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Body Composition

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Integrative and Functional Medical Nutrition Therapy

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Abstract

Anthropometric measurements, such as body size, weight, and proportions, are often used to evaluate and monitor the effects of nutritional interventions as well as reflect an individual’s overall growth and development. Body composition is the proportion of fat, muscle, bone, and water that make up the human body and its measurement helps determine excesses or deficiencies of a component that is related to health risk. In the fitness and sports setting, body fatness is an indicator of physical fitness and may be assessed by personal trainers and athletic coaches since fat content can affect sports performance. Nutrition practitioners often assess body composition since certain proportions are associated with a variety of health problems. Obesity and the newer identification of sarcopenic obesity of increased body fat percentage and loss of muscle, independent of BMI, has been associated with a number of diseases such as type 2 diabetes, hypertension, heart disease, arthritis, autoimmunity, liver disease, cancer, and kidney disease.

At the other end of the spectrum, too little body fat is often seen in those with eating disorders, oligomenorrhea, exercise addiction, and certain diseases such as cystic fibrosis, Crohn’s disease, and cancer. Since physiological dysfunction can occur with too much or too little body fat, sarcopenic obesity and its distribution in the body, assessment and monitoring of body composition has become widespread and important for health practitioners.

Current methods for body composition assessment are characterized from simple to complex and all have some degree of measurement error. Some inherent problems with assessment techniques occur with the methodology, interpretation of data, and assumptions made with certain methods. The choice often depends on the intended purpose, cost, and available technology.

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References

  1. Benton M, Whyte MD, Dyal BW. Sarcopenic obesity: strategies for management. AJN. 2011;111(12):38–44.

    Article  Google Scholar 

  2. Norgan NG. Laboratory and field measurements of body composition. Public Health Nutr. 2005;8(7A):1108–22.

    Article  CAS  Google Scholar 

  3. Briot K, Legrand E, Pouchain D, Monnier S, Roux C. Accuracy of patient-reported height loss and risk factors for height loss among postmenopausal women. CMAJ. 2010;182(6):558–62.

    Article  Google Scholar 

  4. Mikula AL, Hetzel SJ, Binkley N, Anderson PA. Validity of height loss as a predictor for prevalent vertebral fractures, low bone mineral density, and vitamin D deficiency. Osteoporosis Int: a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2017;28:1659.

    Article  CAS  Google Scholar 

  5. Yorkin M, Spaccarotella K, Martin-Biggers J, Quick V, Byrd-Bredbenner C. Accuracy and consistency of weights provided by home bathroom scales. BMC Public Health. 2013;13:1194.

    Google Scholar 

  6. Witt KA, Bush EA. College athletes with an elevated body mass index often have a high upper arm muscle area, but not elevated triceps and subscapular skinfolds. J Am Diet Assoc. 2005;105(4):599–602.

    Article  Google Scholar 

  7. Nevill AM, Winter EM, Ingham S, Watts A, Metsios GS, Stewart AD. Adjusting athletes’ body mass index to better reflect adiposity in epidemiological research. J Sports Sci. 2010;28(9):1009–16.

    Article  Google Scholar 

  8. Kesavachandran CN, Bihari V, Mathur N. The normal range of body mass index with high body fat percentage among male residents of Lucknow city in north India. Indian J Med Res. 2012;135:72–7.

    Article  Google Scholar 

  9. World Health Organization Global Database on Body Mass Index.

    Google Scholar 

  10. Park J, Lee ES, Lee DY, Kim J, Park SE, Park CY, et al. Waist circumference as a marker of obesity is more predictive of coronary artery calcification than body mass index in apparently healthy Korean adults: the Kangbuk Samsung Health Study. Endocrinol Metab (Seoul). 2016;31(4):559–66.

    Article  CAS  Google Scholar 

  11. Seo DC, Choe S, Torabi MR. Is waist circumference >/=102/88cm better than body mass index >/=30 to predict hypertension and diabetes development regardless of gender, age group, and race/ethnicity? Meta-analysis. Prev Med. 2017;97:100–8.

    Article  Google Scholar 

  12. Borugian MJ, Sheps SB, Kim-Sing C, Olivotto IA, Van Patten C, Dunn BP, et al. Waist-to-hip ratio and breast cancer mortality. Am J Epidemiol. 2003;158(10):963–8.

    Article  Google Scholar 

  13. Ringhofer C, Lenglinger J, Riegler M, Kristo I, Kainz A, Schoppmann S. Waist to hip ratio is a better predictor of esophageal acid exposure than body mass index. Neurogastroenterol Motil. 2017;29(7).

    Google Scholar 

  14. Pimenta NM, Santa-Clara H, Melo X, Cortez-Pinto H, Silva-Nunes J, Sardinha LB. Waist-to-hip ratio is related to body fat content and distribution regardless of the waist circumference measurement protocol in nonalcoholic fatty liver disease patients. Int J Sport Nutr Exerc Metab. 2016;26(4):307–14.

    Article  Google Scholar 

  15. Ashwell M, Gibson S. Waist-to-height ratio as an indicator of ‘early health risk’: simpler and more predictive than using a ‘matrix’ based on BMI and waist circumference. BMJ Open. 2016;6(3):e010159.

    Article  Google Scholar 

  16. Ashwell M, Mayhew L, Richardson J, Rickayzen B. Waist-to-height ratio is more predictive of years of life lost than body mass index. PLoS One. 2014;9(9):e103483.

    Article  Google Scholar 

  17. Jaswant S, Nitish M. Use of upper-arm anthropometry as measure of body-composition and nutritional assessment in children and adolescents (6-20 years) of Assam, Northeast India. Ethiop J Health Sci. 2014;24(3):243–52.

    Article  Google Scholar 

  18. Friedl KE, Westphal KA, Marchitelli LJ, Patton JF, Chumlea WC, Guo SS. Evaluation of anthropometric equations to assess body-composition changes in young women. Am J Clin Nutr. 2001;73(2):268–75.

    Article  CAS  Google Scholar 

  19. Varghese DS, Sreedhar S, Balakrishna N, Venkata Ramana Y. Evaluation of the relative accuracy of anthropometric indicators to assess body fatness as measured by air displacement plethysmography in Indian women. Am J Hum Biol. 2016;28(5):743–5.

    Article  Google Scholar 

  20. Biggs J, Cha K, Horch K. Electrical resistivity of the upper arm and leg yields good estimates of whole body fat. Physiol Meas. 2001;22(2):365–76.

    Article  CAS  Google Scholar 

  21. Martin AD, Ross WD, Drinkwater DT, Clarys JP. Prediction of body fat by skinfold caliper: assumptions and cadaver evidence. Int J Obes. 1985;9(Suppl 1):31–9.

    PubMed  Google Scholar 

  22. Khalil SF, Mohktar MS, Ibrahim F. The theory and fundamentals of bioimpedance analysis in clinical status monitoring and diagnosis of diseases. Sensors (Basel). 2014;14(6):10895–928.

    Article  Google Scholar 

  23. Earthman C, Traughber D, Dobratz J, Howell W. Bioimpedance spectroscopy for clinical assessment of fluid distribution and body cell mass. Nutr Clin Pract. 2007;22(4):389–405.

    Article  Google Scholar 

  24. Ackland TR, Lohman TG, Sundgot-Borgen J, Maughan RJ, Meyer NL, Stewart AD, et al. Current status of body composition assessment in sport: review and position statement on behalf of the ad hoc research working group on body composition health and performance, under the auspices of the I. OC Med Comm Sports Med. 2012;42(3):227–49.

    Article  Google Scholar 

  25. Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gomez JM, Heitmann BL, Kent-Smith L, Melchior JC, Pirlich M, Scharfetter H, Schols AM, Pichard C. Bioelectrical impedance analysis – part I: review of principles and methods. Clin Nutr. 2004;23:1226–43.

    Google Scholar 

  26. Blausen.com staff (2014). Medical gallery of blausen medical 2014. Wikijournal Med 1 (2). Doi:https://doi.org/10.15347/wjm/2014.010. Issn 2002-4436. https://commons.wikimedia.org/w/index.php?curid=31574254.

  27. Saladino CF. The efficacy of Bioelectrical Impedance Analysis (BIA) in monitoring body composition changes during treatment of restrictive eating disorder patients. J Eat Disord. 2014;2(1):34.

    Article  Google Scholar 

  28. Mager JR, Sibley SD, Beckman TR, Kellogg TA, Earthman CP. Multifrequency bioelectrical impedance analysis and bioimpedance spectroscopy for monitoring fluid and body cell mass changes after gastric bypass surgery. Clin Nutr. 2008;27(6):832–41.

    Article  Google Scholar 

  29. Mulasi U, Kuchnia AJ, Cole AJ, Earthman CP. Bioimpedance at the bedside: current applications, limitations, and opportunities. Body Comp/Phys Asses. 2015;30(2):180–93.

    Google Scholar 

  30. da Silva KT, Berbigier MC, de Almeida Rubin B, Moraes RB, Souza GC, Perry IDS. Phase angle as a prognostic marker in patients with critical illness. Nutr Clin Pract. 2015;30(2):261–5. Body Composition/Physical Assessment.

    Article  Google Scholar 

  31. Ripka WL, Ulbricht L, Menghin L, Gewehr PM. Portable A-mode ultrasound for body composition assessment in adolescents. J Ultrasound Med. 2016;35(4):755–60.

    Article  Google Scholar 

  32. Moissl UM, Wabel P, Chamney PW, Bosaeus I, Levin NW, Bosy-Westphal A, Korth O, Muller MJ, Ellegard L, Malmros V. Body fluid volume determination via body composition spectroscopy in health and disease. Physiol Measure. 2008;27(9):921.

    Article  Google Scholar 

  33. Fujii T, Phillips B. Quick review: the metabolic cart. Int J Int Med. 2002;3(2):1–4.

    Google Scholar 

  34. Clark RR, Kuta JM, Sullivan JC. Prediction of percent body fat in adult males using dual energy X-ray absorptiometry, skinfolds, and hydrostatic weighing. Med Sci Sports Exerc. 1993;25(4):528–35.

    CAS  PubMed  Google Scholar 

  35. Gibson AL, Roper JL, Mermier CM. Intraindividual variability in test-retest air displacement plethysmography measurements of body density for men and women. Int J Sport Nutr Exerc Metab. 2016;26(5):404–12.

    Article  Google Scholar 

  36. Gibby JT, Njeru DK, Cvetko ST, Heiny EL, Creer AR, Gibby WA. Whole-body computed tomography-based body mass and body fat quantification: a comparison to hydrostatic weighing and air displacement plethysmography. J Comput Assist Tomogr. 2016;41(2):302–8.

    Google Scholar 

  37. Fields DA, Gunatilake R, Kalaitzoglou E. Air displacement plethysmography: cradle to grave. Nutr Clin Pract. 2015;30(2):219–26.

    Article  Google Scholar 

  38. Messina C, Monaco CG, Ulivieri FM, Sardanelli F, Sconfienza LM. Dual-energy X-ray absorptiometry body composition in patients with secondary osteoporosis. Eur J Radiol. 2016;85(8):1493–8.

    Article  Google Scholar 

  39. Lee SY, Gallagher D. Assessment methods in human body composition. Curr Opin Clin Nutr Metab Care. 2008;11(5):566–72.

    Article  Google Scholar 

  40. Prior BM, Cureton KJ, Modlesky CM, Evans EM, Sloniger MA, Saunders M, et al. In vivo validation of whole body composition estimates from dual-energy X-ray absorptiometry. J Appl Physiol (1985). 1997;83(2):623–30.

    Article  CAS  Google Scholar 

  41. Lowry DW, Tomiyama AJ. Air displacement plethysmography versus dual-energy x-ray absorptiometry in underweight, normal-weight, and overweight/obese individuals. PLoS One. 2015;10(1):1–8.

    Google Scholar 

  42. Rossner S, Bo WJ, Hiltbrandt E, Hinson W, Karstaedt N, Santago P, et al. Adipose tissue determinations in cadavers--a comparison between cross-sectional planimetry and computed tomography. Int J Obes. 1990;14(10):893–902.

    CAS  PubMed  Google Scholar 

  43. Schoenfeld BJ, Aragon AA, Moon J, Krieger JW, Tiryaki-Sonmez G. Comparison of amplitude-mode ultrasound versus air displacement plethysmography for assessing body composition changes following participation in a structured weight-loss programme in women. Clin Physiol Funct Imaging. 2017;37(6):663–68.

    Google Scholar 

  44. Smith-Ryan AE, Fultz SN, Melvin MN, Wingfield HL, Woessner MN. Reproducibility and validity of A-mode ultrasound for body composition measurement and classification in overweight and obese men and women. PLoS One. 2014;9(3):1–8.

    Google Scholar 

  45. Monteiro PA, Antunes Bde M, Silveira LS, Christofaro DG, Fernandes RA, Freitas Junior IF. Body composition variables as predictors of NAFLD by ultrasound in obese children and adolescents. BMC Pediatr. 2014;14:25.

    Article  Google Scholar 

  46. Muller W, Horn M, Furhapter-Rieger A, Kainz P, Kropfl JM, Ackland TR, et al. Body composition in sport: interobserver reliability of a novel ultrasound measure of subcutaneous fat tissue. Br J Sports Med. 2013;47(16):1036–43.

    Article  Google Scholar 

  47. Wagner DR, Cain DL, Validity CNW. Reliability of A-mode ultrasound for body composition assessment of NCAA Division I Athletes. PLoS One. 2016;11(4):e0153146.

    Article  Google Scholar 

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Authors and Affiliations

  1. Sanoviv Medical Institute, Rosarito, BC, Mexico

    Sue Ward

  2. Noland Nutrition, Burbank, CA, USA

    Diana Noland

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  1. Sue Ward
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  2. Diana Noland
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Editors and Affiliations

  1. Noland Nutrition, Burbank, CA, USA

    Diana Noland

  2. Professor Emeritus, School of Medicine, University of Kansas Health System, Kansas City, KS, USA

    Jeanne A. Drisko

  3. Department of Dietetics & Nutrition, University of Kansas Medical Center, Kansas City, KS, USA

    Leigh Wagner

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Ward, S., Noland, D. (2020). Body Composition. In: Noland, D., Drisko, J., Wagner, L. (eds) Integrative and Functional Medical Nutrition Therapy. Humana, Cham. https://doi.org/10.1007/978-3-030-30730-1_21

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  • DOI: https://doi.org/10.1007/978-3-030-30730-1_21

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  • Publisher Name: Humana, Cham

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