Use of Continuous Metabolic Syndrome Score in Overweight and Obese Children
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To assess the utility of continuous metabolic syndrome score (cMetS) for predicting metabolic syndrome (MS) and determine the cut-off values in overweight and obese children.
This study was conducted among 104 children (7–14 y) attending obesity clinics of a tertiary care hospital in Mumbai, India. The cMetS was computed by standardizing the residuals of waist circumference (WC), mean arterial blood pressure (MAP), high density lipoprotein cholesterol (HDL-C), triglycerides (TG), and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) by regressing them according to age and sex and aggregating them. The optimal cut-off of cMetS for predicting MS was determined by the receiver operation characteristic (ROC) curve analysis.
The cMetS increased significantly with increase in the number of MS risk factors. It was significantly high in children with MS than those without it (boys: 1.070 + 1.834 vs. -1.478 + 2.262; girls: 2.092 + 1.963 vs. -2.253 + 2.140; combined children group: 1.572 + 1.950 vs. -1.907+ 2.374; p < 0.001). The score predicted MS with high accuracy in girls; (AUC of 0.95, 95% CI: 0.90–1.00), moderate accuracy in boys (AUC of 0.79, 95% CI: 0.65–0.92) and in the combined group (AUC of 0.87, 95% CI 0.80–0.94) respectively. The cut-off of cMetS yielding maximal sensitivity and specificity for predicting the MS was −1.009 in boys (sensitivity 93% and specificity 62%); −0.652 in girls (sensitivity 96.4% and specificity 77%) and − 0.6881 in the combined group (sensitivity 91.2% and specificity 70.2%).
cMetS predicted MS with moderate to high accuracy. It had high sensitivity and specificity in predicting MS in overweight and obese children.
KeywordsContinuous metabolic syndrome score Children Overweight Obesity Metabolic syndrome
The authors thank all children and their parents who agreed for the participation in this study. They acknowledge help of Dr. Susan Cherian, Head Pathology, BARC Hospital and Dr. A. R. Kulkarni, MO-In-charge, Medical Section, BARC Hospital.
SPS: Data collection, statistical analysis, manuscript preparation and editing the manuscript. ASA: Data collection and editing the manuscript. ASA is the guarantor for this paper.
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Conflict of Interest
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