Skip to main content
SpringerLink
Log in

Thigh muscle volume predicted by anthropometric measurements and correlated with physical function in the older adults

  • JNHA: Nutrition
  • Published:
The journal of nutrition, health & aging

Abstract

Objectives

1) to correlate thigh muscle volume measured by magnetic resonance image (MRI) with anthropometric measurements and physical function in elderly subjects; 2) to predict MRI-measured thigh muscle volume using anthropometric measurements and physical functional status in elderly subjects.

Design

Crosssectional, nonrandomized study.

Setting

Outpatient clinic in Taiwan.

Participants

Sixty-nine elderly subjects (33 men and 36 women) aged 65 and older.

Measurments

The anthropometric data (including body height, body weight, waist size, and thigh circumference), physical activity and function (including grip strength, bilateral quadriceps muscle power, the up and go test, chair rise, and five meters walk time) and bioelectrical impedance analysis data (including total body fat mass, fat-free mass, and predictive muscle size) were measured. MRI-measured muscle volume of both thighs was used as the reference standard.

Results

The MRI-measured thigh volume was positively correlated with all anthropometric data, quadriceps muscle power and the up and go test as well as fat-free mass and predictive muscle mass, whereas it was negatively associated with age and walk time. In predicting thigh muscle volume, the variables of age, gender, body weight, and thigh circumference were significant predictors in the linear regression model: Muscle volume(cm3) =4226.3−42.5×Age(year)−955.7×gender(male=1, female=2)+45.9×body weight(kg) +60.0×thighcircumference (cm) (r2 = 0.745, P < 0.001; Standard Error of the Estimate = 581.6cm3).

Conclusion

The current work provides evidence of a strong relationship between thigh muscle volume and physical function in the elderly. We also developed a prediction equation model using anthropometric measurements. This model is a simple and noninvasive method for everyday clinical practice and follow-up.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Doherty TJ. Invited review: Aging and sarcopenia. J Appl Physiol 2003;95:1717–1727.

    PubMed  CAS  Google Scholar 

  2. Rolland Y, Czerwinski S, Abellan Van Kan G, et al. Sarcopenia: its assessment, etiology, pathogenesis, consequences and future perspectives. J Nutr Health Aging 2008;12:433–450.

    Article  PubMed  CAS  Google Scholar 

  3. Morley JE, Baumgartner RN, Roubenoff R, Mayer J, Nair KS. Sarcopenia. J Lab Clin Med 2001;137:231–243.

    Article  PubMed  CAS  Google Scholar 

  4. Janssen I, Heymsfield SB, Ross R. Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc 2002;50:889–896.

    Article  PubMed  Google Scholar 

  5. Janssen I, Baumgartner RN, Ross R, Rosenberg IH, Roubenoff R. Skeletal muscle cutpoints associated with elevated physical disability risk in older men and women. Am J Epidemiol 2004;159:413–421.

    Article  PubMed  Google Scholar 

  6. Melton LJ, 3rd, Khosla S, Crowson CS, O’Connor MK, O’Fallon WM, Riggs BL. Epidemiology of sarcopenia. J Am Geriatr Soc 2000;48:625–630.

    PubMed  Google Scholar 

  7. Wang ZM, Gallagher D, Nelson ME, Matthews DE, Heymsfield SB. Total-body skeletal muscle mass: evaluation of 24-h urinary creatinine excretion by computerized axial tomography. Am J Clin Nutr 1996;63:863–869.

    PubMed  CAS  Google Scholar 

  8. Wang Z, Zhu S, Wang J, Pierson RN, Jr., Heymsfield SB. Whole-body skeletal muscle mass: development and validation of total-body potassium prediction models. Am J Clin Nutr 2003;77:76–82.

    PubMed  CAS  Google Scholar 

  9. Salinari S, Bertuzzi A, Mingrone G, et al. New bioimpedance model accurately predicts lower limb muscle volume: validation by magnetic resonance imaging. Am J Physiol Endocrinol Metab 2002;282:E960–966.

    PubMed  CAS  Google Scholar 

  10. Visser M, Kritchevsky SB, Goodpaster BH, et al. Leg muscle mass and composition in relation to lower extremity performance in men and women aged 70 to 79: the health, aging and body composition study. J Am Geriatr Soc 2002;50:897–904.

    Article  PubMed  Google Scholar 

  11. 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;88:452–456.

    PubMed  CAS  Google Scholar 

  12. Wang ZM, Visser M, Ma R, et al. Skeletal muscle mass: evaluation of neutron activation and dual-energy X-ray absorptiometry methods. J Appl Physiol 1996;80:824–831.

    PubMed  CAS  Google Scholar 

  13. Hansen RD, Williamson DA, Finnegan TP, et al. Estimation of thigh muscle crosssectional area by dual-energy X-ray absorptiometry in frail elderly patients. Am J Clin Nutr 2007;86:952–958.

    PubMed  CAS  Google Scholar 

  14. Shih R, Wang Z, Heo M, Wang W, Heymsfield SB. Lower limb skeletal muscle mass: development of dual-energy X-ray absorptiometry prediction model. J Appl Physiol 2000;89:1380–1386.

    PubMed  CAS  Google Scholar 

  15. Woo J, Leung J, Sham A, Kwok T. Defining Sarcopenia in Terms of Risk of Physical Limitations: A 5-Year Follow-Up Study of 3,153 Chinese Men and Women. J Am Geriatr Soc 2009;57:2224–2231.

    Article  PubMed  Google Scholar 

  16. Delmonico MJ, Harris TB, Lee JS, et al. Alternative definitions of sarcopenia, lower extremity performance, and functional impairment with aging in older men and women. J Am Geriatr Soc 2007;55:769–774.

    Article  PubMed  Google Scholar 

  17. Estrada M, Kleppinger A, Judge JO, Walsh SJ, Kuchel GA. Functional impact of relative versus absolute sarcopenia in healthy older women. J Am Geriatr Soc 2007;55:1712–1719.

    Article  PubMed  Google Scholar 

  18. Modlesky CM, Bickel CS, Slade JM, Meyer RA, Cureton KJ, Dudley GA. Assessment of skeletal muscle mass in men with spinal cord injury using dual-energy X-ray absorptiometry and magnetic resonance imaging. J Appl Physiol 2004;96:561–565.

    Article  PubMed  Google Scholar 

  19. Candow DG, Chilibeck PD. Differences in size, strength, and power of upper and lower body muscle groups in young and older men. J Gerontol A Biol Sci Med Sci 2005;60:148–156.

    PubMed  Google Scholar 

  20. Nunez C, Gallagher D, Grammes J, et al. Bioimpedance analysis: potential for measuring lower limb skeletal muscle mass. JPEN J Parenter Enteral Nutr 1999;23:96–103.

    Article  PubMed  CAS  Google Scholar 

  21. Nunez C, Gallagher D, Visser M, Pi-Sunyer FX, Wang Z, Heymsfield SB. Bioimpedance analysis: evaluation of leg-to-leg system based on pressure contact footpad electrodes. Med Sci Sports Exerc 1997;29:524–531.

    PubMed  CAS  Google Scholar 

  22. Rolland Y, Lauwers-Cances V, Cournot M, et al. Sarcopenia, calf circumference, and physical function of elderly women: a cross-sectional study. J Am Geriatr Soc 2003;51:1120–1124.

    Article  PubMed  Google Scholar 

  23. Baumgartner RN, Waters DL, Gallagher D, Morley JE, Garry PJ. Predictors of skeletal muscle mass in elderly men and women. Mech Ageing Dev 1999;107:123–136.

    Article  PubMed  CAS  Google Scholar 

  24. Miller DK, Malmstrom TK, Andresen EM, et al. Development and validation of a short portable sarcopenia measure in the African American health project. J Gerontol A Biol Sci Med Sci 2009;64:388–394.

    Article  PubMed  Google Scholar 

  25. Liou YM, Jwo CJ, Yao KG, Chiang LC, Huang LH. Selection of appropriate Chinese terms to represent intensity and types of physical activity terms for use in the Taiwan version of IPAQ. J Nurs Res 2008;16:252–263.

    Article  PubMed  Google Scholar 

  26. Craig CL, Marshall AL, Sjostrom M, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 2003;35:1381–1395.

    Article  PubMed  Google Scholar 

  27. Fried LP, Borhani NO, Enright P, et al. The Cardiovascular Health Study: design and rationale. Ann Epidemiol 1991;1:263–276.

    Article  PubMed  CAS  Google Scholar 

  28. Alley EA, Kopacz DJ, McDonald SB, Liu SS. Hyperbaric spinal levobupivacaine: a comparison to racemic bupivacaine in volunteers. Anesth Analg 2002;94:188–193.

    PubMed  CAS  Google Scholar 

  29. Podsiadlo D, Richardson S. The timed “Up & Go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 1991;39:142–148.

    PubMed  CAS  Google Scholar 

  30. Thapa PB, Gideon P, Fought RL, Kormicki M, Ray WA. Comparison of clinical and biomechanical measures of balance and mobility in elderly nursing home residents. J Am Geriatr Soc 1994;42:493–500.

    PubMed  CAS  Google Scholar 

  31. Sherman FT. Functional assessment. Easy-to-use screening tools speed initial office work-up. Geriatrics 2001;56:36–40; quiz 43.

    CAS  Google Scholar 

  32. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146–156.

    PubMed  CAS  Google Scholar 

  33. Sports Medicine Institute. Thigh circumference. (online). Available at: http://wwwsportsdocumnedu/Clinical_Folder/Knee_Folder/Knee_Exam/thigh%20circumferencehtm. Accessed December 11, 2009.

  34. Chien MY, Huang TY, Wu YT. Prevalence of sarcopenia estimated using a bioelectrical impedance analysis prediction equation in community-dwelling elderly people in Taiwan. J Am Geriatr Soc 2008;56:1710–1715.

    Article  PubMed  Google Scholar 

  35. Baumgartner RN, Koehler KM, Gallagher D, et al. Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 1998;147:755–763.

    PubMed  CAS  Google Scholar 

  36. Melton LJ, 3rd, Khosla S, Riggs BL. Epidemiology of sarcopenia. Mayo Clin Proc 2000;75Suppl:S10–12;discussion S12–13.

    PubMed  Google Scholar 

  37. Phillips SM, Tipton KD, Aarsland A, Wolf SE, Wolfe RR. Mixed muscle protein synthesis and breakdown after resistance exercise in humans. Am J Physiol 1997;273:E99–107.

    PubMed  CAS  Google Scholar 

  38. Koopman R, van Loon LJ. Aging, exercise, and muscle protein metabolism. J Appl Physiol 2009;106:2040–2048.

    Article  PubMed  CAS  Google Scholar 

  39. Lee RC, Wang ZM, Heymsfield SB. Skeletal muscle mass and aging: regional and whole-body measurement methods. Can J Appl Physiol 2001;26:102–122.

    Article  PubMed  CAS  Google Scholar 

  40. Mitsiopoulos N, Baumgartner RN, Heymsfield SB, Lyons W, Gallagher D, Ross R. Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography. J Appl Physiol 1998;85:115–122.

    PubMed  CAS  Google Scholar 

  41. Ross R, Rissanen J, Pedwell H, Clifford J, Shragge P. Influence of diet and exercise on skeletal muscle and visceral adipose tissue in men. J Appl Physiol 1996;81:2445–2455.

    PubMed  CAS  Google Scholar 

  42. Lee RC, Wang Z, Heo M, Ross R, Janssen I, Heymsfield SB. Total-body skeletal muscle mass: development and cross-validation of anthropometric prediction models. Am J Clin Nutr 2000;72:796–803.

    PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Departments of Medical Imaging and Radiology, National Taiwan University Hospital and National Taiwan University, college of medicine, Yun-Lin Branch, Taipei, Taiwan

    B. -B. Chen

  2. Departments of Medical Imaging and Radiology, National Taiwan University Hospital and National Taiwan University, College of Medicine, Taipei, Taiwan

    T. T. F. Shih, C. -Y. Hsu, C. -W. Yu & S. -Y. Wei

  3. Department of Family Medicine, National Taiwan University Hospital and National Taiwan University, College of Medicine, Taipei, Taiwan

    C. -Y. Chen & Ching-Yu Chen

  4. Division of Geriatric research, Institute of Population Health Sciences, National Health Research Institutes, Taipei, Taiwan

    C. -H. Wu & Ching-Yu Chen

  5. Division of Geriatric Research, Institute of Population Health Sciences, National Health Research Institutes, 100 R440, 4F, No. 17 Xu-Zhou Road, Taipei, Taiwan

    Ching-Yu Chen

Authors
  1. B. -B. Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. T. T. F. Shih
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. C. -Y. Hsu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. C. -W. Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. S. -Y. Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. C. -Y. Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. C. -H. Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ching-Yu Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ching-Yu Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, B.B., Shih, T.T.F., Hsu, C.Y. et al. Thigh muscle volume predicted by anthropometric measurements and correlated with physical function in the older adults. J Nutr Health Aging 15, 433–438 (2011). https://doi.org/10.1007/s12603-010-0281-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12603-010-0281-9

Key words

Search

Navigation