Skip to main content

Advertisement

Log in

Alterations of body composition patterns in pre-dialysis chronic kidney disease patients

  • Nephrology - Original Paper
  • Published:
International Urology and Nephrology Aims and scope Submit manuscript

Abstract

Purpose

Body mass index (BMI) might be an inaccurate estimate of detailed body composition because it does not differentiate muscle from fat mass. We sought to understand the effect of kidney function decline on alterations of body composition patterns among pre-dialysis CKD patients.

Methods

Body composition was measured by multi-frequency bioelectrical impedance analysis (BIA). Low muscle mass was defined as appendicular muscle mass (kg) adjusted to the square of height in meters < 7.0 and 5.7 kg/m2 in men and women, respectively. The designation of obesity by percent body fat was ≥ 25% in men and ≥ 30% in women. Alternative definition of obesity by BMI was ≥ 25 kg/m2. Visceral fat area cut point was > 100 cm2 as indication of abdominal obesity.

Results

Mean age of participants was 61.3 ± 13.8 years (n = 103). The average glomerular filtration rate (GFR) was 34.0 ± 24.2 mL/min/1.73 m2. By BIA, the prevalence of low muscle mass was 16.5% and was comparable between both sexes. Obesity by percent body fat was identified in 71.8% of patients and 38.2% had abdominal obesity. Using BMI criteria, the prevalence of obesity was less common (55.3%) and associated with under-identification of obesity by 27.0%. Low muscle mass and obesity by percent body fat were more prevalent in the more advanced stages of CKD. By multivariable regression analysis, a 10 mL/min/1.73 m2 decline in GFR was associated with a 0.59 kg reduction of total body muscle mass (p = 0.01), but not fat mass or BMI, after adjusting for confounders.

Conclusion

Low muscle mass was prevalent among pre-dialysis CKD patients. BMI commonly classified obese CKD individuals by percent body fat criteria as non-obese. The reduction of muscle mass was associated with GFR decline.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Zoccali C, Torino C, Tripepi G, Mallamaci F (2012) Assessment of obesity in chronic kidney disease: what is the best measure? Curr Opin Nephrol Hypertens 21:641–646

    Article  Google Scholar 

  2. Foley RN, Wang C, Ishani A, Collins AJ, Murray AM (2007) Kidney function and sarcopenia in the United States general population: NHANES III. Am J Nephrol 27:279–286

    Article  Google Scholar 

  3. Sharma D, Hawkins M, Abramowitz MK (2014) Association of sarcopenia with eGFR and misclassification of obesity in adults with CKD in the United States. Clin J Am Soc Nephrol 9:2079–2088

    Article  CAS  Google Scholar 

  4. Beaudart C, McCloskey E, Bruyere O et al (2016) Sarcopenia in daily practice: assessment and management. BMC Geriatr 16:170

    Article  Google Scholar 

  5. Carrero JJ, Johansen KL, Lindholm B et al (2016) Screening for muscle wasting and dysfunction in patients with chronic kidney disease. Kidney Int 90:53–66

    Article  Google Scholar 

  6. Cruz-Jentoft AJ, Bahat G, Bauer J et al (2019) Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48:16–31

    Article  Google Scholar 

  7. Chen LK, Woo J, Assantachai P et al (2020) Asian Working Group for Sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc. https://doi.org/10.1016/j.jamda.2019.12.012

    Article  PubMed  PubMed Central  Google Scholar 

  8. Saitoh M, Ogawa M, Kondo H et al (2019) Sarcopenic obesity and its association with frailty and protein-energy wasting in hemodialysis patients: preliminary data from a single center in Japan. Ren Replace Ther 5:46. https://doi.org/10.1186/s41100-019-0240-9

    Article  Google Scholar 

  9. Honda H, Qureshi AR, Axelsson J et al (2007) Obese sarcopenia in patients with end-stage renal disease is associated with inflammation and increased mortality. Am J Clin Nutr 86:633–638

    Article  CAS  Google Scholar 

  10. Malhotra R, Deger SM, Salat H et al (2017) Sarcopenic obesity definitions by body composition and mortality in the hemodialysis patients. J Ren Nutr 27:84–90

    Article  Google Scholar 

  11. Tabibi H, As'habi A, Najafi I, Hedayati M (2018) Prevalence of dynapenic obesity and sarcopenic obesity and their associations with cardiovascular disease risk factors in peritoneal dialysis patients. Kidney Res Clin Pract 37:404–413

    Article  Google Scholar 

  12. Levey AS, Stevens LA, Schmid CH et al (2009) A new equation to estimate glomerular filtration rate. Ann Intern Med 150:604–612

    Article  Google Scholar 

  13. Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group (2013) KDIGO Clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 3:1–150

    Article  Google Scholar 

  14. Okorodudu DO, Jumean MF, Montori VM et al (2010) Diagnostic performance of body mass index to identify obesity as defined by body adiposity: a systematic review and meta-analysis. Int J Obes (Lond) 34:791–799

    Article  CAS  Google Scholar 

  15. Kanazawa M, Yoshiike N, Osaka T et al (2005) Criteria and classification of obesity in Japan and Asia-Oceania. World Rev Nutr Diet 94:1–12

    PubMed  Google Scholar 

  16. Japan Society for the Study of Obesity (2002) New criteria for ‘obesity disease’ in Japan. Circ J 66:987–992

    Article  Google Scholar 

  17. Androga L, Sharma D, Amodu A, Abramowitz MK (2017) Sarcopenia, obesity, and mortality in US adults with and without chronic kidney disease. Kidney Int Rep 2:201–211

    Article  Google Scholar 

  18. Rymarz A, Zajbt M, Jeznach-Steinhagen A, Wozniak-Kosek A, Niemczyk S (2019) Body composition and biochemical markers of nutrition in non-dialysis-dependent chronic kidney disease patients. Adv Exp Med Biol. https://doi.org/10.1007/5584_2019_444

    Article  PubMed  Google Scholar 

  19. Dierkes J, Dahl H, Lervaag Welland N et al (2018) High rates of central obesity and sarcopenia in CKD irrespective of renal replacement therapy—an observational cross-sectional study. BMC Nephrol 19:259

    Article  CAS  Google Scholar 

  20. Cruz-Jentoft AJ, Baeyens JP, Bauer JM et al (2010) Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on Sarcopenia in older people. Age Ageing 39:412–423

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

  23. Cawthon PM, Peters KW, Shardell MD et al (2014) Cutpoints for low appendicular lean mass that identify older adults with clinically significant weakness. J Gerontol A Biol Sci Med Sci 69:567–575

    Article  Google Scholar 

  24. Saitoh M, Ishida J, Springer J (2017) Considering technique of assessment and method for normalizing skeletal muscle mass. J Cachexia Sarcopenia Muscle 8:853–854

    Article  Google Scholar 

  25. Dufour AB, Hannan MT, Murabito JM, Kiel DP, McLean RR (2013) Sarcopenia definitions considering body size and fat mass are associated with mobility limitations: the Framingham Study. J Gerontol A Biol Sci Med Sci 68:168–174

    Article  Google Scholar 

  26. Dam TT, Peters KW, Fragala M et al (2014) An evidence-based comparison of operational criteria for the presence of sarcopenia. J Gerontol A Biol Sci Med Sci 69:584–590

    Article  Google Scholar 

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

    Article  Google Scholar 

  28. World Health Organization (2000) Obesity: preventing and managing the global epidemic. World Health Organization, Geneva (WHO Technical Report Series 894)

    Google Scholar 

  29. Agarwal R, Bills JE, Light RP (2010) Diagnosing obesity by body mass index in chronic kidney disease: an explanation for the "obesity paradox?". Hypertension 56:893–900

    Article  CAS  Google Scholar 

  30. Sanches FM, Avesani CM, Kamimura MA et al (2008) Waist circumference and visceral fat in CKD: a cross-sectional study. Am J Kidney Dis 52:66–73

    Article  Google Scholar 

  31. Sheean P, Gonzalez MC (2020) American Society for Parenteral and Enteral Nutrition Clinical Guidelines: the validity of body composition assessment in clinical populations. J Parenter Enter Nutr 44:12–43

    Article  Google Scholar 

  32. Zhou Y, Hellberg M, Svensson P, Hoglund P, Clyne N (2018) Sarcopenia and relationships between muscle mass, measured glomerular filtration rate and physical function in patients with chronic kidney disease stages 3–5. Nephrol Dial Transplant 33:342–348

    Article  CAS  Google Scholar 

  33. Zhang L, Wang XH, Wang H, Du J, Mitch WE (2010) Satellite cell dysfunction and impaired IGF-1 signaling cause CKD-induced muscle atrophy. J Am Soc Nephrol 21:419–427

    Article  CAS  Google Scholar 

  34. Wang XH, Mitch WE (2014) Mechanisms of muscle wasting in chronic kidney disease. Nat Rev Nephrol 10:504–516

    Article  CAS  Google Scholar 

  35. Souza VA, Oliveira D, Barbosa SR et al (2017) Sarcopenia in patients with chronic kidney disease not yet on dialysis: analysis of the prevalence and associated factors. PLoS ONE 12:e0176230

    Article  Google Scholar 

  36. Ling CH, de Craen AJ, Slagboom PE et al (2011) Accuracy of direct segmental multi-frequency bioimpedance analysis in the assessment of total body and segmental body composition in middle-aged adult population. Clin Nutr 30:610–615

    Article  Google Scholar 

  37. Ogawa H, Fujitani K, Tsujinaka T et al (2011) InBody 720 as a new method of evaluating visceral obesity. Hepatogastroenterology 58:42–44

    PubMed  Google Scholar 

Download references

Acknowledgements

We would like to thank Wasan Panyasang, M.Sc. (Applied statistics), as the consulting statistician for this project.

Funding

This work has been made possible in part by a Special Task Force for Activating Research (STAR) in Renal Nutrition, Chulalongkorn University funded grant to Dr. Kittiskulnam.

Author information

Authors and Affiliations

Authors

Contributions

PK: research idea and study design. MN, KM, KP: data acquisition. SE, SS data analysis and interpretation. PK: statistical analysis. SE: supervision and mentorship. Each author contributed important intellectual content during manuscript drafting. All authors made substantial contributions, read, and approved the final manuscript.

Corresponding author

Correspondence to Somchai Eiam-Ong.

Ethics declarations

Conflict of interest

None to declare.

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

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kittiskulnam, P., Nitesnoppakul, M., Metta, K. et al. Alterations of body composition patterns in pre-dialysis chronic kidney disease patients. Int Urol Nephrol 53, 137–145 (2021). https://doi.org/10.1007/s11255-020-02599-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11255-020-02599-4

Keywords

Navigation