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April 25, 2007Medicine & Science in Sports & Exercise664 citations

Longitudinal Modeling of the Relationship between Age and Maximal Heart Rate

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RGRonald GellishBGBrian R. GoslinRORonald E. Olson

Key Result

Age was found to predict maximal heart rate during exercise according to the longitudinal model HRmax = 207 - 0.7 x age (P<0.001), which differs from the conventional 220 - age formula.

Key Points

  • To examine the longitudinal relationship between aging and maximal heart rate during exercise to test whether individual trajectories match established cross-sectional prediction formulas.
  • Retrospectively analyzed maximal graded exercise test (GXT) data collected between 1978 and 2003 from N = 132 individuals across 908 total tests over a 25-year follow-up.
  • Employed linear mixed-models statistical analysis to model the rate of change in maximal heart rate as a function of age and fitness levels.
  • Generated a longitudinal univariate prediction model of maximal heart rate: HRmax = 207 - 0.7 × age.
  • Model parameters showed strong statistical significance (P < 0.001), differing substantially from the traditional 220 - age estimation formula.

Study Design

Type

Cohort (n=132)

Multicenter

No

Structured PICO

Does longitudinal tracking of maximal heart rate with age yield a different prediction equation than the conventional 220-age formula?

P
Population
132 individuals of both sexes representing a broad range of age and fitness levels, participating in a university-based health-assessment/fitness center, with multiple graded exercise tests (total N = 908) conducted over 25 years.
I
Intervention
Longitudinal tracking of maximal heart rate during graded exercise tests (GXT) as individuals age.
O
Outcome
Maximal heart rate (HRmax) prediction equation based on age.surrogate

Longitudinal tracking confirms that the relationship between age and maximal heart rate is best described by the equation HRmax = 207 - 0.7 x age, challenging the conventional 220 - age formula.

Main Result

p-value: p=<0.001

Abstract

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.

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Cite This Study

Gellish et al. (2007) conducted a cohort in General population (n=132). Age (longitudinal tracking) vs. Conventional HRmax formula (220 - age) was evaluated on Maximal heart rate (HRmax) during exercise (p=<0.001). Age was found to predict maximal heart rate during exercise according to the longitudinal model HRmax = 207 - 0.7 x age (P<0.001), which differs from the conventional 220 - age formula.

synapsesocial.com/papers/6a1308dcc031bb6829a7bfdahttps://doi.org/10.1097/mss.0b013e31803349c6
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