Abstract
PURPOSE: Although body mass index (BMI) is an established risk factor for cardiovascular diseases (CVD), many studies found that obese patients with established CVD had better prognosis than their lean counterparts. The study aimed to investigate whether this inverse association between BMI and arterial stiffness can be explained by body composition analysis. PATIENTS AND METHODS: Participants, aged from 26 to 86 years, were included in the cross-sectional study from October 2016 to January 2020. The brachial-ankle PWV (baPWV) was measured to assess arterial stiffness. Body composition was measured using bioelectrical impedance analysis (BIA). Lean Mass Index (LMI) and Fat Mass Index (FMI), calculated as lean mass and fat mass divided by squared height (kg/m²) respectively, are complementary indices that quantitatively assess individual's non-fat and fat compartments. Multiple linear regression analysis was conducted to investigate the associations between BMI, LMI and arterial stiffness. Mediation analysis was performed to examine the effect of bone mineral density (BMD) on the association between LMI and baPWV. RESULTS: A total of 744 participants were included. The median age was 61.00 (55.00, 67.00) years, and 502 (67.47%) of them were men. The median BMI, FMI and LMI were 25.56 (23.35, 28.01) kg/m(2), 7.18 (5.81, 8.68) kg/m(2) and 18.45 (17.10, 19.73) kg/m(2) respectively. The median baPWV was 1514.50 (1358.00, 1689.00) cm/s. Among all the anthropometric parameters, only BMI (r=-0.150, p<0.001) and LMI (r=-0.206, p<0.001) were significantly correlated with baPWV. Although BMI was inversely associated with baPWV [β=-5.99, 95% CI (-11.10, -0.89), p=0.022], the association became insignificant after LMI [β=-25.85, 95% CI (-44.73, -6.96), p=0.007] was included in the model. Furthermore, 19.68% of the association between LMI and baPWV was mediated by BMD. CONCLUSION: Lean mass is the essential body component that determines the inverse association between BMI and arterial stiffness. Body composition analysis may provide important information for subclinical atherosclerosis beyond BMI.