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Combination of DXA and BIS body composition measurements is highly correlated with physical function—an approach to improve muscle mass assessment

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Abstract

Summary

Rationale: Fluid volume estimates may help predict functional status and thereby improve sarcopenia diagnosis. Main Result: Bioimpedance-derived fluid volume, combined with DXA, improves identification of jump power over traditional measures. Significance: DXA-measured lean mass should be corrected for fluid distribution in older populations; this may be a surrogate of muscle quality.

Purpose

Sarcopenia, the age-related loss of muscle mass and function, negatively impacts functional status, quality of life, and mortality. We aimed to determine if bioimpedance spectroscopy (BIS)-derived estimates of body water compartments can be used in conjunction with dual-energy X-ray absorptiometry (DXA) measures to aid in the prediction of functional status and thereby, ultimately, improve the diagnosis of sarcopenia.

Methods

Participants (≥ 70 years) had physical and muscle function tests, DXA, and BIS performed. Using a BMI correction method, intracellular water (ICWc), extracellular water (ECWc), and ECWc to ICWc (E/Ic) ratio was estimated from standard BIS measures. Jump power was assessed using jump mechanography.

Results

The traditional measure used to diagnose sarcopenia, DXA-derived appendicular lean mass (ALM) corrected for height (ALM/ht2), was the least predictive measure explaining jump power variability (r2 = 0.31, p < 0.0001). The best measure for explaining jump power was a novel variable combining DXA ALM and BIS-derived E/Ic ratio (ALM/(E/Ic); r2 = 0.70, p < 0.0001). ALM/(E/Ic) and ICWc had the highest correlation with jump power and grip strength, specifically jump power (r = 0.84 and r = 0.80, respectively; p < 0.0001).

Conclusions

The creation of a novel variable (ALM/(E/Ic)) improved the ability of DXA to predict jump power in an older population. ALM/(E/Ic) substantially outperformed traditional lean mass measures of sarcopenia and could well be an improved diagnostic approach to predict functional status. DXA-measured ALM should be corrected for fluid distribution, i.e., ALM/(E/Ic); this correction may be considered a surrogate of muscle quality.

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References

  1. Dawson-Hughes B, Bischoff-Ferrari H (2016) Considerations concerning the definition of sarcopenia. Osteoporos Int 27:3139–3144. https://doi.org/10.1007/s00198-016-3674-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Janssen I, Heymsfield SB, Ross R (2002) Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc 50:889–896. https://doi.org/10.1046/j.1532-5415.2002.50216.x

    Article  PubMed  Google Scholar 

  3. Perez-Zepeda MU, Sgaravatti A, Dent E (2017) Sarcopenia and post-hospital outcomes in older adults: a longitudinal study. Arch Gerontol Geriatr 69:105–109. https://doi.org/10.1016/j.archger.2016.10.013

    Article  PubMed  Google Scholar 

  4. Manrique-Espinoza B, Salinas-Rodríguez A, Rosas-Carrasco O, Gutiérrez-Robledo LM, Avila-Funes JA (2017) Sarcopenia is associated with physical and mental components of health-related quality of life in older adults. J Am Med Dir Assoc 18:636.e1–636.e5. https://doi.org/10.1016/j.jamda.2017.04.005

    Article  Google Scholar 

  5. Landi F, Liperoti R, Russo A, Giovannini S, Tosato M, Capoluongo E, Bernabei R, onder G (2012) Sarcopenia as a risk factor for falls in elderly individuals: results from the ilSIRENTE study. Clin Nutr 31:652–658. https://doi.org/10.1016/j.clnu.2012.02.007

    Article  PubMed  Google Scholar 

  6. World Health Organization (2015) World Report on Ageing and Health

  7. Trombetti A, Reid KF, Hars M, Herrmann FR, Pasha E, Phillips EM, Fielding RA (2016) Age-associated declines in muscle mass, strength, power, and physical performance: impact on fear of falling and quality of life. Osteoporos Int 27:463–471. https://doi.org/10.1007/s00198-015-3236-5.Age-associated

    Article  CAS  PubMed  Google Scholar 

  8. Lustgarten MS, Fielding RA (2011) Assessment of analytical methods used to measure changes in body composition in the elderly and recommendations for their use in phase II clinical trials. J Nutr Health Aging 15:368–375. https://doi.org/10.1007/s12603-011-0049-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Studenski SA, Peters KW, Alley DE, Cawthon PM, McLean RR, Harris TB, Ferrucci L, Guralnik JM, Fragala MS, Kenny AM, Kiel DP, Kritchevsky SB, Shardell MD, Dam TTL, Vassileva MT (2014) The FNIH sarcopenia project: rationale, study description, conference recommendations, and final estimates. Journals Gerontol - Ser A Biol Sci Med Sci 69(A):547–558. https://doi.org/10.1093/gerona/glu010

    Article  Google Scholar 

  10. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, Martin FC, Michel JP, Rolland Y, Schneider SM, Topinkova E, Vandewoude M, Zamboni M (2010) Sarcopenia: European consensus on definition and diagnosis. Age Ageing 39:412–423. https://doi.org/10.1093/ageing/afq034

    Article  PubMed  PubMed Central  Google Scholar 

  11. Fielding R, Vellas B, Evans W et al (2012) Sarcopenia:an undiagnosed condition in older adults. Consensus definition: prevalence, etiology, and consequences. J Am Med Dir Assoc 12:249–256. https://doi.org/10.1016/j.jamda.2011.01.003.Sarcopenia

    Article  Google Scholar 

  12. Krueger D, Siglinsky E, Buehring B, Binkley N (2017) Total body less head measurement is most appropriate for lean mass assessment in adults. J Clin Densitom 20:128–129. https://doi.org/10.1016/j.jocd.2016.08.068

    Article  PubMed  Google Scholar 

  13. Chamney PW, Wabel P, Moissl UM, et al (2007) A whole-body model to distinguish excess fluid from the hydration of major body tissues. Am J Clin Nutr 85:80–89 .

    Article  CAS  PubMed  Google Scholar 

  14. Yamada Y, Schoeller DA, Nakamura E, Morimoto T, Kimura M, Oda S (2010) Extracellular water may mask actual muscle atrophy during aging. Journals Gerontol - Ser A Biol Sci Med Sci 65 A:510–516. https://doi.org/10.1093/gerona/glq001

    Article  Google Scholar 

  15. Yamada Y, Buehring B, Krueger D, Anderson RM, Schoeller DA, Binkley N (2017) Electrical properties assessed by bioelectrical impedance spectroscopy as biomarkers of age-related loss of skeletal muscle quantity and quality. J Gerontol A Biol Sci Med Sci 72:1180–1186. https://doi.org/10.1093/gerona/glw225

    Article  PubMed  Google Scholar 

  16. Moissl UM, Wabel P, Chamney PW, Bosaeus I, Levin NW, Bosy-Westphal A, Korth O, Müller MJ, Ellegård L, Malmros V, Kaitwatcharachai C, Kuhlmann MK, Zhu F, Fuller NJ (2006) Body fluid volume determination via body composition spectroscopy in health and disease. Physiol Meas 27:921–933. https://doi.org/10.1088/0967-3334/27/9/012

    Article  PubMed  Google Scholar 

  17. Goodpaster BH, Park SW, Harris TB, Kritchevsky SB, Nevitt M, Schwartz AV, Simonsick EM, Tylavsky FA, Visser M, Newman AB, for the Health ABC Study (2006) The loss of skeletal muscle strength, mass, and quality in older adults: the health, aging and body composition study. J Gerontol Med Sci 61:1059–1064. https://doi.org/10.1093/gerona/61.10.1059

    Article  Google Scholar 

  18. Marcelli D, Usvyat LA, Kotanko P, Bayh I, Canaud B, Etter M, Gatti E, Grassmann A, Wang Y, Marelli C, Scatizzi L, Stopper A, van der Sande FM, Kooman J, on behalf of the MONitoring Dialysis Outcomes (MONDO) Consortium (2015) Body composition and survival in dialysis patients: results from an international cohort study. Clin J Am Soc Nephrol 10:1192–1200. https://doi.org/10.2215/CJN.08550814

    Article  PubMed  PubMed Central  Google Scholar 

  19. Chamney PW, Krämer M, Rode C, Kleinekofort W, Wizemann V (2002) A new technique for establishing dry weight in hemodialysis patients via whole body bioimpedance. Kidney Int 61:2250–2258. https://doi.org/10.1046/j.1523-1755.2002.00377.x

    Article  PubMed  Google Scholar 

  20. Kuchnia A, Earthman C, Teigen L, Cole A, Mourtzakis M, Paris M, Looijaard W, Weijs P, Oudemans-van Straaten H, Beilman G, Day A, Leung R, Compher C, Dhaliwal R, Peterson S, Roosevelt H, Heyland DK (2016) Evaluation of bioelectrical impedance analysis in critically ill patients: results of a multicenter prospective study [Epub ahead of print]. J Parenter Enter Nutr 41:1131–1138. https://doi.org/10.1177/0148607116651063

    Article  Google Scholar 

  21. Itobi E, Stroud M, Elia M (2006) Impact of oedema on recovery after major abdominal surgery and potential value of multifrequency bioimpedance measurements. Br J Surg 93:354–361. https://doi.org/10.1002/bjs.5259

    Article  CAS  PubMed  Google Scholar 

  22. Leong DP, Teo KK, Rangarajan S, Lopez-Jaramillo P, Avezum A Jr, Orlandini A, Seron P, Ahmed SH, Rosengren A, Kelishadi R, Rahman O, Swaminathan S, Iqbal R, Gupta R, Lear SA, Oguz A, Yusoff K, Zatonska K, Chifamba J, Igumbor E, Mohan V, Anjana RM, Gu H, Li W, Yusuf S (2015) Prognostic value of grip strength: findings from the prospective urban rural epidemiology (PURE) study. Lancet 386:266–273. https://doi.org/10.1016/S0140-6736(14)62000-6

    Article  PubMed  Google Scholar 

  23. Studenski S, Perera S, Patel K (2011) Gait speed and survival in older adults. Jama 305:50–58. https://doi.org/10.1001/jama.2010.1923.Gait

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Siglinsky E, Krueger D, Ward RE et al (2015) Effect of age and sex on jumping mechanography and other measures of muscle mass and function. J Musculoskelet Neuronal Interact 15:301–308

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Buehring B, Siglinsky E, Krueger D, Evans W, Hellerstein M, Yamada Y, Binkley N (2018) Comparison of muscle / lean mass measurement methods : correlation with functional and biochemical testing. Osteoporos Int 29:675–683

    Article  CAS  PubMed  Google Scholar 

  26. Menant JC, Weber F, Lo J, Sturnieks DL, Close JC, Sachdev PS, Brodaty H, Lord SR (2017) Strength measures are better than muscle mass measures in predicting health-related outcomes in older people: time to abandon the term sarcopenia? Osteoporos Int 28:59–70. https://doi.org/10.1007/s00198-016-3691-7

    Article  CAS  PubMed  Google Scholar 

  27. Metter EJ (2004) Arm-cranking muscle power and arm isometric muscle strength are independent predictors of all-cause mortality in men. J Appl Physiol 96:814–821. https://doi.org/10.1152/japplphysiol.00370.2003

    Article  PubMed  Google Scholar 

  28. Buehring B, Krueger D, Fidler E, Gangnon R, Heiderscheit B, Binkley N (2015) Reproducibility of jumping mechanography and traditional measures of physical and muscle function in older adults. Osteoporos Int 26:819–825. https://doi.org/10.1007/s00198-014-2983-z

    Article  CAS  PubMed  Google Scholar 

  29. Edwards MH, Buehring B (2015) Novel approaches to the diagnosis of sarcopenia. J Clin Densitom 18:472–477. https://doi.org/10.1016/j.jocd.2015.04.010

    Article  PubMed  Google Scholar 

  30. Kuchnia AJ, Teigen LM, Cole AJ, Mulasi U, Gonzalez MC, Heymsfield SB, Vock DM, Earthman CP (2016) Phase angle and impedance ratio: reference cut-points from the United States National Health and nutrition examination survey 1999–2004 from bioimpedance spectroscopy data [epub ahead of print]. J Parenter Enter Nutr 41:1310–1315. https://doi.org/10.1177/0148607116670378

    Article  Google Scholar 

  31. Wadsworth CT, Krishnan R, Sear M et al (1987) Interrater reliability of manual muscle testing and hand-held dynamometric muscle testing. Phys Ther 9:1342–1347

    Article  Google Scholar 

  32. Mathiowetz V, Weber K, Volland G, Kashman N (1984) Reliability and validity of grip and pinch strength evaluations. J Hand Surg Am 9:222–226. https://doi.org/10.1016/S0363-5023(84)80146-X

    Article  CAS  PubMed  Google Scholar 

  33. McGregor RA, Cameron-Smith D, Poppitt SD (2014) It is not just muscle mass: a review of muscle quality, composition and metabolism during ageing as determinants of muscle function and mobility in later life. Longev Heal 3:9. https://doi.org/10.1186/2046-2395-3-9

    Article  Google Scholar 

  34. Wang Z, St-Onge M-P, Lecumberri B, Pi-Sunyer FX, Heshka S, Wang J, Kotler DP, Gallagher D, Wielopolski L, Pierson RN Jr, Heymsfield SB (2004) Body cell mass: model development and validation at the cellular level of body composition. Am J Physiol Endocrinol Metab 286:E123–E128. https://doi.org/10.1152/ajpendo.00227.2003

    Article  CAS  PubMed  Google Scholar 

  35. Moore F, Olesen K, McMurrey J et al (1963) The body cell mass and its supporting environment, Philadelphia

  36. Wang Z, Deurenberg P, Wang W et al (1999) Hydration of fat-free body mass: new physiological modeling approach. Am J Phys 276:E995–E1003

    Article  CAS  Google Scholar 

  37. Taniguchi M, Yamada Y, Fukumoto Y, Sawano S, Minami S, Ikezoe T, Watanabe Y, Kimura M, Ichihashi N (2017) Increase in echo intensity and extracellular-to-intracellular water ratio is independently associated with muscle weakness in elderly women. Eur J Appl Physiol 117:1–7. https://doi.org/10.1007/s00421-017-3686-x

    Article  Google Scholar 

  38. Yamada Y, Yoshida T, Yokoyama K, Watanabe Y, Miyake M, Yamagata E, Yamada M, Kimura M, Kyoto-Kameoka Study (2016) The extracellular to intracellular water ratio in upper legs is negatively associated with skeletal muscle strength and gait speed in older people. J Gerontol - Ser A Biol Sci Med Sci 72:293–298. https://doi.org/10.1093/gerona/glw125

    Article  Google Scholar 

  39. Matias CN, Santos DA, Gonçalves EM, Fields DA, Sardinha LB, Silva AM (2013) Is bioelectrical impedance spectroscopy accurate in estimating total body water and its compartments in elite athletes? Ann Hum Biol 40:152–156. https://doi.org/10.3109/03014460.2012.750684

    Article  PubMed  Google Scholar 

  40. Matias CN, Júdice PB, Santos DA, Magalhães JP, Minderico CS, Fields DA, Sardinha LB, Silva AM (2016) Suitability of bioelectrical based methods to assess water compartments in recreational and elite athletes. J Am Coll Nutr 35:413–421. https://doi.org/10.1080/07315724.2015.1058198

    Article  CAS  PubMed  Google Scholar 

  41. Tuuri G, Keenan MJ, West KM et al (2005) Body water indices as markers of aging in male masters swimmers. J Sport Sci Med 4:406–414

    Google Scholar 

  42. Tengvall M, Ellegård L, Malmros V, Bosaeus N, Lissner L, Bosaeus I (2009) Body composition in the elderly: reference values and bioelectrical impedance spectroscopy to predict total body skeletal muscle mass. Clin Nutr 28:52–58. https://doi.org/10.1016/j.clnu.2008.10.005

    Article  PubMed  Google Scholar 

  43. Schoeller DA (2000) Bioelectrical impedance analysis. What does it measure? Ann N Y Acad Sci 904:159–162 . doi: 10.1111/j.1749-6632.2000.tb06441.x

    Article  Google Scholar 

  44. Kyle U, Genton L, Hans D (2001) Age-related differences in fat-free mass, skeletal muscle, body cell mass and fat mass between 18 and 94 years. Eur J 55:663–672

    CAS  Google Scholar 

  45. Silva AM (2005) Extracellular water: greater expansion with age in African Americans. J Appl Physiol 99:261–267. https://doi.org/10.1152/japplphysiol.01317.2004

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Nutritional Sciences, University of Wisconsin-Madison, Nutritional Sciences Building, 1415 Linden Drive Suite 266, Madison, WI, 53706, USA

    Adam J. Kuchnia & Dale Schoeller

  2. Section of Healthy Longevity Researches, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan

    Yosuke Yamada

  3. Department of Food Science and Nutrition, University of Minnesota-Twin Cities, Saint Paul, MN, USA

    Levi Teigen

  4. University of Wisconsin Osteoporosis Clinical Research Program, Madison, WI, USA

    Diane Krueger & Neil Binkley

  5. Biotechnology Center, University of Wisconsin-Madison, Madison, WI, USA

    Dale Schoeller

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  1. Adam J. Kuchnia
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Correspondence to Adam J. Kuchnia.

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Kuchnia, A.J., Yamada, Y., Teigen, L. et al. Combination of DXA and BIS body composition measurements is highly correlated with physical function—an approach to improve muscle mass assessment. Arch Osteoporos 13, 97 (2018). https://doi.org/10.1007/s11657-018-0508-7

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