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

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

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

Suggested Citation

  • Claudia Porto Sabino Pinho & Alcides da Silva Diniz & Ilma Kruze Grande de Arruda & Ana Paula Dornelas Leão Leite & Marina de Moraes Vasconcelos Petribú & Isa Galvão Rodrigues, 2017. "Predictive models for estimating visceral fat: The contribution from anthropometric parameters," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-12, July.
  • Handle: RePEc:plo:pone00:0178958
    DOI: 10.1371/journal.pone.0178958
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