Development of Predictive Equations to Estimate Regional Muscle Cross Sectional Area Based on Anthropometry

Background. Muscle hypertrophy is one of the main goals of resistance training and is frequently associated with an increase in muscle cross-sectional area (CSA). Imaging techniques are valid and reliable techniques for measuring CSA but are inaccessible to most professionals. Anthropometric-based multiple regression equations (i.e. using circumference and skinfolds outcomes) have been proposed to estimate muscle CSA describing a limited number of muscles. Purpose. The aim of this study was to develop anthropometric-based multiple regres­sion equations using ultrasound images to estimate CSA of pectoralis major, biceps brachii, triceps brachii, rectus abdominis, rectus femoris, vastus lateralis, biceps femo­ris, gastrocnemius lateralis and medialis muscles at two distinct regions for each muscle assessed. Methods. Thirty trained women and men (mean ± SD; body mass = 69.6 ± 11.1 kg; stature = 168.5 ± 8.9 cm; and age = 25.7 ± 4. years) participated in the study. Circum­ference and skinfold measurements were taken at the same points where ultrasound images were acquired to evaluate the CSA of muscles analyzed. Muscle CSA area was assessed using panoramic-view ultrasound. Results. Seventeen multiple regression equations were developed using measures of circumference, skinfold, body weight, height and muscle CSA. Conclusions. Ten equations developed presented the relative errors between 7.2 and 19.9%. These values are comparable or less than those found in equations commonly used by sport and exercise professionals. Thus, these equations are recommended for single-time point estimation of muscle CSA. However, their usefulness for monitoring the CSA changes promoted by resistance training requires further research.