Percent Body Fat Prediction from Body Mass Index and Waist Circumference: New Cross-validated Equations for Young Adults

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Background: A simple prediction equation that accurately predicts an individual’s percent body fat (PBF) with easy to obtain inputs could benefit health and exercise science professionals. The purpose of this study was to develop and cross-validate a set of regression equations predicting PBF in young adults. Methods: A subset of N=684 participants from a national health survey between the ages of 18 and 24 years was used in this study. Criterion values of PBF (PBF.DXA) were obtained using dual energy X-ray absorptiometry (DXA). Predictor variables included age, sex, body mass index (BMI), and waist circumference (WC). The sample was split equally and randomly into training and validation samples. Two sets of equations were evaluated in the training sample, one set using BMI and the other using WC. Both sets were tested to determine if age was a useful predictor of PBF.DXA. Cross-validation of selected model coefficients using the validation sample was evaluated using Pearson correlation coefficients, Bland and Altman limits of agreement (LOA) plots and Kappa statistics for obesity classification. Results: The selected models were both two-predictor equations: PBF.BMI2 = 10.47827 + BMI*0.98342 – 12.50670; R2 = .872 and PBF.WC2 = 2.51020 + WC*0.38914 – 13.34843; R2 = .866. Cross-validation correlation coefficients were large for both PBF.BMI2 (r = .91) and PBF.WC2 (r = .92) equations. LOA plots indicated small bias of -0.49 ± 7.5% and -0.25 ± 6.8% in PBF.BMI2 and PBF.WC2 analyses, respectively. Kappa coefficients for agreement between the two obesity classification methods were considered “substantial” for PBF.BMI2 (κ = .64) and PBF.WC2 (κ = .70) models. Conclusion: This study provides validation evidence supporting the use of BMI- and WC-based PBF prediction equations in young adult populations.