Determination of Optimal Cut-off Points for Obesity-related Measures of Metabolic Syndrome Based on Insulin Resistance

  • Chizumi Yamada
    Department of Clinical Health Science, Tokai University School of Medicine
  • Toshitake Mitsuhashi
    Department of Clinical Health Science, Tokai University School of Medicine
  • Noboru Hiratsuka
    Department of Clinical Health Science, Tokai University School of Medicine Shinjuku Center Bldg. Clinic
  • Fumiyo Inabe
    Department of Clinical Health Science, Tokai University School of Medicine
  • Nami Araida
    Department of Clinical Health Science, Tokai University School of Medicine
  • Eiko Takahashi
    Department of Clinical Health Science, Tokai University School of Medicine

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Background The aim of the present study was to determine the cut-off points for obesity-related measures based on insulin resistance, which contributes to the clustering of borderline risk factors in the early stage of metabolic syndrome (MetS).<br>Methods We determined the cut-off points of waist circumference (WC), BMI, and percentage of body fat (%fat) in 2129 men and 1879 women by receiver operating characteristics (ROC) analysis to predict homeostasis model assessment of insulin resistance (HOMA-IR) ≥2.5, and compared them with cut-offs in current use and those determined by linear regression corresponding to HOMA-IR=2.5. We then compared diagnostic efficiency in predicting insulin resistance among WC, BMI, and %fat.<br>Results ROC analysis yielded cut-off points of WC 88 cm and 82 cm, BMI 25 kg/m2 and 23 kg/m2 , and %fat 24% and 29% for men and women, respectively. The cut-off points derived from ROC had better diagnostic efficiency than those from linear regression or currently used values. WC, BMI, and %fat appeared to be equivalent in the diagnosis of obesity in early-stage MetS, as shown by comparable values for area under the curve and 95% CI.<br>Conclusion The optimal cut-off points for predicting insulin resistance were determined as WC 88 cm and 82 cm, BMI 25kg/m2 and 23 kg/m2, and %fat 24% and 29% for men and women, respectively. (Ningen Dock 2011; 25: 53-59)

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