Add like
Add dislike
Add to saved papers

Anthropometry-based Equations to Estimate Body Composition: A Suitable Alternative in Renal Transplant Recipients and Patients With Nondialysis Dependent Kidney Disease?

OBJECTIVE: Chronic kidney disease (CKD) patients and renal transplant recipients (RTRs) are characterized by aberrant body composition such as muscle wasting and obesity. It is still unknown which is the most accurate method to estimate body composition in CKD. We investigated the validity of the Hume equation and bioelectrical impedance analysis (BIA) as an estimate of body composition against dual-energy X-ray absorptiometry (DXA) in a cohort of nondialysis dependent (NDD)-CKD and RTRs.

DESIGN AND METHODS: This was a cross-sectional study with agreement analysis of different assessments of body composition conducted in 61 patients (35 RTRs and 26 NDD-CKD) in a secondary care hospital setting in the UK. Body composition (lean mass [LM], fat mass [FM], and body fat% [BF%]) was assessed using multifrequency BIA and DXA, and estimated using the Hume formula. Method agreement was assessed by intraclass correlation coefficient (ICC), regression, and plotted by Bland and Altman analysis.

RESULTS: Both BIA and the Hume formula were able to accurately estimate body composition against DXA. In both groups, the BIA overestimated LM (1.7-2.1 kg, ICC .980-.984) and underestimated FM (1.3-2.1 kg, ICC .967-.972) and BF% (3.1-3.8%, ICC .927-.954). The Hume formula also overestimated LM (3.5-3.6 kg, ICC .950-.960) and underestimated BF% (1.9-2.1%, ICC .808-.859). Hume-derived FM was almost identical to DXA in both groups (-0.3 to 0.1 kg, ICC .947-.960).

CONCLUSION: Our results demonstrate, in RTR and NDD-CKD patients, that the Hume formula, whose estimation of body composition is based only upon height, body mass, age, and sex, may reliably predict the same parameters obtained by DXA. In addition, BIA also provided similar estimates versus DXA. Thus, the Hume formula and BIA could provide simple and inexpensive means to estimate body composition in renal disease.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app