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Construct validity of a continuous metabolic syndrome score in children
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: 37...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2830968/ https://www.ncbi.nlm.nih.gov/pubmed/20181030 http://dx.doi.org/10.1186/1758-5996-2-8 |
Sumario: | 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. |
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