Utility of the Z-score of log-transformed A Body Shape Index (LBSIZ) in the assessment for sarcopenic obesity and cardiovascular disease risk in the United States.

Abstract

Body mass index (BMI) has limited accuracy for predicting cardiovascular diseases (CVD) and is not capable of identifying sarcopenic obesity, the combination of sarcopenia (an age-associated decline in muscle mass and physical function) and obesity. To overcome this, the z-score of the log-transformed A Body Shape Index (LBSIZ) was recently introduced as a measure of obesity using waist circumference, height, and weight. We aimed to investigate the association of LBSIZ with sarcopenic obesity and CVD, and propose appropriate cut-off values using the National Health and Nutrition Examination Survey 1999-2016 data. Of 92,062 participants, 40,468 adults (>= 20 years) were included. Overall area under curve (AUC) of LBSIZ was 0.735 (95% confidence interval [CI]: 0.716-0.754) for sarcopenic obesity, and 0.695 (95% CI: 0.687-0.703) for CVD. The subgroup analysis of ethnicity/race showed similar results. Waist circumference (WC), BMI, conicity index, body roundness index (BRI), Clinica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), new BMI, and waist to height ratio (WHtR) showed a negative association with sarcopenic obesity, while LBSIZ and conicity index showed a positive association. The AUC of LBSIZ was significantly higher for sarcopenic obesity than that of conicity index (p < 0.001). The AUC of LBSIZ was significantly higher for CVD than those of parameters including WC, BMI, BRI, CUN-BAE, new BMI, and WHtR (p < 0.001). The AUC for conicity index alone was comparable to that of LBSIZ for CVD. Overall LBSIZ cut-off was 0.35 for both sarcopenic obesity (sensitivity, 65.3%; specificity, 71.5%) and CVD (sensitivity, 63.3%; specificity, 66.6%). These results may be useful not only to identify sarcopenic obesity, but also to conduct CVD risk assessment in the clinical setting.