The aim of the study was to evaluate the predictive ability of obesity indices derived by dual-energy x-ray absorptiometry (DXA) regarding coronary heart disease (CHD).
DXA total body scans were performed on 71 consecutive postmenopausal women who were referred for myocardial perfusion imaging (MPI). Twenty-four women with CHD diagnosed by MPI were considered as cases, whereas the remaining 47 women with normal MPI results were considered as controls. Biochemical markers, body mass index (BMI) and waist circumference (WC) were also recorded for all women and correlated to DXA adiposity indices. Receiver operating characteristic curve analysis was performed to evaluate the ability of DXA and anthropometrically obtained obesity indices on predicting CHD.
Participants with CHD were found to have increased fat mass in the trunk (P < 0.01), in the android area (P < 0.01), and in the total body (P < 0.05) in agreement with the anthropometric indices WC (P < 0.01) and BMI (P < 0.05). Strong correlation was observed between BMI and fat mass in total body (R = 0.835), trunk (R = 0.731), and android (R = 0.796) and between WC and fat mass in android (R = 0.713). DXA-derived central fat indices were found to have higher potential for identification of individuals at high risk for CHD than BMI and WC but differences were not statistically significant.
DXA central fat indices were found to have the power to identify individuals with CHD; however, the superiority of DXA indices over the commonly used anthropometric indices (BMI, WC) in identifying women with CHD did not reach statistical significance.