Abstract
Sarcopenia is an age-related loss of muscle mass and strength, a highly prevalent issue for older people and constitutes a major health problem. The measurement of appendicular skeletal muscle mass (ASM) in diagnosing sarcopenia can be challenging. Despite a clinical need to identify sarcopenia, there is still a lack of bedside clinical tools to screen for low appendicular skeletal muscle mass (ASM). The gold standard tools used to determine ASM are expensive, invasive, and complex requiring highly trained staff, therefore, anthropometric prediction equations (PEs) were developed for usage in a clinical and community environments, to estimate ASM.
Thus the objectives of this scoping review were as follows:
1) To map the disparate international literature on the diverse anthropometric variable parameters included in predictive equationsfor estimating ASM.
2) To map the development of the anthropometric prediction equations for used in estimating ASM.
This scoping review was undertaken in accordance with the Joanna Briggs Institute’s methodology. Ten studies were included. Eight studies involved community dwelling healthy older people and two studies focused on hospitalized older patients. The most common anthropometric variable parameters included in PEs for ASM were body weight, height and BMI. Regression analysis was used to determine predictive equations for DEXA derived ASM. Included studies reported the use of Bland-Altman analysis for measurement agreement. It was concluded that it is possible to define the range of anthropometric parameters used in estimating ASM and to identify parameters that can be used with ease in clinical practice.