HR Max Prediction Based on Age, Body Composition, Fitness Level, Testing Modality and Sex in Physically Active Population - Lach, Jacek; Wiecha, Szczepan; Śliż, Daniel; Price, Szymon; Zaborski, Mateusz; Cieśliński, Igor; Postuła, Marek; Knechtle, Beat; Mamcarz, Artur (Frontiers in Physiology, 2021)
Maximal heart rate (HRmax) is associated mostly with age, but age alone explains the variance in HRmax to a limited degree and may not be adequate to predict HRmax in certain groups. The present study was carried out on 3374 healthy Caucasian men and women including mostly sportspeople, ranging from recreational to professional. Cardiopulmonary exercise tests were carried out on treadmills or cycle ergometers to evaluate HRmax and maximum oxygen uptake (VO2max). Linear regression modelling was applied to establish the relationship between HRmax and age, and subsequently with fitness level, VO2max, body mass, age, testing device and body mass index (BMI). Mean HRmax predictions calculated with 5 previously published for-mulae were evaluated in subgroups created according to BMI, fitness level, sex, age and body fat. HRmax was univariately explained by a 202.5-0.53*age (yrs) formula (R2=19.18). The weak relationship may be explained by the low age SD. Adding further variables to the model increased the coefficient of determina-tion R2 significantly but not substantially in the case of body fat percentage and sex, by 0.0005 to 0.005 (p<0.05). Previously published formulae were less precise in the more outlying groups, especially overes-timating HRmax in older age groups and underestimating in younger. Of the previously published formulae, Tanaka’s offers the best overall prediction, while the 220-age formula yields remarkably high mean errors of up to 9bpm. The 202.5-0.53*age yielded lower mean errors in these groups, suggesting it could be used in more active individuals.