Abdominal visceral adiposity is related to risks for insulin resistance and metabolic perturbations. Magnetic resonance imaging (MRI) and computed tomography are advanced instruments that quantify abdominal adiposity; yet field use is constrained by their bulkiness and costliness. The purpose of this study is to develop prediction equations for total abdominal, subcutaneous, and visceral adiposity via anthropometrics, stereovision body imaging (SBI), and MRI.


Participants (67 men and 55 women) were measured for anthropometrics and abdominal adiposity volumes evaluated by MRI umbilicus scans. Body circumferences and central obesity were obtained via SBI. Prediction models were developed via multiple linear regression analysis, utilizing body measurements and demographics as independent predictors, and abdominal adiposity as a dependent variable. Cross-validation was performed by the data-splitting method.


The final total abdominal adiposity prediction equation was –470.28 + 7.10 waist circumference – 91.01 gender + 5.74 sagittal diameter (R2 = 89.9%), subcutaneous adiposity was –172.37 + 8.57 waist circumference – 62.65 gender – 450.16 stereovision waist-to-hip ratio (R2=90.4%), and visceral adiposity was –96.76 + 11.48 central obesity depth – 5.09 central obesity width + 204.74 stereovision waist-to-hip ratio – 18.59 gender (R2 = 71.7%). R2 significantly improved for predicting visceral fat when SBI variables were included, but not for total abdominal or subcutaneous adiposity.


SBI is effective for predicting visceral adiposity and the prediction equations derived from SBI measurements can assess obesity.