Two-Hour Insulin Determination Improves the Ability of Abdominal Fat Measurement to Identify Risk for the Metabolic Syndrome

OBJECTIVE — Visceral obesity is shown to be a predictor of morbidity and mortality. We evaluated the association of measurements of generalized adiposity and visceral fat area (VFA), with abnormalities of metabolic syndrome (MS). RESEARCH DESIGN AND METHODS — Seventy-six women (47.9 9.2 years) with BMI of 38.7 5.4 kg/m2 underwent anthropometric measurements, laboratory procedures, bioeletrical impedance, and abdominal computed tomography (CT) scan. Diagnosis of MS was based on the presence of abdominal obesity and at least two of the following components: hypertension, dyslipidemia, and glucose intolerance and/or hyperinsulinemia. RESULTS — BMI was correlated with both components of adipose tissue—subcutaneous (r 0.66, P 0.01) and VFA (r 0.33, P 0.02)—and leptin levels (r 0.38, P 0.01). In contrast, VFA was correlated with 2-h glucose and insulin levels (r 0.32 and 0.35, P 0.05, respectively), triglyceride, HDL cholesterol, and uric acid (r 0.33, –0.34 and 0.24, P 0.05, respectively). Subjects with high VFA, matched for BMI, showed greater plasma glucose area under the curve (621 127 vs. 558 129 mg h1 dl1, P 0.05), 2-h insulin (804 599 vs. 579 347 pmol/l, P 0.05), and uric acid levels (0.33 0.07 vs. 0.26 0.06 mmol/l, P 0.05) than subjects with low VFA. In logistic regression analysis, waist circumference, VFA, and 2-h insulin were identified as independent predictors of MS. Receiver operating characteristic curve analysis pointed out the values of 104 cm for waist circumference (58.1 % specificity, 84.1 % sensitivity), 158.5 cm2 for VFA (78.1 % specificity, 52.3 % sensitivity), and 559.8 pmol/l for 2-h insulin (71.9 % specificity, 69.8 % sensitivity); the presence of at least two of the three variables resulted in a degree of concordance of 76%. CONCLUSIONS — While BMI was unable to differentiate between obese people and those at higher risk for MS, abdominal fat was shown to be associated with its metabolic abnormalities. The usefulness of abdominal fat in the identification of high-risk subjects may be improved when combined with 2-h insulin determination