Clinical Pharmacokinetics

, Volume 57, Issue 7, pp 781–795 | Cite as

A Review of the Methods and Associated Mathematical Models Used in the Measurement of Fat-Free Mass

  • Jaydeep Sinha
  • Stephen B. Duffull
  • Hesham S. Al-Sallami
Review Article


Fat-free mass (FFM) represents the lean component of the body devoid of fat. It has been shown to be a useful predictor of drug dose requirements, particularly in obesity where the excess fat mass does not contribute to drug clearance. However, measuring FFM involves complex and/or expensive experimental methodologies that preclude their use in routine clinical practice. Thus, models to predict FFM from readily measurable variables, such as body weight and height, have been developed and are used in both population pharmacokinetic modelling and clinical practice. In this review, methods used to measure FFM are explained and compared in terms of their assumptions, precision, and limitations. These methods are broadly classified into six different principles: densitometry, hydrometry, bioimpedance, whole-body counting, dual energy X-ray absorptiometry, and medical imaging. They vary in their processes and key biological assumptions that are often not applicable in certain populations (e.g. children, elderly, and certain disease states). This review provides a summary of the various methods of FFM measurement and estimation, and links these methods to a scientific framework to help clinicians and researchers understand the usefulness and potential limitations of these methods.


Compliance with Ethical Standards

Conflicts of interest

Jaydeep Sinha, Stephen B. Duffull, and Hesham S. Al-Sallami declare no conflicts of interest.

Ethics Approval

No ethical approval was required for this literature review.


This review required no specific funding. Jaydeep Sinha received a doctoral scholarship from the School of Pharmacy, University of Otago, New Zealand, during this work.

Supplementary material

40262_2017_622_MOESM1_ESM.docx (283 kb)
Supplementary material 1 (DOCX 284 kb)


  1. 1.
    Siri WE. Body composition from fluid spaces and density: analysis of methods. In: Josef Brozek AH, editor. Techniques for measuring body composition. Washington, DC: National Academy of Sciences-National Research Council; 1961. p. 223–44.Google Scholar
  2. 2.
    Snyder WS, Cook MJ, Karhausen LR, Nasset ES, Howells GP, Tipton IH. Report of the Task Group on Reference Man. The International Commission on Radiological Protection. Pergamon Press. 1974. Accessed 10 Aug 2017.
  3. 3.
    Morgan DJ, Bray KM. Lean body mass as a predictor of drug dosage. Clin Pharmacokinet. 1994;26(4):292–307.CrossRefPubMedGoogle Scholar
  4. 4.
    De Baerdemaeker LE, Mortier EP, Struys MM. Pharmacokinetics in obese patients. Contin Educ Anaesth Crit Care Pain. 2004;4(5):152–5.CrossRefGoogle Scholar
  5. 5.
    Green B, Duffull SB. What is the best size descriptor to use for pharmacokinetic studies in the obese? Br J Clin Pharmacol. 2004;58(2):119–33.CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Han P, Duffull S, Kirkpatrick C, Green B. Dosing in obesity: a simple solution to a big problem. Clin Pharmacol Ther. 2007;82(5):505–8.CrossRefPubMedGoogle Scholar
  7. 7.
    Eleveld DJ, Proost JH, Absalom AR, Struys MM. Obesity and allometric scaling of pharmacokinetics. Clin Pharmacokinet. 2011;50(11):751–3.CrossRefPubMedGoogle Scholar
  8. 8.
    Leykin Y, Miotto L, Pellis T. Pharmacokinetic considerations in the obese. Best Prac Res Clin Anaesthesiol. 2011;25(1):27–36.CrossRefGoogle Scholar
  9. 9.
    De Baerdemaeker LEC, Van Limmen JGM, Van Nieuwenhove Y. How should obesity be measured and how should anesthetic drug dosage be calculated?  In: Leykin Y, Brodsky JB, editors. Controversies in the anesthetic management of the obese surgical patient. Milan: Springer; 2013. pp. 15–30.CrossRefGoogle Scholar
  10. 10.
    Lukaski HC. Methods for the assessment of human body composition: traditional and new. Am J Clin Nutr. 1987;46(4):537–56.CrossRefPubMedGoogle Scholar
  11. 11.
    Heymsfield SB, Wang Z, Baumgartner RN, Ross R. Human body composition: advances in models and methods. Annu Rev Nutr. 1997;17(1):527–58.CrossRefPubMedGoogle Scholar
  12. 12.
    Mattsson S, Thomas BJ. Development of methods for body composition studies. Phys Med Biol. 2006;51(13):R203.CrossRefPubMedGoogle Scholar
  13. 13.
    Ellis KJ. Human body composition: in vivo methods. Physiol Rev. 2000;80(2):649–80.CrossRefPubMedGoogle Scholar
  14. 14.
    Lee SY, Gallagher D. Assessment methods in human body composition. Curr Opin Clin Nutr Metab Care. 2008;11(5):566.CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Wells J, Fewtrell M. Measuring body composition. Arch Dis Child. 2006;91(7):612–7.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Fidanza F, Keys A, Anderson JT. Density of body fat in man and other mammals. J Appl Physiol. 1953;6:252–6.CrossRefPubMedGoogle Scholar
  17. 17.
    Brožek J, Grande F, Anderson JT, Keys A. Densitometric analysis of body composition: revision of some quantitative assumptions. Ann N Y Acad Sci. 1963;110(1):113–40.PubMedCrossRefGoogle Scholar
  18. 18.
    Siri WE. The gross composition of the body. In: Lawrence JH, editor. Advances in biological and medical physics. New York: Academic Press; 1956. p. 239–80.Google Scholar
  19. 19.
    Going SB. Hydrodensitometry and air displacement plethysmography. In: Heymsfield SB, Lohman TG, Wang Z, Going SB, editors. Human body composition. 2nd ed. Champaign, IL: Human Kinetics; 2005. pp. 17–33.Google Scholar
  20. 20.
    COSMED. Air Displacement Plethysmography (ADP) Body Composition. Rome. 2011. Available at: Accessed 10 Aug 2017.
  21. 21.
    Dempster P, Aitkens S. A new air displacement method for the determination of human body composition. Med Sci Sports Exerc. 1995;27(12):1692–7.CrossRefPubMedGoogle Scholar
  22. 22.
    Ruppel GL. Manual of pulmonary function testing. 9th ed. St Louis: Mosby Elsevier; 2009.Google Scholar
  23. 23.
    Du Bois D, Du Bois E. A formula to estimate the approximate surface area if height and weight be known. 1916. Nutrition. 1989;5(5):303.PubMedGoogle Scholar
  24. 24.
    Jackson AS, Pollock ML. Generalized equations for predicting body density of men. Br J Nutr. 1978;40(03):497–504.CrossRefPubMedGoogle Scholar
  25. 25.
    Jackson AS, Pollock ML, Ward A. Generalized equations for predicting body density of women. Med Sci Sports Exerc. 1979;12(3):175–81.Google Scholar
  26. 26.
    Schoeller DA. Hydrometry. In: Heymsfield SB, Lohman TG, Wang Z, Going SB, editors. Human body composition. 2nd ed. Champaign, IL: Human kinetics; 2005. pp. 35–49.Google Scholar
  27. 27.
    Vaisman N, Pencharz PB, Koren G, Johnson JK. Comparison of oral and intravenous administration of sodium bromide for extracellular water measurements. Am J Clin Nutr. 1987;46(1):1–4.CrossRefPubMedGoogle Scholar
  28. 28.
    Bell E, Ziegler E, Forbes G. Corrected bromide space. Pediatr Res. 1984;18(4):392–3.CrossRefPubMedGoogle Scholar
  29. 29.
    Miller ME, Cosgriff J, Forbes GB. Bromide space determination using anion-exchange chromatography for measurement of bromide. Am J Clin Nutr. 1989;50(1):168–71.CrossRefPubMedGoogle Scholar
  30. 30.
    Brodie BB, Brand E, Leshin S. The use of bromide as a measure of extracellular fluid. J Biol Chem. 1939;130(2):555–63.Google Scholar
  31. 31.
    Kim J, Wang Z, Gallagher D, Kotler DP, Ma K, Heymsfield SB. Extracellular water: sodium bromide dilution estimates compared with other markers in patients with acquired immunodeficiency syndrome. J Parenter Enter Nutr. 1999;23(2):61–6.CrossRefGoogle Scholar
  32. 32.
    Moore FD, Lister J, Boyden CM, Ball MR, Sullivan N, Dagher FJ. The skeleton as a feature of body composition: values predicted by isotope dilution and observed by cadaver dissection in an adult human female. Hum Biol. 1968;40(2):135–88.PubMedGoogle Scholar
  33. 33.
    Barnes BA, Gordon EB, Cope O. Skeletal muscle analyses in health and in certain metabolic disorders. I. The method of analysis and the values in normal muscle. J Clin Investig. 1957;36(8):1239.CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Maffy R. The body fluids: volume, composition, and physical chemistry. In: Brenner BM, Rector FC, editors. The kidney. Philadelphia: WB Saunders; 1976. p. 65–103.Google Scholar
  35. 35.
    Kushner RF. Bioelectrical impedance analysis: a review of principles and applications. J Am Coll Nutr. 1992;11(2):199–209.PubMedGoogle Scholar
  36. 36.
    Aroom KR, Harting MT, Cox CS, Radharkrishnan RS, Smith C, Gill BS. Bioimpedance analysis: a guide to simple design and implementation. J Surg Res. 2009;153(1):23–30.CrossRefPubMedGoogle Scholar
  37. 37.
    Lukaski H, Bolonchuk W. Estimation of body fluid volumes using tetrapolar bioelectrical impedance measurements. Aviat Space Environ Med. 1988;59(12):1163–9.PubMedGoogle Scholar
  38. 38.
    Lukaski HC, Johnson PE, Bolonchuk W, Lykken G. Assessment of fat-free mass using bioelectrical impedance measurements of the human body. The American journal of clinical nutrition. 1985;41(4):810–7.CrossRefPubMedGoogle Scholar
  39. 39.
    Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gómez JM, et al. Bioelectrical impedance analysis—part I: review of principles and methods. Clin Nutr. 2004;23(5):1226–43.CrossRefPubMedGoogle Scholar
  40. 40.
    Wu C-S, Chen Y-Y, Chuang C-L, Chiang L-M, Dwyer GB, Hsu Y-L, et al. Predicting body composition using foot-to-foot bioelectrical impedance analysis in healthy Asian individuals. Nutr J. 2015;14(1):1.CrossRefGoogle Scholar
  41. 41.
    Janmahasatian S, Duffull SB, Ash S, Ward LC, Byrne NM, Green B. Quantification of lean bodyweight. Clin Pharmacokinet. 2005;44(10):1051–65.CrossRefPubMedGoogle Scholar
  42. 42.
    Ellis KJ. Whole-body counting and neutron activation analysis. In: Heymsfield SB, Lohman TG, Wang Z, Going SB, editors. Human Body Composition. 2nd ed. Champaign, IL: Human Kinetics; 2005. pp. 51–62.Google Scholar
  43. 43.
    Damilakis J, Adams JE, Guglielmi G, Link TM. Radiation exposure in X-ray-based imaging techniques used in osteoporosis. Eur Radiol. 2010;20(11):2707–14.CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    IAEA. Dual energy X ray absorptiometry for bone mineral density and body composition assessment. In: IAEA human health series. Vienna. 2010. Available at: Accessed 10 Aug 2017.
  45. 45.
    Pietrobelli A, Formica C, Wang Z, Heymsfield SB. Dual-energy X-ray absorptiometry body composition model: review of physical concepts. Am J Physiol Endocrinol Metab. 1996;271(6):E941–51.CrossRefGoogle Scholar
  46. 46.
    Lohman TG, Chen Z. Dual-energy X-ray absorptiometry. In: Heymsfield SB, Lohman TG, Wang Z, Going SB, editors. Human body composition. 2nd ed. Champaign, IL: Human Kinetics; 2005. pp 63–77.Google Scholar
  47. 47.
    Ross R, Janssen I. Computed tomography and magnetic resonance imaging. In: Heymsfield SB, Lohman TG, Wang Z, Going SB, editors. Human body composition. 2nd ed. Champaign, IL: Human kinetics; 2005. pp 89–108.Google Scholar
  48. 48.
    Kvist H, Chowdhury B, Grangård U, Tylen U, Sjöström L. Total and visceral adipose-tissue volumes derived from measurements with computed tomography in adult men and women: predictive equations. Am J Clin Nutr. 1988;48(6):1351–61.CrossRefPubMedGoogle Scholar
  49. 49.
    Kim CG, Kim WH, Kim MH, Kim D-W. Direct determination of lean body mass by CT in F-18 FDG PET/CT studies: comparison with estimates using predictive equations. Nucl Med Mol Imaging. 2013;47(2):98–103.CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Snijder M, Visser M, Dekker J, Seidell J, Fuerst T, Tylavsky F, 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. 2002;26(7):984.CrossRefGoogle Scholar
  51. 51.
    Hume R. Prediction of lean body mass from height and weight. J Clin Pathol. 1966;19(4):389–91.CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    James WPT, Waterlow JC. Research on obesity: a report of the DHSS/MRC Group. London: Her Majesty’s Stationery Office: UK Department of Health and Social Security/Medical Research Council Group on Obesity Research; 1976.Google Scholar
  53. 53.
    Boer P. Estimated lean body mass as an index for normalization of body fluid volumes in humans. Am J Physiol Renal Physiol. 1984;247(4):F632–6.CrossRefGoogle Scholar
  54. 54.
    Garrow JS, Webster J. Quetelet’s index (W/H2) as a measure of fatness. International journal of obesity. 1984;9(2):147–53.Google Scholar
  55. 55.
    Heitmann BL. Evaluation of body fat estimated from body mass index, skinfolds and impedance. A comparative study. Eur J Clin Nutr. 1990;44(11):831–7.PubMedGoogle Scholar
  56. 56.
    Deurenberg P, Weststrate JA, Seidell JC. Body mass index as a measure of body fatness: age-and sex-specific prediction formulas. Br J Nutr. 1991;65(02):105–14.CrossRefPubMedGoogle Scholar
  57. 57.
    Cheymol G. Effects of obesity on pharmacokinetics. Clin Pharmacokinet. 2000;39(3):215–31.CrossRefPubMedGoogle Scholar
  58. 58.
    Bucaloiu ID, Wood GC, Norfolk ER, Still CD, Hartle JE, Perkins RM. Fat-free weight prediction in morbidly obese females. Int J Nephrol Renovasc Dis. 2011;4:149.CrossRefPubMedPubMedCentralGoogle Scholar
  59. 59.
    Al-Sallami HS, Goulding A, Grant A, Taylor R, Holford N, Duffull SB. Prediction of fat-free mass in children. Clin Pharmacokinet. 2015;54(11):1169–78.CrossRefPubMedGoogle Scholar
  60. 60.
    La Colla L, Albertin A, La Colla G, Porta A, Aldegheri G, Di Candia D, et al. Predictive performance of the ‘Minto’ remifentanil pharmacokinetic parameter set in morbidly obese patients ensuing from a new method for calculating lean body mass. Clin Pharmacokinet. 2010;49(2):131–9.CrossRefPubMedGoogle Scholar
  61. 61.
    Lohman TG. Assessment of body composition in children. Pediatr Exerc Sci. 1989;1(1):19–30.CrossRefGoogle Scholar
  62. 62.
    Fomon SJ, Haschke F, Ziegler EE, Nelson SE. Body composition of reference children from birth to age 10 years. Am J Clin Nutr. 1982;35(5):1169–75.CrossRefPubMedGoogle Scholar
  63. 63.
    Werdein EJ, Kyle LH. Estimation of the constancy of density of the fat-free body. J Clin Investig. 1960;39(4):626.CrossRefPubMedPubMedCentralGoogle Scholar
  64. 64.
    Cohn S, Vartsky D, Yasumura S, Vaswani A, Ellis K. Indexes of body cell mass: nitrogen versus potassium. Am J Physiol Endocrinol Metab. 1983;244(3):E305–10.CrossRefGoogle Scholar
  65. 65.
    Cleroux J, Van Nguyen P, Taylor A, Leenen F. Effects of beta 1-vs. beta 1+ beta 2-blockade on exercise endurance and muscle metabolism in humans. J Appl Physiol. 1989;66(2):548–54.CrossRefPubMedGoogle Scholar
  66. 66.
    Sica DA. Antihypertensive therapy and its effects on potassium homeostasis. J Clin Hypertens. 2006;8(1):67–73.CrossRefGoogle Scholar
  67. 67.
    Collaboration NRF. Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19· 2 million participants. The Lancet. 2016;387(10026):1377–96.CrossRefGoogle Scholar
  68. 68.
    Wang YC, McPherson K, Marsh T, Gortmaker SL, Brown M. Health and economic burden of the projected obesity trends in the USA and the UK. The Lancet. 2011;378(9793):815–25.CrossRefGoogle Scholar
  69. 69.
    McLeay SC, Morrish GA, Kirkpatrick CM, Green B. The relationship between drug clearance and body size. Clin Pharmacokinet. 2012;51(5):319–30.CrossRefPubMedGoogle Scholar
  70. 70.
    Bhavnani SM, Rubino CM, Ambrose PG, Drusano GL. Daptomycin exposure and the probability of elevations in the creatine phosphokinase level: data from a randomized trial of patients with bacteremia and endocarditis. Clin Infect Dis. 2010;50(12):1568–74.CrossRefPubMedGoogle Scholar
  71. 71.
    Ingrande J, Brodsky JB, Lemmens HJ. Lean body weight scalar for the anesthetic induction dose of propofol in morbidly obese subjects. Anesth Analg. 2011;113(1):57–62.CrossRefPubMedGoogle Scholar
  72. 72.
    Cortinez LI, Anderson BJ, Holford NH, Puga V, de la Fuente N, Auad H, et al. Dexmedetomidine pharmacokinetics in the obese. Eur J Clin Pharmacol. 2015;71(12):1501–8.CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of PharmacyUniversity of OtagoDunedinNew Zealand

Personalised recommendations