Predicting muscle mass from anthropometry using magnetic resonance imaging as reference: a systematic review

Al-Gindan, Y.Y., Hankey, C.R., Leslie, W., Govan, L. and Lean, M.E. (2014) Predicting muscle mass from anthropometry using magnetic resonance imaging as reference: a systematic review. Nutrition Reviews, 72(2), pp. 113-126. (doi: 10.1111/nure.12096)

Abstract

Identification and management of sarcopenia are limited by lack of reliable simple approaches to assess muscle mass. The aim of this review is to identify and evaluate simple methods to quantify muscle mass/volume of adults. Using Cochrane Review methodology, Medline (1946-2012), Embase (1974-2012), Web of Science (1898-2012), PubMed, and the Cochrane Library (to 08/2012) were searched for publications that included prediction equations (from anthropometric measurements) to estimate muscle mass by magnetic resonance imaging (MRI) in adults. Of 257 papers identified from primary search terms, 12 studies met the inclusion criteria. Most studies (n = 10) assessed only regional/limb muscle mass/volume. Many studies (n = 9) assessed limb circumference adjusted for skinfold thickness, which limits their practical applications. Only two included validation in separate subject-samples, and two reported relationships between whole-body MRI-measured muscle mass and anthropometry beyond linear correlations. In conclusion, one simple prediction equation shows promise, but it has not been validated in a separate population with different investigators. Furthermore, it did not incorporate widely available trunk/limb girths, which have offered valuable prediction of body composition in other studies.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Govan, Dr Lindsay and Lean, Professor Michael and Leslie, Dr Wilma and Hankey, Dr Catherine
• Authors: Al-Gindan, Y.Y., Hankey, C.R., Leslie, W., Govan, L., and Lean, M.E.
• College/School: College of Medical Veterinary and Life Sciences; College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Health Economics and Health Technology Assessment
• Journal Name: Nutrition Reviews
• Publisher: Wiley
• ISSN: 0029-6643
• ISSN (Online): 1753-4887