4% of the total variance in force. The first factor consisted of body mass, muscle circumferences, and skinfolds accounting for 47.8% of the variance in force. In contrast, the third factor included height and limb lengths and accounted for only 7% of the total variance in force. The regression analysis for males in the present study is consistent with the findings of Scanlan et al.20 because a circumference measure (ELB) had a greater impact on the equation for predicting elbow flexion strength than a length measure (L3). In contrast, the inclusion of L3 to a prediction equation with BW had a greater impact for females than it did for males, in terms of accounting for

additional variance in elbow flexion strength. The large contribution of limb length to the strength prediction equation for females may be explained by the relationship between the length of a muscle and the number of sarcomeres in series.21 and 22 The number of Ibrutinib research buy sarcomeres in parallel (physiological cross-sectional area) is proportional to the amount of tension that is produced whereas the number of sarcomeres in series (muscle fiber length) is proportional to the velocity at which tension is.23 and 24 While

the dependent measure in this study was mean torque, not velocity of shortening, it has been suggested that DNA Damage inhibitor the number of sarcomeres in series, and therefore the length of a muscle, has a relationship with the amount of force being produced.22 and 25 Ketanserin This relationship was demonstrated for sprint performance and leg characteristics in female sprinters. Abe and colleagues26 found that increased fascicle length was highly correlated with increased shortening velocity and concurrently, sprint performance. These physiological characteristics combined with females’ decreased proportion of lean tissue mass may explain the large contribution of limb length compared to weight and circumference measurements.

The contribution of muscle activation in addition to muscle size to the prediction of strength was assessed by incorporating RMS sEMG amplitude to equations consisting of BW and a second anthropometric variable. The addition of sEMG RMS resulted in a significant (p < 0.05) increase in the variance-accounted-for by each equation, except when the second variable was L3 for females. The minimal contribution may have been due to the immense contribution of L3 alone (partial R2 = 39.1%). Excluding this particular case, on average, sEMG RMS accounted for an additional 10.1% of the variance in strength. Surprisingly, the addition of a third anthropometric variable instead of sEMG RMS resulted in superior prediction equations for both males and females. The majority of the literature on force and sEMG is focused on the linear versus non-linear nature of the relationship, to create a calibrating equation throughout the range of muscle forces (0–100% maximal voluntary contraction).