Prediction Equation for Calculating Fat Mass in Young Indian Adults

Authors

Jaspal Singh Sandhu,*
*Corresponding Author: :: Faculty of Sports Medicine and Physiotherapy, Guru Nanak Dev University, Amritsar-143005, Punjab, India, [email protected]. Email: [email protected]

Asian Journal of Sports Medicine:Vol. 1, issue 2; 101-107
Published online:May 31, 2010
Article type:Research Article
Received:Apr 05, 2010
Accepted:May 18, 2010
How to Cite:Sandhu JS. Prediction Equation for Calculating Fat Mass in Young Indian Adults. Asian J Sports Med. 2010;1(2):34862. doi: https://doi.org/10.5812/asjsm.34862

Abstract

Purpose:

Accurate measurement or prediction of fat mass is useful in physiology, nutrition and clinical medicine. Most predictive equations currently used to assess percentage of body fat or fat mass, using simple anthropometric measurements were derived from people in western societies and they may not be appropriate for individuals with other genotypic and phenotypic characteristics. We developed equations to predict fat mass from anthropometric measurements in young Indian adults.

Methods:

Fat mass was measured in 60 females and 58 males, aged 20 to 29 yrs by using hydrostatic weighing and by simultaneous measurement of residual lung volume. Anthropometric measure included weight (kg), height (m) and 4 skinfold thickness [STs (mm)]. Sex specific linear regression model was developed with fat mass as the dependent variable and all anthropometric measures as independent variables.

Results:

The prediction equation obtained for fat mass (kg) for males was 8.46+0.32 (weight) ? 15.16 (height) + 9.54 (log of sum of 4 STs) (R2= 0. 53, SEE=3.42 kg) and ? 20.22 + 0.33 (weight) + 3.44 (height) + 7.66 (log of sum of 4 STs) (R2=0.72, SEE=3.01kg) for females.

Conclusion:

A new prediction equation for the measurement of fat mass was derived and internally validated in young Indian adults using simple anthropometric measurements.

Full Text

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Copyright

© 2010, Author(s). This open-access article is available under the Creative Commons Attribution 4.0 (CC BY 4.0) International License (https://creativecommons.org/licenses/by/4.0/), which allows for unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.

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