BACKGROUND/OBJECTIVES - New methods to measure visceral adipose tissue (VAT) by dual-energy X-ray absorptiometry (DXA) may help discern sex, race and phenotype differences in the role of VAT in cardiometabolic risk. This study was designed (1) to compare relationships of DXA-VAT, anthropometric and body composition variables with cardiometabolic risk factors in obese women; (2) to determine which variables most robustly predict impaired glucose tolerance (IGT) and metabolic syndrome (MetSx); and (3) to determine thresholds for DXA-VAT by race.
SUBJECTS/METHODS - VAT mass (g) and volume (cm(3)) were measured in 229 obese (body mass index (BMI), 30-49.9) women aged 21-69 years of European-American (EA=123) and African-American (AA=106) descent using the CoreScan algorithm on a Lunar iDXA scanner. Linear regression modeling and areas under the curve (AUC of ROC (receiver operating characteristic) curves) compared relationships with cardiometabolic risk. Bootstrapping with LASSO (least absolute shrinkage and selection operator) regression modeling determined thresholds and predictors of IGT and MetSx.
RESULTS - DXA-VAT explained more of the variance in triglycerides, blood pressure, glucose and homeostatic model assessment-insulin resistance (HOMA-IR) compared with anthropometric and other body composition variables. DXA-VAT also had the highest AUC for IGT (0.767) and MetSx (0.749). Including race as a variable and the interaction between VAT and race in modeling did not significantly change the results. Thresholds at which the probability of developing IGT or MetSx was⩾50% were determined separately for AA women (IGT: 2120 cm(3); MetSx: 1320 cm(3)) and EA women (IGT: 2550 cm(3); MetSx: 1713 cm(3)). The odds for IGT or MetSx were fourfold greater with each standard deviation increase in DXA-VAT.
CONCLUSIONS - DXA-VAT provides robust clinical information regarding cardiometabolic risk in AA and EA obese women and offers potential utility in the risk reduction interventions.