Determination of Cutoff Values for DEXA-Based Body Composition Measurements for Determining Metabolic and Cardiovascular Health

The two components of the body weight (i.e., fat mass and muscle mass) appeared to be of high interest to consider in predicting metabolic health related risks. We aimed to determine cutoff values for fat mass index (FMI) and muscle mass index (MMI), FM/MM, and BMI for metabolic and cardiovascular health. This study was a cross-sectional analysis study conducted in a center of preventive medicine. It included 616 consecutive outpatients: mean age was 56.0±10.0 years (74.6% aged ≥50), and 61.4% were female. Fat and muscle mass were obtained with dual energy X-ray absorptiometry scan analyses. Metabolically unhealthy individuals were defined as people with biological features of dyslipidemia, hyperuricemia, diabetes, and/or hepatitis steatosis. Documented hypertension and/or atherosclerosis of at least one major artery defined individuals with cardiovascular complications. Receiver-operating characteristic curve analysis revealed that the cutoff values for MMI, FMI, and FM/MM were respectively 18.8kg/m(2) (sensitivity [Se]=58%; specificity [Sp]=59%), 5.5kg/m(2) (Se=61%; Sp=62%), and 0.31 (Se=62%; Sp=62%) in men; and 14.1kg/m(2) (Se=52%; Sp=54%), 5.5kg/m(2) (Se=65%; Sp=67%), 0.39 (Se=73%; Sp=73%) in women for predicting metabolic health. Values were 19.3kg/m(2) (Se=58%; Sp=59%), 7.0kg/m(2) (Se=61%; Sp=62%) and 0.49 (Se=62%; Sp=62%) in men; and 15.7kg/m(2) (Se=58%; Sp=59%), 6.4kg/m(2) (Se=61%; Sp=62%) and 0.35 (Se=62%; Sp=62%) in women for cardiovascular complications. Whatever the outcomes considered, the Youden indexes for BMI values were systematically below 25 kg/m(2), except for cardiovascular complications in men, where the threshold for the best Se/Sp was 25.7 kg/m(2). These cutoff values for FMI, MMI, and FM/MM could be of practical value for the clinical evaluation of a deficit in MM with or without excess of FM. They complement the classical concept of BMI in a more qualitative manner and extend the analysis of its impact on health outcomes to all BMI categories.