title: Dual-energy X-ray absorptiometry for quantification of visceral fat.
abstract: Obesity is the major risk factor for metabolic syndrome and through it diabetes as well as cardiovascular disease. Visceral fat (VF) rather than subcutaneous fat (SF) is the major predictor of adverse events. Currently, the reference standard for measuring VF is abdominal X-ray computed tomography (CT) or magnetic resonance imaging (MRI), requiring highly used clinical equipment. Dual-energy X-ray absorptiometry (DXA) can accurately measure body composition with high-precision, low X-ray exposure, and short-scanning time. The purpose of this study was to validate a new fully automated method whereby abdominal VF can be measured by DXA. Furthermore, we explored the association between DXA-derived abdominal VF and several other indices for obesity: BMI, waist circumference, waist-to-hip ratio, and DXA-derived total abdominal fat (AF), and SF. We studied 124 adult men and women, aged 18-90 years, representing a wide range of BMI values (18.5-40 kg/m(2)) measured with both DXA and CT in a fasting state within a one hour interval. The coefficient of determination (r(2)) for regression of CT on DXA values was 0.959 for females, 0.949 for males, and 0.957 combined. The 95% confidence interval for r was 0.968 to 0.985 for the combined data. The 95% confidence interval for the mean of the differences between CT and DXA VF volume was -96.0 to -16.3 cm(3). Bland-Altman bias was +67 cm(3) for females and +43 cm(3) for males. The 95% limits of agreement were -339 to +472 cm(3) for females and -379 to +465 cm(3) for males. Combined, the bias was +56 cm(3) with 95% limits of agreement of -355 to +468 cm(3). The correlations between DXA-derived VF and BMI, waist circumference, waist-to-hip ratio, and DXA-derived AF and SF ranged from poor to modest. We conclude that DXA can measure abdominal VF precisely in both men and women. This simple noninvasive method with virtually no radiation can therefore be used to measure VF in individual patients and help define diabetes and cardiovascular risk.
authors.affiliation: Cardiovascular Medicine Division, Oregon Health & Science University, Portland, Oregon, USA. kauls@ohsu.edu
authors.forename: Sanjiv
authors.initials: S
authors.lastname: Kaul
authors.forename: Megan P
authors.initials: MP
authors.lastname: Rothney
authors.forename: Dawn M
authors.initials: DM
authors.lastname: Peters
authors.forename: Wynn K
authors.initials: WK
authors.lastname: Wacker
authors.forename: Cynthia E
authors.initials: CE
authors.lastname: Davis
authors.forename: Michael D
authors.initials: MD
authors.lastname: Shapiro
authors.forename: David L
authors.initials: DL
authors.lastname: Ergun
mesh_terms: D015502:Absorptiometry, Photon / Q000379:methods*; D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001823:Body Composition; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000000981:diagnostic imaging* / Q000473:pathology; D015331:Cohort Studies; D005260:Female; D006801:Humans; D050152:Intra-Abdominal Fat / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D024821:Metabolic Syndrome / Q000000981:diagnostic imaging* / Q000473:pathology; D008875:Middle Aged; D012307:Risk Factors; D014057:Tomography, X-Ray Computed / Q000379:methods*; D055105:Waist Circumference; D055815:Young Adult