Predictive models for estimating visceral fat: The contribution from anthropometric parameters

Claudia Porto Sabino Pinho, Alcides da Silva Diniz, Ilma Kruze Grande de Arruda, Ana Paula Dornelas Leão Leite, Marina de Moraes Vasconcelos Petribú and Isa Galvão Rodrigues

PLOS ONE, 2017, vol. 12, issue 7, 1-12

Abstract: Background: Excessive adipose visceral tissue (AVT) represents an independent risk factor for cardiometabolic alterations. The search continues for a highly valid marker for estimating visceral adiposity that is a simple and low cost tool able to screen individuals who are highly at risk of being viscerally obese. The aim of this study was to develop a predictive model for estimating AVT volume using anthropometric parameters. Objective: Excessive adipose visceral tissue (AVT) represents an independent risk factor for cardiometabolic alterations. The search continues for a highly valid marker for estimating visceral adiposity that is a simple and low cost tool able to screen individuals who are highly at risk of being viscerally obese. The aim of this study was to develop a predictive model for estimating AVT volume using anthropometric parameters. Methods: A cross-sectional study involving overweight individuals whose AVT was evaluated (using computed tomography–CT), along with the following anthropometric parameters: body mass index (BMI), abdominal circumference (AC), waist-to-hip ratio (WHpR), waist-to-height ratio (WHtR), sagittal diameter (SD), conicity index (CI), neck circumference (NC), neck-to-thigh ratio (NTR), waist-to-thigh ratio (WTR), and body adiposity index (BAI). Results: 109 individuals with an average age of 50.3±12.2 were evaluated. The predictive equation developed to estimate AVT in men was AVT = -1647.75 +2.43(AC) +594.74(WHpR) +883.40(CI) (R2 adjusted: 64.1%). For women, the model chosen was: AVT = -634.73 +1.49(Age) +8.34(SD) + 291.51(CI) + 6.92(NC) (R2 adjusted: 40.4%). The predictive ability of the equations developed in relation to AVT volume determined by CT was 66.9% and 46.2% for males and females, respectively (p

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0178958

DOI: 10.1371/journal.pone.0178958

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