Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Nutrition in acute and chronic diseases

Assessing lean tissue by bioelectrical impedance analysis pre hemodialysis underestimates the prevalence of sarcopenia in maintenance hemodialysis patients



Patients undergoing maintenance hemodialysis dialysis (MHD) are at high risk of sarcopenia. Diagnosing sarcopenia requires measurement of both muscle mass and muscle function. However, few studies have rigorously evaluated the best timing for assessment. This study aimed to evaluate the changes in body composition following hemodialysis in an Asian population.


Overall, 87 MHD patients were included. Body composition was estimated using bioelectrical impedance analysis. Handgrip strength was measured using a quantitative handgrip dynamometer, and physical performance was assessed using the 6-m usual gait speed. All measurements were performed pre and post dialysis. Blood samples were collected before and after the same dialysis session.


The prevalence of sarcopenia ranged from 6.9% to 18.8% pre dialysis (40–59-year group, 6.9%; 60–80-year group, 16.7%; >80-year group, 18.8%) and from 13.8% to 62.5% post dialysis. The body weight decreased from 59.32 ± 11.20 kg pre dialysis to 57.71 ± 11.05 kg post dialysis. Both the extracellular and intracellular water levels decreased post dialysis (from 14.70 ± 3.81 to 13.6 ± 2.82 L, P < 0.001, and from 21.30 ± 4.20 to 20.8 ± 4.13 L, P < 0.001, respectively). Albumin and creatinine levels were significantly lower in patients with sarcopenia. Elevated high-sensitivity C-reactive protein and interleukin-6 levels were observed in sarcopenia patients.


The prevalence of sarcopenia in MHD patients varies greatly according to the timing of measurements. Although predialysis measurement is preferred, it underestimates the prevalence of sarcopenia in MHD patients.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Patient flowchart.
Fig. 2: Prevalence of sarcopenia in different age groups pre and post dialysis.
Fig. 3: Bland–Altman analysis comparing pre and post dialysis.
Fig. 4: Pearson correlation of change in body water and lean tissue mass.


  1. 1.

    Hankin JH. Development of a diet history questionnaire for studies of older persons. Am J Clin Nutr. 1989;50:1121–7.

    CAS  Article  Google Scholar 

  2. 2.

    Edwina A, Johansson L. Old age and frailty in the dialysis population. J Nephro. 2010;23:502–7.

    Google Scholar 

  3. 3.

    Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010;39:412–23.

    Article  Google Scholar 

  4. 4.

    Noori N, Kopple JD, Kovesdy CP, Feroze U, Sim JJ, Murali SB, et al. Mid-arm muscle circumference and quality of life and survival in maintenance hemodialysis patients. Clin J Am Soc Nephrol. 2010;5:2258–68.

    Article  Google Scholar 

  5. 5.

    Pollock CA, Lloyd IS, Barry AJ, Widad A, Caterson RJ, Waugh DA, et al. Total body nitrogen as a prognostic marker in maintenance dialysis. J Am Soc Nephrol. 1995;6:82–8.

    CAS  Article  Google Scholar 

  6. 6.

    Zhu F, Levin NW. Estimation of body composition and normal fluid status using a calf bioimpedance technique. Blood Purif. 2015;39:25–31.

    Article  Google Scholar 

  7. 7.

    Davies SJ, Davenport A. The role of bioimpedance and biomarkers in helping to aid clinical decision-making of volume assessments in dialysis patients. Kidney Int. 2014;86:489–96.

    Article  Google Scholar 

  8. 8.

    Furstenberg A, Davenport A. Comparison of multifrequency bioelectrical impedance analysis and dual-energy X-ray absorptiometry assessments in outpatient hemodialysis patients. Am J Kidney Dis. 2011;57:123–9.

    Article  Google Scholar 

  9. 9.

    Furstenberg A, Davenport A. Assessment of body composition in peritoneal dialysis patients using bioelectrical impedance and dual-energy x-ray absorptiometry. Am J Nephrol. 2011;33:150–6.

    Article  Google Scholar 

  10. 10.

    Moissl UM, Wabel P, Chamney PW, Bosaeus I, Levin NW, Bosy-Westphal A, et al. Body fluid volume determination via body composition spectroscopy in health and disease. Physiol Meas. 2006;27:921–33.

    Article  Google Scholar 

  11. 11.

    Tangvoraphonkchai K, Davenport A. Changes in body composition following haemodialysis as assessed by bioimpedance spectroscopy. Eur J Clin Nutr. 2017;71:169–72.

    CAS  Article  Google Scholar 

  12. 12.

    El-Kateb S, Davenport A. Changes in intracellular water following hemodialysis treatment lead to changes in estimates of lean tissue using bioimpedance spectroscopy. Nutr Clin Pr. 2016;31:375–7.

    Article  Google Scholar 

  13. 13.

    Yang M, Zhao J, Xing L, Shi L. The association between angiotensin-converting enzyme 2 polymorphisms and essential hypertension risk: A meta-analysis involving 14,122 patients. J Renin Angiotensin Aldosterone Syst. 2015;16:1240–4.

    CAS  Article  Google Scholar 

  14. 14.

    Isoyama N, Qureshi AR, Avesani CM, Lindholm B, Barany P, Heimburger O, et al. Comparative associations of muscle mass and muscle strength with mortality in dialysis patients. Clin J Am Soc Nephrol. 2014;9:1720–8.

    Article  Google Scholar 

  15. 15.

    Kim JK, Choi SR, Choi MJ, Kim SG, Lee YK, Noh JW, et al. Prevalence of and factors associated with sarcopenia in elderly patients with end-stage renal disease. Clin Nutr. 2014;33:64–8.

    Article  Google Scholar 

  16. 16.

    Lamarca F, Carrero JJ, Rodrigues JDC, Bigogno FG, Fetter RL, Avesani CM. The prevalence of sarcopenia in elderly maitenance hemodialysis patients: the impact of different diagnosistic criteria. J Nutr Health Aging. 2014;18:710–7.

    CAS  Article  Google Scholar 

  17. 17.

    Lang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L, et al. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging. 2015;16:233–70.

    Article  Google Scholar 

  18. 18.

    Chen LK, Liu LK, Woo J, Assantachai P, Auyeung TW, Bahyah KS, et al. Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J Am Med Dir Assoc. 2014;15:95–101.

    Article  Google Scholar 

  19. 19.

    Hinton BJ, Fan B, Ng BK, Shepherd JA. Dual energy X-ray absorptiometry body composition reference values of limbs and trunk from NHANES 1999-2004 with additional visualization methods. PLoS One. 2017;12:e0174180.

    Article  Google Scholar 

  20. 20.

    Baumgartner RichardN, Koehler KathleenM, Gallagher Dympna, Romero Linda, Heymstleld StevenB, Ross RobertR, et al. Epidemiology of Sarcopenia among the Elderly in New Mexico. Am J Epidemiol. 1998;147:755–63.

    CAS  Article  Google Scholar 

  21. 21.

    Chua HR, Xiang L, Chow PY, Xu H, Shen L, Lee E, et al. Quantifying acute changes in volume and nutritional status during haemodialysis using bioimpedance analysis. Nephrology. 2012;17:695–702.

    Article  Google Scholar 

  22. 22.

    Panorchan K, Nongnuch A, El-Kateb S, Goodlad C, Davenport A. Changes in muscle and fat mass with haemodialysis detected by multi-frequency bioelectrical impedance analysis. Eur J Clin Nutr. 2015;69:1109–12.

    CAS  Article  Google Scholar 

  23. 23.

    Abbas SR, Zhu F, Kaysen GA, Kotanko P, Levin NW. Effect of change in fluid distribution in segments in hemodialysis patients at different ultrafiltration rates on accuracy of whole body bioimpedance measurement. J Appl Physiol. 2014;116:1382–9.

    Article  Google Scholar 

  24. 24.

    Dahlmann A, Dorfelt K, Eicher F, Linz P, Kopp C, Mossinger I, et al. Magnetic resonance-determined sodium removal from tissue stores in hemodialysis patients. Kidney Int. 2015;87:434–41.

    CAS  Article  Google Scholar 

  25. 25.

    Cunningham JohnJ. Body composition as a determinant of energy expenditure: a synthetic review and proposed general prediction equation. Am J Clin Nutr. 1991;54:963–9.

    CAS  Article  Google Scholar 

  26. 26.

    Ravussin Eric, Bogardus Clifton. Relationship of genetics, age, and physical fitness to daily energy expenditure and fuel utilization. Am J Clin Nutr. 1989;49:968–75.

    CAS  Article  Google Scholar 

Download references


This study was supported by grants from the Project of Scientific Research Foundation of Chinese Medicine (2017ZA012) and General Project Funds from the Health Department of Zhejiang Province (2017KY213).

Author information



Corresponding author

Correspondence to Qiang He.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wang, M., Liu, L., Shen, X. et al. Assessing lean tissue by bioelectrical impedance analysis pre hemodialysis underestimates the prevalence of sarcopenia in maintenance hemodialysis patients. Eur J Clin Nutr (2021).

Download citation


Quick links