Waist circumference, dual-energy X-ray absortiometrically measured abdominal adiposity, and computed tomographically derived intra-abdominal fat area on detecting metabolic risk factors in obese women.
OBJECTIVE
We investigated which abdominal adiposity measurements, waist circumference (WC), dual-energy X-ray absorptiometry (DXA)-measured abdominal fat, and computed tomography (CT)-derived intra-abdominal fat areas (IAF), were the most predictive in identifying metabolic risk factors.


METHODS
Ninety-five Korean women (body mass index 27.5 +/- 3.2 kg/m(2), WC 90.2 +/- 6.8 cm, age 42 +/- 10.6 y) with abdominal obesity (WC > or = 80 cm) were examined in this study. Abdominal adiposity was assessed using DXA (absolute values and percentages of trunk and android fat, trunk-to-leg fat ratio, and android-to-gynoid fat ratio) and CT (IAF and ratio of IAF to subcutaneous abdominal fat [SAF]). Metabolic indicators were blood pressure, high-density lipoprotein cholesterol, triacylglycerol, fasting glucose, insulin, and high-sensitivity C-reactive protein. Metabolic syndrome (MS) was defined as the presence of at least two of the following: triacylglycerol level > or = 150 mg/dL, high-density lipoprotein cholesterol level <50 mg/dL, blood pressure > or = 130/85 mmHg, and/or fasting glucose level > or = 100 mg/dL.


RESULTS
The correlations between adiposity measurements and metabolic indicators were stronger in premenopausal compared with postmenopausal women. Areas under the curve for MS and all abdominal adiposity measurements (WC, DXA-measured abdominal fat, and CT-derived IAF) were significant. Areas under the curve were not significantly different among measurements. The sensitivity and specificity at the threshold value of each abdominal adiposity measurement to predict MS were 38-93% and 34-96%, respectively. Women with 1 SD higher abdominal adiposity were 1.6-3.4 times more likely to have MS.


CONCLUSIONS
No single abdominal adiposity measurement, i.e., WC, DXA-measured abdominal fat, and CT-assessed IAF, was a stronger predictor of metabolic risk factors than the other.
Lee
Kayoung
K
Department of Family Medicine, Inje University Busan Paik Hospital, Busan, Korea. kayoung@fmlky@gmail.com
Lee
Sangyeoup
S
Kim
Young-Joo
YJ
Kim
Yun-Jin
YJ
D015502:Absorptiometry, Photon / Q000379:methods*; D000273:Adipose Tissue / Q000378:metabolism; D000328:Adult; D019540:Area Under Curve; D001786:Blood Glucose / Q000378:metabolism; D001823:Body Composition / Q000502:physiology; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D024821:Metabolic Syndrome / Q000097:blood / Q000175:diagnosis / Q000209:etiology*; D008875:Middle Aged; D009765:Obesity / Q000097:blood / Q000150:complications*; D017698:Postmenopause; D011237:Predictive Value of Tests; D017697:Premenopause; D012307:Risk Factors; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014280:Triglycerides / Q000097:blood; D049629:Waist-Hip Ratio / Q000379:methods*
D001786:Blood Glucose; D014280:Triglycerides