Predictive equations for body fat and abdominal fat with DXA and MRI as reference in Asian Indians

Abstract

Objective:To develop accurate and reliable equations from simple anthropometric parameters that would predict percentage of total body fat (%BF), total abdominal fat (TAF), subcutaneous abdominal adipose tissue (SCAT), and intra-abdominal adipose tissue (IAAT) with a fair degree of accuracy.Methods and Procedures:Anthropometry, %BF by dual-energy X-ray absorptiometry (DXA) in 171 healthy subjects (95 men and 76 women) and TAF, IAAT, and SCAT by single slice magnetic resonance imaging (MRI) at L3-4 intervertebral level in 100 healthy subjects were measured. Mean age and BMI were 32.2 years and 22.9 kg/m 2, respectively. Multiple regression analysis was used on the training data set (70%) to develop equations, by taking anthropometric and demographic variables as potential predictors. Predicted equations were applied on validation data set (30%).Results:Multiple regression analysis revealed the best equation for predicting %BF to be: %BF 42.42 0.003 × age (years) 7.04 × gender (M 1, F 2) 0.42 × triceps skinfold (mm) 0.29 × waist circumference (cm) 0.22 × weight (kg) 0.42 × height (cm) (R 2 86.4%). The most precise predictive equation for estimating IAAT was: IAAT (mm 2) 238.7 16.9 × age (years) 934.18 × gender (M 1, F 2) 578.09 × BMI (kg/m 2) 441.06 × hip circumference (cm) 434.2 × waist circumference (cm) (R 2 52.1%). SCAT was best predicted by: SCAT (mm 2) 49,376.4 17.15 × age (years) 1,016.5 × gender (M 1, F 2) 783.3 × BMI (kg/m 2) 466 × hip circumference (cm) (R 2 67.1).Discussion:We present predictive equations to quantify body fat and abdominal adipose tissue sub-compartments in healthy Asian Indians. These equations could be used for clinical and research purposes. © 2008 The Obesity Society.