International Journal of Endocrinology and Metabolism
Research Institute for Endocrine Sciences
Authors
5,*The choice of what parameters are needed for the diagnosis of Metabolic syndrome (MetS) has been criticized due to the lack of an actual gold standard diagnostic test even in adults. This problem seems to be greater in children and adolescents.
Stability assessment of factor structure underlying metabolic syndrome (MetS) components from childhood to adolescence in a panel study.
A total number of 643 (305 boys and 338 girls) children (from 1999 to 2001), aged 6-10 years, with a complete median follow-up of 6.7 years (from 2006 to 2008) were selected among participants of Tehran Lipid and Glucose Study. We proposed 6 measured variables based on risk factors defined in Adult Treatment Panel III guidelines to describe clustering of MetS components.
The Goodness of fit of the two-factor model, extracted from exploratory factor analysis, was appropriate for boys and girls in both stages of the study using confirmatory factor analysis. Systolic blood pressure (SBP) and triglycerides (TGs), with parameter estimates (PE) of 1 and 0.75, respectively, were the greatest risk factors at baseline in boys and girls. Waist circumference with PE of 0.88 and 0.62, and SBP with PE of 0.99 and 0.86 in adolescent boys and girls, respectively, were important risk factors.
Our panel study supports the stability of the two-factor six-variable model across two developmental stages from childhood to adolescence, among which adiposity, SBP, and TG were the predominant risk factors.
© 2012, Author(s). This open-access article is available under the Creative Commons Attribution 4.0 (CC BY 4.0) International License (https://creativecommons.org/licenses/by/4.0/), which allows for unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.
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Kawada T. Insulin-Related Biomarkers to Predict the Risk of Metabolic Syndrome. Int J Endocrinol Metab. 2013;11(4):e10418. doi: https://doi.org/10.5812/ijem.10418
Bostan Gayret O, Erol M, Buke O, Ozel A, Tenekecigil A, et al. Systemic Inflammation Response Index and Immune-Inflammation Index as Predictors of Metabolic Syndrome in Obese Children and Adolescents: A Prospective Cross-Sectional Study. Inn J Pediatr. 2025;35(2):e148712. doi: https://doi.org/10.5812/ijp-148712
Hosseini-Esfahani F, Bahadoran Z, Moslehi N, Asghari G, Yuzbashian E, et al. Metabolic Syndrome: Findings from 20 Years of the Tehran Lipid and Glucose Study. Int J Endocrinol Metab. 2018;16(4 (Suppl)):e84771. doi: https://doi.org/10.5812/ijem.84771
Mahdavi-Roshan M, Shoaibinobarian N, Noormohammadi M, Fakhr Mousavi A, Savar Rakhsh A, et al. Inflammatory Markers and Atherogenic Coefficient: Early Markers of Metabolic Syndrome. Int J Endocrinol Metab. 2022;20(4):e127445. doi: https://doi.org/10.5812/ijem-127445
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