Comparison of eight equations that predict percent body fat using skinfolds in American Youth

Kimberly P. Truesdale, Amy Roberts, Jianwen Cai, Jerica M. Berge, June Stevens

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Background: Skinfolds are often used in equations to predict percent body fat (PBF) in youth. Although there are numerous such equations published, there is limited information to help researchers determine which equation to use for their sample. Methods: Using data from the 1999-2006 National Health and Nutrition Examination Surveys (NHANES), we compared eight published equations for prediction of PBF. These published equations all included triceps and/or subscapular skinfold measurements. We examined the PBF equations in a nationally representative sample of American youth that was matched by age, sex, and race/ethnicity to the original equation development population and a full sample of 8- to 18-year-olds. We compared the equation-predicted PBF to the dual-emission X-ray absorptiometry (DXA)-measured PBF. The adjusted R2, root mean square error (RMSE), and mean signed difference (MSD) were compared. The MSDs were used to examine accuracy and differential bias by age, sex, and race/ethnicity. Results: When applied to the full range of 8- 18-year-old youth, the R2 values ranged from 0.495 to 0.738. The MSD between predicted and DXA-measured PBF indicated high average accuracy (MSD between -1.0 and 1.0) for only three equations (Bray subscapular equation and Dezenberg equations [with and without race/ethnicity]). The majority of the equations showed differential bias by sex, race/ethnicity, weight status, or age. Conclusions: These findings indicate that investigators should use caution in the selection of an equation to predict PBF in youth given that results may vary systematically in important subgroups.

Original languageEnglish (US)
Pages (from-to)314-323
Number of pages10
JournalChildhood Obesity
Issue number4
StatePublished - Aug 2016

Bibliographical note

Publisher Copyright:
© Copyright 2016, Mary Ann Liebert, Inc. 2016.


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