|O'Connor, Daniel -|
|Bray, Molly -|
|Mcfarlin, Brian -|
|Sailors, Mary -|
|Ellis, Kenneth -|
|Jackson, Andrew -|
Submitted to: American College of Sports Medicine
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 1, 2010
Publication Date: March 1, 2010
Citation: O'Connor, D.P., Bray, M.S., Mcfarlin, B.K., Sailors, M.H., Ellis, K.J., Jackson, A.S. 2010. Generalized equations for estimating DXA percent fat of diverse young women and men: The Tiger Study. American College of Sports Medicine. 42(10):1959-1965. Interpretive Summary: Obesity is defined as an excess of body fat. Measuring the thickness of the fat layer under the skin at multiple locations on the body, called skinfolds, has been used for more than 50 years to estimate body fatness. More recently, the body mass index (BMI), a measure of weight adjusting for a person's height, has become the preferred field method to assess body fatness. In this study, these two methods were combined, along with knowing a person's gender and ethnicity/race, to develop new equations that more accurately predict an individual's body fatness than using either of the methods alone. It was shown that these equations could be used to examine groups of young adults or to monitor changes with time for an individual, such as during a weight loss program.
Technical Abstract: Popular generalized equations for estimating percent body fat (BF%) developed with cross-sectional data are biased when applied to racially/ethnically diverse populations. We developed accurate anthropometric models to estimate dual-energy x-ray absorptiometry BF% (DXA-BF%) that can be generalized to ethnically diverse young adults in both cross-sectional and longitudinal field settings.This longitudinal study enrolled 705 women and 428 men (aged 17-35 yr) for 30 wk of exercise training (3 d/wk(-1) for 30 min/d(-1) of 65%-85% predicted V O2max). The distribution of ethnicity was as follows: 37% non-Hispanic white, 29% Hispanic, and 34% African-American. DXA-BF%, skinfold thicknesses, and body mass index (BMI) were collected at baseline and after 15 and 30 wk. Skinfolds, BMI, and race/ethnicity were significant predictors of DXA-BF% in linear mixed model regression analysis. For comparable anthropometric measures (e.g., BMI), DXA-BF% was lower in African-American women and men but higher in Hispanic women compared with non-Hispanic white. Addition of BMI to the skinfold model improved the SEE for women (3.6% vs 4.0%), whereas BMI did not improve prediction accuracy of men (SEE = 3.1%). These equations provide accurate predictions of DXA-BF% for diverse young women and men in both cross-sectional and longitudinal settings. To our knowledge, these are the first published body composition equations with generalizability to multiple time points, and the SEE estimates are among the lowest published in the literature.