One can browse health and fitness websites for articles regarding training intensities, or pick up a book at Barnes and Noble on the topic, and likely encounter the ever-popular formula for predicting an athlete’s maximum heart rate (HRmax); 220-age. This traditional method for determining an athlete’s HRmax has been promoted for nearly 80 years, with the earliest citation in research being that of Fox, Naughton, and Haskell, published in 1971. Remarkably, no evidence has been produced to demonstrate the dependability of this age-predicted maximum heart rate (APMHR) formula (Robergs & Landwehr, 2002).
A study conducted in 2016 utilized HRmax data gathered from 4,796 participants and compared these results to their APMHR predictions. The authors of the study concluded that the error associated with using this APMHR formula was unacceptably high (Arena, Myers, & Kaminsky, 2016). Another study of particular interest in this matter is the 45-year longitudinal study of 26 elite male athletes that compared their HRmax values (among other biometrics) just prior to the 1968 Olympic games, and again in 2013. How accurately could the APMHR formula predict HRmax when these athletes were an average age of 24 years, and how accurate were the predictions when the formula was used 45 years later when the men were an average age of 69 years-old? Once again, this study further demonstrated the lack of reliability of the APMHR method of HRmax prediction, as the athletes’ HRmax values were grossly overestimated in 1968 (APMHR predicted to be 196 bpm, with actual HRmax values of 178) and grossly underestimated in 2013 (APMHR predicted to be 151 bpm, with actual values of 168 bpm) (Everman, Farris, Bay, & Daniels, 2017). While the individuals assessed in this study are atypical, the data still point to the ineffectiveness of the APMHR formula to accurately predict HRmax at the relative near and relative end of a person’s expected lifetime. While it may be simple to calculate, the APMHR formula of 220 minus age has been demonstrated to be untrustworthy.
In the third chapter of his book, Daniels’ Running Formula, Daniels points out the wild variability that can be observed in HRmax by highlighting an elite athlete whose actual HRmax was 148 bpm when the APMHR formula predicted a value of 190 bpm, a 32 bpm range of error. Conversely, Daniels identifies athletes in their 50s with HRmax values greater than 190 bpm whose APMHR should have been at least 20 bpm lower (Daniels, 2014).
So when does this play a significant role in training athletes? In order to elicit specific adaptations to training, athletes and coaches may use target heart rate zones. For example, Daniels describes easy paced running as a pace that elicits a heart rate between 65% and 79% of an athlete’s HRmax, and interval training to elicit 98-100% HRmax (Daniels, 2014). It also can be useful for determining when an athlete has recovered to the desirable level prior to beginning another work-bout, for example.
In light of the evidence (both empirical and anecdotal) that APMHR formula is not useful for determining an athlete’s HRmax, researchers have developed much more complex multivariate alternative formulas for predicting HRmax, all of which have been shown to be statistically unreliable as well (Robergs & Landwehr, 2002).
Because every individual is so unique, the best way I’ve found to determine the HRmax of one of the young distance athletes I train, is to gather heart rate data using a heart rate monitor during a maximal effort race. This kind of effort is likely to yield a reliable HRmax value without placing excessive strain on the athlete or place them at risk of harm since athletes in my care have been medically cleared to run distance races at maximal effort. Coupled with the average of a week's minimum heart rates (collected upon waking), heart rate percentages can be calculated on an individual basis for the aforementioned training purposes.
While this kind of data collection is not nearly as simple as using an HRmax prediction formula, it has been demonstrated to be the only reliable way to truly know the level of effort an athlete is putting forth during training.
References
Arena, R., Myers, J., & Kaminsky, L. A. (2016). Revisiting age-predicted maximal heart rate: Can it be used as a valid measure of effort? American Heart Journal, 173, 49-56.
Daniels, J. T. (2014). Daniels' running formula. Champaign, IL: Human Kinetics.
Everman, S., Farris, J. W., Bay, R. C., & Daniels, J.T. (2017). Elite distance runners: A 45-year follow-up. Medicine and Science in Sports and Exercise, 73-78.
Fox III, S. M., Naughton, J. P., & Haskell W. L. (1971). Physical activity and the prevention of coronary heart disease. Annals of Clinical Research, 3, 404-432.
Robergs, R. A., & Landwehr, R. (2002). The surprising history of the "HRmax=220-age" equation. Journal of Exercise Physiology Online, 5(2), 1-10.
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