Measurement in Physical Education and Exercise Science, 13: 1–12, 2009 Copyright © Taylor & Francis Group, LLC ISSN: 1091-367X print / 1532-7841 online DOI: 10.1080/10913670802609086
1532-7841 in Physical Education and Exercise Science 1091-367X HMPE Measurement Science, Vol. 13, No. 1, November 2008: pp. 1–29
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ARTICLES
Prediction of Maximum Oxygen Uptake Using Both Exercise and Non-Exercise Data Submaximal GEORGE ETTreadmill AL. Test
James D. George, Samantha L. Paul, Annette Hyde, Danielle I. Bradshaw, Pat R. Vehrs, and Ronald L. Hager Department of Exercise Sciences Brigham Young University
Frank G. Yanowitz University of Utah School of Medicine and The Fitness Institute at LDS Hospital
This study sought to develop a regression model to predict maximal oxygen uptake (VO2max) based on submaximal treadmill exercise (EX) and non-exercise (N-EX) data involving 116 participants, ages 18–65 years. The EX data included the participants’ self-selected treadmill speed (at a level grade) when exercise heart rate first reached at least 70% of predicted maximum heart rate (HRmax; 220 – age) by the end of any one of three 4-min consecutive stages involving walking (3.0–4.0 mph; Stage 1), jogging (4.1–6.0 mph; Stage 2), and running (> 6.0 mph; Stage 3). The N-EX data included various demographic (age, gender), biometric (body mass), and questionnaire (participants’ perceived functional ability [PFA] to walk, jog, or run given distances, and their self-reported level of physical activity [PA-R]) information. All participants (n = 100) who completed the study requirements and successfully achieved a maximal level of exertion during a graded exercise test (GXT) to assess VO2max (mean ± SD; 41.39 ± 9.15 ml · kg–1 · min–1) were included in the data analysis. Stepwise regression was used to generate the following prediction equation (R = .94, SEE = 3.09 ml · kg–1 · min–1): VO2max (ml · kg–1 · min–1) = 30.04 + (6.37 × gender; females = 0, males = 1) – (0.243 × age) – (0.122 × body mass) + (3.263 × ending self-selected treadmill speed; mph) + (0.391 × PFA) + (0.669 × PA-R). Each of the predictor variables were statistically significant (p < .001) and cross-validation procedures using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (Rp = .92 and SEEp = 3.29 ml · kg–1 · min–1). In summary, this submaximal treadmill test and accompanying regression model yields relatively accurate VO2max estimates in healthy men and women (ages 18–65 years) using both EX and N-EX data. Key words: maximum oxygen uptake, exercise testing, cardiorespiratory fitness Correspondence should be sent to James D. George, Ph.D., Department of Exercise Sciences, 228A Smith Fieldhouse, Brigham Young University, Provo, Utah 84602. E-mail:
[email protected]
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INTRODUCTION Maximum oxygen uptake (VO2max) is defined as the maximum ability to transport and consume oxygen during strenuous endurance exercise and is considered the single best measure of cardiorespiratory (CR) fitness. CR fitness is an important component of health-related physical fitness because higher levels enhance the ability to sustain large muscle, dynamic, moderate- to highintensity exercise (walking, jogging, or cycling) for prolonged periods, while lower levels elevate the risk of various disease conditions such as coronary artery disease, high blood pressure, stroke, obesity, and type 2 diabetes (American College of Sports Medicine (ACSM), 2006). The most accurate way to assess VO2max is during a maximal graded exercise test (GXT) performed to volitional exhaustion on a motorized treadmill or cycle ergometer. Although maximal GXTs accurately assess CR fitness, they are usually limited to laboratory and clinical settings because they are time consuming, involve costly equipment, depend on trained technicians to administer the tests, and require physician supervision in individuals who are stratified in the moderate- or high-risk categories based on current exercise testing guidelines (ACSM, 2006). In addition, maximal GXTs may be unappealing in some individuals who dislike exercising to the point of volitional exhaustion. Because of the potential drawbacks of maximal exercise testing, a number of VO2max regression equations have been developed to estimate CR fitness from various submaximal exercise (EX) data (exercise work rate and exercise heart rate (HR)), as well as demographic (age, gender) and biometric (body mass or body mass index (BMI)) information. Common submaximal test protocols involve walking (Ebbeling, Ward, Puleo, Widrick, & Rippe, 1991; Kline et al., 1987), jogging (George, Vehrs, Allsen, Fellingham, & Fisher, 1993a), and running (Cooper, 1968) on indoor/outdoor tracks or treadmills, cycling on ergometers (Astrand & Rhyming, 1954), bench stepping (Jette, Campbell, Mongeon, & Routhier, 1976), or performing the 20-meter shuttle run (Liu, Plowman, & Looney, 1992). Of these submaximal tests, those involving motorized treadmills as the exercise mode are appealing given that treadmill protocols are convenient and easy to administer, involve a familiar form of exercise (walking, jogging, and running), allow the exercise intensity to be easily regulated, and permit the health/fitness professional to constantly monitor the participant during the test. Additionally, motorized treadmills are widely available in university, community, and commercial fitness centers (ACSM, 2006). In 1991, Ebbeling et al. developed a submaximal treadmill protocol for healthy adults (20–59 years), involving walking up a 5% grade at 2.0, 3.0, 4.0, or 4.5 mph. The corresponding VO2max regression model includes age, gender, treadmill speed, and exercise HR as predictor variables and demonstrates acceptable accuracy (R = .93, SEE = 4.85 ml · kg–1 · min–1). Shortly thereafter, George, Vehrs, Allsen, Fellingham, & Fisher, (1993b) developed a submaximal treadmill test for healthy young adults (18–29 years), involving jogging at a level grade and a self-selected exercise pace (4.3–7.5 mph). The accompanying VO2max regression model, employing gender, body mass, exercise pace, and exercise HR as predictor variables, also demonstrates acceptable accuracy (Radj = .84, SEE = 3.2 ml · kg–1 · min–1). In like fashion, submaximal walking (Kline et al., 1987) and jogging (George et al., 1993a) track tests were developed and demonstrate similar predictive accuracy, along with a 1.5-mile track test involving walking, jogging, or running at a self-selected exercise pace (Larsen, George, Alexander, Fellingham, Aldana, & Parcell, 2002).
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Several non-exercise (N-EX) regression equations are also available to estimate VO2max without the need to perform a maximal or submaximal exercise test. In 1990, Jackson, Blair, Mahar, Wier, Rossand, & Stuteville generated a N-EX regression model (R = .81, SEE = 5.35 ml · kg–1 · min–1) utilizing age, gender, body mass index (BMI), percent body fat, and physical activity rating (PA-R) as predictor variables in a sample involving healthy adults (ages 18–70 years). Subsequently, in a college-age sample, George, Stone, & Burkett (1997) improved on the predictive accuracy (R = .86, SEE = 3.34 ml · kg–1 · min–1) of previous N-EX regression models by adding an additional predictor variable involving the participants’ perceived functional ability (PFA) to walk, jog, or run given distances (e.g., 1 and 3 miles) at a comfortable pace. In 2005, Bradshaw, George, Vehrs, Hager, LaMonte, & Yanowitz also demonstrated an improvement in predictive accuracy when including PFA in a N-EX regression model (R = .93, SEE = 3.45 ml · kg–1 · min–1) involving healthy adults ages 18–65 years. To date, it appears that the PFA predictor variable has been employed in two N-EX regression models (Bradshaw et al., 2005; George et al., 1997). However, this predictor variable may also improve VO2max predictions in exercise-based regression models that include EX data (work rate, heart rate) along with N-EX data (age, gender, body mass, PA-R). Thus, the primary purpose of this study was to determine whether or not the PFA predictor variable in combination with other predictor variables can account for a statistically significant amount of VO2max variance in an exercise-based regression model. A second purpose was to improve on the work of Ebbeling et al. (1991) and develop a submaximal treadmill test that includes not only walking but also jogging and running as possible exercise options in order to better match the varying fitness levels and exercise habits of healthy adults.
METHODS Participants One hundred sixteen participants, contacted through college classes at Brigham Young University, the Y-Be-Fit Wellness Program at Brigham Young University, and employees from the LDS Hospital in Salt Lake City, Utah, were recruited to participate in this study. In accordance with ACSM guidelines (ACSM, 2000) for vigorous exercise, any individuals at a moderate or high level of risk were tested at the LDS Hospital (using a five-lead electrocardiogram as part of the testing protocol) with an attending physician in close proximity and readily available to assist with any emergency. Before data collection, each participant signed an informed consent document, and all research methods and procedures were approved by the BYU and LDS Hospital Institutional Review Boards for Human Subjects. Procedures To prepare for exercise testing, participants were instructed to come to the BYU Human Performance Research Center or the LDS Hospital dressed in lightweight clothing and comfortable exercise shoes, and to avoid any fatiguing exercise the day of the test. Participants were also instructed to avoid large meals, caffeine, alcohol, and tobacco products within at least three hours of their appointment (ACSM, 2006). Before the submaximal treadmill test, a test
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administrator measured the height (cm) and body mass (kg) of each person (wearing no shoes) using a stadiometer and balance beam scale, respectively. In addition, participants completed the PFA (George et al., 1997) and a modified PA-R questionnaire (Bradshaw et al., 2005; George et al., 1997; Jackson et al., 1990). The PFA includes two questions that ascertain how fast participants feel they can cover a 1- and 3-mile distance at a comfortable pace. The sum of the participants’ two 13-point questions count as the PFA score (range 2–26). The PA-R questionnaire has individuals rate their level of physical activity on a 10-point scale over the past six months.
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Submaximal Treadmill Test For the submaximal treadmill test, participants exercised at a self-selected steady pace at level grade until their exercise heart rate rose to at least 70% of age-predicted maximum heart rate (HRmax; 220 – age) while moving through three consecutive 4-min stages that progressively increased in intensity from walking (3.0–4.0 mph) in stage 1, to jogging (4.1–6.0 mph) in stage 2, and to running (> 6.0 mph) in stage 3. The self-selected pace within each stage was determined by the participant who would use hand signals to inform the test administrator to either increase or decrease the treadmill speed until the pace was comfortable (e.g., not too easy and not too hard). The self-selected pace was set within the initial 20 sec of a given stage. When participants reached at least 70% of age-predicted HRmax at any time during a given stage, participants completed that stage and then the treadmill was decreased to a slow walking pace for a 2- to 5-min cool down. When the age-predicted HRmax cut-point was not reached in a given stage, participants progressed immediately to the next stage of the treadmill test. Exercise heart rate (HR) was measured with either an electronic heart rate monitor (Polar, Levittown, PA) or a five-lead electrocardiogram (ECG). The self-selected treadmill speed, exercise stage, exercise HR, and ratings of perceived exertion (RPE; 15-point scale; Borg, 1982) were recorded during the last 15 sec of each completed exercise stage. Maximal Treadmill Graded Exercise Test After the submaximal treadmill protocol, participants performed a maximal GXT using the Arizona State University (ASU) maximal protocol (George, 1996; George et al., 2007), with a slightly modified warm-up. In the time between the submaximal and maximal tests (5–10 min), a test administrator briefly summarized the test procedures for the maximal GXT and assisted participants in putting on the necessary head-gear, mouthpiece, and nose clip. The ending treadmill speed of the submaximal test served as the exercise pace for the maximal GXT. During the maximal protocol, the treadmill grade was increased 1.5% each minute, while the speed remained constant. Participants continued to exercise until they reached a maximal level of exertion and were unable to continue despite verbal encouragement. After the test, the treadmill speed (mph) maintained during the exercise was recorded, along with the final treadmill grade (%) that was sustained for a full minute at the end of the test. The VO2 and respiratory exchange ratio (RER) were computed, averaged, and printed by an on-line computer system every 15 sec. During the maximal GXT, the participants’ exercise HR and RPE scores were recorded at the end of each exercise stage, and metabolic gases were continuously collected using the TrueMax 2400 metabolic measurement system (Consentius
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Technologies, Sandy, UT). VO2max was calculated as the average of the highest four consecutive 15-sec scores near the end of the GXT. To consider a given VO2max as valid, at least two of the following three criteria were satisfied (Ebbeling et al., 1991; Howley, Bassett, & Welch, 1995; Kline et al., 1987):
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1. Maximum heart rate (HRmax) within 15 beats of age-predicted maximal heart rate (using the equation: 220 – age). 2. Maximum respiratory exchange ratio (RERmax) equal to or greater than 1.10. 3. No increase in VO2 despite an increase in workload. Of the 116 participants in the study, all were stratified in either the “low” or “moderate” risk categories according to ACSM guidelines (ACSM, 2000). After evaluating the submaximal treadmill data, four participants were dropped from the analysis because they self-selected relatively high exercise intensities (e.g., age-predicted HRmax of greater than 90%) in their final exercise stage of the submaximal treadmill test. In addition, 12 participants were excluded because they failed to satisfy at least two of the three criteria during the maximal GXT. Statistics Multiple linear regression was used to generate multivariate VO2max regression equations for those participants (n = 100; 50 female, 50 male) who successfully completed the requirements of the study. To determine the contribution and statistical significance of the possible VO2max prediction variables (e.g., gender, age, body mass, BMI, final self-selected treadmill speed, ending exercise heart rate (HR), ending treadmill stage, PFA, and PA-R), the data were evaluated using a stepwise model selection tool (SAS; Cary, NC). The relative accuracy of the VO2max prediction model was evaluated using correlation coefficients, standard error of estimates (SEEs), and the percent SEE (SEE ÷ mean VO2max). In addition, predicted residual sum of squares (PRESS) statistics (Holiday, Ballard, & McKeown, 1995) were calculated to estimate the degree of shrinkage one could expect when the VO2max prediction equation is used across similar but independent samples. Finally, a Pearson correlation was calculated to assess the strength of the relationship between predicted versus measured HRmax, along with a paired t-test to compare the mean difference between these two variables. Statistical significance was set at p < .05.
RESULTS Descriptive statistics of the participants (n = 100) and specific sub-groups are presented in Tables 1–3. Participants’ body mass, BMI, PFA, and PA-R scores ranged from 48.1–115.9 kg, 19.3–38.9 kg · m–2, 2–26, and 1–10, respectively. During the final stage of the submaximal treadmill test, the participants’ self-selected treadmill speed ranged from 3–8 mph (mean ± SD = 5.3 ± 1.0 mph) with 7 participants reaching at least 70% HRmax (age-predicted HRmax) during the walking stage (3.0–4.0 mph), 75 participants during the jogging stage (4.1–6.0 mph), and 18 participants during the running stage (> 6.0 mph; see Table 3). During the maximal GXT, participants’ HR, RER, and RPE responses (mean ± SD) reflected a maximal level of exertion (HRmax = 185.2 ± 13.2 bpm; RERmax = 1.17 ± 0.05; RPEmax = 19.0 ± 0.8)
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TABLE 1 Descriptive Statistics for the Total, Younger, and Older Participants
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Variable Age (yr) Female Male Height (m) Body mass (kg) Body mass index (kg · m–2) Perceived functional ability (PFA) Physical activity rating (PA-R)
Total (n = 100)
18–39 yr (n = 57)
40–65 yr (n = 43)
M
SD
M
M
36.2 50 50 1.72 74.86 25.25 14.8 4.8
13.2
0.09 15.29 4.00 4.8 2.3
26.1 30 27 1.73 73.92 24.50 16.2 4.6
SD 5.7
0.10 14.43 3.26 3.9 2.0
49.7 22 21 1.70 76.11 26.23 12.8 5.1
SD 6.7
0.08 16.46 4.68 5.3 2.5
Submaximal treadmill values Ending treadmill speed (mph) HR (bpm) %HRmaxa RPE (15-point scale) Final exercise stage (1–3)
5.3 147.7 80.4 12.7 2.1
1.0 12.4 4.3 1.7 0.5
5.6 154.7 79.8 12.7 2.2
0.9 9.6 3.9 1.9 0.5
4.7 138.5 81.3 12.6 1.9
1.0 9.1 4.7 1.5 0.5
Maximal treadmill test HRmax (beats · min–1) RPEmax (15-point scale) RERmax (VCO2 ÷ VO2) VO2max (L · min–1) VO2max (ml · kg–1 · min–1)
185.2 19.0 1.17 3.08 41.39
13.2 0.8 0.05 0.88 9.15
193.4 19.1 1.15 3.41 46.11
8.1 0.8 0.04 0.83 6.39
174.3 18.9 1.19 2.64 35.12
10.4 0.8 0.05 0.75 8.50
Note: All data = mean ± SD. %HRmax = ([measured exercise HR ÷ age-predicted maximum HR (220 – age)] × 100).
a
with the mean (± SD) VO2max equal to 41.39 ± 9.15 ml · kg–1 · min–1 (range = 20.2–60.1 ml · kg–1 · min–1). The Pearson correlation between predicted HRmax (220 – age) and measured HRmax reflected an acceptable value (r = 0.83), and the paired t-test (n = 100, t = 1.79, p = .076) showed no statistical difference between these two variables. The stepwise regression analysis yielded the following age-generalized VO2max prediction equation: (R = .94, SEE = 3.09 ml · kg–1 · min–1, n = 100; Table 4: VO2max (ml · kg–1 · min–1) = 30.04 + (6.37 × gender; females = 0, males = 1) – (0.243 × age) – (0.122 × body mass) + (3.263 × ending self-selected treadmill speed; mph) + (0.391 × PFA) + (0.669 × PA-R). Each predictor variable was statistically significant (p < .001) in predicting VO2max, explaining 88.6% (R2 = .886) of the variance of VO2max. Of the initial nine possible predictor variables, the stepwise regression analysis dropped three from the model, including BMI, ending exercise HR, and ending treadmill stage. Based on standardized β-weights (Table 4), ending self-selected treadmill speed (0.362) explained the largest amount of variance in VO2max scores followed by age (–0.352), gender (0.350), PFA (0.207), body mass (–0.204), and PA-R (0.165). The cross-validation PRESS statistics (Rp = .92 and SEEp = 3.29 ml · kg–1 · min–1), demonstrated minimal shrinkage in the accuracy of the regression model (see Table 4). Figure 1 provides a scatter plot of predicted versus observed VO2max values. In addition, regression models were generated for the
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TABLE 2 Descriptive Statistics for the Total, Female, and Male Participants
Variable
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Age (yr) Height (m) Body mass (kg) Body mass index (kg · m–2) Perceived functional ability (PFA) Physical activity rating (PA-R)
Total (n = 100)
Females (n = 50)
Males (n = 50)
M
SD
M
SD
M
SD
36.2 1.72 74.86 25.25 14.8 4.8
13.2 0.09 15.29 4.00 4.8 2.3
36.4 1.65 65.72 23.97 13.3 4.9
13.9 0.07 11.64 3.79 4.8 2.3
36.1 1.78 84.00 26.52 16.2 4.8
12.7 0.06 12.90 3.84 4.5 2.3
Submaximal treadmill values Ending treadmill speed (mph) HR (bpm) %HRmaxa RPE (15-point scale) Final exercise stage (1–3)
5.3 147.7 80.4 12.7 2.1
1.0 12.4 4.3 1.7 0.5
4.9 149.5 81.4 12.7 2.0
0.9 13.3 4.7 1.8 0.5
5.6 146.0 79.4 12.7 2.2
1.0 11.2 3.7 1.7 0.5
Maximal treadmill test HRmax (beats · min–1) RPE (15-point scale) RER (VCO2 ÷ VO2) VO2max (L · min–1) VO2max (ml kg–1 min–1)
185.2 19.0 1.17 3.08 41.39
13.2 0.8 0.05 0.88 9.15
183.0 19.1 1.16 2.42 37.66
15.1 0.6 0.05 0.48 8.71
187.5 18.9 1.18 3.74 45.11
10.6 0.9 0.06 0.67 8.05
Note: All data = mean ± SD. %HRmax = ([measured exercise HR ÷ age-predicted maximum HR (220 – age)] × 100).
a
gender-specific subsamples, with the male sample (R = .93, SEE = 2.87 ml · kg–1 · min–1, n = 50) slightly more accurate in estimating VO2max than the female sample (R = .93, SEE = 3.22 ml · kg–1 · min –1, n = 50).
DISCUSSION The age-generalized VO2max regression model developed in this study is noteworthy because it provides a relatively accurate prediction of CR fitness (R = .94; SEE = 3.09 ml · kg–1 · min–1; Table 4) using a unique combination of both EX and N-EX predictor variables in a sample of healthy men and women, ages 18–65 years. Previous exercise-based studies include demographic, biometric, and exercise data (such as age, gender, body mass, and exercise pace) in VO2max regression models, but this appears to be the first exercise-based study that also includes meaningful questionnaire data (PFA and PA-R responses) in the same equation. Interestingly, the accuracy of this model meets or exceeds that of other age-generalized equations (R = .71–.94; SEE = 3.12–4.85 ml · kg–1 · min–1) involving submaximal or maximal treadmill tests (Bruce, Kusumi, & Hosmer, 1973; Ebbeling et al., 1991; George, 1996; George et al., 2007), submaximal track tests (Kline et al., 1987), and N-EX regression models (Bradshaw et al., 2005; Jackson et al., 1990). It is not surprising that the participants’ ending self-selected treadmill pace explains the largest amount of VO2max variance (based on the standardized β-weights; Table 4), since a low-fit,
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TABLE 3 Descriptive Statistics for the Walkers, Joggers, and Runnersa
Variable
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Age (yr) Height (m) Body mass (kg) Body mass index (kg · m–2) Perceived functional ability (PFA) Physical activity rating (PA-R)
Walkers (n = 7)
Joggers (n = 75)
Runners (n = 18)
M
SD
M
SD
M
SD
49.6 1.70 83.10 28.53 10.7 5.7
10.5 0.08 20.17 5.24 5.4 2.6
36.3 1.71 74.90 25.39 14.4 4.7
13.5 0.09 15.21 4.00 4.6 2.2
30.7 1.74 71.52 23.37 17.6 5.2
8.9 0.10 13.05 2.38 4.3 2.3
Submaximal treadmill values Ending treadmill speed (mph) HR (bpm) %HRmaxb RPE (15-point scale)
3.3 133.9 78.6 10.4
0.3 8.1 4.2 1.1
5.1 148.7 81.0 12.6
0.7 12.3 4.3 1.5
6.5 148.9 78.6 14.1
Maximal treadmill test HRmax (beats · min–1) RPE (15-point scale) RER (VCO2 ÷ VO2) VO2max (L · min–1) VO2max (ml · kg–1 min–1)
173.9 19.4 1.18 2.33 28.55
17.0 0.5 0.0 5 0.56 6.68
185.5 19.0 1.17 3.04 40.63
13.4 0.8 0.05 0.85 7.89
188.1 19.0 1.17 3.55 49.53
a
0.8 11.0 4.1 1.7 8.5 0.8 0.06 0.89 7.73
Participants (n = 100) categorized as walkers, joggers, or runners based on their final submaximal exercise stage when exercise HR initially equaled 70–90% HRmax. b %HRmax = ([measured exercise HR ÷ age-predicted maximum HR (220 – age)] × 100).
TABLE 4 VO2max Regression Equation (n = 100) Variable Intercept Gender (0 = female, 1 = male) Age (yr) Body mass (kg) Ending self-selected treadmill speed (mph) Perceived functional ability (PFA) Physical activity rating (PA-R) R2 R SEE (ml · kg–1 · min–1) % SEE (% of VO2max) RPRESS SEEPRESS (ml · kg–1 min–1)
b 30.04 6.37 0.243 0.122 3.263 0.391 0.669 0.89 0.94 3.09 7.5 0.92 3.29
Note: All predictor variables p < .001. β-weights = standard multiple regression coefficients. RPRESS = (1-(PRESS/SStotal))–1/2. SEEPRESS = (PRESS/n)–1/2.
b-weight
0.350 −0.352 −0.204 0.362 0.207 0.165
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Predicted VO2max (mL·kg–1·min–1)
70 60 50 40 Females
30
Males 20 10 10
20
30 40 50 Measured VO2max (mL·kg–1·min–1)
60
70
FIGURE 1 Predicted VO2max vs. measured VO2max scatter plot.
average-fit, and high-fit person would most likely reach ≥ 70% of predicted HRmax in the walking, jogging, and running stage, respectively. However, the PFA and PA-R questionnaire data still account for an additional 8.1% of unique VO2max variance, not explained by the selfselected treadmill pace, age, gender, and body mass (a change in R2 from 0.804 to 0.885). The PFA variable likely contributes to the regression model because it further classifies participants as walkers, joggers, and runners based on their response to how fast they think they can cover a 1- and 3-mile distance at a comfortable pace. The PFA variable may do this by more fully accounting for key factors such as the lactate threshold and running economy (Bassett & Howley, 2000). Although less predictive, the PA-R variable also accounts for a significant amount of VO2max variance. This is logical since it is well documented that regular participation in aerobic exercise typically improves CR fitness or VO2max within a range of 5% to 30% during an endurance exercise program (ACSM, 2006). Along with the goal of creating an accurate VO2max regression model, this study sought to develop a submaximal treadmill protocol that allows participants of differing CR fitness levels to progress across three modes of exercise (walking, jogging, or running) until an appropriate submaximal exercise endpoint is reached (e.g., ≥ 70% age-predicted HRmax). Based on the sample’s age-predicted %HRmax data (range = 72–90%; mean ± SD; %HRmax = 80.4 ± 4.3%; Table 1), it appears that reasonable submaximal exercise intensities were achieved during the final stage of the treadmill test. In addition, it appears that participants reached this submaximal endpoint while performing an exercise mode that corresponds with their CR fitness level. For example, the mean VO2max for the 7 walkers, 75 joggers, and 18 runners equaled 28.55 ml · kg–1 · min–1, 40.63 ml · kg–1 · min–1, and 49.53 ml · kg–1 · min–1, respectively, which shows that as the person’s CR fitness increases, so does his or her ending submaximal exercise intensity. However, a possible concern is that some participants may self-select a treadmill exercise pace that is too high for their current ability, one that may approach a maximum exertion. In this case, the participant’s predicted VO2max score, as generated from the regression equation (Table 4),
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would be overestimated by 3.3 ml · kg–1 · min–1 for every 1 mph they are above a realistic submaximal treadmill speed, all else remaining equal. If this were to happen in the walking stage or jogging stage, the maximal amount a given VO2max prediction score could be overestimated would be 3.3 ml · kg–1 · min–1 and 6.3 ml · kg–1 · min–1, respectively, since the speed in the walking stage varies only 1 mph (from 3.0–4.0 mph) and the speed in the jogging stage varies 1.9 mph (from 4.1–6.0 mph). The running stage, on the other hand, has no upper exercise pace limit (> 6.0 mph) so this may be more of a concern assuming a person progresses to this stage. However, higher fit people are normally very familiar with what it means to exercise at a “comfortable, not too easy, and not too hard exercise pace,” so this may pose less of a potential problem. A possible way to minimize this concern is to use an upper exercise HR limit of 90% agepredicted HRmax for those who may self-select an exercise pace that is above their current ability. This is the rationale we used for truncating the present data set and removing four participants who had a relatively high ending exercise heart rate (HR > 90% of age-predicted HRmax). Our aim was to establish a reasonable upper exercise intensity limit so a mechanism could be in place to help ensure that participants stay within a submaximal exercise intensity. Thus, if a given participant were to self-select an excessively fast pace when using this treadmill protocol, the test administrator could simply repeat the test at a later time after educating the participant on how to select an appropriate submaximal exercise pace. Normally, it is best to use a measured maximum exercise HR when calculating exercise intensities for individuals who participate in CR exercise programs. However, when individuals undergo initial CR fitness testing, most health/fitness professionals do not have access to maximum HR data. Similarly, we did not have access to our participants’ measured maximum HR at the beginning of the current study. Therefore, we calculated an age-predicted (220 – age) HRmax value when establishing the 70% exercise HR cut-point and recommend that health/fitness professionals do the same when administering this treadmill protocol in a field or non-laboratory setting. According to ACSM, the age-based prediction formula (220 – age) is appropriate for healthy adults up to 65 years of age (ACSM, 2006). Unlike other submaximal field tests (Astrand & Ryhming, 1954; Ebbeling et al., 1991; George et al., 1993a; Kline et al., 1987), exercise HR was not found to be statistically significant in predicting VO2max and therefore was dropped from the regression model. This is probably the case because participants’ exercise HR values were all within a relatively narrow range of agepredicted HRmax (range = 72–90%; mean ± SD; %HRmax = 80.4 ± 4.3%) in the final exercise stage and therefore did not discriminate well between less-fit and more-fit individuals. It should also be noted that since exercise HR is not included in the regression model, it is unnecessary for participants to reach a steady-state HR (two heart rates within 5 bpm) during the last 2 min of a given 4-min exercise stage (ACSM, 2006). A potential factor influencing the accuracy of the regression models (Table 4) involves participants who naturally exhibit a higher- or lower-than-normal HR response and reach the 70% of age-predicted HRmax cut-point in an earlier or later exercise stage. When this occurs, measured VO2max may either be under- or overestimated depending on how the ending treadmill speed influences the VO2max prediction. To illustrate this, consider two examples from the current data set. The first includes a 36-year-old female who had a relatively high VO2max (42.7 ml · kg–1 · min–1), but met the ≥ 70% of age-predicted HRmax cut-point in the first stage while walking at 3.2 mph. In her case, measured VO2max was underestimated by 4.3 ml · kg–1 · min–1. In the second example, a 41-year-old female had a relatively low VO2max (32.9 ml · kg–1 · min–1)
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but failed to satisfy the HR requirement until reaching the second stage while jogging 5.4 mph. In her case, measured VO2max was overestimated by 4.2 ml · kg–1 · min–1. Nevertheless, the accuracy of these two isolated examples are relatively close to the SEE generated for the full regression model (SEE = 3.09 ml · kg–1 · min–1; Table 4). Subtle sample characteristics may also influence how well the VO2max prediction models (Table 4) can generalize to other healthy adults. In the current study, for example, the average (± SD) VO2max for females (37.7 ± 8.7 ml · kg–1 · min–1; n = 50) and males (45.1 ± 8.1 ml · kg–1 · min–1; n = 50) appears to be between the 60th and 70th percentile considering an average age of 30–39 years for both sexes (based on population norms; ACSM, 2006). Thus, the age-generalized regression model (Table 4) may predict VO2max more accurately in those who are slightly above average in terms of CR fitness. In addition, the PA-R data were somewhat unique in that the older age group exhibited a slightly higher mean physical activity score than the younger group (5.1 vs. 4.6; see Table 1). Nevertheless, the results of the PRESS analysis (Rp = .88–.93 and SEEp = 3.31–4.25 ml · kg–1 · min–1; Table 4) suggest that the regression model should provide acceptable accuracy when it is applied to independent samples of healthy adults with comparable biometric, physical activity, and CR fitness data. The ACSM (2006) recommends assessing CR fitness for the purpose of educating participants about their current health-related fitness status, providing data that are helpful in developing safe and effective exercise programs, collecting baseline and follow-up data that allow evaluation of participants’ progress, motivating participants by establishing reasonable and attainable fitness goals, and stratifying cardiovascular risk. The submaximal treadmill test developed in this study, along with the accompanying regression model, appear to be potentially useful in satisfying each of these recommendations. For example, the regression model provides an estimate of CR fitness that can be classified using norm- or criterion-referenced standards to further educate participants about their current CR fitness status or estimate potential cardiovascular risk (ACSM, 2006; Cureton & Warren, 1990). In terms of developing safe and effective exercise programs, the submaximal treadmill test requires participants to self-select a comfortable exercise pace and progress to a recommended heart rate training zone (≥ 70 age-predicted HRmax), which may be useful in teaching participants how to safely select and monitor their exercise intensity while walking, jogging, or running. In addition, health/fitness professionals can discuss how RPE scores should correspond to the exercise HR data and to exercise intensity recommendations. Based on the PFA questionnaire results, the health/fitness professional can reinforce or help to adjust participants’ fitness perceptions so there is a greater chance that safe and effective modes of exercise will be selected and realistic goals for improving functional ability will be set. Finally, based on the PA-R questionnaire results, health/fitness professionals can discuss current levels of physical activity with participants and, if necessary, set appropriate goals to help them reach a more desirable level. In conclusion, the submaximal treadmill test and accompanying multivariate regression model developed in this study provide accurate estimates of VO2max using EX and N-EX data in healthy adults ages 18–65 years. The submaximal exercise test allows participants to walk, jog, or run at exercise intensities appropriate for their fitness level, involves a common form of exercise, and does not require a maximal physical effort. The test is simple to administer, time-efficient, costeffective, educational, and poses a low risk of injury to healthy adults. In addition, the N-EX data are easy to collect, appear to provide meaningful information, and help to improve the accuracy of the regression model. Based on the cross-validation results, the predictive accuracy of the
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regression models should be comparable in similar samples of healthy adults; thus, this submaximal treadmill test appears to be a favorable test option when estimating and evaluating CR fitness.
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REFERENCES American College of Sports Medicine. (2000). ACSM’s guidelines for exercise testing and prescription (6th ed.). Philadelphia: Lippincott Williams & Wilkins. American College of Sports Medicine. (2006). ACSM’s guidelines for exercise testing and prescription (7th ed.). Philadelphia: Lippincott Williams & Wilkins. Astrand, P. O., & Ryhming, I. (1954). A nomogram for calculation of aerobic capacity (physical fitness) from pulse rate during submaximal work. Journal of Applied Physiology, 7, 218–221. Bassett, D. R., & Howley, E. T. (2000). Limiting factors for maximum oxygen uptake and determinants of endurance performance. Medicine and Science in Sports and Exercise, 32, 70–84. Borg, G. A. V. (1982). Psychophysical bases of perceived exertion. Medicine and Science in Sports and Exercise, 14, 377–381. Bradshaw, D., George, J. D., Vehrs, P. R., Hager, R. L., LaMonte, M. J., & Yanowitz, F. G. (2005). An accurate VO2max nonexercise regression model for 18- to 65-year-old adults. Research Quarterly for Exercise and Sport, 76(4), 426–432. Bruce, R. A., Kusumi, F., & Hosmer, D. (1973). Maximal oxygen intake and nomographic assessment of functional aerobic impairment in cardiovascular disease. American Heart Journal, 85, 546–562. Cooper, K. H. (1968). A means of assessing maximal oxygen uptake. The Journal of the American Medical Association, 203, 135–138. Cureton, K. J., & Warren, G. L. (1990). Criterion-referenced standards for youth health-related fitness tests: A tutorial. Research Quarterly for Exercise and Sport, 61, 7–19. Ebbeling, C. B., Ward, A., Puleo, E. M., Widrick, J., & Rippe, J. M. (1991). Development of a single-stage submaximal treadmill walking test. Medicine and Science in Sports and Exercise, 23, 966–973. George, J. D. (1996). Alternative approach to maximal exercise testing and VO2max prediction in college students. Research Quarterly for Exercise and Sport, 67(4), 452–457. George, J. D., Vehrs, P. R, Allsen, P. E., Fellingham, G. W., & Fisher, A. G. (1993a). VO2max estimation from a submaximal 1-mile track jog for fit college-age individuals. Medicine and Science in Sports and Exercise, 25(3), 401–406. George, J. D., Vehrs, P. R., Allsen, P. E., Fellingham, G. W., & Fisher, A. G. (1993b). Development of a submaximal treadmill jogging test for fit college-aged individuals. Medicine and Science in Sports and Exercise, 25, 643–647. George, J. D., Stone, W. J., & Burkett, L. N. (1997). Non-exercise VO2max estimation for physically active college students. Medicine and Science in Sports and Exercise, 29(3), 415–423. George, J. D., Bradshaw, D., Hyde, A., Vehrs, P. R., Hager, R. L., & Yanowitz, F. G. (2007). A maximal graded exercise test to accurately predict VO2max in 18- to 65-year-old adults. Measurement in Physical Education and Exercise Science, 11(3), 149–160. Holiday, D. B., Ballard, J. E., & McKeown, B. C. (1995). PRESS-related statistics: Regression tools for cross-validation and case diagnostics. Medicine and Science in Sports of Exercise, 27, 612–620. Howley, E. T., Bassett, D. R., Jr., & Welch, H. G. (1995). Criteria for maximal oxygen uptake: Review and commentary. Medicine and Science in Sports of Exercise, 27, 1293–1301. Jackson, A. S., Blair, S. N., Mahar, M. T., Wier, L. T., Rossand, R. M., & Stuteville, J. E. (1990). Prediction of functional aerobic capacity without exercise testing. Medicine and Science in Sports and Exercise, 22(6), 863–870. Jette, M., Campbell, J., Mongeon, J., & Routhier, R. (1976). The Canadian home fitness test. Canadian Medical Association Journal, 114, 680–683. Kline, G. M., Porcari, J. P., Hintermeister, R., Freedson, P. S., Ward, A., Mccarron, R. F., et al. (1987). Estimation of VO2max from a one-mile track walk, gender, age, and body weight. Medicine and Science in Sports of Exercise, 19, 252–259. Larsen, G. E., George, J. D., Alexander, J. L., Fellingham, G. W., Aldana, S. G., & Parcell, A. C. (2002). Prediction of maximal oxygen consumption from walking, jogging, or running. Research Quarterly for Exercise and Sport, 73, 66–72. Liu, N. Y. S., Plowman S. A., & Looney M. A. (1992). The reliability and validity of the 20-meter shuttle test in American students 12 to 15 years old. Research Quarterly for Exercise and Sport, 64, 360–365.
