Body adiposity indicators and cardiometabolic risk: Cross-sectional analysis in participants from the PREDIMED-Plus trial. Issue 4 (August 2019) - Konieczna, Jadwiga; Abete, Itziar; Galmés, Aina M.; Babio, Nancy; Colom, Antoni; Zulet, Maria Angeles; Estruch, Ramón; Vidal, Josep; Toledo, Estefanía; Díaz-López, Andrés; Fiol, Miguel; Casas, Rosa; et al.
Summary: Background & aims: Excess adiposity is associated with poor cardiometabolic (CM) health. To date, several techniques and indicators have been developed to determine adiposity. We aimed to compare the ability of traditional anthropometric, as well as standard and novel DXA-derived parameters related to overall and regional adiposity, to evaluate CM risk. Methods: Using the cross-sectional design in the context of the PREDIMED-Plus trial, 1207 Caucasian senior men and women with overweight/obesity and metabolic syndrome (MetS) were assessed. At baseline, anthropometry- and DXA-measured parameters of central, visceral, peripheral and central-to-peripheral adiposity together with comprehensive set of CM risk factors were obtained. Partial correlations and areas under the ROC curve (AUC) were estimated to compare each adiposity measure with CM risk parameters, separately for men and women, and in the overall sample. Results: DXA-derived indicators, other than percentage of total body fat, showed stronger correlations (rho −0.172 to 0.206, p  < 0.001) with CM risk than anthropometric indicators, after controlling for age, diabetes and medication use. In both sexes, DXA-derived visceral adipose tissue measures (VAT, VAT/Total fat, visceral-to-subcutaneous fat) together with lipodystrophy indicators (Trunk/Legs fat and Android/Gynoid fat) were strongly and positively correlated ( p  < 0.001) with glycated hemoglobin (HbA1c), the triglyceride and glucose index (TyG), triglycerides (TG), the ratio TG/HDL-cholesterol (TG/HDL-C), and were inversely related to HDL-C levels ( p  < 0.001). Furthermore, in AUC analyses for both sexes, VAT/Total fat showed the highest predictive ability for abnormal HbA1c levels (AUC = 0.629), VAT for TyG (AUC = 0.626), both lipodystrophy indicators for TG (AUCs = 0.556), and Trunk/Legs fat for HDL-C (AUC = 0.556) and TG/HDL-C (AUC = 0.581). Conclusions: DXA regional adiposity measures offer advantages beyond traditional anthropometric and DXA overall adiposity indicators for CM risk assessment in senior overweight/obese subjects with MetS. In particular, in both sexes, visceral adiposity better stratifies individuals at risk for glucose abnormalities, and indicators of lipodystrophy better predict markers of dyslipidemia.