» Articles » PMID: 22346358

Metabolic Syndrome in a Sample of the 6- to 16-year-old Overweight or Obese Pediatric Population: a Comparison of Two Definitions

Overview
Publisher Dove Medical Press
Date 2012 Feb 21
PMID 22346358
Citations 8
Authors
Affiliations
Soon will be listed here.
Abstract

Purpose: The purpose of this study was to estimate the presence of metabolic syndrome (MS) in a group of children and adolescents with a body mass index (BMI) above the 85th percentile for their age and sex in Qazvin Province, Iran; to evaluate the relationship between obesity and metabolic abnormalities; and to compare two proposed definitions of MS.

Patients And Methods: The study was conducted on 100 healthy subjects aged between 6 and 16 years (average age, 10.52 ± 2.51 years) with a high BMI for their age and sex. Fifty- eight percent of subjects were female. Physical examination including evaluation of weight, height, BMI, and blood pressure measurement was performed ("overweight" was defined as a BMI between the 85th and 95th percentiles for children of the same age and sex; "obese" was defined as a BMI over the 95th percentile for children of the same age and sex). Blood levels of glucose, insulin, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, and uric acid were measured after a 12-hour overnight fast. The authors used and compared two definitions of MS: the National Cholesterol Education Program's Adult Treatment Panel III (NCEP ATP III) criteria and a modified definition by Weiss et al. Variables were compared using the Student's t-test and chi-square and Mann-Whitney U tests, and agreement between the two definitions was analyzed using kappa values.

Results: The subjects had a mean BMI of 26.02 ± 4.38 and 80% had obesity. Insulin resistance was found in 81% of the study population. MS was present in ten (50%) of the overweight and 53 (66.2%) of the obese subjects using the NCEP ATP III criteria. MS was present in five (25%) of the overweight and 34 (42.5%) of the obese subjects using the definition by Weiss et al. The overall kappa value for the two definitions of MS was 0.533. There were no statistically significant differences between the two definitions of MS in participants.

Conclusion: The prevalence of MS in children and adolescents depends on the criteria chosen and their respective cutoff points. The NCEP ATP III criteria, the parameters of which include higher cutoff values for high-density lipoprotein cholesterol and triglycerides, detected the higher prevalence and therefore the NCEP ATP III criteria are able to diagnose a larger number of children and adolescents at metabolic risk.

Citing Articles

The impacts of dietary sphingomyelin supplementation on metabolic parameters of healthy adults: a systematic review and meta-analysis of randomized controlled trials.

Li C, Wu L, Zhu C, Du H, Chen G, Yang F Front Nutr. 2024; 11:1363077.

PMID: 38463938 PMC: 10922005. DOI: 10.3389/fnut.2024.1363077.


Prevalence of Metabolic Syndrome and its Associated Risk Factors in Pediatric Obesity.

Wan Mahmud Sabri W, Mohamed R, Yaacob N, Hussain S J ASEAN Fed Endocr Soc. 2022; 37(1):24-30.

PMID: 35800595 PMC: 9242664. DOI: 10.15605/jafes.037.01.05.


Metabolic syndrome among children and adolescents in low and middle income countries: a systematic review and meta-analysis.

Bitew Z, Alemu A, Ayele E, Tenaw Z, Alebel A, Worku T Diabetol Metab Syndr. 2020; 12:93.

PMID: 33117455 PMC: 7590497. DOI: 10.1186/s13098-020-00601-8.


Association of Total and High Molecular Weight Adiponectin with Components of Metabolic Syndrome in Mexican Children.

Magana Gomez J, Moreno-Mascareno D, Angulo Rojo C, de la Pena G J Clin Res Pediatr Endocrinol. 2019; 12(2):180-188.

PMID: 31552725 PMC: 7291397. DOI: 10.4274/jcrpe.galenos.2019.2019.0113.


Waist Circumference and Abdominal Volume Index Can Predict Metabolic Syndrome in Adolescents, but only When the Criteria of the International Diabetes Federation are Employed for the Diagnosis.

Perona J, Schmidt-RioValle J, Fernandez-Aparicio A, Correa-Rodriguez M, Ramirez-Velez R, Gonzalez-Jimenez E Nutrients. 2019; 11(6).

PMID: 31216719 PMC: 6627132. DOI: 10.3390/nu11061370.


References
1.
Porkka K, Viikari J, Ronnemaa T, Marniemi J, Akerblom H . Age and gender specific serum lipid and apolipoprotein fractiles of Finnish children and young adults. The Cardiovascular Risk in Young Finns Study. Acta Paediatr. 1994; 83(8):838-48. DOI: 10.1111/j.1651-2227.1994.tb13155.x. View

2.
Weiss R, Taksali S, Tamborlane W, Burgert T, Savoye M, Caprio S . Predictors of changes in glucose tolerance status in obese youth. Diabetes Care. 2005; 28(4):902-9. DOI: 10.2337/diacare.28.4.902. View

3.
Ogden C, Flegal K, Carroll M, Johnson C . Prevalence and trends in overweight among US children and adolescents, 1999-2000. JAMA. 2002; 288(14):1728-32. DOI: 10.1001/jama.288.14.1728. View

4.
Brotons Cuixart C, Gabriel Sanchez R, Muniz Garcia J, Ribera Sole A, Malaga Guerrero S, Saenz Aranzubia P . [Pattern of the distribution of total cholesterol and cHDL cholesterol Spanish children and adolescents: RICARDIN Study]. Med Clin (Barc). 2001; 115(17):644-9. DOI: 10.1016/s0025-7753(00)71650-2. View

5.
. Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser. 1995; 854:1-452. View