Advertisement

DXA-Rectified Appendicular Lean Mass: Development of Ultrasound Prediction Models in Older Adults

  • Takashi Abe
  • R. S. Thiebaud
  • J. P. Loenneke
  • E. Fujita
  • T. Akamine
Article

Abstract

Objective

Dual-energy X-ray absorptiometry (DXA)-derived appendicular lean soft tissue mass (aLM) is used to diagnose sarcopenia. However, DXA-derived aLM includes non-skeletal muscle components, such as fat-free component of adipose tissue fat cell. These components, if not accounted for, could falsely inflate the aLM in individuals with a high amount of adipose tissue mass. B-mode ultrasound accurately measures muscle size in older adults. We sought to develop regression-based prediction equations for estimating DXA-rectified appendicular lean tissue mass (i.e. DXA-derived aLM minus appendicular fat-free adipose tissue (aFFAT); abbreviated as aLM minus aFFAT) using B-mode ultrasound.

Design

Cross-sectional study.

Measurements

Three hundred and eighty-nine Japanese older adults (aged 60 to 79 years) volunteered in the study. aLM was measured using a DXA, and muscle thickness (MT) was measured using ultrasound at nine sites. An ordinary least-squares multiple linear regression model was used to predict aLM minus aFFAT from sex, age and varying muscle thicknesses multiplied by height. Based on previous studies, we chose to use 4 MT sites at the upper and lower extremities (4-site MT model) and a single site (1-site MT model) at the upper extremity to develop prediction models.

Results

The linear prediction models (4 site MT model; R2 = 0.902, adjusted R2 = 0.899, and 1-site MT model; R2 = 0.868, adjusted R2 = 0.866) were found to be stable and accurate for estimating aLM minus aFFAT. Bootstrapping (n=1000) resulted in optimism values of 0.0062 (4-site MT model) and 0.0036 (1-site MT model).

Conclusion

The results indicated that ultrasound MT combined with height, age and sex can be used to accurately estimate aLM minus aFFAT in older Japanese adults. Newly developed ultrasound prediction equations to estimate aLM minus aFFAT may be a valuable tool in population-based studies to assess age-related rectified lean tissue mass loss.

Key words

Aging sarcopenia skeletal muscle ultrasonography 

References

  1. 1.
    Carmeli E. Frailty and Primary Sarcopenia: A Review. Adv Exp Med Biol 2017;1020:53–58CrossRefPubMedGoogle Scholar
  2. 2.
    Rizzoli R, Reginster JY, Arnal JF et al. Quality of life in sarcopenia and frailty. Calcif Tissue Int 2013;93:101–120CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Hairi NN, Cumming RG, Naganathan V et al. Loss of muscle strength, mass (sarcopenia), and quality (specific force) and its relationship with functional limitation and physical disability: the Concord Health and Ageing in Men Project. J Am Geriatr Soc 2010;58: 2055–2062CrossRefPubMedGoogle Scholar
  4. 4.
    Lauretani F, Russo CR, Bandinelli S et al. Age-associated changes in skeletal muscles and their effect on mobility: an operational diagnosis of sarcopenia. J Appl Physiol 2003;95: 1851–1860CrossRefPubMedGoogle Scholar
  5. 5.
    McLean RR, Shardell MD, Alley DE et al. Criteria for clinically relevant weakness and low lean mass and their longitudinal association with incident mobility impairment and mortality: The Foundation for the National Institutes of Health (FNIH) Sarcopenia Project. J Gerontol A Biol Sci Med Sci 2014;69: 576–583CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Landi F, Liperoti R, Russo A et al. Sarcopenia as a risk factor for falls in elderly individuals: results from the ilSIRENTE study. Clin Nutr 2012;31: 652–658CrossRefPubMedGoogle Scholar
  7. 7.
    Vetrano DL, Landi F, Volpato S et al. Association of sarcopenia with short-and longterm mortality in older adults admitted to acute care wards: results from the CRIME study. J Gerontol A Biol Sci Med Sci 2014;69: 1154–1161CrossRefPubMedGoogle Scholar
  8. 8.
    Srikanthan P, Karlamangla AS. Muscle mass index as a predictor of longevity in older adults. Am J Med 2014;127: 547–553CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Cawthon PM, Fox KM, Gandra SR et al. Do muscle mass, muscle density, strength, and physical function similarly influence risk of hospitalization in older adults? J Am Geriatr Soc 2009;57: 1411–1419CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Janssen I, Shepard DS, Katzmarzyk PT, Roubenoff R. The healthcare costs of sarcopenia in the United States. J Am Geriatr Soc 2004;52: 80–85CrossRefPubMedGoogle Scholar
  11. 11.
    Guglielmi G, Ponti F, Agostini M, Amadori M, Battista G, Bazzocchi A. The role of DXA in sarcopenia. Aging Clin Exp Res 2016;28: 1047–1060CrossRefPubMedGoogle Scholar
  12. 12.
    Cruz-Jentoft AJ, Baeyens JP, Bauer JM et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010;39: 412–423CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Heymsfield SB, Gallagher D, Kotler DP, Wang Z, Allison DB, Heshka S. Bodysize dependence of resting energy expenditure can be attributed to nonenergetic homogeneity of fat-free mass. Am J Physiol Endocrinol Metab 2002;282: E132–138CrossRefPubMedGoogle Scholar
  14. 14.
    Abe T, Patterson KM, Stover CD, Young KC. Influence of adipose tissue mass on DXA-derived lean soft tissue mass in middle-aged and older women. Age (Dordr) 2015;37: 9741Google Scholar
  15. 15.
    Loenneke JP, Loprinzi PD, Abe T. The prevalence of sarcopenia before and after correction for DXA-derived fat-free adipose tissue. Eur J Clin Nutr 2016;70: 1458–1460CrossRefPubMedGoogle Scholar
  16. 16.
    Boutin RD, Yao L, Canter RJ, Lenchik L. Sarcopenia: Current concepts and imaging implications. AJR Am J Roentgenol 2015;205: W255–266CrossRefPubMedGoogle Scholar
  17. 17.
    Nijholt W, Scafoglieri A, Jager-Wittenaar H, Hobbelen JS, van der Schans CP. The reliability and validity of ultrasound to quantify muscles in older adults: a systematic review. J Cachexia Sarcopenia Muscle 2017;8: 702–712CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Abe T, Loenneke JP, Thiebaud RS. The use of ultrasound for the estimation of muscle mass: One site fits most? J Cachexia Sarcopenia Muscle 2018;9: 213–214CrossRefPubMedGoogle Scholar
  19. 19.
    Sanada K, Kearns CF, Midorikawa T, Abe T. Prediction and validation of total and regional skeletal muscle mass by ultrasound in Japanese adults. Eur J Appl Physiol 2006;96: 24–31CrossRefPubMedGoogle Scholar
  20. 20.
    Abe T, Thiebaud RS, Loenneke JP, Young KC. Prediction and validation of DXAderived appendicular lean soft tissue mass by ultrasound in older adults. Age (Dordr) 2015;37: 114CrossRefPubMedCentralGoogle Scholar
  21. 21.
    Abe T, Fujita E, Thiebaud RS, Loenneke JP, Akamine T. Ultrasound-derived muscle thickness is a powerful predictor for estimating DXA-derived appendicular lean mass in Japanese older adults. Ultrasound Med Biol 2016;42: 2341–2344CrossRefPubMedGoogle Scholar
  22. 22.
    Abe T, Kondo M, Kawakami Y, Fukunaga T. Prediction equations for body composition of Japanese adults by B-mode ultrasound. Am J Hum Biol 1994;6: 161–70CrossRefPubMedGoogle Scholar
  23. 23.
    Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and SEM. J Strength Cond Res 2005;19: 231–240PubMedGoogle Scholar
  24. 24.
    Abe T, Counts BR, Barnett BE, Dankel SJ, Lee K, Loenneke JP. Associations between handgrip strength and ultrasound-measured muscle thickness of the hand and forearm in young men and women. Ultrasound Med Biol 2015;41: 2125–2130CrossRefPubMedGoogle Scholar
  25. 25.
    Abe T, Loenneke JP, Thiebaud RS, Fukunaga T. Age-related site-specific muscle wasting of upper and lower extremities and trunk in Japanese men and women. Age (Dordr) 2014;36: 813–821CrossRefGoogle Scholar
  26. 26.
    Abe T, Patterson KM, Stover CD et al. Site-specific thigh muscle loss as an independent phenomenon for age-related muscle loss in middle-aged and older men and women. Age (Dordr) 2014;36: 9634CrossRefGoogle Scholar
  27. 27.
    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/2017.
  28. 28.
    Chen LK, Liu LK, Woo J et al. Sarcopenia in Asia: Consensus Report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc 2014;15: 95–101CrossRefPubMedGoogle Scholar
  29. 29.
    Chen Z, Wang ZM, Lohman T et al. Dual-energy X-ray absorptiometry is a valid tool for assessing skeletal muscle mass in older women. J Nutr 2007;137: 2775–2780CrossRefPubMedGoogle Scholar
  30. 30.
    Levine JA, Abboud L, Barry M, Reed JE, Sheedy PF, Jensen MD. Measuring leg muscle and fat mass in humans: comparison of CT and dual-energy X-ray absorptiometry. J Appl Physiol 2000;88: 452–456CrossRefPubMedGoogle Scholar

Copyright information

© Serdi and Springer-Verlag France SAS, part of Springer Nature 2018

Authors and Affiliations

  • Takashi Abe
    • 1
    • 4
  • R. S. Thiebaud
    • 2
  • J. P. Loenneke
    • 1
  • E. Fujita
    • 3
  • T. Akamine
    • 3
  1. 1.Department of Health, Exercise Science, & Recreation ManagementThe University of MississippiUniversityUSA
  2. 2.Department of KinesiologyTexas Wesleyan UniversityFort WorthUSA
  3. 3.Department of Sports and Life SciencesNational Institute of Fitness and Sports in KanoyaKagoshimaJapan
  4. 4.UniversityUSA

Personalised recommendations