Combination of DXA and BIS body composition measurements is highly correlated with physical function—an approach to improve muscle mass assessment
- 132 Downloads
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.
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.
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.
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).
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.
KeywordsSarcopenia Bioimpedance spectroscopy Intracellular water Extracellular water Muscle quality Muscle function
Compliance with ethical standards
Conflicts of interest
- 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 CrossRefGoogle Scholar
- 6.World Health Organization (2015) World Report on Ageing and HealthGoogle Scholar
- 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 CrossRefPubMedGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 CrossRefGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 CrossRefGoogle 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 .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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 CrossRefGoogle 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 CrossRefPubMedPubMedCentralGoogle 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 CrossRefGoogle 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 CrossRefPubMedGoogle 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 CrossRefPubMedGoogle 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 CrossRefGoogle 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 CrossRefPubMedGoogle Scholar
- 35.Moore F, Olesen K, McMurrey J et al (1963) The body cell mass and its supporting environment, PhiladelphiaGoogle 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 CrossRefGoogle 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 CrossRefGoogle 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 CrossRefPubMedGoogle 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 4:406–414Google 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 CrossRefPubMedGoogle 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.xGoogle 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 55:663–672Google Scholar