Body Composition Analysis using various Techniques and Equipment
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This document discusses a study on body composition analysis using various techniques and equipment. It covers the different methods used, the results obtained, and the limitations of the study. The document also highlights the importance of using multiple methods for accurate body fat analysis. The study concludes that body composition techniques produce more accurate results compared to bio-impedance techniques. The full document is available on Desklib.
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Running head: BODY COMPOSITION PRACTICAL
BODY COMPOSITION PRACTICAL
Name of the Student:
Name of the University:
Author note:
BODY COMPOSITION PRACTICAL
Name of the Student:
Name of the University:
Author note:
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1BODY COMPOSITION PRACTICAL
Responses as per Boxes in ‘SCANNED DOCUMENT 2’
Summary and Title
The title of the study was based on the formulated aim and hence, was decided to be:
‘Body Composition Analysis using various Techniques and Equipment’. This title was
decided since different techniques use different working principles and hence produce
different results. Hence, one must use multiple methods in conjunction for improved accuracy
(Pleuss et al., 2018).
Introduction: Key Points and References
1. Different techniques are being considered for body composition and anthropometric
analysis (Franco-Villoria et al., 2016).
2. Each method produces different results hence necessitating usage of multiple methods
instead of relying on just one (Makwana & Makwana, 2015).
3. Each method produces different results since they follow different working principles
(Lang et al., 2015).
Hypothesis
1. Different body measurement methods produce different results.
2. Bio-impedance and body composition methods produce more detailed anthropometric
analysis.
3. Body composition methods produce different and accurate body fat percentage values
as compared to bio-impedance techniques.
Responses as per Boxes in ‘SCANNED DOCUMENT 2’
Summary and Title
The title of the study was based on the formulated aim and hence, was decided to be:
‘Body Composition Analysis using various Techniques and Equipment’. This title was
decided since different techniques use different working principles and hence produce
different results. Hence, one must use multiple methods in conjunction for improved accuracy
(Pleuss et al., 2018).
Introduction: Key Points and References
1. Different techniques are being considered for body composition and anthropometric
analysis (Franco-Villoria et al., 2016).
2. Each method produces different results hence necessitating usage of multiple methods
instead of relying on just one (Makwana & Makwana, 2015).
3. Each method produces different results since they follow different working principles
(Lang et al., 2015).
Hypothesis
1. Different body measurement methods produce different results.
2. Bio-impedance and body composition methods produce more detailed anthropometric
analysis.
3. Body composition methods produce different and accurate body fat percentage values
as compared to bio-impedance techniques.
2BODY COMPOSITION PRACTICAL
Anonymised Participant Details
A total of 10 participants were selected whose names were anonymised using
numbers and comprised of 5 males and 5 females. The participants comprised of university
students in the age group of 19 to 25 years.
Details of Equipment
Body mass index was measured using weight and height scales. Waste-to-hip ratio
was measured using measuring tapes. Body fat percentages were measured using bio-
impedance or body fat scales. Body fat percentages were also measured using body
composition equipment ‘Body Stat’.
Other Relevant Information
The provided data showed missing values of body fat percentages in participant 10.
Required Graphs and Tables
A table which will summarise all the values of various methods as well as the
diagnostic comments is required. A graph which will pictorially display differences in body
fat percentages by bio-impedance and body composition methods will be added. A pie chart
which will show percentages of ‘healthy’ people reported by each method will be added.
Summary of Results
Different methods were found to demonstrate different values. Body composition
method reported higher values of body fat percentage and more detailed analysis than bio-
impedance technique.
Anonymised Participant Details
A total of 10 participants were selected whose names were anonymised using
numbers and comprised of 5 males and 5 females. The participants comprised of university
students in the age group of 19 to 25 years.
Details of Equipment
Body mass index was measured using weight and height scales. Waste-to-hip ratio
was measured using measuring tapes. Body fat percentages were measured using bio-
impedance or body fat scales. Body fat percentages were also measured using body
composition equipment ‘Body Stat’.
Other Relevant Information
The provided data showed missing values of body fat percentages in participant 10.
Required Graphs and Tables
A table which will summarise all the values of various methods as well as the
diagnostic comments is required. A graph which will pictorially display differences in body
fat percentages by bio-impedance and body composition methods will be added. A pie chart
which will show percentages of ‘healthy’ people reported by each method will be added.
Summary of Results
Different methods were found to demonstrate different values. Body composition
method reported higher values of body fat percentage and more detailed analysis than bio-
impedance technique.
3BODY COMPOSITION PRACTICAL
Results and Discussion
Results
The results showed that body composition methods reported least number of
participants as ‘healthy’ or with ‘acceptable’ anthropometrics which may be due to their
detailed fat analysis. Differences in body percentages were observed between bio-impedance
and body composition possibly due to laboratory settings in the latter (Finch, 2017).
Hypothesis: Support or Refuted
The results support the hypothesis of differential results and higher accuracy by body
composition equipment.
Correlation
Correlation between accuracy and body composition analysis equipment was
supported with relevant literature.
Data Set Differences and Differences in Methods
There were differences in the data set since different analytical methods gave different
data since each method relies upon different working principles.
Limitations and their effect on Data
BMI and waist-to-hip ratios measure only weight as per height or fat distributions and
hence, lack of specifying fat percentage is a limitation resulting in different results. Hence,
participants noted to be ‘healthy’ were reported to possess ‘unacceptable’ fat percentages as
due to comprehensiveness of bio-impedance and body composition techniques (Achamrah et
al., 2018).
Similarities and Differences
BMI and waist-to-hip ratios produced different results since one measures weight
distribution and the other focusses on abdominal obesity. Bio-impedance and body
Results and Discussion
Results
The results showed that body composition methods reported least number of
participants as ‘healthy’ or with ‘acceptable’ anthropometrics which may be due to their
detailed fat analysis. Differences in body percentages were observed between bio-impedance
and body composition possibly due to laboratory settings in the latter (Finch, 2017).
Hypothesis: Support or Refuted
The results support the hypothesis of differential results and higher accuracy by body
composition equipment.
Correlation
Correlation between accuracy and body composition analysis equipment was
supported with relevant literature.
Data Set Differences and Differences in Methods
There were differences in the data set since different analytical methods gave different
data since each method relies upon different working principles.
Limitations and their effect on Data
BMI and waist-to-hip ratios measure only weight as per height or fat distributions and
hence, lack of specifying fat percentage is a limitation resulting in different results. Hence,
participants noted to be ‘healthy’ were reported to possess ‘unacceptable’ fat percentages as
due to comprehensiveness of bio-impedance and body composition techniques (Achamrah et
al., 2018).
Similarities and Differences
BMI and waist-to-hip ratios produced different results since one measures weight
distribution and the other focusses on abdominal obesity. Bio-impedance and body
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4BODY COMPOSITION PRACTICAL
composition techniques showed insignificant similarity in results possibly due to the latter
being conducted quality laboratory settings (Tewari et al., 2018).
Methodological Limitations and Alternative Methodologies
Differential working principles resulted data differences resulting in difficulty
compare. Additional body fat percentage assessments of underwater weighing and ‘Bodpod’
could be used due to their accuracies but were excluded due to financial constraints and time
constraints (Nyström et al., 2018).
Conclusion and Outcomes
Body composition techniques produces accurate body fat results followed by bio-
impedance since these measure fat and muscle mass. Multiple methods along with costs must
be considered for future assessments.
composition techniques showed insignificant similarity in results possibly due to the latter
being conducted quality laboratory settings (Tewari et al., 2018).
Methodological Limitations and Alternative Methodologies
Differential working principles resulted data differences resulting in difficulty
compare. Additional body fat percentage assessments of underwater weighing and ‘Bodpod’
could be used due to their accuracies but were excluded due to financial constraints and time
constraints (Nyström et al., 2018).
Conclusion and Outcomes
Body composition techniques produces accurate body fat results followed by bio-
impedance since these measure fat and muscle mass. Multiple methods along with costs must
be considered for future assessments.
5BODY COMPOSITION PRACTICAL
References
Achamrah, N., Colange, G., Delay, J., Rimbert, A., Folope, V., Petit, A., ... & Coëffier, M.
(2018). Comparison of body composition assessment by DXA and BIA according to
the body mass index: A retrospective study on 3655 measures. PloS one, 13(7),
e0200465. doi: https://doi.org/10.1371/journal.pone.0200465.
Finch, P. (2017). Intra-abdominal fat: Comparison of computed tomography fat segmentation
and bioimpedance spectroscopy. Malawi Medical Journal, 29(2), 155-159. doi:
http://dx.doi.org/10.4314/mmj.v29i2.15.
Franco-Villoria, M., Wright, C. M., McColl, J. H., Sherriff, A., Pearce, M. S., & Gateshead
Millennium Study core team. (2016). Assessment of adult body composition using
bioelectrical impedance: comparison of researcher calculated to machine outputted
values. BMJ open, 6(1), e008922. doi: http://dx.doi.org/10.1136/bmjopen-2015-
008922.
Lang, P. O., Trivalle, C., Vogel, T., Proust, J., & Papazian, J. P. (2015). Markers of metabolic
and cardiovascular health in adults: Comparative analysis of DEXA-based body
composition components and BMI categories. Journal of cardiology, 65(1), 42-49.
doi: https://doi.org/10.1016/j.jjcc.2014.03.010.
Makwana, N., & Makwana, A. (2015). Gender specificity in detecting obesity with
bioelectrical impedance analysis machine. Journal of Obesity and Metabolic
Research, 2(4), 206. doi: 10.4103/2347-9906.170908.
Nyström, C. D., Söderström, E., Henriksson, P., Henriksson, H., Poortvliet, E., & Löf, M.
(2018). The paediatric option for BodPod to assess body composition in preschool
References
Achamrah, N., Colange, G., Delay, J., Rimbert, A., Folope, V., Petit, A., ... & Coëffier, M.
(2018). Comparison of body composition assessment by DXA and BIA according to
the body mass index: A retrospective study on 3655 measures. PloS one, 13(7),
e0200465. doi: https://doi.org/10.1371/journal.pone.0200465.
Finch, P. (2017). Intra-abdominal fat: Comparison of computed tomography fat segmentation
and bioimpedance spectroscopy. Malawi Medical Journal, 29(2), 155-159. doi:
http://dx.doi.org/10.4314/mmj.v29i2.15.
Franco-Villoria, M., Wright, C. M., McColl, J. H., Sherriff, A., Pearce, M. S., & Gateshead
Millennium Study core team. (2016). Assessment of adult body composition using
bioelectrical impedance: comparison of researcher calculated to machine outputted
values. BMJ open, 6(1), e008922. doi: http://dx.doi.org/10.1136/bmjopen-2015-
008922.
Lang, P. O., Trivalle, C., Vogel, T., Proust, J., & Papazian, J. P. (2015). Markers of metabolic
and cardiovascular health in adults: Comparative analysis of DEXA-based body
composition components and BMI categories. Journal of cardiology, 65(1), 42-49.
doi: https://doi.org/10.1016/j.jjcc.2014.03.010.
Makwana, N., & Makwana, A. (2015). Gender specificity in detecting obesity with
bioelectrical impedance analysis machine. Journal of Obesity and Metabolic
Research, 2(4), 206. doi: 10.4103/2347-9906.170908.
Nyström, C. D., Söderström, E., Henriksson, P., Henriksson, H., Poortvliet, E., & Löf, M.
(2018). The paediatric option for BodPod to assess body composition in preschool
6BODY COMPOSITION PRACTICAL
children: what fat-free mass density values should be used?. British Journal of
Nutrition, 120(7), 797-802. https://doi.org/10.1017/S0007114518002064.
Pleuss, J. D., Talty, K., Morse, S., Kuiper, P., Scioletti, M., Heymsfield, S. B., & Thomas, D.
M. (2018). A machine learning approach relating 3D body scans to body composition
in humans. European journal of clinical nutrition. Retrieved from:
https://www.nature.com/articles/s41430-018-0337-1.
Tewari, N., Awad, S., Macdonald, I. A., & Lobo, D. N. (2018). A comparison of three
methods to assess body composition. Nutrition, 47, 1-5. doi:
https://doi.org/10.1016/j.nut.2017.09.005.
children: what fat-free mass density values should be used?. British Journal of
Nutrition, 120(7), 797-802. https://doi.org/10.1017/S0007114518002064.
Pleuss, J. D., Talty, K., Morse, S., Kuiper, P., Scioletti, M., Heymsfield, S. B., & Thomas, D.
M. (2018). A machine learning approach relating 3D body scans to body composition
in humans. European journal of clinical nutrition. Retrieved from:
https://www.nature.com/articles/s41430-018-0337-1.
Tewari, N., Awad, S., Macdonald, I. A., & Lobo, D. N. (2018). A comparison of three
methods to assess body composition. Nutrition, 47, 1-5. doi:
https://doi.org/10.1016/j.nut.2017.09.005.
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