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Body Fat and Modern Medical Techniques of Defining and Predicting its presence in the human body

   Body fat and the calculation of its amount in the human body has become one of the most widely used measurements by various doctors. It is done to identify the patient’s weight loss program, their food requirements, risks and other health factors. There is a number of different techniques, such as dual-energy x-ray absorptiometry (DXA), isotope dilution, and air displacement plethysmography, performed in order to study and monitor body reactions to certain changes. These techniques are often used for research work, but generally are too expensive, time consuming, and impractical for use in field evaluations, gym environments and healthcare settings (Vogel & Friedel, 1992, Swan & McConnell, 1999). A number of field techniques solve the problems, outlined above, and have the added benefits of being portable, are relatively simplistic to use and are noninvasive (Lukasaki, Bolonchuk, Hall & Siders, 1986). They do, however, have limitations of lower accuracy and validity (Vogel & Friedel, 1992). Field methods such as Skinfold (SkF) tests, bioelectrical impedance analysis (BIA), circumference measures, and near infra-red interactance (NIR), are all doubly indirect, and are based upon regression models devised by comparing measure to criterion measurements (Williams, Going, Milliken, Hall & Lohman, 1994, Swan & McConnell, 1999). The aim of this study was to compare two methods of predicting fat from SkF thickness, the Durnin & Wormersly (D & W) (1974) equation and the Jackson & Pollock (J & W) (1978) equation, with body fat predictions from BIA.

   SkF measurements indirectly measure the thickness of the subcutaneous adipose tissue, and must be taken by a trained individual; at the correct sites (Reilly, Maughan & Hardy, 1996). The ∑SkF is then entered into a prediction equation to calculate body density. The body density value may then be used in the Siri (1956) equation to predict body fat; this equation is only for white Caucasians. The prediction equations, used to predict body fat need to be population specific, in terms of gender, race, age, and activity level (Davis & Cole, 1995). SkF has been recommended for use on athletes and sports people, but often cannot be used on the obese (Clarys, Martin, Drinkwater & Marfell-Jones, 1987). This has led to over 100 population specific equations, devised using linear regression models, being formulated (Heyward & Stolarczyk, 1996). SkF methods are based upon two basic assumptions; that there is a relationship between total body fat and subcutaneous fat, and that SkF can accurately measure subcutaneous fat (Wagner & Heyward, 1999). SkF is susceptible to many sources of error; for example SkF sites need to be exactly located, and only the subcutaneous fat measured. The callipers compress the fatty tissue, therefore if sufficient time isn’t given before re-measuring then the data will be inaccurate.

   BIA is a method by which a low level electrical current, of a fixed frequency, is introduced to the subject (Wagner & Heyward, 1999). The impedance (Z) of this current is then measured and, through the use of regression equations, displayed as easily understood information such as lean body weight, body fat percentage, and water content (Heyward & Stolarczyk, 1996). This is achieved due to bone and fat being a poor electrical conductor as it is anhydrous, conversely lean tissue is a good conductor as it has a high water and electrolyte content (McArdle, Katch & Katch 2001). The equation assumes that the human body is cylindrical in shape. BIA is very popular as it is quick and easy to perform, and is less obtrusive than the SkF method (Wagner & Heyward, 1999). BIA, like SkF, is open to error. It is very sensitive to hypo and hyper-hydration; hyper-hydration raises the prediction of body fat due to an increase in the impedance measure, the opposite effect is found when the subject is hypo-hydrated. A reduction in skin temperature will also increase the predicted body fat percentage.

   Due to the different assumptions and prediction equations made, by each method of predicting body fat, the hypothesis are:

Ho: There is no significant difference in body fat predicted by the D & W (1974) prediction equation and BIA
Ha: There is a significant difference in body fat predicted by the D & W (1974) prediction equation and BIA
Ho: There is no significant difference in body fat predicted by the J & P (1978) prediction equation and BIA
Ha: There is a significant difference in body fat predicted by the J & P (1978) prediction equation and BIA

Method

Participants

    The participants in this study consisted of 11 male and 8 female Sport & Exercise Science Students, N = 19. All subjects did not complete all of the protocols so data was manipulated. After manipulation N = 12, with 7 male subjects and 5 female. x age = 21.4 years.

Measures & Procedures

   All measurements were taken in a temperate room. Stature was measured; using a standard stadiometer, to the nearest 1mm. Body mass was assessed, to the nearest 0.5 Kg, with participants wearing minimal clothing.

   SkF measurements were taken from the right side of the body, with the subject standing in the anatomical position and with Harpenden skinfold callipers (British Indicators Ltd, Luton, UK). The sites were located as described in Eston & Reilly (2001). The sites measured for the D & W (1974) prediction equation were the bicep, tricep, subscapular and the iliac crest. Those taken for J & P(1978) prediction equation were the pectoral, triceps, subscapular, abdominal, axilla, suprailium and midthigh. A minimum of three measures was taken from each site to gain maximum validity. There was at least 3 minutes between each measurement to allow for compression of the adipose tissue. SkF was measured after 2 seconds of applying the callipers, and measured to the nearest 2mm.

   BIA was assessed using the bodystat BIA system. The subjects had electro-conducting gel placed upon the right hand and foot proximal to the metacarpel-phalangeal and the metatarsal-phalangeal joints, electodes were then placed upon this gel. A voltage sensing electrode was then placed at the midpoint between the dital prominences of the radius and ulna of the right wrist, and between the medial and lateral malleoli of the right ankle. During the measurement the subjects were supine with their arms and legs abducted, on a non-conducting surface. The instrument gathered body fat was then recorded.

Data Analysis

Body density was calculated using the D & W(1974) prediction equation, and the Jackson and Pollock (1978) prediction equation.

The D & W(1974) equations uses the ∑4 SkF (bicep,tricep,subscapular and iliac crest). The equation for male and females are shown below:

Male = 1.1610 - (0.0632 x log ∑4 SkF)

Female = 1.1581 – (0.072 x log ∑4 SkF)

The J & P(1978) equations uses the ∑7 SkF (pectoral, triceps, subscapular, abdominal, axilla, suprailium and midthigh). The equation for males and females are shown below:

Male = 1.112 – (0.00043499 x ∑7 SkF) + [0.00000055 x (∑7)2] – (0.00028826 x age)

Female = 1.097 - (0.00046971 x ∑7 SkF) + [0.00000056 x (∑7)2] – (0.0001288 x age)

The body density data was then manipulated using the Siri equation (1956) to predict body fat. The equation is shown below:

%Fat = [(4.95/body density) – 4.5] x 100

   A paired T-test was performed between the body fat prediction, by using the D & W (1974) equation, and body fat predicted by BIA. A paired T-test was also performed between the body fat prediction, by using the J & P(1978) equation, and body fat predicted by BIA

 

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