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Appendicular Skeletal Muscle Mass: Development and Validation of Anthropometric Prediction Equations
11. Renuka Visvanathan MBBS PhD, Aged and Extended Care Services, Level 8B Main Building, The Queen Elizabeth Hospital, 21 Woodville Road, Woodville South, South Australia 5011. University of Adelaide, Adelaide, South Australia, Phone:+61 8 8222 8592; Fax:+61 8 8222 8593,
The Journal of Frailty & Aging
|April 20, 2016
Summary
New prediction equations (PEs) estimate appendicular skeletal muscle mass (ASM) using anthropometric data. These PEs aid in diagnosing sarcopenia, the age-related loss of muscle, in primary and aged care settings.
Area of Science:
- Gerontology
- Human Physiology
- Biostatistics
Background:
- Sarcopenia, characterized by age-related muscle mass and function decline, necessitates accurate assessment of appendicular skeletal muscle mass (ASM).
- Current diagnostic methods for sarcopenia often require specialized equipment, limiting their use in primary and aged care.
Purpose of the Study:
- To develop and validate novel anthropometric prediction equations (PEs) for estimating ASM.
- To create accessible tools for sarcopenia assessment in community and aged care settings.
Main Methods:
- Prediction equations (PEs) were developed using best subset regression analysis.
- Three top-performing PEs were selected and validated using Bland-Altman and Sheiner-Beal methods.
- Appendicular skeletal muscle mass (ASM) was measured using dual-energy X-ray absorptiometry (DEXA) in 188 healthy adults for development and 2275 older adults for validation.
Main Results:
- A strong correlation was observed between PE-derived ASM and DEXA-derived ASM.
- The best performing equation (PE3) demonstrated good accuracy, with an adjusted R² of 0.869 and an overestimation of ASM by 0.36 kg.
- PE3 showed consistent performance across various age and body mass index (BMI) categories.
Conclusions:
- Novel anthropometric prediction equations for ASM have been developed.
- These PEs offer a practical approach for estimating ASM in primary and aged care.
- The developed equations are specific to Caucasian populations.
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