Development and validation of anthropometric equations to estimate body composition in adult women
Abstract
Objective: To develop anthropometric equations to predict body fat percentage (BF%) in adult women. Methods: In 151 women (aged 18-59) BF% was obtained by hydrodensitometry with simultaneous measurement of lung volumes. Body weight, height, eight- skinfold thickness (STs) and six- circumference (CIs) measurements were obtained from all participants. Subjects data were randomly divided in two groups, equation-building group (n=106) and validation group (n=45). The equation-building group was used to run multiple linear regression models using anthropometric measurements as predictors to find the best prediction equations of the BF%. The validation group was used to compare the performance of the new equations with those of Durnin-Womersley, Jackson-Pollock and Ramirez-Torun. Results: There were two preferred equations: Equation 1 = 11.76 + (0.324 x tricipital ST) + (0.133 x calf ST) + (0.347 x abdomen CI) + (0.068 x age) - (0.135 x height) and Equation 2 = 11.37 + (0.404 x tricipital ST) + (0.153 x axilar ST) + (0.264 x abdomen CI) + (0.069 x age) - (0.099 x height). There were no significant differences in BF% obtained by hydrodensitometry (31.5±5.3) and Equation 1 (31.0±4.0) and Equation 2 (31.2±4.0). The BF% estimated by Durning-Womersley (35.8±4.0), Jackson-Pollock (26.5±5.4) and Ramirez-Torun (32.6±4.8) differed from hydrodensitometry (p<0.05). The interclass correlation coefficient (ICC) was high between hydrodensitometry and Equation 1 (ICC=0.77), Equation 2 (ICC=0.76), and Ramirez-Torun equation (ICC=0.75). The ICC was low between hydrodensitometry and Durnin-Womersley (ICC=0.51) and Jackson-Pollock (ICC=0.53) equations. Conclusion: The new Equations-1 and 2, performed better than the commonly used anthropometric equations to predict BF% in adult women.Authors
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Keywords
- Obesity
- fat free mass
- fat mass
- body fat
- fat mass percentage
- hydrodensitometry
- anthropometry
- underwater weighing
- validation study
- prediction equations.
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