Issues and problems that exist in the fractionation of total body mass using anthropometrics

Recently, the use of anthropometric measurements (i.e., skinfolds, circumferences, girths, and bone breaths) to fractionate body mass into different compartments (i.e., skin, muscle, adipose tissue, bone, and organs) has become popular.  These measurements are then put into a series of formulae to estimate muscle, bone, fat masses, etc.  Some anthropometrics professionals use these measurements to than determine how much weight an individual can add to their body frame, etc. In this blog, we will explore some of the issues and problems that exist in the fractionation of total body mass using anthropometrics.  

There are two approaches one can use to fractionate total body mass into its various subcomponents. The chemical-based approach measures the amounts of water, fat, protein, and mineral components and places the total body mass into one of these four compartments. The anatomical approach separates the total body mass into skin, muscle, adipose tissue, bone, and organs. Obviously, in humans the chemical approach is not possible so for fractionating total body mass into various compartments the anatomical approach is used. Traditionally, the anatomical approach uses anthropometric measurements to fractionate total body mass into the various compartments.  After the anthropometric measurements are made, a series of equations are used to estimate the masses of the various subcomponents (i.e., skin, muscle, adipose tissue, bone, and organs). 

Although some individuals act as if this is a new method, it actually has been around for over 100 years. The Czechoslovakian anthropologist Jindrich Matiegka (Matiegka, 1921) actually proposed this concept in the 1920s. Using a series of anthropometric measurements, Matiegka (1921) developed a series of equations to fractionate body mass into its anatomical components. Then, in 1986, Drinkwater et al. (1986) revised these formulae and validated them against data from 25 cadavers between the ages of 55-94 years. Soon after, Martin et al. (1990) proposed a new approach to estimate muscle mass from anthropometric measurements based upon 12 male cadavers.  

Although some individuals tout the accuracy of skinfolds, girths and circumferences in determining muscle, fat, and even bone there are a number of issues with these measures. Skinfold measurements include a double layer of skin, which can vary within an individual as well as among individuals based upon age, diet, activity level, etc. (Martin et al., 1985). Girths and circumferences are also subject to error in placement as well as pressure used with the implementation. In addition, tester error is always an issue in anthropometric measures (Norton et al., 2009).  

Besides issues with the actual anthropometric measurements, the formulae used to fractionate the total body mass into the various components are problematic due to assumptions they make. One of the assumptions is that the body grows geometrically. We know that this assumption is incorrect since body mass does not increase proportionally with stature (Ross and Ward, 1982). Certain parts of the body grow while others remain static. The second assumption is that the distribution of the different masses is the same for males and females. This assumption disregards sex-specific fat distributions amongst the subcutaneous depots and between subcutaneous and visceral fat depots. Finally, in the anatomical approach using anthropometric measurements, the densitometric determination of percent body fat assumes the body can be divided into fat mass and fat-free mass. To do this one has to assume a density for fat mass and fat-free mass.  For fat mass, a density of 0.9997 or 1.1000 g/cm3 is used (Fidanaza et al., 1953; Keys and Brozek, 1953).  For fat-free mass, a density of 1.1000 g/cm3 (Brozek et al., 1963) is used. This value was derived from cadaver analysis of just three Caucasian males aged 25, 35, and 46 years. Since this initial value of 1.1000 g /cm3 for fat-free mass was proposed, it has been challenged (Jones and Corlett, 1980; Haschke et al., 1981). However, the value of 1.1000 g/cm3 is still used and is applied universally irrespective of the subject’s age, gender, ethnicity, or state of training. This creates a problem in those individuals with a fat-free mass density of 1.1000 g/cm3 who will have their percent body fat overestimated, whereas individuals with a density of fat-free mass greater than 1.1000 g/cm3 percent body fat will be underestimated.  A similar problem exists with the density of bone, which has an assumed value of 2.982 g/cm3 (Brozek et al., 1963). As with fat-free mass, this value was determined based upon the data of three Caucasian males.  In the fractionation of body mass, this value for bone density is used irrespective of the subject’s age, gender, ethnicity, or state of training, which we know to affect bone density. This creates another source of error within the current formulae used to fractionate body mass using anthropometric measures.

Take-Home Message
Although the idea of fractionating body mass into its various components using anthropometric measurements would be of value, the actual practice of this concept is fraught with numerous problems. One of these problems is the assumption of set values for the density of muscle, fat, bone, etc. These assumptions often lead to inaccuracy in the determination of different masses. Another issue is the formulas used in the fractionating of body mass.  Whether the formula of Drinkwater et al (1986) or Martin et al. (1990) is used, both have been found to lead to a significant overestimation of total body mass as well as muscle mass (Cattrysse et al., 2002). One should not be discouraged with the development of newer more accurate measures of body composition, such as dual X-ray absorptiometry (DXA). Often multiple methods such as DXA, bioelectrical impedance, magnetic resonance, etc., can be combined to develop very accurate and precise methods.

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About the Author
Donald Dengel, Ph.D., is a Professor in the School of Kinesiology at the University of Minnesota and is a co-founder of Dexalytics. He serves as the Director of the Laboratory of Integrative Human Physiology, which provides clinical vascular, metabolic, exercise and body composition testing for researchers across the University of Minnesota.

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