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Abstract

International Journal of Exercise Science 5(3) : 223-231, 2012. Clinical guidelines define obesity in terms of excess body weight adjusted for height (i.e., bodymass index [BMI] categories) and/or gender-specific waist circumference (WC) cut-point values. Since body composition, particularly fat mass, is the most variable among individuals due to differences by gender, age, and race, and total percent body fat (%BF) can be estimated accurately using dual-energy X-ray absorptiometry (DXA), the purpose of this study was to develop and compare two field-based body fat prediction equations suitable for a nationally representative sample of the US adult population. Data were analyzed from subjects 20+ years of age (n = 11,907) with BMI and WC values, and that participated in DXA scans as part of the 1999-2004 National Health and Nutrition Examination Survey (NHANES). Multiple linear regression was used to develop and compare DXA-estimated %BF as the dependent variable versus BMI or WC, gender, age, and race as predictor variables. Mean values for age, BMI, WC, and %BF among the sample were 46.84 ± 0.30 years, 28.17 ± 0.11 kg/m2, 96.69 ± 0.27 cm, and 34.19 ± 0.14 %, respectively. Both equations were similar in terms of explained variance, with R2 values of 0.82 for the BMI and WC equations, respectively. Both equations are easy to use, and could easily be developed as an application on a smartphone or other handheld device, or simply integrated into a spreadsheet for use as an additional tool for health professionals to assess the current health status of individuals based on predicted body fat from BMI, WC, and demographics.

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