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Am J Hum Biol. 2012 Sep-Oct;24(5):648-53. doi: 10.1002/ajhb.22286. Epub 2012 May 26.

New insights into scaling of fat-free mass to height across children and adults.

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  • 1Obesity Research Center, St. Luke's-Roosevelt Hospital, Columbia University, College of Physicians and Surgeons, New York City, New York, USA.



Forbes expressed fat-free mass (FFM, in kg) as the cube of height (H, in m): FFM = 10.3 × H(3). Our objective is to examine the potential influence of gender and population ancestry on the association between FFM and height.


This is a cross-sectional analysis involving an existing dataset of 279 healthy subjects (155 males and 124 females) with age 5-59 years and body mass index (BMI) 14-28 kg/m(2). FFM was measured by a four-component model as the criterion.


Nonlinear regression models were fitted: FFM = 10.8 × H(2.95) for the males and FFM = 10.1 × H(2.90) for the females. The 95% confidence intervals for the exponential coefficients were (2.83, 3.07) for the males and (2.72, 3.08) for the females, both containing hypothesized value 3.0. Population ancestry adjustment was considered in the H-FFM model. The coefficient of the H-FFM model for male Asians is smaller than that for male Caucasians (P = 0.006), while there is no statistically significant difference among African-Americans, Caucasians and Hispanics: 10.6 for the males (10.1 for Asians, 10.8 for African-Americans, 10.7 for Caucasians and 10.4 for Hispanics) and 9.6 for the females (9.3 for Asians, 9.8 for African-Americans, 9.6 for Caucasians and 9.5 for Hispanics). Age adjustment was unnecessary for the coefficient of the H-FFM model.


Height is the most important factor contributing to the magnitude of FFM across most of the lifespan, though both gender and ancestry effects are significant in the H-FFM model. The proposed H-FFM model can be further used to develop a mechanistic model to explain why population ancestry, gender and age influence the associations between BMI and %Fat.

Copyright © 2012 Wiley Periodicals, Inc.

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