Skip to main content

Body Composition Analysis

  • Chapter
  • First Online:
Bone Densitometry for Technologists

Abstract

Most full-size central DXA densitometers have software options to determine body composition from a total body bone density study. This application was first developed for dual photon absorptiometers, but the almost 1-h scan time made such measurements clinically impractical. In contrast, today’s DXA devices can perform total body scans in a matter of minutes. In spite of this dramatic improvement in speed, body composition assessment with DXA remains an underutilized application.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Notes

  1. 1.

     See Appendix H for conversion formulas.

  2. 2.

    This technique is also known as hydrostatic weighing or hydrodensitometry.

  3. 3.

    A perfect correlation would result in a correlation coefficient of 1.0.

  4. 4.

    See Chap. 7 for a discussion of the percent coefficient of variation and the number of subjects and studies needed for a valid precision study.

  5. 5.

    Chemical fat is actually a component of adipose tissue. Fat can be found in other tissues as well. Similarly, adipose tissue also contains protein, minerals, and water. The terms fat and adipose tissue are unfortunately often used interchangeably, even though they are not synonymous.

References

  1. Garrow JS, Webster J. Quetelet’s index (W/H2) as a measure of fatness. Int J Obes. 1985;9:147–53.

    PubMed  CAS  Google Scholar 

  2. World Health Organization. Physical status: the use and interpretation of anthropometry. Report of a WHO expert committee. 1–452. 1995. Geneva, World Health Organization. WHO Technical Report Series 854.

    Google Scholar 

  3. World Health Organization. Obesity: preventing and managing the global epidemic. Report of a WHO consultation on obesity. 1–158. 1998. Geneva, World Health Organization.

    Google Scholar 

  4. Wang J, Heymsfield SB, Aulet M, Thornton JC, Pierson RN. Body fat from body density: underwater weighing vs. dual photon absorptiometry. Am J Physiol. 1989;256:E829–34.

    PubMed  CAS  Google Scholar 

  5. Heymsfield SB, Wang J, Lichtman S, et al. Body composition in elderly subjects: a critical appraisal of clinical methodology. Am J Clin Nutr. 1989;50:1167–75.

    PubMed  CAS  Google Scholar 

  6. Siri WE. Body composition from fluid spaces and density: analysis of methods. University of California Radiation Laboratory Report 3349, 1956.

    Google Scholar 

  7. Durnin JVGA, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: measurements on 481 men and women aged from 16 to 72 years. Br J Nutr. 1974;32:77–97.

    Article  PubMed  CAS  Google Scholar 

  8. Jackson AS, Pollock ML. Generalized equations for predicting body density of men. Br J Nutr. 1978;40:497–504.

    Article  PubMed  CAS  Google Scholar 

  9. Jackson AS, Pollock ML, Ward A. Generalized equations for predicting body density of women. Med Sci Sports Exerc. 1980;12:175–82.

    PubMed  CAS  Google Scholar 

  10. McCrory MA, Gomez TD, Bernauer EM, Molé PA. Evaluation of a new air displacement plethysmograph for measuring human body composition. Med Sci Sports Exerc. 1995;27:1686–91.

    PubMed  CAS  Google Scholar 

  11. Fields DA, Goran MI, McCrory MA. Body-composition assessment via air-displacement plethysmography in adults and children: a review. Am J Clin Nutr. 2002;75:453–67.

    PubMed  CAS  Google Scholar 

  12. McLean KP, Skinner JS. Validity of Futrex-5000 for body composition determination. Med Sci Sports Exerc. 1992;24:253–8.

    PubMed  CAS  Google Scholar 

  13. Brodie DA, Eston RG. Body fat estimations by electrical impedance and infra-red interactance. Int J Sports Med. 1992;13:319–25.

    Article  PubMed  CAS  Google Scholar 

  14. Heyward VH, Cook KL, Hicks VL, et al. Predictive accuracy of three field methods for estimating relative body fatness of nonobese and obese women. Int J Sports Nutr. 1992;2:75–86.

    CAS  Google Scholar 

  15. Horber FF, Thomi F, Casez JP, Fonteille J, Jaeger P. Impact of hydration status on body composition as measured by dual energy X-ray absorptiometry in normal volunteers and patients on haemodialysis. Br J Radiol. 1992;65:895–900.

    Article  PubMed  CAS  Google Scholar 

  16. Pietrobelli A, Wang Z, Formica C, Heymsfield SB. Dual-energy X-ray absorptiometry: fat estimation errors due to variation in soft tissue hydration. Am J Physiol. 1998;274:E808–16.

    PubMed  CAS  Google Scholar 

  17. Dalsky GP, Kraemer W, Zetterlund AE, et al. A comparison of methods to assess body composition. Abstract. American College of Sports Medicine, Salt Lake City, UT, May 22–25, 1990.

    Google Scholar 

  18. Kiebzak GM, Leamy LJ, Person LM, Nord RH, Zhang ZY. Measurement precision of body composition variables using the Lunar DPX-L densitometer. J Clin Densitom. 2000;3:35–41.

    Article  PubMed  CAS  Google Scholar 

  19. Black E, Petersen L, Kreutzer M, et al. Fat mass measured by DXA varies with scan velocity. Obes Res. 2002;10:69–77.

    Article  PubMed  Google Scholar 

  20. Soriano JM, Ioannidou E, Wang J, et al. Pencil-beam vs fan-beam dual-energy X-ray absorptiometry comparisons across four systems: body composition and bone mineral. J Clin Densitom. 2004;7:281–9.

    Article  PubMed  Google Scholar 

  21. Tothill P, Avenell A, Love J, Reid DM. Comparisons between Hologic, Lunar, and Norland dual-energy X-ray absorptiometers and other techniques used for whole-body soft tissue measurements. Eur J Clin Nutr. 1994;48:781–94.

    PubMed  CAS  Google Scholar 

  22. Ellis KJ, Shypailo RJ. Bone mineral and body composition measurements: cross-calibration of pencil-beam and fan-beam dual-energy X-ray absorptiometers. J Bone Miner Res. 1998;13:1613–8.

    Article  PubMed  CAS  Google Scholar 

  23. Abrahamsen B, Gram J, Hansen TB, Beck-Nielsen H. Cross calibration of QDR 2000 and QDR 1000 dual energy X-ray densitometers for bone mineral and soft-tissue measurements. Bone. 1995;16:385–90.

    Article  PubMed  CAS  Google Scholar 

  24. Grundy SM. Metabolic syndrome scientific statement by the American Heart Association and the National Heart, Lung, and Blood Institute. Arterioscler Thromb Vasc Biol. 2005;25(11):2243–4.

    Article  PubMed  CAS  Google Scholar 

  25. Alberti KG, Zimmet P, Shaw J. The metabolic syndrome–a new worldwide definition. Lancet. 2005;366(9491):1059–62.

    Article  PubMed  Google Scholar 

  26. Pouliot MC, Despres JP, Lemieux S, et al. Waist circumference and abdominal sagittal diameter: best simple anthropometric indexes of abdominal visceral adipose tissue accumulation and related cardiovascular risk in men and women. Am J Cardiol. 1994;73:460–8.

    Article  PubMed  CAS  Google Scholar 

  27. Zamboni M, Turcato E, Armellini F, et al. Sagittal abdominal diameter as a practical predictor of visceral fat. Int J Obes Relat Metab Disord. 1998;22(7):655–60.

    Article  PubMed  CAS  Google Scholar 

  28. Clasey JL, Bouchard C, Teates CD, et al. The use of anthropometric and dual-energy X-ray absorptiometry (DXA) measures to estimate total abdominal and abdominal visceral fat in men and women. Obes Res. 1999;7(3):256–64.

    Article  PubMed  CAS  Google Scholar 

  29. Rankinen T, Kim SY, Perusse L, Despres JP, Bouchard C. The prediction of abdominal visceral fat level from body composition and anthropometry: ROC analysis. Int J Obes Relat Metab Disord. 1999;23(8):801–9.

    Article  PubMed  CAS  Google Scholar 

  30. Onat A, Avci GS, Barlan MM, Uyarel H, Uzunlar B, Sansoy V. Measures of abdominal obesity assessed for visceral adiposity and relation to coronary risk. Int J Obes Relat Metab Disord. 2004;28(8):1018–25.

    Article  PubMed  CAS  Google Scholar 

  31. Larsson B, Seidell J, Svardsudd K, et al. Obesity, adipose tissue distribution and health in men–the study of men born in 1913. Appetite. 1989;13(1):37–44.

    Article  PubMed  CAS  Google Scholar 

  32. Despres JP, Moorjani S, Lupien PJ, Tremblay A, Nadeau A, Bouchard C. Regional distribution of body fat, plasma lipoproteins, and cardiovascular disease. Arteriosclerosis. 1990;10(4):497–511.

    Article  PubMed  CAS  Google Scholar 

  33. Stevens J, Keil JE, Rust PF, Tyroler HA, Davis CE, Gazes PC. Body mass index and body girths as predictors of mortality in black and white women. Arch Intern Med. 1992;152(6):1257–62.

    Article  PubMed  CAS  Google Scholar 

  34. Stevens J, Keil JE, Rust PF, et al. Body mass index and body girths as predictors of mortality in black and white men. Am J Epidemiol. 1992;135(10):1137–46.

    PubMed  CAS  Google Scholar 

  35. Folsom AR, Kaye SA, Sellers TA, et al. Body fat distribution and 5-year risk of death in older women. JAMA. 1993;269(4):483–7.

    Article  PubMed  CAS  Google Scholar 

  36. Reeder BA, Senthilselvan A, Despres JP, et al. The association of cardiovascular disease risk factors with abdominal obesity in Canada. Canadian Heart Health Surveys Research Group. CMAJ. 1997;157 Suppl 1:S39–45.

    PubMed  Google Scholar 

  37. Snijder MB, van Dam RM, Visser M, Seidell JC. What aspects of body fat are particularly hazardous and how do we measure them? Int J Epidemiol. 2006;35(1):83–92.

    Article  PubMed  CAS  Google Scholar 

  38. Kelley DE, Thaete FL, Troost F, Huwe T, Goodpaster BH. Subdivisions of subcutaneous abdominal adipose tissue and insulin resistance. Am J Physiol Endocrinol Metab. 2000;278(5):E941–8.

    PubMed  CAS  Google Scholar 

  39. Monzon JR, Basile R, Heneghan S, Udupi V, Green A. Lipolysis in adipocytes isolated from deep and superficial subcutaneous adipose tissue. Obes Res. 2002;10(4):266–9.

    Article  PubMed  Google Scholar 

  40. Shen W, Wang Z, Punyanita M, et al. Adipose tissue quantification by imaging methods: a proposed classification. Obes Res. 2003;11(1):5–16.

    Article  PubMed  Google Scholar 

  41. Park YW, Heymsfield SB, Gallagher D. Are dual-energy X-ray absorptiometry regional estimates associated with visceral adipose tissue mass? Int J Obes Relat Metab Disord. 2002;26(7):978–83.

    Article  PubMed  Google Scholar 

  42. Snijder MB, Visser M, Dekker JM, et al. The prediction of visceral fat by dual-energy X-ray absorptiometry in the elderly: a comparison with computed tomography and anthropometry. Int J Obes Relat Metab Disord. 2002;26(7):984–93.

    Article  PubMed  CAS  Google Scholar 

  43. Glickman SG, Marn CS, Supiano MA, Dengel DR. Validity and reliability of dual-energy X-ray absorptiometry for the assessment of abdominal adiposity. J Appl Physiol. 2004;97(2):509–14.

    Article  PubMed  Google Scholar 

  44. Albanese CV, Diessel E, Genant HK. Clinical applications of body composition measurements using DXA. J Clin Densitom. 2003;6:75–85.

    Article  PubMed  Google Scholar 

  45. Paradisi G, Smith L, Burtner C, et al. Dual energy X-ray absorptiometry assessment of fat mass distribution and its association with the insulin resistance syndrome. Diabetes Care. 1999;22(8):1310–7.

    Article  PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media New York

About this chapter

Cite this chapter

Bonnick, S.L., Lewis, L.A. (2013). Body Composition Analysis. In: Bone Densitometry for Technologists. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3625-6_14

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-3625-6_14

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-3624-9

  • Online ISBN: 978-1-4614-3625-6

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics