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What variables are important in the measurement of the body composition? Comment by Amy Allnutt: Dont include these headers in your final paper

The important elements of health in individuals and the populations are the growth and the composition of the body. The golden average for the body composition examination is cadaver examination, so no in vivo method may be measured to attain the largest standards of accurateness. In these, the important variables considered in measuring body composition are: resting metabolic rate (RMR), BMI, fat-free mass and pounds to lose. Their dimension is rapidly increasing and is reflected in medical exercise; conversely, pediatricians are solemnly not sure as to which methods are suitable and proper for application in precise circumstances. Comment by Amy Allnutt: standard? Comment by Amy Allnutt: These are not variables for measuring body composition Comment by Amy Allnutt: sp

What is the reliability of these formulas? (Reliability =consistency)

The SKF technique is based on the guidelines that there is a relation between internal body fat (SKF thickness) and entire body fat, whereas the BIA technique is grounded on the guidelines that electric current runs at changed rays through the body subject to its composition. This study explains that the skin fold formulas used “were established from non-obese young Americans and are built on the notion that fat is scattered within in the same way for all persons” (Chambers et al., 2014). That notion is problematic because fat distribution and formulas can also vary by the population being assessed. Conversely, BIA reliability was universally larger as compared to SKF technique. Most of the BIA comparisons also revealed complex dependability as likened to the three position SKF formula. Similarly, the dependability of BIA outcomes in affected by factors like surroundings, culture, a period of the menstrual cycle and underlying medicinal circumstances (American College of Sports Medicine. 2014).

What is the margin of error? (This will typically be a percentage i.e. 3-5%)

The study on BIA accuracy also suggests that in most of the readings they came across, the BIA technique was inaccurate when a general comparison was used. This makes the overall SEE for BIA in general according to the ACSM ranges from +3.5% to + 5%.

Experiment with 2 subjects using these 2 different formulas. Using each formula on each subject compare the results

Both formulas with their respective methods were reliable to a certain degree. The reliability and accuracy depended on each case as long as conditions needed for each method were met. Using these ranges and considering the skin- fold method calculation as more accurate, subject A is within the range at 31.5%. Both methods were tested on each subject and results did vary, mostly on subject B where the difference in body fat % was greater between the two body composition methods Comment by Amy Allnutt: show formulas

Determine their Resting Metabolic Rate (RMR) using the Harris-Benedict formulas, BMI, fat-free mass and pounds to lose (if applicable) based on the ACSM recommendations for body composition.

Subject A

RMR – 1,731 kCal Comment by Amy Allnutt: kcal/day

BMI – 28.23 kg/m2

Fat-Free Mass - 68.5% Comment by Amy Allnutt: how do you know this? what is his weight?

Pounds to lose -

Subject B

RMR – 2,67

BMI – 31.6 kg/m2

Fat-Free Mass - 68.5%

Pounds to lose - 5%

(BMI and Waist-Hip Ratio are NOT considered body compositions formulas.) You may NOT use either of these.

Human error and compliance are key factors in affecting measurements in both methods of body composition (Dehghan & Merchant, 2008). The hip ratio does not notice variations in the body conformation over a time when lean tissue rises and fat quantity reduces. Hence, they seem to be impractical for regular estimation of body fat proportion. Death rates from heart illnesses, cancer, and diabetes rise as the BMI also rise. Significant increases in dangers start at a BMI of around 30.0 kg/m2 for both ladies and gentlemen.

References

American College of Sports Medicine. (2014). ACSMs health-related physical fitness assessment manual (4th ed.). Philadelphia, PA: Wolters Kluwer Health/Lippincott Williams & Wilkins.

Chambers, A., Parise, E., McCrory, J., & Cham, R. (2014). A Comparison of Prediction Equations for the Estimation of Body Fat Percentage in Non-obese and Obese Older Caucasian Adults in the United States. Retrieved March 04, 2018, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4396823/

Dehghan, M., & Merchant, A. T. (2008). Is bioelectrical impedance accurate for use in large epidemiological studies? Retrieved March 05, 2018, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2543039/

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