Abstract and Introduction
Abstract
Background Visceral adiposity index (VAI) has recently been suggested to be used as a surrogate of visceral adiposity. We examined if VAI could improve predictive performances for CVD of the Framingham's general CVD algorithm (a multivariate model incorporating established CVD risk factors). We compared the predictive abilities of the VAI with those of simple anthropometric measures i.e. BMI, waist-to-height ratio (WHtR) or waist-to-hip ratio (WHpR).
Design and methods In a nine-year population-based follow-up, 6 407 (2 778 men) participants, free of CVD at baseline, aged ≥ 30 years were eligible for the current analysis. The risk of CVD was estimated by incorporating VAI, BMI, WHpR, and WHtR, one at a time, into multivariate accelerated failure time models.
Results We documented 534 CVD events with the annual incidence rate (95%CIs) being 7.3 (6.4–8.3) among women and 13.0 (11.7–14.6) among men. Risk of future CVD increased with increasing levels of VAI among both men and women. VAI was associated with multivariate-adjusted increased risk of incident CVD among women. However, the magnitude of risk conferred by VAI was not significantly higher than those conferred by BMI, WHpR, or WHtR. Among men, after adjustment for established CVD risk factors, VAI was no longer associated with increased risk of CVD. VAI failed to add to the predictive ability of the Framingham general CVD algorithm.
Conclusions Using VAI instead of simple anthropometric measures may lead to loss of much information needed for predicting incident CVD.
Introduction
There is no consensus on the definition of obesity or on specific aspects of obesity that contribute to the risk of CVD. The precise measurement of the total amount of body fat and its regional distribution is possible by using computed tomography (CT), dual-energy X-ray absorption. Magnetic resonance imaging (MRI), like CT, can separate visceral fat from subcutaneous fat and since there is no radiation involved, it can perform a total body scan for maximal accuracy and fat distribution. However, these methods are primarily used at the research level. Besides, they are time-consuming, costly, and not routinely available. Accordingly there is a need for simple techniques that can discriminate regional fat. Amato et al. have recently individuated a novel sex-specific index based on waist circumference, body mass index (BMI), triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), and indirectly expressing visceral fat and termed it the visceral adiposity index (VAI). VAI had significant correlation with visceral adiposity and its increase was strongly associated with cardiometabolic risk. However, the prospective relation between VAI and CVD is less clear. Clinical importance of visceral adiposity lies in its association with health risks like CVD. Therefore, from clinical point-of-view, indices developed to measure visceral adiposity should be examined with respect to their ability to predict risks known to be associated with it.
Using data from a large community-based study, we examined if VAI would improve CVD prediction currently made by multivariate algorithms and if VAI could add to the predictive ability of the simple anthropometric measures of adiposity i.e. BMI, waist-to-height ratio (WHtR) or waist-to-hip ratio (WHpR).