ArticlePloS one2017
Validation of surrogate markers for metabolic syndrome and cardiometabolic risk factor clustering in children and adolescents: A nationwide population-based study.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 46 citations in OpenAlex.
- Anthropometric trajectories of Korean children and adolescents with severe obesity.Clinical and experimental pediatrics · 2026Article
- Exploring the Association Between DTC Obesity-Related Gene Polymorphisms and Obesity Risk Factors in Koreans: Focus onNutrients · 2026Article
- Assessing Metabolic Syndrome Risk in Children and Adolescents with Prader-Willi Syndrome: A Comparison of Index Performance.Journal of clinical medicine · 2025Article
- Value of waist-to-hip ratio as a predictor of metabolic syndrome in adolescents with obesity.Acta bio-medica : Atenei Parmensis · 2023Article
- Exploratory Longitudinal Analysis of the Circulating CHIT1 Activity in Pediatric Patients with Obesity.Children (Basel, Switzerland) · 2023Article
- Reference Values for Waist Circumference and Waist-Height Ratio in Korean Children and Adolescents.Journal of obesity & metabolic syndrome · 2022Article
- Commentary on "Single point insulin sensitivity estimator for predicting type 2 diabetes mellitus in obese adolescents".Annals of pediatric endocrinology & metabolism · 2022Article
- Endocrine comorbidities of pediatric obesity.Clinical and experimental pediatrics · 2021Article
- Performance of waist-to-height ratio as a screening tool for identifying cardiometabolic risk in children: a meta-analysis.Diabetology & metabolic syndrome · 2021Article
- CARDIOMETABOLIC RISK AMONG MONTENEGRIN URBAN CHILDREN IN RELATION TO OBESITY AND GENDER.Acta clinica Croatica · 2021Article
- Metabolic risk associated with liver enzymes, uric acid, and hemoglobin in adolescents.Pediatric research · 2020Article
- Association of sugar-sweetened beverage intake with risk of metabolic syndrome among children and adolescents in urban China.Public health nutrition · 2020Article
- Article
- Presenting Health Status in Children Using a Radar Plot.Sports (Basel, Switzerland) · 2020Article
- Secular Trends in Pediatric Overweight and Obesity in Korea.Journal of obesity & metabolic syndrome · 2020Review
- Article
- Alternative waist-to-height ratios associated with risk biomarkers in youth with diabetes: comparative models in the SEARCH for Diabetes in Youth Study.International journal of obesity (2005) · 2019Article
- Association between hemoglobin glycation index and cardiometabolic risk factors in Korean pediatric nondiabetic population.Annals of pediatric endocrinology & metabolism · 2018Article
- Hypertriglyceridemia in Obese Children and Adolescents.Journal of obesity & metabolic syndrome · 2018Review
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prevalence of metabolic syndrome (MetS) in children is increasing and identifying the risk factors for MetS during childhood is an important first step to prevent chronic diseases later in life. The aim of the present study was to evaluate the prevalence of MetS and cardiometabolic risk factor (CMRF) clustering among Korean children and adolescents and to validate the associated anthropometric and laboratory surrogate markers. We used data from the 2011-2014 Korean National Health and Nutrition Examination Survey. In total, data for 2,935 subjects (1539 boys, 52.6%) aged 10-19 years were assessed. MetS was defined by central obesity plus any two or more of CMRFs such as abdominal obesity, hypertension, hyperglycemia, hypertriglyceridemia, and decreased high density lipoprotein cholesterol (HDL-C) using the International Diabetes Federation criteria for children and adolescents. The presence of two or more CMRFs was classified as CMRF clustering. The prevalence of MetS and CMRF clustering in this group was found to be 1.8% and 8.9%, respectively. The receiver operating characteristic analysis of MetS and CMRF clustering, and the area under the curve (95% confidence interval) of surrogate markers revealed that the waist circumference to height ratio [0.960 (95% CI 0.959-0.960), cut-off 0.491] showed the highest predictability for MetS whereas triglyceride to HDL-C ratio [0.891 (95% CI 0.891-0.892), cut-off 2.63] showed the highest predictability for CMRF clustering. Long-term follow-up is needed for further validation.
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