Abstract 13223: Structural Equation Modeling Demonstrates only an Indirect Effect of Obesity on Carotid Intima-Media thickness in Adolescents and Young Adults
Introduction: Increased carotid intima-media thickness (cIMT) is associated with cardiovascular (CV) events in adults. Thicker cIMT is found in youth with elevated CV risk factors including obesity although biologically plausible reasons for a direct effect are not clear. We hypothesized that obesity affects cIMT only indirectly through other CV risk factors and this could be demonstrated with use of structural equation modeling (SEM).
Methods: Ultrasound of the right and left common, bulb and internal carotid arteries was performed in 784 adolescent and young adults (10-24 years old, 65% female, 41% Caucasian, 32% T2DM). Demographics, anthropometrics and fasting laboratory data were collected. Traditional multiple regression analyses (MRA) were performed to assess independent determinants of cIMT. Analyses were then repeated with SEM.
Results: MRA models explained 11%-22% of variation of common, bulb and internal cIMT. Obesity, age, sex and SBP z-score were significant determinants of all cIMT segments. Race, presence of T2DM, HbA1c and non-HDL contributed for some segments. In SEM, latent variable “cIMT” was used to represent the 3 segments of cIMT. Latent variable “BP” was extracted from SBP and DBP z-score. Latent variable “BGC” (blood glucose control) was extracted from fasting glucose and HbA1c. The final SEM explained a larger amount of the variance of cIMT (43%). The largest direct effect on cIMT was age followed by BP, blood glucose control and non-HDL. BMI, another central risk factor in the pathway towards atherosclerosis, only had a significant indirect effect through blood glucose control, BP & non-HDL. CRP had a small indirect effect through blood glucose control. We conclude that traditional CV risk factors have important direct effects on cIMT in adolescents and young adults but adiposity exerts its influence only through other CV risk factors. SEM may be a useful tool in modeling complex biological pathways.
Author Disclosures: Z. Gao: None. P.R. Khoury: None. C.E. McCoy: None. A.S. Shah: None. T.R. Kimball: Research Grant; Modest; R01 HL105591-01 (Urbina). L.M. Dolan: Research Grant; Modest; R01 HL105591-01 (Urbina). E.M. Urbina: Research Grant; Significant; R01 HL105591-01 (Urbina).
- © 2014 by American Heart Association, Inc.