» Articles » PMID: 28493988

Prediction of Whole-body Fat Percentage and Visceral Adipose Tissue Mass from Five Anthropometric Variables

Overview
Journal PLoS One
Date 2017 May 12
PMID 28493988
Citations 108
Authors
Affiliations
Soon will be listed here.
Abstract

Background: The conventional measurement of obesity utilises the body mass index (BMI) criterion. Although there are benefits to this method, there is concern that not all individuals at risk of obesity-associated medical conditions are being identified. Whole-body fat percentage (%FM), and specifically visceral adipose tissue (VAT) mass, are correlated with and potentially implicated in disease trajectories, but are not fully accounted for through BMI evaluation. The aims of this study were (a) to compare five anthropometric predictors of %FM and VAT mass, and (b) to explore new cut-points for the best of these predictors to improve the characterisation of obesity.

Methods: BMI, waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and waist/height0.5 (WHT.5R) were measured and calculated for 81 adults (40 women, 41 men; mean (SD) age: 38.4 (17.5) years; 94% Caucasian). Total body dual energy X-ray absorptiometry with Corescan (GE Lunar iDXA, Encore version 15.0) was also performed to quantify %FM and VAT mass. Linear regression analysis, stratified by sex, was applied to predict both %FM and VAT mass for each anthropometric variable. Within each sex, we used information theoretic methods (Akaike Information Criterion; AIC) to compare models. For the best anthropometric predictor, we derived tentative cut-points for classifying individuals as obese (>25% FM for men or >35% FM for women, or > highest tertile for VAT mass).

Results: The best predictor of both %FM and VAT mass in men and women was WHtR. Derived cut-points for predicting whole body obesity were 0.53 in men and 0.54 in women. The cut-point for predicting visceral obesity was 0.59 in both sexes.

Conclusions: In the absence of more objective measures of central obesity and adiposity, WHtR is a suitable proxy measure in both women and men. The proposed DXA-%FM and VAT mass cut-offs require validation in larger studies, but offer potential for improvement of obesity characterisation and the identification of individuals who would most benefit from therapeutic intervention.

Citing Articles

Tinnitus and cardiovascular disease: the population-based Tromsø Study (2015-2016).

Ausland J, Engdahl B, Oftedal B, Hopstock L, Johnsen M, Krog N BMJ Public Health. 2025; 2(2):e000621.

PMID: 40018628 PMC: 11816207. DOI: 10.1136/bmjph-2023-000621.


The association between visceral fat metabolic score and stroke: mediation by declining kidney function.

Cao Y, Wen W, Zhang H, Li W, Huang G, Huang Y Diabetol Metab Syndr. 2025; 17(1):50.

PMID: 39920850 PMC: 11806899. DOI: 10.1186/s13098-025-01608-9.


Visceral adipose tissue area and proportion provide distinct reflections of cardiometabolic outcomes in weight loss; pooled analysis of MRI-assessed CENTRAL and DIRECT PLUS dietary randomized controlled trials.

Klein H, Zelicha H, Meir A, Rinott E, Tsaban G, Kaplan A BMC Med. 2025; 23(1):57.

PMID: 39901232 PMC: 11792534. DOI: 10.1186/s12916-025-03891-9.


Patterns of general and abdominal obesity and their association with hypertension control in the iranian hypertensive population: insights from a nationwide study.

Esmaeili F, Karimi K, Akbarpour S, Naderian M, Djalalinia S, Tabatabaei-Malazy O BMC Public Health. 2025; 25(1):241.

PMID: 39833748 PMC: 11748872. DOI: 10.1186/s12889-024-21264-4.


Alterations in Biomarkers Associated with Cardiovascular Health and Obesity with Short-Term Lifestyle Changes in Overweight Women: The Role of Exercise and Diet.

Sengun N, Pala R, Cinar V, Akbulut T, Larion A, Padulo J Medicina (Kaunas). 2025; 60(12.

PMID: 39768899 PMC: 11727739. DOI: 10.3390/medicina60122019.


References
1.
Karelis A, St-Pierre D, Conus F, Rabasa-Lhoret R, Poehlman E . Metabolic and body composition factors in subgroups of obesity: what do we know?. J Clin Endocrinol Metab. 2004; 89(6):2569-75. DOI: 10.1210/jc.2004-0165. View

2.
Ashwell M, Hsieh S . Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health risks of obesity and how its use could simplify the international public health message on obesity. Int J Food Sci Nutr. 2005; 56(5):303-7. DOI: 10.1080/09637480500195066. View

3.
Myint P, Kwok C, Luben R, Wareham N, Khaw K . Body fat percentage, body mass index and waist-to-hip ratio as predictors of mortality and cardiovascular disease. Heart. 2014; 100(20):1613-9. DOI: 10.1136/heartjnl-2014-305816. View

4.
Ortega F, Sui X, Lavie C, Blair S . Body Mass Index, the Most Widely Used But Also Widely Criticized Index: Would a Criterion Standard Measure of Total Body Fat Be a Better Predictor of Cardiovascular Disease Mortality?. Mayo Clin Proc. 2016; 91(4):443-55. PMC: 4821662. DOI: 10.1016/j.mayocp.2016.01.008. View

5.
Ashwell M . Plea for simplicity: use of waist-to-height ratio as a primary screening tool to assess cardiometabolic risk. Clin Obes. 2015; 2(1-2):3-5. DOI: 10.1111/j.1758-8111.2012.00037.x. View