Journal of Strength and Conditioning Research Publish Ahead of Print DOI: 10.1519/JSC.0000000000000978
Cross-validation of Age-predicted Maximal Heart Rate Equations among Female Collegiate Athletes
Michael R. Esco1, Nik Chamberlain2, Andrew A. Flatt1, Ronald L. Snarr1, Phillip A. Bishop1,
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and Henry N. Williford2
Department of Kinesiology, University of Alabama, Tuscaloosa, AL
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Human Performance Laboratory, Auburn University at Montgomery, Montgomery, AL
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[email protected]
Michael R. Esco Department of Kinesiology University of Alabama Moore Hall 2008 Box 870312 Tuscaloosa, AL 35487-0312
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Corresponding Author:
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Maximal HR Female Athletes
ABSTRACT The purpose of this study was to determine the accuracy of three general and two female-specific age-predicted maximal heart rate (HRmax) prediction equations in female collegiate athletes. Thirty female collegiate athletes (age = 21.5 ± 1.9 years, height = 164.7 ± 6.6 cm, weight = 61.3 ± 8.2 kg) participated. HRmax was determined with a maximal graded exercise test and
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predicted with three general equations (Fox et al., Astrand, and Tanaka et al.) and two female specific equations (Fairnbarn et al. and Gulati et al.). There was no significant difference
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between observed HRmax (185.9 ± 5.0 beats.min-1) and the Fairbarn (187.5 ± 1.2 beats.min-1) and Gulati (187.1 ± 1.7 beats.min-1) equations (p = 0.11 and 0.23, respectively). The Fox (198.5 ± 1.9 beats.min-1), Astrand (198.1 ± 1.6 beats.min-1), and Tanaka (193.0 ± 1.4 beats.min-1) equations
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provided significantly higher estimates compared to observed HRmax (p < 0.001 for each). The standard error of the estimate was similar for all the prediction equations (between 5.0 and 5.4 beats.min-1), but the total error was smallest for Fairbarn and Gulati (5.3 beats.min-1 for each) and largest for Fox and Astrand (13.9 beats.min-1 and 13.3 beats.min-1, respectively). The 95% limits
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of agreement of the mean error were similar for all of the prediction equations with values varying between 9.9 and 10.5 beats.min-1. Due to the wide limits of agreement displayed by each equation, the use of age-predicted methods for estimating HRmax in collegiate female athletes
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should be performed only with caution.
Key Words: Women; Cardiovascular; Aerobic; Endurance
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Maximal HR Female Athletes
INTRODUCTION Maximum heart rate (HRmax), achieved when one’s heart rate reaches the greatest number of beats per minute possible during exercise, has many applications. To facilitate oxygen demand and blood distribution requirements to the working tissues during maximal physical exertion,
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heart rate increases above resting values until reaching a plateau (i.e., HRmax). This natural
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cardiac response to exercise is largely mediated by autonomic innervation of the heart wherein vagal withdrawal and sympathetic overdrive modulate contraction rate and intensity in response to work rate (27). HRmax generally decreases with age and is influenced by gender and fitness level (16, 17, 28). Though the most accurate method for determining HRmax requires maximal
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exercise testing, this is not often performed in practical settings and is often not justifiable. Instead, estimation of HRmax with the use of age-prediction equations has become a common practice.
HRmax is often used to determine target heart rate zones at specific exercise intensities (1);
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as a variable within certain predictors of aerobic power (25); and as a criterion that a maximal effort was achieved during a graded exercise test (3). However, age predicted HRmax formulas have been shown to provide wide ranges of individual error (24). Naturally, this can result in
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inaccurate exercise intensities, inflated estimates of aerobic power, and invalid criteria as a maximal effort determinate. The majority of research pertaining to HRmax estimation has been performed in non-
athletic men across a wide range of ages, with females being largely underrepresented (7). Of the limited research on this topic pertaining to women, general age-predicted HRmax formulas tend to significantly overestimate values in sedentary and college-age individuals (7, 14). Furthermore, there is a paucity of data available that has evaluated the validity of HRmax prediction equations
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Maximal HR Female Athletes
in young-adult female athletes. Specific research among this population is needed, especially considering that athletes typically have lower HRmax values compared to non-athletes (21). The purpose of this study was to determine the accuracy of three general and two female-specific
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age-predicted HRmax prediction equations in female collegiate athletes.
METHODS
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Experimental Approach to the Problem
HRmax values were measured in a group of female athletes (n = 30) via graded exercise testing and predicted with five age-predicted equations. Of the five prediction methods, the equations of Fox et al. (13), Astrand (2), and Tanaka et al. (24) are general models that are
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commonly used for estimating HRmax in non-athletic adults from the general population. The equations of Fairbarn et al. (12) and Gulati et al. (14) were developed to specifically be utilized for women. The accuracy of the five HRmax prediction equations were compared as independent
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variables to observed HRmax derived from graded exercise testing, which served as the dependent variable.
Participants
Thirty female collegiate athletes (age = 21.5 ± 1.9 years, height = 164.7 ± 6.6 cm, weight
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= 61.3 ± 8.2 kg) from the National Association for Intercollegiate Athletics sports volunteered to participate in the study. The study was approved by the University’s Institutional Review Board for Human Participants. Each participant provided written informed consent. The participants were recruited from the University’s soccer (n = 15), tennis (n = 8), and cross-country (n = 7) teams. Each participant completed a health history questionnaire which indicated that they were free from cardiopulmonary, metabolic, and orthopedic disorders. Data collection occurred during
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Maximal HR Female Athletes
any weekday between7:00am to 9:00am, as close as possible to awakening from sleep. Each participant was required to report to the laboratory following an overnight fast, though the consumption of water (12 oz) was allowed. They were told to avoid consuming stimulants (e.g., caffeine) or depressants (e.g., alcohol) and refrain from strenuous exercise for 24 hours prior to
place during the off-season when no athletic competitions occurred.
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Maximal Exercise Testing
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data collection. All of the participants verbally agreed to the testing conditions. The study took
Each participant completed a maximal graded exercise test on a treadmill (Trackmaster, Full Vision, Inc., Carrollton, TX). The Bruce protocol was used which involved a series of 3minute stages with consecutive increases in speed and grade. Expired gas fractions were
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evaluated with a metabolic cart (ParvoMedicsTrueOne® 2400 ,Sandy, UT). The test was terminated when the participant reached at least two of the criteria for maximal oxygen consumption (VO2max) as follows: a plateau in VO2 (± 2 ml.kg-1.min-1) with increasing work rate;
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respiratory exchange ratio > 1.10; Ratings of Perceived Exertion of at least an 8 out of 10; or volitional fatigue.
Heart rate was monitored continuously during the test with an electronic heart rate monitor (Polar Electro Oy, Kemple, Finland). The heart rate monitor was moistened and fitted to
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each participant’s chest at the level of the xiphoid process. When VO2max was reached, the highest HR value was recorded as observed HRmax. Predicted HRmax was determined with the
following equations of Fox et al. (13), Astrand (2), Tanaka et al. (24), Fairbarn et al. (12) and Gulati et al. (14): Fox
HRmax = 220 - age
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HRmax = 216.16 – (0.84 x age)
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Maximal HR Female Athletes
Tanaka
HRmax = 208 – (0.7 x age)
Fairbarn
HRmax = 201 – (0.63 x age)
Gulati
HRmax = 206 – (0.88 x age).
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Statistical Analyses All data were analyzed with a software package (SPSS version 22.0 Somers, NY, USA)
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and spreadsheet (Microsoft Excel 2010 Microsoft Corporation, Redmond, WA, USA). Means and standard deviations were determined for the observed and predicted HRmax values, which were compared with repeated measures analysis of variance followed up with paired T-tests to determine where differences existed. A Bonferroni adjusted p-value was applied to reduce the
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chances of obtaining a type I error when multiple pairwise tests were performed, which resulted in an adjusted alpha level for significance of p < 0.01. Cohen’s d statistic was calculated as the effect size of the differences in observed and predicted HRmax values (8) and Hopkin’s scale of
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magnitude was used where an effect size of 0-0.2 was considered trivial, 0.2-0.6 was small, 0.61.2 was moderate, 1.2-2.0 was large, >2.0 was very large (15). The standard error of the estimate (SEE), total error (TE) and constant error (CE) were calculated for each of the predicted versus observed HRmax values. The method of Bland-Altman was used to identify the 95% limits of
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agreement between the observed and predicted HRmax values (5). Significance for the trend between the mean and differences of each predicted versus actual HRmax was determined as alpha
