BACKGROUND: Overweight and related health problems are becoming increasingly recognized, especially in children and adolescents. For early screening, different anthropometrical measurements of obesity have been proposed to identify individuals at risk. We compared body mass index (BMI), BMI standard deviation score, waist circumference, waist-to-hip ratio (WHR), and waist/height ratio with respect to their power to predict the metabolic syndrome, its components and low-grade inflammation. METHODS: A total of 79 male Caucasian German adolescents (13-17 years) were studied. All anthropometrical measurements of obesity were recorded and blood samples drawn. Predictive power was estimated using receiver operating characteristic curves, by comparing the area under the curve (AUC). RESULTS: Except for WHR, all tested anthropometrical measurements of obesity showed comparably good AUC values for correct prediction, with the highest AUC for BMI (P < 0.001, AUC = 0.885 +/- 0.039). Superior prediction power was not observed for BMI standard deviation score, waist circumference, WHR or waist/height ratio. Furthermore, BMI was the best predictor of elevated C-reactive protein levels as a marker for low-grade inflammation (P < 0.001, AUC = 0.786 +/- 0.064). CONCLUSIONS: In this cross-sectional study the well-established parameter BMI was shown to have the best predictive power to identify metabolic syndrome, its components and markers for low-grade inflammation. Newly developed parameters did not provide superior values. Future longitudinal studies are needed to compare these anthropometrical markers in larger cohorts, incorporating different age groups and ethnic backgrounds.
BACKGROUND: Overweight and related health problems are becoming increasingly recognized, especially in children and adolescents. For early screening, different anthropometrical measurements of obesity have been proposed to identify individuals at risk. We compared body mass index (BMI), BMI standard deviation score, waist circumference, waist-to-hip ratio (WHR), and waist/height ratio with respect to their power to predict the metabolic syndrome, its components and low-grade inflammation. METHODS: A total of 79 male Caucasian German adolescents (13-17 years) were studied. All anthropometrical measurements of obesity were recorded and blood samples drawn. Predictive power was estimated using receiver operating characteristic curves, by comparing the area under the curve (AUC). RESULTS: Except for WHR, all tested anthropometrical measurements of obesity showed comparably good AUC values for correct prediction, with the highest AUC for BMI (P < 0.001, AUC = 0.885 +/- 0.039). Superior prediction power was not observed for BMI standard deviation score, waist circumference, WHR or waist/height ratio. Furthermore, BMI was the best predictor of elevated C-reactive protein levels as a marker for low-grade inflammation (P < 0.001, AUC = 0.786 +/- 0.064). CONCLUSIONS: In this cross-sectional study the well-established parameter BMI was shown to have the best predictive power to identify metabolic syndrome, its components and markers for low-grade inflammation. Newly developed parameters did not provide superior values. Future longitudinal studies are needed to compare these anthropometrical markers in larger cohorts, incorporating different age groups and ethnic backgrounds.
Authors: Carla Moreira; Rute Santos; Susana Vale; Paula C Santos; Sandra Abreu; Ana I Marques; Luísa Soares-Miranda; Jorge Mota Journal: J Obes Date: 2011-07-11
Authors: Michael Lichtenauer; Marcus Franz; Michael Fritzenwanger; Hans-Reiner Figulla; Norbert Gerdes; Christian Jung Journal: Biomed Res Int Date: 2015-02-02 Impact factor: 3.411