The aim of the study was to generate equations predicting visceral (VAT) and subcutaneous (SAT) abdominal adipose tissue (AT) from simple anthropometric measurements. Magnetic resonance imaging (MRI) was used to measure VAT and SAT cross-sectional areas at the level of L4 in 49 subjects (19 men and 30 women) with a large range of age and body mass index (BMI). BMI, waist and hip circumferences, waist to hip ratio (WHR), subscapular and paraumbilical skinfolds (ie, "simple" anthropometric measurements), total body fat content by the isotope-dilution method, and abdominal sagittal diameter by MRI (ie, "nonsimple" anthropometric measurements) were also measured. Equations to estimate VAT and SAT from age and simple anthropometric measurements (ie, excluding total body fat and abdominal sagittal diameter) were developed. These equations were then used in 24 subjects (nine men and 15 women) to Cross-validate them. The best regression equations, including waist circumference in men and waist circumference and age in women, explained 56% and 68% of VAT variability, respectively. The corresponding standard error of the estimate (SEE) in men was approximately 40% and in women approximately 37% of the mean value of VAT measured by MRI. The best regression equations developed to predict SAT had a higher explained variability (∼87% in both men and women) and a lower SEE (<20% of the mean values of SAT measured by MRI). In men, the equation included BMI and hip circumference, and in women, BMI and age. The inclusion of a higher number of simple anthropometric parameters in the predictive models neither significantly increased the explained variability of VAT or SAT nor significantly decreased the SEE of VAT or SAT. Also, inclusion in the multiple regression analysis of total body fat content and abdominal sagittal diameter did not improve prediction. In the cross-validation study, differences between predicted and observed values of VAT were large, with a tendency to overestimation in both men and women. Incontrast, differences between predicted and observed values of SAT were small. We suggest that SAT but not VAT can be estimated from age and simple anthropometric measurements. Direct methods (MRI, computed tomography [ct], or other options) should be used for assessment of VAT.
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism