and above 0.85 indicated clustering of risk factors. A noninvasive risk score based on adiposity and CRF showed sensitivity and specificity of 0.85 and an area under the curve of 0.92 against IDF definition of MetS. Conclusions. Diagnosis for MetS in youth can be improved by using continuous variables for risk factors and by including CRF and leptin.

Abstract

The aim of the study was to test the performance of a new definition of metabolic syndrome (MetS), which better describes metabolic dysfunction in children. Methods. 15,794 youths aged 6–18 years participated. Mean z-score for CVD risk factors was calculated. Sensitivity analyses were performed to evaluate which parameters best described the metabolic dysfunction by analysing the score against independent variables not included in the score. Results. More youth had clustering of CVD risk factors (>6.2%) compared to the number selected by existing MetS definitions (International Diabetes Federation (IDF) < 1%). Waist circumference and BMI were interchangeable, but using insulin resistance homeostasis model assessment (HOMA) instead of fasting glucose increased the score. The continuous MetS score was increased when cardiorespiratory fitness (CRF) and leptin were included. A mean z-score of 0.40–0.85 indicated borderline and above 0.85 indicated clustering of risk factors. A noninvasive risk score based on adiposity and CRF showed sensitivity and specificity of 0.85 and an area under the curve of 0.92 against IDF definition of MetS. Conclusions. Diagnosis for MetS in youth can be improved by using continuous variables for risk factors and by including CRF and leptin.

Statistics

Citations

Dimensions.ai Metrics
55 citations in Web of Science®
82 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

57 downloads since deposited on 26 Jan 2016
10 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Health Sciences > Endocrinology, Diabetes and Metabolism
Life Sciences > Endocrinology
Language:English
Date:2015
Deposited On:26 Jan 2016 14:38
Last Modified:08 Jul 2022 13:00
Publisher:Hindawi Publishing Corporation
ISSN:2314-6745
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1155/2015/539835
PubMed ID:25945355
  • Content: Published Version
  • Licence: Creative Commons: Attribution 3.0 Unported (CC BY 3.0)