Introduction: The predicted maximal heart rate (MHR) is commonly used in exercise testing and prescription. Numerous prediction equations exist; most were developed for adults, and have a low accuracy in children. The study aim was to develop a method to predict MHR in children and adolescents.
Methods: Data from 627 treadmill maximal exercise tests performed by 433 child and adolescent athletes (age 13.7±2.1years, 70%males) in a large sports medicine center were analyzed. Parameters included age, sex, sport type, height, weight, BMI (absolute and percentiles), body fat, fitness level, resting and maximal heart rate. Stepwise multivariate linear regression was used to identify predictors for MHR. A linear mixed model was used to control for repeated measures in the same individual. Agreement between existing prediction equations and MHR was also evaluated.
Results: MHR was 197±8.6bpm, with a clinically-negligible between-sex difference (2.5 bpm,p=0.005). Stepwise linear regression revealed that only resting heart rate, fitness, weight and fat percent were predictors of MHR (R2=0.25,p<0.001). Resting heart rate explained 15.6% of the variance in MHR, weight added 5.7%, fat percent added 2.4%, and fitness level added 1.2%. Existing adult equations showed a low correlation with MHR (r=(-)0.030-0.335).
Conclusion: We developed a new equation to predict MHR in children and adolescents, yet which had a low prediction of MHR- similar to adult equations. Considering the narrow range of MHR in youth, we suggest using 197 bpm as the mean MHR in children and adolescents aged >9 years, with 180 bpm the minimal threshold value (-2 standard deviations).
