Abstract
Body mass index (BMI) and waist circumference (WC) have limitations in stratifying cardio-metabolic risks. Another obesity measure, A Body Shape Index (ABSI), has been introduced but its applicability remains limited. To address this, the z-score of the log-transformed ABSI (LBSIZ) was recently developed. This study aimed to examine the ability of LBSIZ, compared to that of WC and BMI, to predict cardiovascular disease (CVD) risk. The study included 8,485 participants aged 40-69 years (mean age = 52.1) who were followed for 10 years and recruited from the Korean Genome and Epidemiology Study, a population-based cohort study. The area under the curve was 0.635 (95% confidence interval [CI]: 0.614-0.657) for LBSIZ, 0.604 (95%CI: 0.580-0.627) for WC, and 0.538 (95%CI: 0.514-0.562) for BMI. The AUC of the Framingham risk score (FRS) was 0.680 (95%CI: 0.659-0.701) in comparison. When we added LBSIZ to the model, the integrated AUC significantly improved from 0.680 to 0.692 (95%CI: 0.672-0.713; p value, 0.033), whereas there were no changes with BMI (AUC, 0.678; 95%CI: 0.656-0.699) or WC (AUC, 0.679; 95%CI: 0.658-0.701). In the multivariate Cox regression analysis, LBSIZ but not BMI or WC showed a significant hazard ratio of CVD event compared to 1st decile of each parameter. In the restricted cubic spline regression, BMI and WC showed an overall J-shaped relationship with CVD events whereas LBSIZ showed a linear relationship. LBSIZ is strongly associated with CVD risk and should predict CVD risk better than BMI and WC in the general population.