Objective:
To identify a method to predict the maximal heart rate (MHR) in children and adolescents, as available prediction equations developed for adults have a low accuracy in children. We hypothesized that MHR may be influenced by resting heart rate, anthropometric factors, or fitness level.
Design:
Cross-sectional study.
Setting:
Sports medicine center in primary care.
Participants:
Data from 627 treadmill maximal exercise tests performed by 433 pediatric athletes (age 13.7 ± 2.1 years, 70% males) were analyzed.
Independent Variables:
Age, sex, sport type, stature, body mass, BMI, body fat, fitness level, resting, and MHR were recorded.
Main Outcome Measures:
To develop a prediction equation for MHR in youth, using stepwise multivariate linear regression and linear mixed model. To determine correlations between existing prediction equations and pediatric MHR.
Results:
Observed MHR was 197 ± 8.6 b·min−1. Regression analysis revealed that resting heart rate, fitness, body mass, and fat percent were predictors of MHR (R2 = 0.25, P < 0.001), whereas age was not. Resting heart rate explained 15.6% of MHR variance, body mass added 5.7%, fat percent added 2.4%, and fitness added 1.2%. Existing adult equations had low correlations with observed MHR in children and adolescents (r = −0.03-0.34).
Conclusions:
A new equation to predict MHR in children and adolescents was developed, but was found to have low predictive ability, a finding similar to adult equations applied to children.
Clinical Relevance:
Considering the narrow range of MHR in youth, we propose using 197 b·min−1 as the mean MHR in children and adolescents, with 180 b·min−1 the minimal threshold value (−2 standard deviations).
