<p>Predicting Metabolic Syndrome by Visceral Adiposity Index, Body Roundness Index and a Body Shape Index in Adults: A Cross-Sectional Study from the Iranian RaNCD Cohort Data</p>

Abstract

Background: The use of anthropometric indices is one of the new and low-cost diagnostic methods of metabolic syndrome (MetS). The present study aimed to determine optimal cutoff points for the visceral adiposity index (VAI), body roundness index (BRI), and a body shape index (ABSI) in the prediction of MetS. Methods: This cross-sectional study was performed on 10,000 individuals aged from 35 to 65 years, recruited in Ravansar Non-Communicable Diseases (RaNCD) cohort study, in the west region of Iran, in 2019. MetS was defined according to International Diabetes Federation (IDF) criteria. The receiver operating characteristic (ROC) curve analysis was used to assess predictive anthropometric indices and determine optimal cutoff values. Results: The optimal cutoff points for VAI were 4.11 (AUC: 0.82; 95% CI: 0.81-0.84) in men and 4.28 (AUC: 0.86; 95% CI: 0.85-0.87) in women to prediction of MetS. The optimal cutoff points for BRI were 4.75 (AUC: 0.75; 95% CI: 0.74-0.77) in men and 6.17 (AUC: 0.62; 95% CI: 0.61-0.64) in women to prediction of MetS. The optimal cutoff points for ABSI were 0.12 (AUC: 0.49; 95% CI: 0.47-0.51) in men and 0.13 (AUC: 0.49; 95% CI: 0.47-0.51) in women to prediction of MetS. The risk of MetS in men and women with a VAI higher than the optimal cutoff point was, respectively, 9.82 and 11.44 times higher than that in those with a VAI lower than the cutoff point. Conclusion: Although VAI might not be very cost-beneficial compared to IDF, our study showed VAI is a better predictor of MetS than BRI in adults. ABSI was not a suitable predictor for MetS.

Comparison of Various Obesity-Related Indices for Identification of Metabolic Syndrome: A Population-Based Study from Taiwan Biobank

“…In the present study, VAI and TyG index exhibited greater AUCs in identifying MetS than other traditional obesity-related parameters. The cutoff values of VAI to predict MetS were 1.74 in men and 1.83 in women in our study, compared to 4.1 and 4.2 in men and women, respectively, in an Iranian population [ 19 ], and 2.0 in middle-aged and elderly Chinese populations [ 40 ]. The difference between our study and the work by Baveicy et al [ 19 ] may be due to dietary and ethnic differences, as our results were closer to those of the reported Chinese populations [ 40 ].…”

“…A recent systematic review indicated that VAI was a practical predictor for type 2 DM in Asian populations [ 32 ]. Moreover, in a study of 10.000 Iranian individuals aged from 35 to 65 years, Baveicy et al found that VAI had a better predictive value for MetS than BRI and ABSI [ 19 ]. There are several possible reasons to explain why VAI outperforms the other obesity-related indices in predicting MetS.…”

“…In addition to traditional indices, several parameters that combine anthropometric and biochemical measurements have recently been proposed. Among these emerging indices, visceral adiposity index (VAI) is sex-specific and has been reported to be a better indicator of MetS than other traditional indices [ 19 ]. Triglyceride glucose (TyG) index, based on triglycerides and fasting glucose, is another novel parameter that has been reported to be able to reflect insulin resistance [ 20 ] and identify metabolically unhealthy individuals [ 21 ].…”

Comparison of Innovative and Traditional Cardiometabolic Indices in Estimating Atherosclerotic Cardiovascular Disease Risk in Adults

“…Not all the novel anthropometric markers, however, performed well in estimating elevated ASCVD risk. In Asian populations, ABSI failed to predict metabolic syndrome [ 49 , 50 ]. For identifying cardiovascular disease, ABSI seemed not to be a suitable predictor [ 20 ].…”

Visceral Adiposity index and atherogenic index of plasma as reliable indices to prediction of cardiovascular diseases in adults: A Cross-Sectional analysis from the Iranian RaNCD Cohort Data

“…A meta-analysis study (2019) showed that VAI can be an independent predictor to T2DM in Asian populations [21]. Several studies have examined the predictive power of VAI using ROC curve analysis, the results of these studies agree on the accuracy and reliability of VAI for predicting T2DM, hypertension, and MetS [9,11,22]. Similar to some studies, in our study, this association was also established in CVDs risk factors; our ndings showed participants with higher VAI had signi cantly more hypertension, dyslipidemia, anthropometric indices (BMI, WHR, WC, BF and BFM) and lipid pro les compared to those with low VAI.…”