The energy expenditure of resistance exercise (RE) is an important consideration for exercise prescription and weight management, yet prediction models are lacking.
Purpose: This study aimed to develop regression equations to predict energy expenditure (kcal) for RE involving each major muscle group using commonly measured demographic and exercise variables as predictors.
Methods: Fifty-two healthy, active subjects (27 men, 25 women, age 20-58 yr, height 174.1 ± 10.5 cm, weight 188.7 ± 42.6 kg, V˙O2max 36.8 ± 9.2 mL·kg⋅min) were strength tested to estimate their one-repetition maximum 1 wk before their experimental RE bout. The experimental RE bout consisted of a warm-up set followed by 2-3 sets (2-min turnover) of 8-12 reps at 60%-70% of predicted one-repetition maximum for leg press, chest press, leg curl, lat pull, leg extension, triceps push down, and biceps curl. Kilocalories were estimated from V˙O2 measured continuously throughout the RE bout via an automated metabolic cart. Total exercise volume (TV) was calculated as sets × reps × weight lifted. Multiple linear regression (stepwise removal) was used to determine the best model (highest adjusted R) to predict the kilocalorie consumption of the total workout and of the individual RE lifts.
Results: The derived regression equation for the net kilocalorie consumption of an RE bout was as follows: total net kilocalorie = 0.874 (height, cm) - 0.596 (age, yr) - 1.016 (fat mass, kg) + 1.638 (lean mass, kg) + 2.461 (TV × 10) - 110.742 (R = 0.773, SEE = 28.5 kcal). Significant equations were also derived for individual lifts (R = 0.62 to 0.83).
Conclusions: Net energy expenditure for a total RE bout and for individual RE can be reasonably estimated in adult men and women using commonly measured demographic and RE variables.