Longitudinal modeling of the relationship between age and maximal heart rate

Med Sci Sports Exerc. 2007 May;39(5):822-9. doi: 10.1097/mss.0b013e31803349c6.


Purpose: Maximal heart rate (HRmax)-prediction equations based on a person's age are frequently used in prescribing exercise intensity and other clinical applications. Results from various cross-sectional studies have shown a linear decrease in HRmax during exercise with increasing age. However, it is less well established that longitudinal tracking of the same individuals' HRmax as they age exhibits an identical linear relationship. This study examined the longitudinal relationship between age and HRmax during exercise.

Methods: A retrospective analysis of maximal graded exercise test (GXT) results for members participating in a university-based health-assessment/fitness center between 1978 and 2003 was undertaken in 2006. Records were examined from individuals (N = 132) of both sexes who represented a broad range of age and fitness levels and who had multiple GXT (total N = 908) conducted over 25 years. HRmax-prediction equations based on participants' age and HRmax elicited during the tests were developed using a linear mixed-models statistical analysis approach.

Results: Clinical measurements obtained during the administration of the GXT included in this longitudinal study resulted in the generation of a univariate prediction model: HRmax = 207 - 0.7 x age. Model parameters were highly statistically significant (P < 0.001).

Conclusions: The relationship between age and HRmax during exercise developed in this longitudinal study has resulted in a prediction equation appreciably different from the conventional HRmax formula (220 - age) often used in exercise prescription, and it confirms findings from recent cross-sectional investigations of HRmax.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Exercise Test
  • Female
  • Heart Rate / physiology*
  • Humans
  • Male
  • Michigan
  • Middle Aged
  • Physical Exertion / physiology*
  • Reference Values
  • Retrospective Studies
  • Texas