Lower limb skeletal muscle mass: Development of dual-energy X-ray absorptiometry prediction model

Rick Shih, Zimian Wang, Moonseong Heo, Wei Wang, Steven B. Heymsfield

Research output: Contribution to journalArticle

82 Scopus citations

Abstract

Although magnetic resonance imaging (MRI) can accurately measure lower limb skeletal muscle (SM) mass, this method is complex and costly. A potential practical alternative is to estimate lower limb SM with dual-energy X-ray absorptiometry (DXA). The aim of the present study was to develop and validate DXA-SM prediction equations. Identical landmarks (i.e., inferior border of the ischial tuberosity) were selected for separating lower limb from trunk. Lower limb SM was measured by MRI, and lower limb fat-free soft tissue was measured by DXA. A total of 207 adults (104 men and 103 women) were evaluated [age 43 ± 16 (SD) yr, body mass index (BMI) 24.6 ± 3.7 kg/m2]. Strong correlations were observed between lower limb SM and lower limb fat-free soft tissue (R2 = 0.89, P < 0.001); age and BMI were small but significant SM predictor variables. In the cross-validation sample, the differences between MRI-measured and DXA-predicted SM mass were small (-0.006 ± 1.07 and -0.016 ± 1.05 kg) for two different proposed prediction equations, one with fat-free soft tissue and the other with added age and BMI as predictor variables. DXA-measured lower limb fat-free soft tissue, along with other easily acquired measures, can be used to reliably predict lower limb skeletal muscle mass.

Original languageEnglish (US)
Pages (from-to)1380-1386
Number of pages7
JournalJournal of applied physiology
Volume89
Issue number4
DOIs
StatePublished - 2000

Keywords

  • Body composition
  • Nutritional assessment
  • Regional skeletal muscle

ASJC Scopus subject areas

  • Physiology
  • Physiology (medical)

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