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Computed Tomography-Derived Skeletal Muscle Radiodensity Predicts Peak Weight-Corrected Jump Power in Older Adults: The Korean Urban Rural Elderly (KURE) Study

Calcified Tissue International volume 108, pages 764–774 (2021)Cite this article

Abstract

Computed tomography (CT)-derived skeletal muscle area (SMA) and skeletal muscle radiodensity (SMD) reflect distinctive quantitative and qualitative characteristics of skeletal muscles. However, data on whether CT-based muscle parameters, especially SMD, can predict muscle function is limited. In a prospective cohort, 1523 community-dwelling older adults who underwent abdominal CT scans and the countermovement two-legged jumping test on a ground reaction force platform were analyzed (mean age 74.7 years, 65.1% women). SMA and SMD were measured at third lumbar vertebra level (L3). Individuals with low jump power (peak weight-corrected jump power < 23.8 W/kg in men and < 19.0 W/kg in women using clinically validated threshold) were older; had lower SMA, SMD, and maximal grip strength values; and had lower chair rise test and timed up and go test performance than those without low jump power. SMD was positively associated with peak weight-corrected jump power (adjusted β = 0.33 and 0.23 per 1 HU increase in men and women, respectively, p < 0.001). One HU decrement in SMD was associated with 10% elevated odds of low jump power (adjusted OR [aOR] 1.10, p < 0.001) after adjusting for age, sex, height, inflammation, and insulin resistance markers, whereas the association of SMA with low jump power was attenuated (aOR 1.00, p = 0.721). SMD showed better discrimination for low jump power than SMA (AUC 0.699 vs. 0.617, p < 0.001), with additional improvement when added to SMA and conventional risk factors (AUC 0.745 to 0.773, p < 0.001). Therefore, CT-measured L3 SMD can be a sensitive surrogate marker for muscle function along with SMA in older adults, which merits further investigation.

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References

  1. Eriksen CS, Garde E, Reislev NL, Wimmelmann CL, Bieler T, Ziegler AK, Gylling AT, Dideriksen KJ, Siebner HR, Mortensen EL, Kjaer M (2016) Physical activity as intervention for age-related loss of muscle mass and function: protocol for a randomised controlled trial (the LISA study). BMJ Open 6:e012951

    PubMed  PubMed Central  Google Scholar 

  2. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyere O, Cederholm T, Cooper C, Landi F, Rolland Y, Sayer AA, Schneider SM, Sieber CC, Topinkova E, Vandewoude M, Visser M, Zamboni M (2019) Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48:16–31

    PubMed  Google Scholar 

  3. Buehring B, Krueger D, Binkley N (2010) Jumping mechanography: a potential tool for sarcopenia evaluation in older individuals. J Clin Densitom 13:283–291

    PubMed  Google Scholar 

  4. Mayson DJ, Kiely DK, LaRose SI, Bean JF (2008) Leg strength or velocity of movement: which is more influential on the balance of mobility limited elders? Am J Phys Med Rehabil 87:969–976

    PubMed  PubMed Central  Google Scholar 

  5. Hong N, Kim CO, Youm Y, Kim HC, Rhee Y (2018) Low peak jump power is associated with elevated odds of dysmobility syndrome in community-dwelling elderly individuals: the Korean Urban Rural Elderly (KURE) study. Osteoporos Int 29:1427–1436

    PubMed  Google Scholar 

  6. Dietzel R, Felsenberg D, Armbrecht G (2015) Mechanography performance tests and their association with sarcopenia, falls and impairment in the activities of daily living—a pilot cross-sectional study in 293 older adults. J Musculoskelet Neuronal Interact 15:249–256

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Pereira A, Izquierdo M, Silva AJ, Costa AM, Bastos E, Gonzalez-Badillo JJ, Marques MC (2012) Effects of high-speed power training on functional capacity and muscle performance in older women. Exp Gerontol 47:250–255

    PubMed  Google Scholar 

  8. Mourtzakis M, Prado CM, Lieffers JR, Reiman T, McCargar LJ, Baracos VE (2008) A practical and precise approach to quantification of body composition in cancer patients using computed tomography images acquired during routine care. Appl Physiol Nutr Metab 33:997–1006

    PubMed  Google Scholar 

  9. Kim D, Sun JS, Lee YH, Lee JH, Hong J, Lee JM (2018) Comparative assessment of skeletal muscle mass using computerized tomography and bioelectrical impedance analysis in critically ill patients. Clin Nutr. https://doi.org/10.1016/j.clnu.2018.12.002

    Article  PubMed  PubMed Central  Google Scholar 

  10. Hong N, Lee J, Ku CR, Han K, Lee CR, Kang SW, Rhee Y (2019) Changes of computed tomography-based body composition after adrenalectomy in patients with endogenous hypercortisolism. Clin Endocrinol (Oxf) 90:267–276

    CAS  Google Scholar 

  11. Frontera WR, Hughes VA, Fielding RA, Fiatarone MA, Evans WJ, Roubenoff R (2000) Aging of skeletal muscle: a 12-yr longitudinal study. J Appl Physiol (1985) 88:1321–1326

    CAS  Google Scholar 

  12. Larson-Meyer DE, Smith SR, Heilbronn LK, Kelley DE, Ravussin E, Newcomer BR (2006) Muscle-associated triglyceride measured by computed tomography and magnetic resonance spectroscopy. Obesity (Silver Spring) 14:73–87

    CAS  PubMed Central  Google Scholar 

  13. Goodpaster BH, Carlson CL, Visser M, Kelley DE, Scherzinger A, Harris TB, Stamm E, Newman AB (2001) Attenuation of skeletal muscle and strength in the elderly: the Health ABC Study. J Appl Physiol (1985) 90:2157–2165

    CAS  Google Scholar 

  14. Lee J, Lin JB, Wu MH, Jan YT, Chang CL, Huang CY, Sun FJ, Chen YJ (2019) Muscle radiodensity loss during cancer therapy is predictive for poor survival in advanced endometrial cancer. J Cachexia Sarcopenia Muscle. https://doi.org/10.1002/jcsm.12440

    Article  PubMed  PubMed Central  Google Scholar 

  15. van Dijk DP, Bakens MJ, Coolsen MM, Rensen SS, van Dam RM, Bours MJ, Weijenberg MP, Dejong CH, Olde Damink SW (2017) Low skeletal muscle radiation attenuation and visceral adiposity are associated with overall survival and surgical site infections in patients with pancreatic cancer. J Cachexia Sarcopenia Muscle 8:317–326

    PubMed  Google Scholar 

  16. Lee EY, Kim HC, Rhee Y, Youm Y, Kim KM, Lee JM, Choi DP, Yun YM, Kim CO (2014) The Korean urban rural elderly cohort study: study design and protocol. BMC Geriatr 14:33

    PubMed  PubMed Central  Google Scholar 

  17. Rittweger J, Schiessl H, Felsenberg D, Runge M (2004) Reproducibility of the jumping mechanography as a test of mechanical power output in physically competent adult and elderly subjects. J Am Geriatr Soc 52:128–131

    PubMed  Google Scholar 

  18. Hong N, Siglinsky E, Krueger D, White R, Kim CO, Kim HC, Yeom Y, Binkley N, Rhee Y, Buehring B (2020) Defining an international cut-off of two-legged countermovement jump power for sarcopenia and dysmobility syndrome. Osteoporos Int. https://doi.org/10.1007/s00198-020-05591-x

    Article  PubMed  PubMed Central  Google Scholar 

  19. Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, Jang HC, Kang L, Kim M, Kim S, Kojima T, Kuzuya M, Lee JSW, Lee SY, Lee WJ, Lee Y, Liang CK, Lim JY, Lim WS, Peng LN, Sugimoto K, Tanaka T, Won CW, Yamada M, Zhang T, Akishita M, Arai H (2020) Asian Working Group for Sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc 21(300–307):e302

    Google Scholar 

  20. Kear BM, Guck TP, McGaha AL (2017) Timed up and go (TUG) test: normative reference values for ages 20 to 59 years and relationships with physical and mental health risk factors. J Prim Care Community Health 8:9–13

    PubMed  Google Scholar 

  21. Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, Jang HC, Kang L, Kim M, Kim S, Kojima T, Kuzuya M, Lee JSW, Lee SY, Lee WJ, Lee Y, Liang CK, Lim JY, Lim WS, Peng LN, Sugimoto K, Tanaka T, Won CW, Yamada M, Zhang T, Akishita M, Arai H (2020) Asian Working Group for Sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc 21:300–307

    PubMed  Google Scholar 

  22. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC (1985) Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28:412–419

    CAS  PubMed  Google Scholar 

  23. Mohammadbeigi A, Moshiri E, Mohammadsalehi N, Ansari H, Ahmadi A (2015) Dyslipidemia prevalence in iranian adult men: the impact of population-based screening on the detection of undiagnosed patients. World J Mens Health 33:167–173

    PubMed  PubMed Central  Google Scholar 

  24. DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837–845

    CAS  PubMed  Google Scholar 

  25. Youden WJ (1950) Index for rating diagnostic tests. Cancer 3:32–35

    CAS  PubMed  Google Scholar 

  26. Lee EY, Lee SJ, Kim KM, Seo DH, Lee SW, Choi HS, Kim HC, Youm Y, Kim CO, Rhee Y (2017) Lower jump power rather than muscle mass itself is associated with vertebral fracture in community-dwelling elderly Korean women. Calcif Tissue Int 100:585–594

    CAS  PubMed  Google Scholar 

  27. Lee JS, Kim YS, Kim EY, Jin W (2018) Prognostic significance of CT-determined sarcopenia in patients with advanced gastric cancer. PLoS ONE 13:e0202700

    PubMed  PubMed Central  Google Scholar 

  28. Portal D, Hofstetter L, Eshed I, Dan-Lantsman C, Sella T, Urban D, Onn A, Bar J, Segal G (2019) L3 skeletal muscle index (L3SMI) is a surrogate marker of sarcopenia and frailty in non-small cell lung cancer patients. Cancer Manag Res 11:2579–2588

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Kang SH, Lee HS, Lee S, Cho JH, Kim JC (2017) Comparison of muscle mass indices using computed tomography or dual X-ray absorptiometry for predicting physical performance in hemodialysis patients. Kidney Blood Press Res 42:1119–1127

    PubMed  Google Scholar 

  30. Moreau J, Ordan MA, Barbe C, Mazza C, Perrier M, Botsen D, Brasseur M, Portefaix C, Renard Y, Talliere B, Bertin E, Hoeffel C, Bouche O (2019) Correlation between muscle mass and handgrip strength in digestive cancer patients undergoing chemotherapy. Cancer Med 8:3677–3684

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Williams GR, Deal AM, Muss HB, Weinberg MS, Sanoff HK, Nyrop KA, Pergolotti M, Shachar SS (2017) Skeletal muscle measures and physical function in older adults with cancer: sarcopenia or myopenia? Oncotarget 8:33658–33665

    PubMed  PubMed Central  Google Scholar 

  32. 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

    CAS  PubMed  Google Scholar 

  33. Siglinsky E, Krueger D, Ward RE, Caserotti P, Strotmeyer ES, Harris TB, Binkley N, Buehring B (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 

  34. Curtis E, Litwic A, Cooper C, Dennison E (2015) Determinants of muscle and bone aging. J Cell Physiol 230:2618–2625

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Goodpaster BH, Kelley DE, Thaete FL, He J, Ross R (2000) Skeletal muscle attenuation determined by computed tomography is associated with skeletal muscle lipid content. J Appl Physiol (1985) 89:104–110

    CAS  Google Scholar 

  36. Rahemi H, Nigam N, Wakeling JM (2015) The effect of intramuscular fat on skeletal muscle mechanics: implications for the elderly and obese. J R Soc Interface 12:20150365

    PubMed  PubMed Central  Google Scholar 

  37. Ostler JE, Maurya SK, Dials J, Roof SR, Devor ST, Ziolo MT, Periasamy M (2014) Effects of insulin resistance on skeletal muscle growth and exercise capacity in type 2 diabetic mouse models. Am J Physiol Endocrinol Metab 306:E592-605

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Kim D, Nam S, Ahn C, Kim K, Yoon S, Kim J, Cha B, Lim S, Kim K, Lee H, Huh K (2003) Correlation between midthigh low-density muscle and insulin resistance in obese nondiabetic patients in Korea. Diabetes Care 26:1825–1830

    PubMed  Google Scholar 

  39. Wahlin-Larsson B, Carnac G, Kadi F (2014) The influence of systemic inflammation on skeletal muscle in physically active elderly women. Age (Dordr) 36:9718

    Google Scholar 

  40. Lexell J (1995) Human aging, muscle mass, and fiber type composition. J Gerontol A Biol Sci Med Sci 50:11–16

    PubMed  Google Scholar 

  41. Nilwik R, Snijders T, Leenders M, Groen BB, van Kranenburg J, Verdijk LB, van Loon LJ (2013) The decline in skeletal muscle mass with aging is mainly attributed to a reduction in type II muscle fiber size. Exp Gerontol 48:492–498

    PubMed  Google Scholar 

  42. Essen B, Jansson E, Henriksson J, Taylor AW, Saltin B (1975) Metabolic characteristics of fibre types in human skeletal muscle. Acta Physiol Scand 95:153–165

    CAS  PubMed  Google Scholar 

  43. Dwyer A, Doppman JL, Adams AJ, Girton ME, Chernick SS, Cornblath M (1983) Influence of glycogen on liver density: computed tomography from a metabolic perspective. J Comput Assist Tomogr 7:70–73

    CAS  PubMed  Google Scholar 

  44. Hardcastle SA, Gregson CL, Rittweger J, Crabtree N, Ward K, Tobias JH (2014) Jump power and force have distinct associations with cortical bone parameters: findings from a population enriched by individuals with high bone mass. J Clin Endocrinol Metab 99:266–275

    CAS  PubMed  Google Scholar 

  45. Blache Y, Monteil K (2014) Influence of lumbar spine extension on vertical jump height during maximal squat jumping. J Sports Sci 32:642–651

    PubMed  Google Scholar 

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Acknowledgements

We thank Sung-Kil Lim Research Award (4-2018-1215) and 2020 Research fund of Department of Internal Medicine, Severance Hospital, Seoul, Korea for the data quality assurance and statistical assistance by the SENTINEL (Severance ENdocrinology daTa scIeNcE pLatform) team.

Funding

This research was funded by the Korea Centers for Disease Control and Prevention (2013-E63007-01, 2013-E63007-02, 2019-ER6302-01), and Internal Medicine.

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Author notes

  1. Heewon Choi and Namki Hong have contributed equally to this work.

Authors and Affiliations

  1. Yonsei University College of Medicine, Seoul, South Korea

    Heewon Choi

  2. Department of Internal Medicine, Severance Hospital, Endocrine Research Institute, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea

    Namki Hong, Narae Park & Yumie Rhee

  3. Division of Geriatrics, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea

    Chang Oh Kim

  4. Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, South Korea

    Hyeon Chang Kim

  5. Department of Radiology, Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea

    Jin Young Choi

  6. Department of Sociology, Yonsei University College of Social Sciences, Seoul, South Korea

    Yoosik Youm

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Contributions

HC and NH participated in the study concept and design, analysis and interpretation of data, and preparation and revision of manuscript. Extraction of data was done by HC and NP. HCK, JYC, YY played a role in the preparation phase of the paper by performing subject recruitment and data collection. YR contributed in acquisition of subjects and data, interpretation, and revision and final approval of manuscript.

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Correspondence to Yumie Rhee.

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Conflict of interest

Heewon Choi, Namki Hong, Narae Park, Chang Oh Kim, Hyeon Chang Kim, Jin Young Choi, Yoosik Youm, and Yumie Rhee have no conflicts of interest to declare.

Ethical Approval

This study was approved by Institutional Review Board of Severance Hospital (IRB No. 4–2012-0172). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committees and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Written informed consent was obtained from all participants prior to the study.

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Choi, H., Hong, N., Park, N. et al. Computed Tomography-Derived Skeletal Muscle Radiodensity Predicts Peak Weight-Corrected Jump Power in Older Adults: The Korean Urban Rural Elderly (KURE) Study. Calcif Tissue Int 108, 764–774 (2021). https://doi.org/10.1007/s00223-021-00812-9

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  • DOI: https://doi.org/10.1007/s00223-021-00812-9

Keywords

  • Aging
  • Muscle mass
  • Muscle density
  • Physical performance
  • Muscle radiation attenuation
  • Myosteatosis