Background: This study has been designed to predict whole-body fat mass by various anthropometric indices (waist circumference (WC), waist-to-height ratio (WHtR), hip circumference (HC), waist-tohip ratio (WHR) and body mass index (BMI)). Cost and radiation dose reduction are the advantages of this prediction compared to whole body DXA scan.
Methods: For this study, whole-body composition was measured with dual-energy X-ray Absorptiometry (DXA) for 143 adult patients who referred to Isfahan Osteoporosis Diagnosis Center. Values of weight, height, waist and hip circumferences were measured and BMI, waist-hip ratio and waist-to-height ratio was calculated. Datasets were split randomly into two parts, the derivation set with 100 subjects and validation set with 43 subjects. Multiple regression analysis with back ward stepwise elimination procedure was used for derivation set and then the estimates were compared with the actual measurements.
Findings: Using multiple linear regression analyses, the best equation for predicting whole-body fat mass (R2= 0.808) included BMI and gender.
Conclusion: The present study showed that BMI is the best anthropometric predictor of whole-body fat mass (adjusted R2 = 0.680 and SSE = 999.42).