Shargal E, Kislev-Cohen R, Zigel L, Epstein S, Pilz-Burstein R, Tenenbaum G. Age-related maximal heart rate: examination and refinement of prediction equations. J Sports Med Phys Fitness. 2015 Oct;55(10):1207-18. Epub 2014 Nov 12. PMID: 25389634.

J Sports Med Phys Fitness. 2015 Oct;55(10):1207-18. Epub 2014 Nov 12.

Age-related maximal heart rate: examination and refinement of prediction equations.

Shargal E(1), Kislev-Cohen R, Zigel L, Epstein S, Pilz-Burstein R, Tenenbaum G.

Author information:
(1)The Ribstein Center for Sports Medicine Sciences and Research, The Wingate Institute, Netanya, Israel - eyals@wingate.org.il.

AIM: The aim of this study was to establish the maximal heart rate (HRmax)-age relation with minimal error rate.

METHODS: The records of 28,137 participants (20,691 male and 7446 female, age range between 10 and 80 yrs) who performed a maximal stress test were used in this study. Linear regressions between HRmax and age were used for the entire sample, for the male and female samples, separately, and for each section of the gender-by-age category. The equations were then contrasted to a number of equations reported in the literature. The best fitted equations were then tested on a new sample of 2449 subjects (2091 males and 358 females) for validation purposes.

RESULTS: Mean HRmax values were found to decrease at a faster rate in women than in men with age increase. The linear regression functions within each age category were found to be less reliable than the equations derived for the entire sample and for the female and male samples, respectively. The new and updated HRmax prediction equations are as follows: HRmax=208.609-0.716age and 209.273-0.804age for males and females, respectively, and 208.852-0.741age for the entire sample. Those equations along with the other four best equations for predicting HRmax were found to be correlated with the observed HRmax values (validation sample): 0.64 and 0.664 for males and females, respectively.

CONCLUSION: Our equations were derived from a large data set and were found to be highly sensitive for both genders. Therefore, we propose that these new formulas, with their improved accuracy, be used in healthy active and clinical populations.


PMID: 25389634  [PubMed - in process]

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