Skip to main content

Thank you for visiting nature.com. 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.

  • Short Communication
  • Published:

Comparison of resting and total energy expenditure in peritoneal dialysis patients and body composition measured by dual-energy X-ray absorptiometry

European Journal of Clinical Nutrition volume 70, pages 1337–1339 (2016)Cite this article

Subjects

Abstract

Under basal resting conditions muscle metabolism is reduced, whereas metabolism increases with physical activity. We wished to determine whether there was an association between resting energy expenditure (REE) and total energy expenditure (TEE) in peritoneal dialysis (PD) patients and lean body mass (LBM). We determined REE and TEE by recently validated equations, using doubly labelled isotopic water, and LBM by dual-energy X-ray absorptiometry (DXA) scanning. We studied 87 patients, 50 male (57.4%), 25 diabetic (28.7%), mean age 60.3±17.6 years, with a median PD treatment of 11.4 (4.7–29.5) months. The mean weight was 70.1±17.7 kg with a REE of 1509±245 kcal/day and TEE 1947±378 kcal/day. REE was associated with body size (weight r=0.78 and body mass index (BMI) r=0.72) and body composition (LBM r=0.77, lean body mass index (LBMI) r=0.76, r=0.62), all P<0.001). For TEE, there was an association with weight r=0.58, BMI r=0.49 and body composition (LBM r=0.64, LBMI (r=0.54), all P<0.001). We compared LBMI measured by DXA and that estimated by the Boer equation using anthropomorphic measurements, which overestimated and underestimated LBM for smaller patients and heavier patients, respectively. Muscle metabolism is reduced at rest and increases with physical activity. Whereas previous reports based on REE did not show any association with LBM, we found an association between both REE and TEE, using a recently validated equation derived from dialysis patients, and LBM measured by DXA scanning. Estimation of muscle mass from anthropomorphic measurements systematically overestimated LBM for small patients and conversely underestimated for heavier patients.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2

Similar content being viewed by others

References

  1. Paniagua R, Amato D, Vonesh E, Guo A, Mujais S, Mexican Nephrology Collaborative Study Group. Health-related quality of life predicts outcomes but is not affected by peritoneal clearance: The ADEMEX trial. Kidney Int 2005; 67: 1093–1104.

    Article  Google Scholar 

  2. Daugirdas JT, Levin NW, Kotanko P, Depner TA, Kuhlmann MK, Chertow GM et al. Comparison of proposed alternative methods for rescaling dialysis dose: resting energy expenditure, high metabolic rate organ mass, liver size, and body surface area. Semin Dial 2008; 21: 377–384.

    Article  Google Scholar 

  3. Bazanelli AP, Kamimura MA, da Silva CB, Avesani CM, Lopes MG, Manfredi SR et al. Resting energy expenditure in peritoneal dialysis patients. Perit Dial Int 2006; 26: 697–704.

    PubMed  Google Scholar 

  4. Sridharan S, Wong J, Vilar E, Farrington K . Comparison of energy estimates in chronic kidney disease using doubly-labelled water. J Hum Nutr Diet 2016; 29: 59–66.

    Article  CAS  Google Scholar 

  5. Fürstenberg A, Davenport A . Comparison of multifrequency bioelectrical impedance analysis and dual-energy X-ray absorptiometry assessments in outpatient haemodialysis patients. Am J Kidney Dis 2011; 57: 123–129.

    Article  Google Scholar 

  6. Fürstenberg 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: 150–156.

    Article  Google Scholar 

  7. Ainsworth BE, Haskell WL, Herrmann SD, Meckes N, Bassett DR Jr., Tudor-Locke C et al. 2011 Compendium of physical activities: a second update of codes and MET values. Med Sci Sports Exerc 2011; 43: 1575–1581.

    Article  Google Scholar 

  8. Vilar E, Machado A, Garrett A, Kozarski R, Wellsted D, Farrington K . Disease-specific predictive formulas for energy expenditure in the dialysis population. J Ren Nutr 2014; 24: 243–251.

    Article  Google Scholar 

  9. Wang AY, Sea MM, Tang N, Sanderson JE, Lui SF, Li PK et al. Resting energy expenditure and subsequent mortality risk in peritoneal dialysis patients. J Am Soc Nephrol 2004; 15: 3134–3143.

    Article  Google Scholar 

  10. Zuo ML, Yue WS, Yip T, Ng F, Lam KF, Yiu KH et al. Prevalence of and associations with reduced exercise capacity in peritoneal dialysis patients. Am J Kidney Dis 2013; 62: 939–946.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by a grant from British Renal Society. SE-K was awarded an International Society for Nephrology fellowship.

Disclaimer

None of the data contained in this report has been previously published in whole or part form.

Author information

Authors and Affiliations

  1. UCL Centre for Nephrology, Royal Free Hospital, University College London Medical School, London, UK

    S El-Kateb & A Davenport

  2. Renal Unit, Lister Hospital, Stevenage, UK

    S Sridharan & K Farrington

  3. University of Hertfordshire, Hatfield, UK

    K Farrington

Authors
  1. S El-Kateb
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S Sridharan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. K Farrington
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A Davenport
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A Davenport.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Appendix

Appendix

Resting energy expenditure (REE) was estimated from a newer novel predictive equation which was derived and validated in a cohort of HD patients.4

REE=−2.497 × Age(years) × Factorage+0.011 × Height2.023(cm)+83.573 × Weight0.6291(kg)+68.171 × Factorsex

where Factor age is 0 if age <65 and 1 if ⩾65 and Factor sex is 0 if female and 1 if male.

Physical activity data—Each reported activity was assigned a metabolic equivalent of task (MET) value as per the Compendium of Physical Activities.4 Sleep time per day was assumed to be 8 h and any unreported time during the day was assumed as the time performing light activities at home. A Mean daily MET value was calculated.

Total energy expenditure (TEE) was estimated from the following equation.

Boer equation

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

El-Kateb, S., Sridharan, S., Farrington, K. et al. Comparison of resting and total energy expenditure in peritoneal dialysis patients and body composition measured by dual-energy X-ray absorptiometry. Eur J Clin Nutr 70, 1337–1339 (2016). https://doi.org/10.1038/ejcn.2016.120

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ejcn.2016.120

Search

Advanced search

Quick links