Objective: To compare the two skeletal muscle mass index (SMI) algorithms. One is SMM [SMM(%) = total skeletal muscle mass (kg)/body weight mass (kg) × 100%]; and the other is SMH [SMH (kg/m2) = total skeletal muscle mass (kg)/height (m)2]. Methods: Body composition, body mass index (BMI) and body fat percentage (BFP) were estimated using a bioelectrical impedance analyzer. SMI was calculated by the two algorithms described above, and measurement parameters were stratified by age, BMI and levels of physical activity. Results: Levels of BMI, BFP, SMM and SMH differed significantly between the sexes. BMI and BFP were positively associated with age, while SMM was negatively associated with age (β = −0.2294, P < 0.001). Furthermore, SMM was determined to have a negative association with BMI (β = −0.5340, P < 0.001), while a positive association between SMH and BMI (β = 0.7930, P < 0.001) was observed. Both SMM (β = −0.9849, P < 0.001) and SMH (β = −0.0642, P < 0.001) were negatively associated with BFP. In both men and women, SMM maintained the analogous correlation with other indicators. In the general population, SMM showed a gradual downward trend from low body weight to grade III obesity (F = 9528.32, P < 0.001), but SMH (F = 34395.46, P < 0.001) and BFP (F = 9706.20, P < 0.001) had a reciprocal association. BMI, BFP and SMM differences were observed based on levels of physical activity (P < 0.001). However, there was no significant difference in SMH based on exercise (P > 0.05). Conclusions: SMM may be a more ideal and accurate clinical algorithm for SMI because it is more tightly associated with other body composition indices, as compared with SMH.
Loading....