Fanny Buckinx1, Francesco Landi2, Matteo Cesari3,4, Roger A Fieding5, Marjolein Visser6,7, Klaus Engelke8, Stefania Maggi9, Elaine Dennison10, Nasser M Al-Daghri11, Sophie Allepaerts12, Jurgen Bauer13, Ivan Bautmans14, Maria Luisa Brandi15, Olivier Bruyère1, Tommy Cederholm16, Francesca Cerreta16, Antonio Cherubini17, Cyrus Cooper10,18, Alphonso Cruz-Jentoft19, Eugene McCloskey20,21, Bess Dawson-Hughes22, Jean-Marc Kaufman23, Andrea Laslop24, Jean Petermans12, Jean-Yves Reginster1, René Rizzoli25, Sian Robinson10,26, Yves Rolland27, Ricardo Rueda28, Bruno Vellas27, John A Kanis29. 1. Department of Public Health, Epidemiology and Health Economics, University of Liège, Liège, Belgium. 2. Department of Geriatrics, Neurosciences and Orthopedics, Catholic University of the Sacred Heart Rome, Milan, Italy. 3. Gérontopôle, University Hospital of Toulouse, Toulouse, France. 4. INSERM UMR1027, University of Toulouse III Paul Sabatier, Toulouse, France. 5. Nutrition, Exercise Physiology and Sarcopenia Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA. 6. Department of Health Sciences, VU University Amsterdam, Amsterdam, Netherlands. 7. Department of Nutrition and Dietetics, Internal Medicine, VU University Medical Center, Amsterdam, Netherlands. 8. Institute of Medical Physics, University of Erlangen, Erlangen, Germany. 9. National Research Council, Neuroscience Institute, Aging Branch, Padova, Italy. 10. MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK. 11. Prince Mutaib Chair for Biomarkers of Osteoporosis, Biochemistry Department, College of Science, King Saud University, Riyadh, 11451, Saudi Arabia. 12. Department of Geriatrics, CHU-Liège, Liège, Belgium. 13. Department of Geriatric Medicine, Klinikum, Carl von Ossietzky University, Oldenburg, Germany. 14. Gerontology and Frailty in Ageing Research Department, Vrije Universiteit Brussel (VUB), Brussels, Belgium. 15. Department of Surgery and Translational Medicine, University of Florence, viale Pieraccini 6, Florence, 59139, Italy. 16. Human Medicines Research and Development Support Division, Scientific Advice, London, UK. 17. Geriatrics and Geriatric Emergency Care, IRCCS-INRCA, Ancona, Italy. 18. NIHR Musculoskeletal Biomedical Research Unit, University of Oxford, Oxford, UK. 19. Hospital Universitario Ramón y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (Irycis), Madrid, Spain. 20. Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, UK. 21. MRC and Arthritis Research UK Centre for Integrated Research in Musculoskeletal Ageing (CIMA), London, UK. 22. Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA. 23. Department of Endocrinology and Unit for Osteoporosis and Metabolic Bone Diseases, Ghent University Hospital, Ghent, Belgium. 24. Scientific Office, Austrian Agency for Health and Food Safety, Vienna, Austria. 25. Service of Bone Diseases, Department of Internal Medicine Specialties, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland. 26. National Institute for Health Research Southampton Biomedical Research Centre, University of Southampton and University Hospital, Southampton NHS Foundation Trust, Southampton, UK. 27. Gérontopôle de Toulouse, Institut du Vieillissement, Centre Hospitalo-Universitaire de Toulouse (CHU Toulouse); UMR INSERM 1027, University of Toulouse III, Toulouse, France. 28. Abbott Nutrition R&D, Granada, Spain. 29. Centre for Metabolic Bone Diseases, University of Sheffield, UK and Institute of Health and Ageing, Australian Catholic University, Melbourne, Australia.
We appreciate your interest in our recent publication1 and your valuable comments. We completely agree that there is still ambiguity in the literature on the definition and use of parameters characterizing body composition.2 From this perspective, DXA actually is a progress as the definition of lean and fat (according to DXA terminology) and based on differences of X‐ray mass absorption coefficients. With a two energy X‐ray system, two materials that differ in atomic number can be uniquely identified using a so‐called base material composition.3 Specific calibration equations of identification of dedicated anatomical entities consisting of either one of the materials is not required. As shown by Pietrobelli et al. 4 in terms of the so‐called R‐value that quantifies differences in the mass absorption coefficient for a given material at different X‐ray energies fatty acids and triglycerides the ingredients of can well be separated from non‐lipid body composition materials.From this perspective, lean and fat mass as measured by DXA are clearly defined, but do not necessarily agree with anatomical entities such as the amount of adipose tissue. As fat is a term used in many different contexts, perhaps a different name should have been given to what is now known as DXA fat mass. We agree that DXA lean body mass is smaller than FFM.5 FFM is the mass of the body excluding the chemical fat. So essential lipids are also excluded. Lean body mass, interpreted the ‘DXA way’, is the soft lean tissue of the body, excluding the bone minerals and the chemical fat. However, lean body mass from a historical point of view, does include the bone, and very closely resembles FFM (but is not perfectly the same). What we would like to stress is that the concept of lean body mass (of FFM for that matter) is not very useful for muscle research. You would like to focus on the bone‐free and fat‐free mass of the arms and legs, as this measure most closely resembles the actual skeletal muscle tissue. Apparently, a standardization of terminology in the field of body composition is required.We agree with comments that lean mass and muscle mass are two different measurements but this was clearly outlined as a weakness of DXA in Table 1. However, as the commentators showed themselves, the correlation was high (r = 0.94),6 and lean was almost the sum of muscle, skin, and viscera. In the appendicular skeleton, there is no viscera, thus only the difference in the lean composition, i.e. the variation of relative amounts of water, protein, and glycogen remains.With regard to estimations of fat‐free mass and (appendicular) lean mass using bioelectrical impedance (BIA), we appreciate the confirmation that large prediction errors at the individual level may occur which hampers the use of BIA in clinical practice. We also showed that on a group level, discrepancies might occur between lean mass predicted by BIA and lean mass measured by DXA. We agree these discrepancies should not be interpreted as BIA not being valid to assess lean mass. We merely provided these examples to highlight the fact that estimates of lean mass from BIA clearly differ from those from DXA, thereby influencing the interpretation of findings (e.g. the prevalence of sarcopenia and the comparison of data obtained with different methods).Given the high degree of DXA standardization, excellent precision, the high correlation of DXA lean mass with muscle mass and muscle volume, currently DXA seems to be the best reference technique, in particular for appendicular muscle measurements. This does not imply that DXA will be the gold standard for the diagnosis of sarcopenia, which requires a functional component in addition to appendicular muscle mass assessments. It also calls for further efforts to develop anthropometric standards representing the wide range of body compositions encountered in the clinical routine in order to validate the accuracy of methods, such as DXA and BIA. At this stage, the scientific evidence derived from the published literature seems to support the conclusions of the original article.
Conflict of interest
The authors declare no conflict of interest. The authors certify that they comply with the ethical guidelines for publishing in the Journal of Cachexia, Sarcopenia and Muscle: update 2017.7
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