OBJECTIVE: This study was designed to assess whether waist circumference can predict metabolic syndrome abnormalities in primary schoolchildren. RESEARCH DESIGN AND METHODS: Of 5,103 children (2,526 males) 4-13 years old who underwent anthropometric measurements, 530 had more extensive testing. Body mass index (BMI), waist circumference, and blood pressure were determined in all subjects. The subgroup had Tanner stage, glucose, lipid profile, and insulin assays. The BMI of the 5,103 children was used to calculate our z scores. To determine which marker was a better predictor for metabolic syndrome, a receiver operating characteristic (ROC) curve was generated for BMI and waist circumference, with metabolic syndrome as the dichotomous variable. RESULTS: Over 530 children (8.7 +/- 2.4 years) 6% (n = 32) were obese (BMI >95(th) percentile; z BMI = 2.55), 13.6% (n = 72) were overweight (OW) (85(th) < BMI < 95(th) percentile; z BMI = 1.45), and 80.4% (n = 426) were non-OW (BMI <85(th) percentile; z BMI = - 0.14). Fifty-eight percent [95% confidence interval (CI) 53, 6], 22.8% (95% CI 19, 27), 15.5% (95% CI 12, 19), and 4.1% (95% CI 2, 6) were Tanner stage I, II, III, and IV, respectively. Metabolic syndrome was present in 9.4% overall, 6% of the non-OW, 22.2% of the OW, and 31% in the obese group (P < 0.01). The differences between ROC areas were not significant (0.009) (95% CI -0.035 to 0.053; P = 0.679) for BMI and waist circumference. The optimal threshold for waist circumference percentile was 71.3 with a sensitivity and specificity of 58.9 (95% CI 48.4, 68.9) and 63.1 (95% CI 58.4, 67.7), respectively. CONCLUSIONS: Waist circumference and BMI predict metabolic syndrome abnormalities in children. Waist circumference > or =75(th) percentile could be the optimal threshold to predict metabolic syndrome in children.
OBJECTIVE: This study was designed to assess whether waist circumference can predict metabolic syndrome abnormalities in primary schoolchildren. RESEARCH DESIGN AND METHODS: Of 5,103 children (2,526 males) 4-13 years old who underwent anthropometric measurements, 530 had more extensive testing. Body mass index (BMI), waist circumference, and blood pressure were determined in all subjects. The subgroup had Tanner stage, glucose, lipid profile, and insulin assays. The BMI of the 5,103 children was used to calculate our z scores. To determine which marker was a better predictor for metabolic syndrome, a receiver operating characteristic (ROC) curve was generated for BMI and waist circumference, with metabolic syndrome as the dichotomous variable. RESULTS: Over 530 children (8.7 +/- 2.4 years) 6% (n = 32) were obese (BMI >95(th) percentile; z BMI = 2.55), 13.6% (n = 72) were overweight (OW) (85(th) < BMI < 95(th) percentile; z BMI = 1.45), and 80.4% (n = 426) were non-OW (BMI <85(th) percentile; z BMI = - 0.14). Fifty-eight percent [95% confidence interval (CI) 53, 6], 22.8% (95% CI 19, 27), 15.5% (95% CI 12, 19), and 4.1% (95% CI 2, 6) were Tanner stage I, II, III, and IV, respectively. Metabolic syndrome was present in 9.4% overall, 6% of the non-OW, 22.2% of the OW, and 31% in the obese group (P < 0.01). The differences between ROC areas were not significant (0.009) (95% CI -0.035 to 0.053; P = 0.679) for BMI and waist circumference. The optimal threshold for waist circumference percentile was 71.3 with a sensitivity and specificity of 58.9 (95% CI 48.4, 68.9) and 63.1 (95% CI 58.4, 67.7), respectively. CONCLUSIONS: Waist circumference and BMI predict metabolic syndrome abnormalities in children. Waist circumference > or =75(th) percentile could be the optimal threshold to predict metabolic syndrome in children.
Authors: Vanesa España-Romero; Jonathan A Mitchell; Marsha Dowda; Jennifer R O'Neill; Russell R Pate Journal: Pediatr Exerc Sci Date: 2013-02 Impact factor: 2.333
Authors: Hannah M Badland; Grant M Schofield; Karen Witten; Philip J Schluter; Suzanne Mavoa; Robin A Kearns; Erica A Hinckson; Melody Oliver; Hector Kaiwai; Victoria G Jensen; Christina Ergler; Leslie McGrath; Julia McPhee Journal: BMC Public Health Date: 2009-07-10 Impact factor: 3.295
Authors: Ashley B Yamanaka; James D Davis; Lynne R Wilkens; Eric L Hurwitz; Marie K Fialkowski; Jonathan Deenik; Rachael T Leon Guerrero; Rachel Novotny Journal: Prev Chronic Dis Date: 2021-06-24 Impact factor: 4.354