• DOI:10.1038/oby.2007.109
• Corpus ID: 1633972

Which Obesity Indicators Are Better Predictors of Metabolic Risk?: Healthy Twin Study

@article{Lee2008WhichOI,
  title={Which Obesity Indicators Are Better Predictors of Metabolic Risk?: Healthy Twin Study},
  author={Kayoung Lee and Yun-Mi Song and Joohon Sung},
  journal={Obesity},
  year={2008},
  volume={16}
}

• Kayoung Lee, Yun-Mi Song, J. Sung
• Published 1 April 2008
• Medicine
• Obesity

No consensus exists as to the most sensitive and specific obesity indicator associated with metabolic risk factors. We aimed to validate anthropometry as the predictor for obesity‐related metabolic risk factors through comparison with direct body composition measures in Korean adults. A total of 995 Korean women and 577 Korean men who participated in the Healthy Twin study were the subjects. Anthropometric measurements included BMI, waist circumference (WC), waist‐to‐hip ratio (WHR), and waist‐to‐height ratio (WHTR). Direct body composition measures included the percentage of body fat (%BF) measured using dual‐energy X‐ray absorptiometry scanners and bioelectrical impedance analyzer (BIA). The following criteria were used to define abnormal metabolic risk factors: blood pressure ≥ 130/85 mm Hg, fasting glucose (≥ 100 mg/dl), insulin (≥ 25 μU/ml), homeostasis model assessment (HOMA) (≥ 2.61), high‐density lipoprotein (HDL) (<40 mg/dl for men or <50 mg/dl for women), triacylglycerol (≥ 150 mg/dl), uric acid (>7 mg/dl for men or >6 mg/dl for women), high‐sensitivity C‐reactive protein (hs‐CRP) (≥ 2.11 mg/l). In multiple regression analyses (adjusted for age, education, smoking, alcohol, exercise and past/current medical history, and treated families as a random effect), WC, WHTR, and BMI were consistently associated with all metabolic risk factors regardless of the subject's gender. Some of the areas under the receiver‐operating characteristic curves regarding abnormal metabolic risk factors were significantly higher for the three indicators of central obesity than for %BF. Our study validates the usefulness of anthropometry over direct body fat measures to predict metabolic risks.