Evaluation of muscle mass relative to weight/sitting height improves the association with physical performance.

Objectives: To compare relationships of appendicular skeletal muscle mass (ASM) with the function of the upper and lower extremities, after the former has been adjusted by five body size variables: height; weight; body mass index (BMI); sitting height; and weight/sitting height.

Study Design: A cross-sectional study of data derived from the baseline phase of the Physical Activity and Health in Older Women Study.

Main Outcome Measures: ASM was measured by bioelectrical impedance analysis. Grip strength and the time spent on the 5-times chair stand test (5-CST) were the evaluation indexes of upper and lower extremity function respectively. Standardized grip strength and log-transformed 5-CST were used as dependent variables, and standardized ASM adjusted by the five body size variables were used as independent variables. Multiple linear regression models then assessed the relationships of muscle mass with grip strength and 5-CST.

Results: 1103 community-dwelling women aged 60-70 years were included in this study. After adjustment for covariates, ASM adjusted by height or sitting height was positively associated with grip strength (β = 0.140, 0.164 respectively, all P values <0.001), and only ASM adjusted by sitting height was positively associated with the time spent on the 5-CST (β = 0.129, P < 0.001). Weight-adjusted ASM was associated only with the time spent on the 5-CST (β = -0.158, P < 0.001) and BMI-adjusted ASM was associated only with grip strength (β = 0.190, P < 0.001). ASM adjusted by weight/sitting height was positively associated with grip strength (β = 0.140, P < 0.001) and negatively associated with the time spent on the 5-CST (β = -0.076, P = 0.012).

Conclusions: Compared to ASM adjusted by the other four body size variables, ASM adjusted by weight/sitting height had better associations with upper and lower extremity function, which provides new perspectives for improving muscle mass and predicting adverse outcomes.