Abstract

Objective: Adiposity induces the clustering of cardiometabolic risk factors, and pediatric adiposity is a better indicator for adulthood cardiometabolic diseases than pediatric metabolic syndrome. However, the observed prevalence of pediatric adiposity depends on the methods and cut-points used. Therefore, we aimed to define diagnostic criteria for adiposity which enable more valid identification of prepubertal children at increased cardiometabolic risk.Methods: The participants were 470 prepubertal children (249 boys) aged 6–8 years. The measures of adiposity included body mass index—standard deviation score (BMI-SDS), waist-to-height ratio (WHtR) and body fat percentage (BF%) assessed by bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA). Criteria for adiposity were determined by increased cardiometabolic risk. Cardiometabolic risk factors which correlated with BF% assessed by DXA in the upper but not lower half of BF% (serum insulin and plasma high-density lipoprotein cholesterol, triglycerides, gamma-glutamyl transferase, high-sensitivity C-reactive protein and uric acid) were included in the cardiometabolic risk score (CMS). We computed receiver operating characteristics curves for the measures of adiposity using the ≥90th percentile of CMS as a measure of increased cardiometabolic risk, and local regression curves were graphed to demonstrate the associations of the measures of adiposity with CMS.Results: In girls, WHtR of 0.445 (area under curve 0.778, its 95% confidence interval 0.65–0.91, sensitivity and specificity 0.73) and BF% of 19.5% assessed by BIA (0.801, 0.70–0.90, 0.73) were the best overall criteria for increased cardiometabolic risk. In boys, BMI-SDS of 0.48 (0.833, 0.75–0.92, 0.76) was the best overall criterion for increased cardiometabolic risk. While local regression curves in girls showed that WHtR of 0.445 corresponds well to a point where CMS began to increase, in boys local regression curves suggest that CMS began to increase even at a lower level of BMI-SDS than 0.48. Moreover, the diagnostic ability of the measures of adiposity to exclude increased cardiometabolic risk was poorer than the ability to detect it.Conclusions: In general, the measures of adiposity have sufficient diagnostic accuracy to be utilized as the screening tool for increased cardiometabolic risk. The observed cut-points for adiposity were lower than the traditional cut-points for adiposity.

Highlights

  • The prevalence of childhood overweight and obesity has increased dramatically during the last decades [1, 2]

  • In girls waist-to-height ratio (WHtR) and BF% assessed by bioelectrical impedance analysis (BIA) had the highest point in the ROC-curve (Figure 1) with sensitivity being equal to specificity (0.73), which indicates that they were overall the best measures of adiposity to detect girls being above the 90th

  • BF% assessed by BIA was a slightly more sensitive measure of adiposity to detect boys being above the 90th percentile of the cardiometabolic risk score (CMS) than body mass index—standard deviation score (BMI-standard deviation score (SDS)) or BF% assessed by dualenergy X-ray absorptiometry (DXA) as indicated by the highest sensitivity related to LRpos >5

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Summary

Introduction

The prevalence of childhood overweight and obesity has increased dramatically during the last decades [1, 2]. The prevalence of pediatric adiposity and its usefulness in predicting cardiometabolic diseases depend on the criteria i.e., the methods and the cut-points used [11,12,13]. A recent review concluded that anthropometric indicators, such as BMI percentiles or WHtR, have high capacity to discriminate children and adolescents with and without excess body fat [15], albeit BMI based measurements do not provide specific information on body fat content but only indirectly reflect true adiposity [16,17,18]. More specific measures and criteria for adiposity are needed to identify individuals at increased risk of cardiometabolic diseases in clinical practice and at population level [5, 12, 18, 22]

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