John Handrakis
Lab III: Body Composition
Applied Physiology Lab II
Professor Ronald DeMeersman
I INTRODUCTION
The body is composed of water, lipids, proteins, and fats. In this lab we will concern ourselves
with measuring the ratio of lean body mass (LBM = water, protein, minerals) to fat.
Fat stores can actually be subdivided into storage fat, which is 99% yellow fat and 1%
brown fat or metabolically active fat, and essential fat, which is found in internal organs, muscle,
brain, spinal cord, and bone marrow. Since LBM is comprised of muscle, organs, and fluid, a
more accurate composition of LBM is water, protein, minerals and essential fat. (Robergs &
Roberts, pg. 523) Therefore, we are actually determining the ratio of LBM to storage fat.
The measurement of one’s body composition can be an important index of one’s health
and fitness and assist in exercise program design. A low percentage of body fat is associated
with good health and athletic fitness. A high percentage predicts a greater probability for heart
disease, diabetes, hypertension, cancer, hyperlipidemia, and other health problems. (Robergs &
Roberts, pg. 521)
Since essential fat is important for normal physiological functioning, body fat should not
be lower than 3% for males and 12% for females for optimum health. (Robergs & Roberts, pg.
523)
Anthropometric measurements commonly used to determine health status are body
height/weight tables, waist to hip ratio, body mass index, and skinfold measurements.
Body height/weight tables are perhaps the least accurate fitness and health predictors, as
they do not take muscle mass and fat contributions to body weight into consideration. Waist to
hip ratio is easy to measure and therefore useful. Recommended values for good health are less
than .9 for men and less than .8 for women. Body mass index (BMI) is also an easy to calculate
measurement (BMI = Body weight (kg)/height (m)). Values between 20 and 25 are considered
optimum for good health. (Robergs & Roberts, pg. 537) Skinfold caliper measurements are
perhaps the most useful as they can predict, either through age and sex specific tables, regression
equations, or nomograms, the ratio of one’s LBM to storage fat. However, their accurate
measurement requires a skilled technician and a population specific regression equation.
(Robergs & Roberts, pg. 532)
There are several other methods used to determine body density: hydrodensitometry,
bioelectrical impedance (BIA), isotope dilution, and photo absorptiometry. All of these methods
are fairly accurate with hydrodensitometry considered the gold standard. However, problems
associated with hydrodensitometry are: rather elaborate equipment required, a high degree of
operator proficiency, a high degree of subject compliance and tolerance, and possible
inaccuracies due to the fact that LBM predicted weight values were calculated using a middle
aged Caucasian population only.
Isotope dilution and photo or dual energy X-ray absorptiometry, although accurate, also
requires fairly elaborate equipment. Bioelectrical impedance (BIA), however, has also been
proven to be fairly accurate and it does not require as elaborate equipment nor as high degree of
operator proficiency or subject tolerance, as hydrodensitometry. (*1)
BIA uses the fact that LBM, with its greater fluid and electrolyte content, has greater
conductivity and therefore less resistance than fat. Therefore, by measuring the electrical
resistance from two specific body points and taking age, sex, height, and weight into
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consideration, the percentage of LBM/ fat can be determined. To maintain a homeostatic
electrolyte content and enhance BIA accuracy the subject should:
1) Urinate within 30 min. of the test
2) Not consume alcohol within 48 hours
3) Not exercise within 12 hours
4) Not consume food or fluid within 4 hours. (Robergs & Roberts, pg. 536)
Other less accurate or very expensive and sophisticated densitometry methods
are: potassium-40 count, radiography, ultrasound, computed tomography and nuclear magnetic
resonance imaging, near –infrared interactance, and total body electroconductivity.
It is because of the proven accuracy and relatively low equipment requirements that we
will use skinfold measurements and bioelectrical impedance in this lab experiment.
II PURPOSE
In this lab we will use skinfold measurements and BIA to determine body fat percentage
of two subjects. We will compare values to determine reliability of these two methods.
III MATERIALS
1) Skinfold caliper
2) BCA model 680 bioelectrical impedance monitor
3) Skin electrodes
IV METHODS
Skinfold Measurements
Caliper measurements were taken at three predetermined sites on the right side of the
body: female = triceps, thigh, suprailium, male = chest, abdomen, thigh.
Measurements were made by pinching the skin between thumb and forefinger one cm
proximal to the marked site. The pinched skin is then gently lifted and thickness at the
midportion of that lifted skin site is measured. Caliper measurements were made three times and
recorded to within .5 mm. Two of those measurements, within 5% accuracy of each other, were
used to establish a mean measurement for that site.
The sum of these three measurements were then used to calculate percentage body fat
through either a nomogram (*2), age and sex table (*3), or regression equations (Robergs &
Roberts, pg. 532).
Bioelectrical Impedance
With the subject supine and right arm at 90degrees of abduction, electrodes are placed on
the dorsal surface of the right hand at the base of the third finger and at the wrist between the two
styloid processes. Electrodes are also placed on the dorsum of the right foot at the base of the
second toe and between the malleoli of the ankle.
Electrodes are connected to the unit via leads. Red leads are used on the distal electrodes
(toe, finger) while black leads are used on the proximal electrodes (ankle, wrist).
The BCA model 680 unit measures electrical impedance, and along with weight, height,
age, and sex considerations, calculates percentage body fat.
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V DATA
Skinfold Measurements (mean values mm)
Triceps
Suprailiac
Subject 1 (Robin)
0
l5
Sum = 34.5
Abdomen
Chest
Subject 2 (John)
l2.5
5.5
Sum = 23.5
Thigh
l9.5
Thigh
5.5
Nomogram (*2) Predicted Body Fat Percentage
Subject l (Robin)
l5%
Subject 2 (John)
8.5%
Regression Equation Predicted Body Fat Percentage
Subject l (Robin)
Females l8-55 years
Db = l.099492l - .0009929 (sum) + .0000023 (sum) - .00l392 (age)
= l.099492l - .034255l + .0027376 - .043l52
= l.025
Body Fat Percentage = [(5.03/Db)-4.59] x l00
= 3l.7%
Subject 2 (John)
Males l8-6l years
Db= l.l093800 - .0008267 (sum) + .00000l6 (sum) - .0002574 (age)
= l.l093800 - .0l942745 + .0008836 - .0ll0682
= l.08
Body Fat Percentage = [(4.95/Db) – 4.5] x l00
= 8.3%
BIA
Subject l (Robin) = 22.2%
Subject 2 (John) = l6.3%
VI DISCUSSION
I found the values of 22% and l6% for Robin and John respectively, determined by the
BIA method, to be more accurate but somewhat pessimistic for both subjects. This conclusion is
based on their physical appearance and level of physical activity when compared to the normal
range of 2l% - 29% for women and l7% - 23% for men in their age group. This places Robin in
a better than average low body fat status and John in a good category of body leanness. (Robergs
& Roberts, pg. 523) My confidence is bolstered by data (*l) showing accuracy of BIA to be
within 3%.
Our nomogram (*2) predictions, based on skinfold measurements, proved to be
optimistic as Robin’s value was l5% and John’s 8.5%. However, accuracy of this method is only
within 8%. Therefore, adding 7.5% to both values would yield a high correlation to the BIA
values. Modifying our values further, within predicted error ranges, yields values of 20% for
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Robin and l4% for John (BIA – 2%). This would lower the error of the nomogram to only 5% 5.5%.
These adjusted values would place Robin in the good category and John in the good –
excellent category of body leanness. This seems more probably to me when taking their physical
appearance and level of physical training into account.
When using the regression equations (Robergs & Roberts, pg. 528) to predict body fat,
our calculations were inconsistent. Using the equation for females l8 – 55 years, Robin’s value
was an inaccurate 3l.7%. Using the equation for males l8 – 6l years yielded a nomogram
correlating value of 8.3% for John. I cannot accurately comment on reasons why Robin’s
correlation to her nomogram value was so poor.
It was insightful to see the considerable skill needed to produce inter-tester reliability
when using the skinfold calipers. We also had difficulty obtaining a measurable skinfold at
Robin’s triceps and had to record her value as 0 at that site.
In conclusion, I feel that the BIA method would be the method of choice for an accurate
measurement providing one had that piece of equipment. Correlation between both methods did
prove to be high, however, once predicted error adjustments were taken into account.
I believe a higher correlation, using skinfold measurements, would be possible with
greater operator proficiency and perhaps using an age and sex based table (*3) for comparing
percent fat estimates to nomogram values.
REFERENCES:
1) Olympic Scientific Congress, New Horizons of Human Movement, pg. 9, l988.
2) W.B. Baum, et al., “A Nomogram for the Estimate of Percent Body Fat from Generalized
Equations”, Research Quarterly for Ex & Sport, 52, pg. 380 – 84).
3) Jackson A.S., Pollack M.L.: Phys Sportsmed l3: pg. 76-90, l985)
4) Robergs, R. and Roberts, S., Exercise Physiology, Mosby, St. Louis l997
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