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  • Title: Grip Strength and Demographic Variables Estimate Appendicular Muscle Mass Better Than Bioelectrical Impedance in Taiwanese Older Persons.
    Author: Hsiao MY, Chang KV, Wu WT, Huang KC, Han DS.
    Journal: J Am Med Dir Assoc; 2021 Apr; 22(4):760-765. PubMed ID: 32948471.
    Abstract:
    OBJECTIVES: This study aimed to develop an equation model combining physical fitness and anthropometric parameters and compare its results with those of bioelectrical impedance analysis (BIA)-measured lean mass (LM) using dual-energy X-ray absorptiometry (DXA)-measured appendicular muscle mass (AMM) as reference. DESIGN: Observational analysis. SETTING AND PARTICIPANTS: Healthy community-dwelling older subjects. METHODS: A total of 1020 participants were randomly allocated to the development group (development group, n = 510) or the cross-validation group (validation group, n = 510). Body composition was measured using both DXA and BIA, and physical fitness parameters, including grip strength, timed stepping test, sit-to-stand test, flexibility, and walking speed were also assessed. A prediction equation model of AMM by stepwise linear regression analysis that included or excluded 1 independent variable at each step, based on the P value of significance (P < .05), was developed. RESULTS: Using weight, sex, height, and handgrip strength as independent variables, the equation AMM = -9.833 + 0.397 × weight (kg) + 4.433 × sex + 0.121 × height (cm) + 0.061 × handgrip strength (kg) best predicts DXA-measured AMM (adjusted R2 = 0.914, SEE = 2.062, P < .001). The predicted AMM was more highly correlated with DXA-measured AMM than the commonly used BIA-measured LM (R2= 0.9158 and 0.8427, respectively, both P < .001). Using DXA-measured AMM as reference, the Bland-Altman plot showed mean differences of -0.03 kg and -0.12 kg, with limits of agreement of -3.98 to 3.92 kg and -5.97 to 5.73 kg for the predicted AMM and BIA-measured AMM, respectively. CONCLUSIONS AND IMPLICATIONS: The proposed equation offers a practical alternative method for estimating AMM that is less facility-dependent and more easy to use and affordable than instrumental studies.
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