T Abe1, R S Thiebaud, J P Loenneke, E Fujita, T Akamine. 1. Takashi Abe, 224 Turner Center, University, MS 38677, USA, Phone: +1 (662) 915-5567, FAX: +1 (662) 915-5525, Email: t12abe@gmail.com.
Abstract
OBJECTIVE: Dual-energy X-ray absorptiometry (DXA)-derived appendicular lean soft tissue mass (aLM) is used to diagnose sarcopenia. However, DXA-derived aLM includes non-skeletal muscle components, such as fat-free component of adipose tissue fat cell. These components, if not accounted for, could falsely inflate the aLM in individuals with a high amount of adipose tissue mass. B-mode ultrasound accurately measures muscle size in older adults. We sought to develop regression-based prediction equations for estimating DXA-rectified appendicular lean tissue mass (i.e. DXA-derived aLM minus appendicular fat-free adipose tissue (aFFAT); abbreviated as aLM minus aFFAT) using B-mode ultrasound. DESIGN: Cross-sectional study. MEASUREMENTS: Three hundred and eighty-nine Japanese older adults (aged 60 to 79 years) volunteered in the study. aLM was measured using a DXA, and muscle thickness (MT) was measured using ultrasound at nine sites. An ordinary least-squares multiple linear regression model was used to predict aLM minus aFFAT from sex, age and varying muscle thicknesses multiplied by height. Based on previous studies, we chose to use 4 MT sites at the upper and lower extremities (4-site MT model) and a single site (1-site MT model) at the upper extremity to develop prediction models. RESULTS: The linear prediction models (4 site MT model; R2 = 0.902, adjusted R2 = 0.899, and 1-site MT model; R2 = 0.868, adjusted R2 = 0.866) were found to be stable and accurate for estimating aLM minus aFFAT. Bootstrapping (n=1000) resulted in optimism values of 0.0062 (4-site MT model) and 0.0036 (1-site MT model). CONCLUSION: The results indicated that ultrasound MT combined with height, age and sex can be used to accurately estimate aLM minus aFFAT in older Japanese adults. Newly developed ultrasound prediction equations to estimate aLM minus aFFAT may be a valuable tool in population-based studies to assess age-related rectified lean tissue mass loss.
OBJECTIVE: Dual-energy X-ray absorptiometry (DXA)-derived appendicular lean soft tissue mass (aLM) is used to diagnose sarcopenia. However, DXA-derived aLM includes non-skeletal muscle components, such as fat-free component of adipose tissue fat cell. These components, if not accounted for, could falsely inflate the aLM in individuals with a high amount of adipose tissue mass. B-mode ultrasound accurately measures muscle size in older adults. We sought to develop regression-based prediction equations for estimating DXA-rectified appendicular lean tissue mass (i.e. DXA-derived aLM minus appendicular fat-free adipose tissue (aFFAT); abbreviated as aLM minus aFFAT) using B-mode ultrasound. DESIGN: Cross-sectional study. MEASUREMENTS: Three hundred and eighty-nine Japanese older adults (aged 60 to 79 years) volunteered in the study. aLM was measured using a DXA, and muscle thickness (MT) was measured using ultrasound at nine sites. An ordinary least-squares multiple linear regression model was used to predict aLM minus aFFAT from sex, age and varying muscle thicknesses multiplied by height. Based on previous studies, we chose to use 4 MT sites at the upper and lower extremities (4-site MT model) and a single site (1-site MT model) at the upper extremity to develop prediction models. RESULTS: The linear prediction models (4 site MT model; R2 = 0.902, adjusted R2 = 0.899, and 1-site MT model; R2 = 0.868, adjusted R2 = 0.866) were found to be stable and accurate for estimating aLM minus aFFAT. Bootstrapping (n=1000) resulted in optimism values of 0.0062 (4-site MT model) and 0.0036 (1-site MT model). CONCLUSION: The results indicated that ultrasound MT combined with height, age and sex can be used to accurately estimate aLM minus aFFAT in older Japanese adults. Newly developed ultrasound prediction equations to estimate aLM minus aFFAT may be a valuable tool in population-based studies to assess age-related rectified lean tissue mass loss.
Authors: Steven B Heymsfield; Dympna Gallagher; Donald P Kotler; Zimian Wang; David B Allison; Stanley Heshka Journal: Am J Physiol Endocrinol Metab Date: 2002-01 Impact factor: 4.310
Authors: Robert R McLean; Michelle D Shardell; Dawn E Alley; Peggy M Cawthon; Maren S Fragala; Tamara B Harris; Anne M Kenny; Katherine W Peters; Luigi Ferrucci; Jack M Guralnik; Stephen B Kritchevsky; Douglas P Kiel; Maria T Vassileva; Qian-Li Xue; Subashan Perera; Stephanie A Studenski; Thuy-Tien L Dam Journal: J Gerontol A Biol Sci Med Sci Date: 2014-05 Impact factor: 6.053