SELECfED METABOLIC RESPONSES TO SKATEBOARDING
A THESIS SUBMITTED TO THE GRADUATE DIVISION OF THE UNIVERSITY OF HAWArI IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
IN
KINESIOLOGY AND LEISURE SCIENCE
AUGUST 2004
By Ian K. Hunt
Thesis Committee:
Ronald K. Hetzler, Chairperson Iris F. Kimura Jan Prins iii ACKNOLEDGMENTS
Thank you Lia. Your unconditional support and encouragement made this all possible. Mom and Dad, your role in this achievement began the day I was born. Ronald
K. Hetzler, thank you for the countless early morning hours and guidance through the world of exercise physiology. Iris F. Kimura, I'll miss our short office chats. Jan Prins, thank you for all of your technical guidance. Lastly, I couldn't have done it without the many subjects who volunteered their time. iv ABSTRACf
SELECfED METABOLIC RESPONSES TO SKATEBOARDING
by Ian KHunt
Master of Science
University of Hawai'i at Manoa
Major Advisor: Ronald K. Hetzler
PURPOSE: This study used oxygen uptake (V0z) and heart rate (HR) responses to a skateboard treadmill test (TT) to estimate the metabolic responses to skateboarding during a field test (FT). METHODS: Ten skateboarders (age = 24.5 :l:: 3.1 yr.; weight =
1 74.2 :l:: 8.3 kg; height =176.2 :l:: 6.6 em; V02max =53.7 :l:: 5.2 ml·kg-1·min- ) participated in the TT and the FT. The FT consisted of 30-minutes of skateboarding while wearing a heart rate monitor. The HR data from each FT were used to estimate VOz. RESULTS:
The mean VOz for 30-minutes of skateboarding was estimated to be 28.6 ± 2.3 ml·kg-1·min-1. The mean caloric expenditure, assuming a mixed diet, was 308.6 ± 37.9
1 kcal (10.3 ± 1.3 Kcal·min- ). CONCLUSION: These data indicated that skateboarding could provide an adequate stimulus for increasing cardiorespiratory endurance and the intensity of self paced skateboarding may be adequate for inclusion in a weight management program. v TABLE OF CONTENTS
Acknowledgments iii Abstract iv List ofTables vi List of Figures , vii
Part I Selected Metabolic Responses to Skateboarding Introduction 1 Methods 3 Subjects: 3 Treadmill Tests: 3 Skateboard Treadmill Test Protocol: 4 Development of the Skateboard Treadmill Protocol: 5 Field Tests: 5 Metabolic Measurements: 6 Field Test Estimations and Calculations: 6 Ratings of Perceived Exertion (RPE): 7 Statistical Analysis: 7 Results 8 Physical Characteristics: 8 Metabolic Measures: 8 Heart Rate (HR) Oxygen Uptake Relationship: 10 Field-Tests (FT): 11 Differentiated Ratings of Perceived Exertion: 13 Discussion 14 Conclusion '" : 24
Part II: Review of Literature Skateboarding: 25 Differentiated Ratings of Perceived Exertion: 28
Factors That Influence the HR-V02 Relationship: 33 Energy Expenditure: '" 39
Appendix A. Raw Data Tables 48 Abbreviations 48 Appendix B. Forms 66 Informed Consent 67 Medical History Questionnaire 70 Par-Q 72 Skateboard Skill Assessment 73 Subject Letter 74 Appendix C. Statistics 75 References 93 vi LIST OF TABLES
1. Subject Characteristics 8
2. Skateboard Treadmill Test Metabolic Data 9
3. Individual HR-V02 Correlation Values 10
4. Individual Values From The Field-Test. 12
5. Individual V02 Reserve and Individual Estimated Mean V02 From Field-Test 13
6. Raw Data Tables 48 vii LIST OF FIGURES
Figure Page
1. Heart Rate and Estimated V02 During Field Test 16
2. Relationship of Mean Values for V02 and Heart Rate 17
3. Individual Subject HR-V02 Relationships 18
4. RPE Subjects 1-5 23
5. RPE Subjects 6-10 23 1 PART I
SELECTED METABOLIC RESPONSES TO SKATEBOARDING
Introduction
This study was undertaken to investigate selected physiological responses to the sport of skateboarding. Participation in skateboarding has increased dramatically over the last decade; however, little is known about its potential to impact physical fitness.
The National Sporting Goods Association reported in 1992 that 5.5 million individuals participated in skateboarding more than once. In 2002, it was reported that this number had increased to 9.7 million, a 75% increase over the last decade (NSGA, 2002).
Therefore, annual participation in skateboarding is similar to tennis (11 million) and volleyball (11.5 million), and skateboarding participation exceeds alpine skiing (7.4 million) and snowboarding (5.6 million) (NSGA, 2002). It was estimated that 5.8 million children and adolescents under the age of 18 had participated in skateboarding in 1996, and an estimated 750,000 participated on a weekly basis (CIPP, 2002).
In the past 25 years the annual incidence of skateboarding related injuries requiring medical treatment have risen and fallen. Annual injuries peaked in 1977 at
150,000, fell in 1983 to 16,000, rose in 1994 to 24,000 in individuals under the age of 20, and rose again to about 51,000 in 1999 (CIPP, 2002). Although these numbers appear alarming, Kyle et al. (2002) using participation exposure based estimates revealed that, in
1998, the rate of emergency department treated (ED) injuries were 8.9 injuries per 1000 participants. This value is twice tharof "in-line" skating (3.9 per 1000), and 2 approximately half that of basketball (21.2 per 1000) and football (20.7 per 1000).
Consequently, Kyle et al. (2002) concluded that skateboarding is a comparatively safe sport.
With millions of children participating in skateboarding world wide, there is a surprising lack of research on the sport. A search on the PubMed® database revealed 48 studies relating to skateboarding injuries and one paper from 1980 examining the biomechanical aspects of the sport. It appears that no metabolic research has been published on skateboarding. Therefore, the rise in the popularity of skateboarding, coupled with the absence of published works examining the metabolic responses to skateboarding,, indicates further study is warranted. The purpose of the present study was to examine the following questions: (1) will skateboarding in the field at a self selected pace elicit exercise responses sufficient to increase aerobic fitness; and, (2) is skateboarding a beneficial mode ofexercise for someone who is trying to lose or manage their weight? This was accomplished by: first, establishing an individual heart rate oxygen uptake relationship during an incremental skateboard treadmill test; and second, using heart rate data collected during a 30-minute field test and oxygen uptake data from the skateboard treadmill test to estimate the metabolic responses to skateboarding in the field. In addition, differentiated ratings of perceived exertion data were gathered during the skateboard treadmill test in order to examine the effect the different roles the two legs have on perception of effort. 3
Methods
Subjects:
Eight males and two females volunteered to participate in the study (age =24.5 ±
3.1 yr; weight =74.2 ± 8.3 kg; height =176.2 ± 6.6 cm; % fat =11.5 ± 6.2 %; VOzmax =
53.7 ± 5.2 ml-kg-1-min-1)(mean ± SD). Height was determined using a stedometer and weight was determined using a Detecto® scale (model 442). Skinfolds were taken using a Lange caliper and body composition was estimated from the sum of seven skinfolds
(Jackson and Pollock, 1985). The subjects included nine recreational and one professional skateboarder (Gravity Games gold medalist in the four-man downhill event).
Subjects were required to fill out a questionnaire to determine if their skill level was adequate to safely participate in the study. The criteria in the questionnaire included: at least one year of experience skateboarding, the ability to perform an "Ollie" (a fundamental trick that allows the skateboarder to jump, maintaining contact with the board, and land under control), and the ability to skate for an hour without taking a break.
If the criteria were met, subjects were required to participate in a practice session to familiarize them selves with skateboarding on a treadmill. All subjects were able to safely skateboard on the treadmill. Written consent was obtained in compliance with the
Institutional Review Board's Committee On Human Studies.
Treadmill Tests:
The subjects participated in two treadmill tests separated by at least 48 hours.
During the first visit to the laboratory, anthropometric measures were taken, the subjects participated using the standard Bruce Protocol to determine V02max while running, and 4 they had an opportunity to practice skateboarding on the treadmill. During the second
visit, subjects participated in the skateboard treadmill test.
Skateboard Treadmill Test Protocol:
All laboratory protocols were conducted on a Quinton Medtrack T65 treadmill.
The 10 stages of the treadmill test were as follows: stage 1 consisted of skateboarding at
134 memin-1 (5 mph) at 0% grade; stage 2 consisted of 134 memin- 1 at 1.5% grade; in the
subsequent 8 stages speed was incrementally increased by 13.4 memin- 1 (0.5 mph) while
remaining at 1.5% grade. The final stage, stage 10, was performed at 241.2 memin- 1 (9
mph) at 1.5% grade. Each stage consisted of three minutes of skateboarding followed by
30 seconds of rest.
While skateboarding, the subjects' legs performed different functions. One leg, the support leg, supported the weight of the body; while the other leg, the kicking leg,
was used to propel the body forward. Once the subject gained enough momentum, the
kicking leg was placed back on the skateboard. At this point the kicking leg and support
leg were both used to support the weight of the body (support position). As the
skateboard slowed, the subject resumed kicking in order to maintain their position on the
treadmill.
During the 3-minute stages, the subjects were not required to kick continuously.
They were allowed to assume the support position and coast for a few seconds, thus
relieving the stress on the support leg. They were also required to kick with the same leg
throughout the entire test. This sequence continued throughout the protocol, and
resembled regular skateboard field technique. At the conclusion of the stage, the subjects
. rested for 30 seconds by assuming the support position and holding on to the side rails of 5 the moving treadmill. This rest period was found to be necessary to relieve support leg fatigue. Fatigue of the support leg appeared to be the limiting factor in respect to how many stages the subject could complete. This protocol was designed to establish individual heart rate-oxygen uptake relationships, not to elicit maximal responses.
Development of the Skateboard Treadmill Protocol:
Three months of pilot work were performed to establish a skateboard treadmill protocol that increased heart rate (HR) to a level that included a range of values found during pilot field tests. Various grade and speed combinations were investigated. At 0% grade, HR could not be elevated to the necessary levels without using a speed above 268 m-min- l (10 mph). At this speed, the skateboard becomes more difficult to control.
Through trial and error, it was found that to safely achieve a HR in the desired range, the grade needed to be at least 1.5%. The length of each stage (3-min) was established to elicit steady state (Astrand and Rohdal, 1977), but not long enough to cause unbearable fatigue in the support leg.
Field Tests:
Subjects either participated in the field test 30 minutes after the skateboard treadmill test, or returned to the laboratory a third time. The field test consisted of 30 minutes of continuous skateboarding, on a smooth concrete surface, around the outer concourse of a university sports arena. In this indoor setting, the subjects could skate without interruption in a controlled environment. Subjects were required to wear a Pola:r® heart rate monitor that recorded HR at I-minute intervals. Heart-rate data were later downloaded onto a computer for analysis. 6
Metabolic Measurements:
Metabolic data were collected continuously throughout the treadmill test. Heart rate data were collected electrocardiographically (Quinton 710. Respiratory gasses were continuously collected and data were averaged over 30 second intervals. Metabolic responses were monitored using standard open-circuit spirometry techniques (Applied
Electrochemistry OCM-2). The instruments were calibrated using commercially available "Primary Standard" grade gasses (BOC Gases: Port Allen, LA). During the field tests, heart rate data were collected using a wristwatch HR monitor (Polar Vantage
NV). Data were downloaded to a computer and analyzed using the Polar Performance
Software version 2.0 for windows. The same skateboard was used in all tests. The skateboard was built specifically for this study using the following components: Natural
Koncept Canadian Beast skateboard deck (width: 20.5 em; length: 84.5 em), Independent
159 trucks (width: 15.9 em), and 56 mm wheels.
Field Test Estimations and Calculations:
Heart rate data were collected in one-minute intervals during the 3D-minute field test. The mean HR for each 5-minute period was established and used to estimate the oxygen uptake. This was accomplished using an individualized V02 - HR regression lines previously established for each subject. Caloric expenditure was calculated based
on a respiratory quotient chosen to represent a mixed diet (R.Q. =0.85; 4.862 kcal/L02).
Total caloric expenditure for the 30-minute field test was estimated from the sum of the
V02 values for each 5-minute period. Percent V02 reserve was calculated as presented 7 in ACSM Guidelines For Exercise Testing and Prescription (Franklin, 2000).
Ratings of Perceived Exertion (RPE):
During the initial meeting with the subjects, they were instructed in the use of the
Borg (6-20) category RPE-Scale (Borg, 1962). The subjects were read instructions for differentiated measures of perceived exertion as previously described by Pandolf et al.
(1975). The RPE-Local rating was subdivided into perceptions of effort for the support leg and for the kicking leg.
Statistical Analysis:
Data were analyzed using SAS®. Descriptive data including means and standard deviations were generated. Linear regression was used to establish the individual V02
HR regression lines which were subsequently used to estimate caloric expenditure. An
ANOVA for repeated measures was used to analyze the ratings of perceived exertion data. The alpha level was set at 0.05. 8 Results
Physical Characteristics:
The individual and mean values for age, weight, height, % body fat and V02max are presented in Table 1.
Table 1. Subject characteristics' individual values, means and standard deviations (SD).
Age Weight Height % Body Fat V0 Subjects 2max (yrs) (kg) (cm) (J&P7 site) (ml.kg-l·min-l)
1 27 80.5 182.9 10.14 59.0 2* 23 68.4 175.3 20.91 52.2 3 25 68.1 169.9 11.7 49.3 4* 21 63.4 169.4 23.33 58.8 5 21 69.5 168.9 7.59 56.3 6t 27 72.7 175.6 9.57 54.2 7 21 75.2 187.0 4.8 45.2 8 28 89.1 183.7 13.4 51.5 9 29 69.5 170.9 9.0 49.2 10 23 85.2 178.4 4.7 61.4
Mean 24.5 74.2 176.2 11.5 53.7 SD 3.1 8.3 6.6 6.2 5.2 *Female subjects t Professional skateboarder
Metabolic Measures:
Heart rate, oxygen uptake, respiratory exchange ratio, and RPE (overall) data are presented in Table 2. Table 2. The means and standard deviations of specific metabolic data collected during the skateboard treadmill test. Stages 1 2 3 4 5 6 7 8 9 10 n= 10 10 10 10 10 10 10 9 7 6
l HR (beats·min- ) Mean 120 134 141 147 153 162 167 169 172 173 SD 16 14 15 16 16 19 17 12 14 10
l Mean V02 (L·min- ) 1.7 2.0 2.1 2.2 2.3 2.5 2.6 2.7 2.8 2.9 SD 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.5
1 Mean V02 (ml.kg-1·min- ) 23 27 28 29 31 34 35 36 38 39 SD 2.4 2.4 1.9 2.4 3.2 3.0 3.3 2.8 3.4 3.3
Mean V02 (Allometric) 94.1 112.1 117.8 121.2 128.5 140.1 143.8 148.3 156.5 163.4 (ml.kg-o.67·min-1) SD 9.0 9.4 8.0 10.0 13.3 11.4 0.3 13.6 15.7 17.5
RER Mean 0.89 0.91 0.92 0.93 0.95 0.96 0.98 0.98 0.97 0.99 SD 0.06 0.06 0.06 0.05 0.06 0.06 0.07 0.06 0.06 0.07
RPE (Overall) Mean 8.9 10.8 11.3 11.7 12.7 12.8 13.4 14.1 14.6 15.5 SD 0.9 1.3 1.5 2.3 2.4 1.9 2.7 2.5 2.8 3.6
'0 10 Heart Rate (HR) Oxygen Uptake Relationship:
The relationship of HR to oxygen uptake during the skateboard treadmill test for each subject was examined using correlation coefficients and the results are presented in
Table 3. The mean correlation was 0.981 ± 0.02.
Table 3. Individual correlation (r) coefficients of heart rate to oxygen uptake during the skateboard treadmill test. Skateboard Subjects Oxygen Uptake Heart Rate Relationship (r)
1 0.990 2 0.999 3 0.930 4 0.980 5 0.970 6 0.980 7 0.990 8 0.980 9 0.990 10 0.997
Mean 0.981 SD 0.020 11 Field-tests (FT):
Individual and mean values for average Ff HR, %V02max, total estimated V02, total estimated kcal, kcal per minute, distance in miles and speed in miles per hour are presented in Table 4. Individual and mean values for 40% V02 reserve, 50% V02
reserve, and average Ff relative V02 values are presented in Table 5. During the Ff
l subjects averaged an estimated exercise intensity of 28.6 ± 2.3 ml-kg-1-min- • This is nearly equivalent to the subjects' mean V02 at 50% ofV02 reserve (28.6 ± 2.6
l ml-kg-1-min- ) determined from the treadmill V02rnax test. Table 4. Individual subject and mean values from the 30-minute skateboarding field-test. Total Total Average % Distance estimated estimated kcal per Average Speed Subjects Field Test VO Traveled Zmax VOzL kcal minute (m-min-1/mph) HR (miles) (30 min) (30 min)
1 137.7 53.8 77 372.6 12.4 2 153.2 58.3 62 303.6 10.1 3 158.5 62.7 63 307.3 10.2 4 125.0 44.6 50 242.7 8.1 4.8 257.3/9.6 5 154.2 50.1 59 286.2 9.5 4.8 257.3/9.6 6 136.4 49.5 59 284.9 9.5 6.4 343.0/12.8 7 144.3 63.6 65 315.1 10.5 5.3 284.1110.6 8 136.2 54.7 75 366.1 12.2 5.3 284.1110.6 9 162.1 61.1 63 305.2 10.2 5.8 313.6/11.7 10 112.1 39.6 62 302.1 10.1 4.8 257.3/9.6
Mean 142.0 53.8 64 308.6 10.3 5.3 284.1110.6 SD 15.7 7.9 8 37.9 1.3 0.6 32.2/1.2
I-' N 13 Table 5. Individual subject values, means and standard deviations of I 40% and 50% VOz(ml-kg-I-min- ) reserve and the average VOz(ml-kg I-min-I) estimated from the 30-minute field test. 40% VOz 50% VOz I 1 Average Field Test Subjects (ml-kg-I-min- ) (ml-kg-I-min- ) VO (ml-kg-I-min-I) reserve reserve z
1 25.7 31.3 31.7 2 23.0 27.9 30.4 3 21.8 26.4 30.9 4 25.6 31.2 26.2 5 24.6 29.9 28.2 6 23.8 28.9 26.9 7 20.2 24.3 28.7 8 22.7 27.5 28.2 9 21.8 26.4 30.1 10 26.7 32.5 24.3
Mean 23.6 28.6 28.6 SD 2.1 2.6 2.3 Differentiated Ratings of Perceived Exertion:
Differentiated RPE responses were collected at the end of each stage during the skateboard treadmill test. These included RPE responses for the kicking leg (RPE-K), support leg (RPE-S), chest or breathing (RPE-C), and overall (RPE-O). The mean values these data are presented together in Figure 5. An ANOVA for repeated measures revealed significant differences for differentiated RPE values over time. The RPE-S values were significantly greater than RPE-K,RPE-O, and RPE-C. 14
Discussion
To the authors' knowledge, this is the first study to examine the metabolic responses to skateboarding. The major finding of the present study was that skateboarding is a viable option for developing or maintaining aerobic fitness.
Additionally, the estimated caloric expenditure associated with 30 minutes of continuous skateboarding on a level surface in the field was consistent with recommendations for energy expenditure goals as outlined by the American College of Sports Medicine
(Franklin, 2000). Although skateboarding may be contraindicated for many individuals, results from the present study indicate that skateboarding could be used as part of an exercise prescription for healthy young adults interested in alternative forms of exercise.
In the present study, individual HR-VOz relationships were used to estimate energy expenditure in the field trial. Numerous studies have used this approach to estimate oxygen uptake in field situations (Ceesay et al., 1989; Collins et aI., 1991;
Ekelund et aI., 2001; Hiilloskorpi et al. 1999,2003; Li et aI., 1993; Luke et aI., 1997;
Spurr et aI., 1988; Strath et aI., 2000). However, this method is not without fault. Factors other than exercise intensity can increase or reduce HR in the field, which may affect the
HR-VOz relationship. High ambient temperature and humidity, as well as hydration status can cause increases in HR without a concomitant increase in oxygen consumption
(Achtenand Jeukendrup, 2003). In the present study, all subjects were instructed to report to the laboratory well hydrated. Additionally, performing both the skateboard treadmill and field tests in enclosed air-conditioned settings controlled environmental 15 conditions. Figure 1 presents the HR-V02 results of the field test. The lack of apparent cardiovascular drift suggests that the environment was adequately controlled.
The skateboard treadmill test was an attempt to recreate the movements and intensities encountered while skateboarding in the field. During the months that were spent designing the protocol various treadmill grades and speeds were tested. A grade of
1.5 % was used in the final protocol for three reasons: (1) if an incline was not used, the treadmill speeds required to elicit a consistently increasing HR were unsafe, (2) it appeared that the positive 1.5% grade did not affect the kicking mechanics, and (3) the use of 1.5 % grade allowed the subjects to momentarily assume the support position as they normally would in the field. Grades greaterthan 1.5 % required the subject to kick continuously creating intolerable fatigue of the support leg. The use of this protocol resulted in high correlations between HR and V02 for individual subjects (see Table 3).
When subjects were analyzed as a group, the use of linear regression to estimate V02 from HR resulted in a relatively high R2 (R2 =0.967) (see Figure 2). However, as previously reported (Rayson et aI., 1995; Ceesay et aI., 1988), the need for individual regression equations is apparent upon examining the variation of the HR-V02 responses
between subjects (see Figure 3). Thus, individual results were used to estimate V02 in the present study. Figure 1. Heart Rate and Estimated VOz during Field Test
150.0 2.30
140.0 2.10
130.0 1.90
120.0 1.70 ":' -C .~ )110.0 1.50 ":'c- 1 =. -.s N " 100.0 1.30 ~ 1:: :I :E: 90.0 1.10
80.0 0.90 _Heart Rate 70.0 ___Estimated Oxygen Uptake, 0.70
60.0 0.50 5 10 15 20 25 30 Minutes
~ 0\ Figure 2. Relationship of Mean Values for VOz and Heart Rate
2.9 +1------• y = 0.0214x - 0.9141 Z 2.7 IR = 0.9673 /
2.5 +-1----- ... I C ·e 2.3 I I -.:... /.
~ 2.1 1-----I
1.9
1.7 ~ ./ I
1.5 I I 115 135 155 175
Heart Rate (beats·min-') .....I-" Figure 3. Individual Subject HR-Y02 Relationships
4.0 i i re 1 r =0.99 -2 r = 0.999 3 r =0.93 3.5 I 1-'-4 r = 0.98 -5r= 0.97 -'-6 r = 0.98 --+-7 r = 0.99 3.0 I 1_8 r = 0.98 -9r=0.99 --+- 10 r =0.997 ,, ~., ';'-.~c > ,. 2.5 I -:::;2~~~------:7~.-=~~1tI:~~JY7/7;;,r;- 4i" ...... I -' ..- -gN
2.0 I , L>'"c 0/ .~![" ~ I
1.5 1 ...... -= >' I
1.0 , ii' 100 120 140 160 180 200
1 Heart Rate (beata'mln- ) .... 00 19
The individual relationships between HR and VOz were modeled linearly.
Although other mathematical models such as quadratic, cubic, and quartic have given slightly higher correlations, the increased predictive value has not been shown to be of practical significance (Londeree and Ames, 1976). When using a linear model it must be taken into consideration that at very low « 100 b/min) and very high intensities (> 177 b/min) the relationship becomes non-linear (Achten et aI., 2003; Bunc et aI., 1998;
Ceesay et aI., 1988; Spurr et al., 1988). However, HR data collected during the field test tended to fall near the middle of this range. The mean HR of the field test was 142.0 ±
I I 15.7 bemin- with values ranging from 112.1 to 162.1 bemin- . These values fell within the linear range of the HR-VOz relationship; therefore, the methodology used to estimate
VOz in the field should have yielded valid results. A potential limitation of the present study was the possibility of a sympathetic increase in HR caused by emotional stress due to the unique nature of skateboarding on a standard sized treadmill, which may have skewed the HR-VOz relationship. To help minimize anxiety, subjects were given at least two practice sessions, or as many as was needed until they felt comfortable skateboarding on the treadmill.
One of the goals of this study was to determine the validity of skateboarding as a method that could be used for improving aerobic fitness. In order to increase cardiorespiratory fitness, the American College of Sports Medicine (ACSM) recommends exercising 3-5 days/week, for 20-60 minutes, at intensities between 40 and 50% to 85% 20 of oxygen uptake reserve (VOzR) (Franklin, 2000). The subjects' VOz mean and
1 standard deviations at 40 and 50% ofVOzR were 23.6 ± 2.1 and 28.6 ± 2.6 ml-kg-l-min- , respectively. The mean and standard deviation of VOz estimated from the 30 minute field test was 28.6 ± 2.3. This value is on the low end of the scale, but does meet the
ACSM's exercise intensity guidelines.
When the oxygen uptake data from the field test were converted to caloric expenditure, the mean and standard deviation values for kcal-min-l and total kcal expended while skateboarding at 284.1 ± 32.2 m-min-l were 10.3 ± 1.3 kcal-min-1 and
308.6 ± 37.9 kcal, respectively. This corresponds to values (10.3 ± 1.2 kcal-min-l)
l obtained during stage 3 (147.4 m-min- @ 1.5% grade) of the skateboard treadmill test.
These data are congruent with energy expenditure estimates obtained on similar activities. Wallick et al. (1995) reported that outdoor "in-line" skating on a level surface at 241.2 m-min-l resulted in an energy expenditure of 9.5 kcal-min-l (based on a mean bodyweight value of 74.6 ± 10.3 kg). Other activities with similar energy costs are as follows (estimates are based on a bodyweight of 75 kg): vigorous basketball (10.9 kcal-min-l), canoeing at 134 m-min-l (9.5 kcal-min-l), aerobic dancing (10.0 kcal-min-l), vigorous touch football (9.2 kcal-min-l), hiking with a pack at 80.4 m-min-l
(10 kcal-min-l), mountain climbing (10.8 kcal-min-l), competitive volleyball (10.7 kcal-min-l), and running at 134 m-min-l (10 kcal-min-l) (Williams, 1999). In the present study, the total estimate of kilocalories expended during the 30-minute field test was
308.6 ± 37.9 kcal. The ACSM recommends that individuals participate in enough physical activity to expend 150 to 400 kcal per day (Franklin, 2000). Therefore, 30 21 minutes of skateboarding at intensities similar to those used in the field test meets the
ACSM guidelines.
The interesting dichotomous roles that the two legs play while skateboarding warranted the creation of two new local ratings of perceived exertion; and a unique evaluation of perception of effort. Ratings of perceived exertion provide a valid and reliable reference for monitoring small changes in exercise intensity (Skinner, 1973).
When individuals have trouble palpating heart rate, RPE provides an alternative method in which to monitor exercise intensity (Franklin, 2000). Borg's (1962) Category Scale
(6-20) for RPE provides an estimate of an overall perception ofeffort. To further elucidate the mechanisms underlying perception of effort, Pandolf et aI. (1975) introduced differentiated ratings of perceived exertion to measure central, local and overall aspects of perception of effort. In the present study, the following data were collected on the first five subjects: a central or cardio-pulmonary rating (RPE-C), a local rating pertaining to the exercising muscles or limbs (RPE-L), and the overall rating (RPE
0) which is the standard or combination of the other ratings. Figure 4 presents RPE data obtained from the first five subjects in the present study. The mean RPE-L was consistently higher than RPE-C orRPE-O. It has previously been reported thatRPE-L dominated RPE-C during cycling, while RPE-C may playa greater role in the perception of effort during treadmill walking (Pandolf et aI., 1975; Green et aI., 2003). Thus, the mode of exercise may playa significant role in how subjects perceive effort. Pandolf
(1982) in a later review stated that a majority ofthe studies show thatRPE-L tends to dominate RPE-O in various modes of exercise. 22 After completion of the skateboard trials, the first five subjects were questioned about their experiences associated with skateboarding on the treadmill. They reported a great deal more discomfort in the support leg than in the kicking leg. Therefore, the decision was made to differentiate the RPE measurements into four separate ratings. The instructions for RPE-C and RPE-O were the same as used for the first five subjects; however, the RPE-L was further divided to provide a measure for the support leg (RPE-S) and a measure for the kicking leg (RPE-K) (see Figure 5). While skateboarding on the treadmill, subjects only kicked with one leg, this created very different roles for each leg.
The support leg was used primarily to bear the weight of the entire body, while the kicking leg was involved in a repetitive dynamic kicking motion. Once enough momentum was gained, the subject could place the kicking leg on the skateboard and assume the support position. The means (± SD) across all stages for the last five subjects for RPE-S, RPE-K, RPE-C, and RPE-O were 14.5 ± 1.3, 10.4 ± 0.8, 9.8 ± 0.7, and 11.9 ±
0.9, respectively. Figure 5 presents the mean differentiated RPE data across all stages for these subjects. Ratings of perceived exertion for the support leg were significantly greater than RPE-K, RPE-O, and RPE-C (p < 0.05). Thus, it appears that the effort used to support the body's weight during skateboarding up a slight grade is greater than the effort put forth to propel the subject forward. This may not be the case when skating in the field on a flat surface. In conversations following the field tests, subjects conveyed that the perception of effort in respect to the support leg was far less than when skateboarding on the treadmill. 23
Figure 4. RPE Subjects 1-5
20.0 ORPEChest 1 ~PEOverall ORPE Leg 18.0 ...... I l 1 11 T T 16.0 l-i f- T1 l~J J w 14.0 1 rJii- i-1 -~ - 0.. c:<: T J lur~ 12.0 1 j1-:I i- f- i- f- - ,- 10.0 ~ i- ,- r- !- i- i- r- - ,- 8.0 i- - f- ;- r- r- - --
6.0 2 3 4 5 6 7 8 9 10 Stage
Figure 5. RPE Subjects 6-10
20 - .RPE Support Leg • RPE Kicking Leg I ORPE Chest ORPE Overall 18
16
w 14 1-----'- 1-- -l- I-- I- 0.. c:<:
12 - f---- ;--- -- ,- - f- I-
10 - l- i- - I- - - f- I-
8 R l- I- e- - I- - - f- I-
6 r 1 2 3 4 5 6 7 8 9 10 Stage 24 Conclusion
The most important finding of this study was that subjects skateboarding on a level surface at a self-selected pace for 30 minutes averaged an energy expenditure of
10.3 kcal-min-1and a total energy expenditure of 308.6 ± 37.9 kcal. Based on these results, it was reasonable to conclude that 30 minutes of continuous skateboarding, 3-5 times per week on a level surface, would provide an adequate stimulus for increasing cardiorespiratory endurance, and would expend enough energy (617.2 kcal-hour-1) to be viewed as an adequate mode of exercise to be included in a weight loss/weight management program (Franklin, 2000). 25 PART II
REVIEW OF LITERATURE
The literature in this chapter reviews four major topics: skateboarding, differentiated ratings of perceived exertion (RPE), factors influencing the HR-VOz relationship and energy expenditure.
Skateboarding:
This guideline, written by the American Academy of Pediatrics' Committee on
Injury and Poison Prevention (2002), presents injury statistics on both skateboarding and scooters. Following this injury overview, the committee gives seven preliminary recommendations based on studies evaluating the effectiveness of protective gear used while in-line skating and bicycling. The committee concedes that more time will need to pass before the effectiveness of these recommendations can be determined. It appears that the past decade has seen a resurgence of recreational skateboarding. It is estimated that in 19965.8 million children and adolescents younger than 18 years had participated in skateboarding. Looking at a 25-year trend, the annual incidence of skateboarding injuries peaked in 1977 at 150,000. Injuries decreased to 16,000 in 1983 and rose in individuals under 20 to 24,000 in 1994 and increased further to 51,000 in 1999. The US
Consumer Product Safety Commission (CPSC) reported that in 1999,90% of all children and adolescents injured were male. The most common injury sites were the ankle, wrist, and face, which accounted for 38% of all injuries treated. Five percent of the injuries were defined as severe (concussion or internal), and 31 % were defined as moderate 26 (dislocations or long bone fractures). Very few died. The recommendations relevant to skateboarding include the following: children under five should not use skateboards and children under ten should do so only under adult supervision; never ride a skateboard near traffic; never hold onto a moving vehicle; skateboarders should be advised to wear protective gear; and communities should continue to develop skate-boarding parks and encourage the youth to skate there.
Everett (2002) examined the types and distributions of injuries within a local commercial skatepark (SP), over a one-year period. What makes this study valuable is that it examines where in the SP the injury occurred as well as the type of injury. The author hypothesized that injury is correlated with SP design. The subjects consisted of
100 patients admitted to a university-based level 1 Emergency Department (ED), which was located half a mile from the selected SP. Subjects were at least seven years of age and a signed informed consent was obtained. During a semi-structured interview with each subject, either trained research associates, or medical staff collected data.
Demographic data, experience level, and equipment information were gathered. Subjects were then asked to identify on a map of the SP where they were injured. Pilot data from another study were used to estimate the annual volume of users at the SP. The subjects' ages ranged from 8-39 years with a mean age of 19 years. Ninety-eight % of the subjects were male. Seventy-five % of the injuries occurred while skateboarding. Of the subjects,
15% were beginners, 38% intermediate, 36% advanced and 11 % pro. The estimated annual injury rate was 1.11 injuries per 1000 people. In respect to injury distribution within the SP, 17 injuries occurred on the half-pipe, 32 in the gullies, and 55 in the ramps/bars area. The SP estimated annual injury rate of 1.1111000 is lower than what 27 was found in a previous study involving non-SP skateboarding injuries (7.0/1000).
This demonstrated possible safety advantages of a SP. The author speculated that a number of reasons contribute to the lower rate of injuries in the SP. The SP surfaces were well maintained and well lit. The SP staff enforced safety rules and the use of safety equipment (helmets, elbow and knee guards). The author recommended that wrist and mouth guards be worn in addition to above-mentioned gear. It is clear that significant injuries occurred at the local SP, of these injuries, fractures and dislocations were most common. The author concluded that the design features of the SP did significantly influence injury patterns.
Kyle et al. (2002) studied skateboard-associated injuries (SAl) in participants seven years or older over a 12 year period to determine participation based trends. The
National Electronic Injury Surveillance System was used to determine injury estimates and The National Sporting Goods Annual (NSGA) survey was used to determine participation estimates. In 1998, it was estimated that 5,782,000 individuals age 7 years and above participated in skateboarding more than once a year. Results revealed that in
1998 the rate of emergency department treated (ED) injuries were 8.9 injuries per 1000 participants. This value is twice that of in-line skating (3.9 per 1000), and approximately half that of basketball (21.2 per 1000) and football (20.7 per 1000). An examination of the SAl rate trends over the 12 year period revealed a significant downward trend beginning from a high of 15.5 per 1000 participants in 1987 and ending at a low of 4.5 per 1000 in 1993. At this point a significant upward trend occurs in SAl ending in 1998 at 8.9 per 1000 participants. The authors concluded that skateboarding is a relatively safe sport. 28 Summary: The studies by the American Academy of Pediatrics' Committee on Injury
and Poison Prevention (2002) and Kyle et al. (2002) clearly showed that by using the
amount of injuries per year as an estimation of individual participation rates, and the
NSGA's annual sport participation study, more people were skateboarding.
Differentiated Ratings of Perceived Exertion:
Skinner et al. (1973) examined whether subjects could perceive small differences in work intensity when the workloads are presented in a random order. Eight lean and
eight obese male subjects participated in two trials using the same progressively
increasing workload and two trials in which the magnitude of the workload was randomly
assigned on a Monarch bicycle ergometer. The progressive protocol began at 150
kgm/min and increased every two minutes by 150 kgm-min-1until the subject reached a
self-imposed maximum. The test consisted of4-minute workloads of 300,450,600, 750,
1 or 900 kgm-min- , which were randomly assigned. Ratings of perceived exertion (RPE)
were gathered 20 seconds prior to the end of the stage. The reliability coefficients
between the two trials of the same protocol in both the random and progressive test, with
the exception of respiratory frequency and tidal volume, were sufficiently high. The
reliability coefficient for RPE in the random and progressive test, were r =0.78 and r =
0.80, respectively. There were no significant differences in any of the variables between
the random tests and progressive tests. It appears that subjects are able to perceive small
differences in work effort.
Pandolf et al. (1975) evaluated three new differentiated ratings of perceived
exertion while treadmill walking and cycling: a central or cardio-pulmonary rating (RPE
C), a local rating pertaining to the exercising muscle and joints (RPE-L), and an over-all 29 or general rating (RPE-O). The effect of low intensity leg-weight training over a daily period on the discrete RPE was also examined. Eight subjects were used in the experimental group and four in the control group. The pre and post testing consisted of five periods. The first four periods consisted of treadmill walking for 10 minutes at 4.0 and 5.6 km/hr at 0% grade with and without 1.5 kg weights attached to the ankle. The last period consisted of cycling on a Monark bicycle ergometer for 6 minutes at a work rate of 600 kpm/min. The differentiated RPEs were taken during the second to the last minute at each period. Oxygen consumption (V02) and heart rate (HR) data were collected during the last minute of each period. For three weeks, subjects wore ankle 1.5 kg weights during their daily activities. The weight was increased to 2.25 kg for the next three weeks. Weights were not used during the last three weeks. Post-testing occurred every three weeks. During the pre-training treadmill walking, the three differentiated
RPEs did not differ significantly. During the pre-training cycling, the RPE-L was significantly greater than the RPE-C, but neither differed significantly from the RPE-O.
In general there was a decrease in all measures of RPE over the training period. The author concluded that during cycling local factors dominate central factors, while central or pulmonary factors may playa greater role during treadmill walking, and that lower
RPE at the same workload after training may be representative of the improved cardiovascular function and improved muscle function.
Pandolf (1982) had reviewed the experimental literature that has led to the development of the differentiated ratings of perceived exertion (RPE) model, examined in detail the literature using differentiated RPE that has furthered the understanding of the relationship of central and local factors, and suggested directions for future research. A 30 number of different scales have been developed and used in the literature: Borg's 15 point scale, which a majority of the papers reviewed employ, a nine":point scale, and
Borg's 21-point scale. Some researchers employed differentiated RPE in which, subjects were asked to give a local muscular rating that pertained to generalized local feelings of the exercising muscles and joints, a central rating pertaining to the cardiopulmonary system, and a general overall rating in which subjects were asked to integrate the central and local feelings. Other researchers have used more specific terms for the local and central ratings, such as legs and chest, respectively. PandoIf concluded, from his in-depth review of current literature, that in a majority ofthe studies local ratings of the sensations from the involved muscles andjoints dominate. In a study by Cafarelli et aI., there were no instances ofcentral effort RPE exceeded local effort RPE. A study by Young et aI., involving exercise at altitude, showed instances of central RPE being greater then local and overall RPE. Pandolf suggested the following directions for further research: the systematic study of central and local factors, and other possible sensations that influence overall perception of effort; as well as the effect task aversion and motivation have on the overall perception of effort.
Riebe et aI. (1997) examined the effects of oral and intravenous saline rehydration on both differentiated RPE and thirst in eight men (22.1 ± 0.8 yrs.). Subjects were
randomly assigned to one of three treatment groups and participated in aU three treatments on separate visits to the laboratory. The treatments consisted of no fluids
(NF), a 0.45% saline infusion (IV), or a saline oral ingestion (ORAL). Each laboratory
session consisted of three phases: a two to four hour dehydration exercise session (DHY)
to reduce bodyweight by 4%, followed by a rehydration (RHY) session in which subjects 31 received one of the three treatments, and ending with 90 minutes (or until self termination) of treadmill walking (EX) at 50% of VOZmax. Perceptual measures, RPE
(IS-point Borg scale) and thirst ratings, were gathered every 20 min during EX. Thirst ratings were also taken post dehydration (PD) and during RHY. The duration of EX was significantly shorter during NF (58.9 ± 8.4 min) than during IV (77.4± 5.4) and ORAL
(84.2 ± 2.3). Central RPE during ORAL was significantly lower at all time points than during IV and NF. Local RPE and O-RPE values during NF were significantly greater at
20 and 40 minutes than during IV and ORAL. L-RPE was higher at all time points during all trials than C-RPE. At 20 and 40 minutes during EX, O-RPE was significantly lower during ORAL when compared to NF. After RHY, thirst was rated significantly higher during NF compared to IV and ORAL. Thirst was rated significantly lower during
ORAL when compared to IV at all time points following RHY except at minute 80 during EX. Contrary to the authors' hypothesis, results indicated that IV and oral saline re-hydration of equal volumes resulted in different perceptual responses. Overall RPE and C-RPE during ORAL were generally lower than IV and NF. These lower ratings may have influenced performance, because during ORAL subjects were able to exercise for the longest period of time, followed by IV and NF, respectively. Thirst ratings were also lowest during ORAL and thus might be a cue for RPE. The importance of drinking before, during and after exercise is clearly supported by this study.
Green et al. (2003) examined the effect of gender and mode on differentiated and overall ratings of perceived exertion (RPE) at respiratory compensation threshold (RCT).
Eighteen men and 16 women performed a maximal treadmill (Bruce protocol) and maximal incremental cycle test. During which, subjects gave RPE-Corresponding to 32 overall (RPE-O), legs (RP~-L) and chest (RPE-C). Ratings of perceived exertion were
collected during the last 15 seconds of every minute. The RCT was determined by
examining graphic representation ofVC02 and V02. The point just prior to an increase
in VC02 without a increase in V02 was defined as the RCT. There were no significant
mode x gender or RPE x gender interactions. When gender was combined the mode x
RPE interaction approached significance (p=0.055) with RPE-L during cycling and treadmill exercise with respective mean (SD) values of 14.9 (2.9) and 12.8 (2.8). Main
effects for mode revealed significantly higher RPE values during cycling [14.4 (2.8)] than treadmill exercise [12.7 (2.9)]. Main effects for differentiated RPE revealed that RPE-L
[13.8 (2.6)] was significantly greater than RPE-O [13.5 (2.6)] and RPE-C [13.3 (2.6)], but the magnitude of the difference was so small that it had no practical value. The authors
concluded that gender differences in differentiated RPE do not exist in either mode of exercise, and that at RCT during cycling RPE-L is greater than during treadmill exercise.
Thus, care should be made when prescribing cycling exercise intensity using ratings of
perceived exertion.
Summary: The literature in this section suggest that RPE is a valid measure of perception
of effort not the result of the methodology of a linear incremental test (Skinner et al.
1973). Ratings of perceived exertion can be differentiated to represent perceptions of
effort of different portions of the body. When differentiated RPE are used to compare
modes such as cycling to running, cycling tends to illicit higher local (exercising
muscles) RPE while running tends to be dominated by central (pulmonary) RPE (Pandolf
1975 and 1982, Green et al. 2003). 33
Factors That Influence The HR-V02 Relationship:
Vokac et al. (1974) examined the relationship of oxygen uptake (V02) to heart rate (HR) while cycling, and during arm cranking in a sitting or standing position.
Subjects were seven males who participated in three incremental test protocols: cycling, arm cranking while sitting, and arm cranking while standing. Each protocol consisted of workloads of 300, 600, 900 kpmemin- 1and a stage of maximal effort. Metabolic and HR
1 data were collected during each stage. At workloads of 600 and 900 kpmemin- , both HR and VOz were significantly greater during arm cranking than during cycling. No significant differences were found between arm cranking while sitting and arm cranking while standing. Heart rate data were extrapolated to test the differences at specific VOz.
1 Heart rates were significantly higher at VOz of 1.9lemin- during arm cranking than during cycling. It appears that during cycling the VOz workload relationship is rectilinear up to high submaximalloads, however, this same relationship during arm cranking either sitting or standing appears to be curvilinear. When estimating VOz from
HR data in the field, it must be taken into consideration that the higher HR observed during arm cranking when compared to cycling at the same VOz could cause an over estimation of energy expenditure.
Londere et al. (1976) mathematically modeled the regression of percent of maximal oxygen consumption (%V0Zmax) on percentage of max HR (%HRmax) in 26 subjects classified as being either of low, medium or high fitness level. Subjects 34 participated in a VOZmax treadmill test and five treadmill walks or runs ranging from
30% to 100% of VOZmax' Metabolic and HR data were collected using open circuit spirometry and a cardiotachometer. The VOz and HR data were converted to relative values and then analyzed using linear, quadratic, cubic and quartic regression methods.
The associated RZ were 0.932, 0.942, 0.943, and 0.955, respectively. The bivariate regression equations for low, medium, high fitness groups, and a combination of all groups had correlations of r =0.973, 0.963, 0.959, and 0.959, respectively. There were no significant differences between any of the groups. The quadratic and quartic methods accounted for significantly more ofthe variance, but the increased predictive value was of little or no practical significance. It appears that the linear model of the %V0Zmax-
%HRmax regression is a valid method to determine this relationship. Fitness levels
appeared not to affect the stability of the %VOZmax- % HRmax linear regression.
Bunc et al. (1988) tested the following hypothesis: that the kinetics of heart rate
(HR) response to exercise may be used for the assessment of functional capacity; and that the point at which HR departs from linearity in incremental exercise tests coincides with ventilatory threshold (Tvent). Fifteen highly trained male rowers and 11 untrained male students were used to test functional capacity. Subjects pedaled a cycle ergometer at an intensity of 2 W kg- l for 4 min and HR was measured during this period. From these data, the time it took HR to reach steady state at the initiation of exercise and the time it took HR to return to resting values at the end of the 4 min were measured. These data 35 were expressed as the half time it took HR to reach steady state or return to resting values (tl/2B or tl/2R respectively). The tl/2B and tl/2R were significantlylower in the trained subjects. Twenty-eight trained male distance runners participated in a maximal incremental treadmill test and 17 untrained young male subjects participated in a maximal incremental cycle ergometer test. Heart rate and respiratory gasses were collected through out the tests. This data was then analyzed to determine if Tvent and the point at which HR departs of linearity coincided. Ventilatory threshold was determined from the dependence of ventilation (VE) on V02 or VC02 by means of a two-part discontinuous linear model. The point at which HR breaks from linearity was determined using the same two-part discontinuous linear model. There were no significant differences between the metabolic measures at HR break point or Tvent in either the untrained or trained group. Significant correlations all above r =0.91 were found between both HR break point and Tvent in both groups. In respect to the first part of the study, the author concluded that the kinetics of HR response to the onset and cessation of exercise were faster in trained than untrained subjects and can be used in the assessment of the training state of the athlete. In respect to the second part of the study, HR break point correlated highly with Tvent, which has been found to coincide with lactate determined anaerobic threshold. Thus, the determination of HR break point is a relatively simple, non-invasive method of determining anaerobic threshold.
Collins et al. (1991) studied the relationship of %V02max and %HRmax during weight lifting (WL) exercises of varying intensities. Fifteen male subjects, mean (SD) age of 22 ± 3.2 yr, participated in the study. An incremental treadmill test to volitional exhaustion was used to determine V02max and HRmax. One-repetition maximums (IRM) 36 were determined using free weights for the following exercises: supine bench press, bent-over row, standing two-arm curl, and parallel squat. Subjects participated in four separate exercise sessions in which they trained at 40, 50, 60, or 70% of their lRM. The 11.5-minute exercise session was conducted as a circuit. Subjects performed 10 repetitions at the prescribed intensity, rested for 30 seconds, and then moved on to the next exercise. The circuit was repeated three times. During the entire session, V02 and HR were measured. The significant correlation and regression line equation of the relationship of HR (bpm) to V02 (Umin) was r = 0.54 with a SEE of 0.28 Umin and Y= 0.0083X + 0.4158, respectively. The significant correlation and regression line equation of the relationship of HR (bpm) to %V02max was r =0.78 with a SEE of4.1 % and Y= 0.2418X + 5.6646, respectively. The significant correlation and regression line equation of the relationship of % HRmax to %V02max was r =0.86 with a SEE of 3.4% and Y=
0.5821X + 1.7991, respectively. It was clear that during WL the use of %V02max and %
HRmax provided the most accurate method of estimating V02 from HR. The coefficient of determination for V02 - HR, %V02max - HR, and %V02max - %HRmax relationships were 29%, 61 %, and 74% respectively. This trend is also seen in dynamic low-resistance exercise. The slope of the equation describing the relationship between %V02max and
%HRmax is half that of the reported values for dynamic low-resistance exercise. The author concluded that the use of a HR-V02 relationship obtained during cycling or running to estimate V02 during WL exercise, would estimate values above the actual oxygen consumption.
Rayson et al. (1995) hypothesized that the V02 - HR relationship between running and loaded marching is not the same and should not be used interchangeably.
The subjects consisted of 16 female British soldiers [age 21.9 (2.3) y, height 1.66 (0.06) m, body mass 62.6 (7.6) kg]. At the first visit to the laboratory, subjects participated in a 37 running %VOZmax test. The subject self selected a comfortable speed and after each 3- minute stage the grade was increased 2.5% or 5% until volitional exhaustion. At the second visit to the laboratory subjects participated in a progressive test of maximal load capacity. This test consisted of walking with a backpack at speeds of 1.78 m/sec for 4 minutes. At the end of each 4-minute stage the backpack was filled with 5 kg until the subject's HR reached 140bpm. The load was then increased 2.5 kg every stage until volitional exhaustion. Slopes and y -axis intercepts ofVOz /HR for both protocols were determined for each subject. These were determined using linear regression (least squares fit). The slopes and intercepts were compared using a paired t-test. The level of significance was set at 0.05. The slope of the VOz /HR relationship while running was significantly steeper than while marching under load. The intercepts while running were significantly lower than while marching under load. Heart rate and VOz final means for the loaded march were 90% and 80%, respectively of the final means for the run. The author provides a number of explanations for the greater HR at a given VOz during loaded marching. Previous studies suggest that the pack's straps place constriction on the abdominal and chest cavities, which could alter pulmonary function. The constriction of the straps might also lead to local muscular fatigue of the pulmonary and upper back musculature caused by the increased force needed for proper ventilation. In summary the
VOz /HR relationships of loaded marching and running in women are significantly different and should not be used interchangeably. If HR from running is used to classify the intensity of work while loaded marching, the intensity will be underestimated. 38 Hiilloskorpi et al. (1999) studied the affects that age, gender, and body weight
(BW) had on the individual relationship between heart rate (HR) and energy expenditure during exercise (AEE). The purpose of the study was to create a general equation using
HR and other anthropometric measures to predict AEE. The subjects consisted of42 healthy women (mean age of 38.1 [SD ± 9.8] years) and 45 men (40.3 [SD ± 9.2]). The subjects participated in 4 different laboratory exercise tests: one submaximal incremental cycling ergometer test, a maximal incremental uphill walking test, a 10 minute steady state walking and a 10 minute steady-state cycling test. Data were collected using open circuit spirometry and electrocardiography. The data collected during the last minute of each stage during the incremental tests were used to determine energy expenditure (EE).
A HR range collected during the incremental tests consisting of values above 100 bpm and below 85% of the individuals HRmax were used create the individual AEE prediction equations. If a correlation between HR and EE was <0.97 during the incremental tests, that subjects was excluded. Eight subjects were excluded. The selected predictors used in the model were HR, BW, age and gender. The authors set the level of significance at p
> 0.10. Three models were created: model one consisted of all the predictors and all the interactions, model two used all the predictors, but did not use all the interactions, and model three used HR, BW and gender. There were no significant differences between the different models; thus the simplest model, model three, was used for internal validation.
The predicted AEE from model three was compared to the measured AEE over the 10 minute steady state cycle and walking test. The AEE value predicted by model three overestimated cycling and walking by mean values of 17.9 (SD 22.7) % and 6.6 (SD
19.8)% respectively. Age is a predictor that's not used in model three. It's possible that 39 it was not a factor because of the homogeneity of age in the population studied.
Gender is included and thought to be a factor because men tend to have a greater percentage of lean body mass and generally have a higher EE and similar workloads.
Weight also increases EE at similar workloads during weight bearing exercise. The authors concluded that gender, BW, and age (although not used in model three) are all factors that influence EE and should be included when attempting to accurately predict
EE during exercise from HR.
Energy Expenditure:
Spur et al. (1988) used minute-by-minute heart rate (HR) recording to estimate total daily energy expenditure (TDEE) and energy expended in activity (EAC) in 22 (16 men, 6 women) subjects, whose oxygen consumption (V02) HR relationship and been individually established. These values were compared to values determined from whole body indirect calorimetry. Two oxygen con~umption HR relationships were determined.
First, a low intensity curve was developed based on responses to subjects sitting in a chair, standing, and sitting on a bicycle ergometer. The average of these measurements were used as resting metabolic rate (RMR). Subjects then performed an incremental bicycle ergometer protocol to establish the V02 HR relationship during exercise.
Oxygen consumption was measured using open circuit spirometry and HR was measured using electrocardiography. The subjects spent 22 hours in the calorimeter during which
HR, V02 and carbon dioxide production was collected every minute. While in the calorimeter, subjects followed one of four exercise (bicycle ergometer) protocols: no exercise (1), two 30-min bouts (2), four 30-min bouts (3), and six 30-min bouts (4). 40 There were no significant differences between the estimations of TDEE and EAC
. made by either indirect calorimetery or the minute-by-minute method. The authors
concluded that the minute-by-minute HR method can give reasonably accurate estimates
of EE in free ranging subjects over 22 hour periods.
Ceesay et al. (1989) examined the validity of a modified heart rate (HR) method
in predicting total energy expenditure (EE). This modified HR method used three
equations to determine daily EE, depending on the intensity of the activity. The standard
calculation of basal metabolic rate (BMR) was used to determine EE while sleeping. The
other two were separate regression equations determined from the relationship between
HR and oxygen uptake (VOz) during sedentary activities and during imposed exercise.
The HR that determines which of the two linear regression equations should be used is
called the flex HR (FLEX). The FLEX point can be defined as the HR for each subject at
which HR and VOz become strongly related, while below this point the two variables
become poorly correlated. This study defined FLEX, as the mean of the highest HR
obtained during standing measurements and the mean lowest HR measured during the
stepping measurements. Twenty subjects (11 males, 9 females) with a mean age of 25
years participated in the study. Two oxygen consumption HR relationships were
determined. First, a low intensity curve was developed based on responses to subjects
lying supine, sitting in a chair, and standing. Second, a high intensity curve was created
while subjects exercised on a cycle ergometer, stepped on and off a 225 mm block at 20
steps/min, and jogged on the spot at 138 steps/min. Oxygen consumption was measured
using open circuit spirometry and HR was measured using electrocardiography. Subjects 41 then spent 21.5 hours in a whole-body indirect calorimeter, during which they cycled,
rowed, stepped and jogged in place. This HR method predicted a non-significant mean
underestimation in total energy expenditure (TEE) of 1.2 (SD 6.2) %. The correlation
between TEE by HR and TEE by calorimetry (CAL) was 0.943 (SE of 458 kJ). The
author concluded that the modified HR method, using individual calibration curves that
have established a FLEX HR, provided accurate group measurement less than ± 10%.
Li et al. (1993) studied the inter- and intra-individual variations in EE when
estimated from minute-by-minute HR recording. The subjects consisted of 40 non
pregnant female cotton mill workers, who engaged in moderately strenuous physical
activities (age 29.7± 6.4 y, weight 53.3±6.4 kg, height 160.6±4.6 em, BMI 20.7±2.1).
The subjects stayed overnight in the laboratory and basal metabolic rate (BMR) and HR
were determined in the morning. The calibration procedure was performed 30 min after
breakfast, which involved simultaneous measurement of HR and EE while the subjects
carried out activities that were similar to what they encountered in daily life. Minute-by
minute HR data were collected in free-living conditions either the day before or after the
calibration procedure using wristwatch-electrode type monitors. The total EE over the
sampling period was calculate by adding up each minute's EE, which was estimated from
the corresponding minute's HR using the individual calibration curves. The curvilinear
relationship of the between EE and HR was then modeled as a logistic function. The
entire procedure was repeated 12 weeks later. The inter- and intra-individual differences
in EE resulting from individual calibration curves were both large. They ranged from
14.1 % to 17.6% and 10.6% to 20.4% respectively. The author used the individual
calibration curves (CV) based on an 18-activity trial as the standard of comparison. 42 When the group averaged CVs were used to calculate EE, the discrepancies were
-3986 to +5034 kJ/16 h. The use of individual CVs based on 9 activities resulted in EE discrepancies in the range of -3801 to +2543 kJ/16 h. These large discrepancies suggest that only the individual curves based on 18 activities should be used. The authors concluded that predicted individual EE from HR should be based on individual CVs, which were developed using many related activities.
Luke et al. (1997) studied the accuracy of the use of a combination of heart rate
.(HR) and motion to estimate the oxygen consumption (VOz) during exercise and activities performed during daily living. Ten subjects, eight female and two male, with a mean age of 25 ± 5 years participated in two tests of physical activity: the Activities of
Daily Living Circuit (ADLC) and a sub-maximal walking treadmill test (TT). During both of these tests HR, VOz and motion were collected simultaneously. When compared to direct measurement, motion alone was a poor predictor ofVOz, yielding mean correlations for ADLC and TT of r =0.53 and 0.50 respectively. Heart rate yielded mean correlations for ADLC and TT of r =0.81 and 0.90 respectively. The combination of motion and HR yielded mean correlations that were not significantly different from HR alone. Although not significant, the correlation values for the combination of HR and motion were higher than HR alone in nine of the ten subjects. The authors concluded that during ADLC a combination of motion analysis and HR monitoring improved VOz prediction and, although time consuming, the development of individual calibration 43 curves for the relationship of HR and motionto V02 is necessary to accurately predict energy expenditure.
Strath et al. (2000) examined the relationship between heart rate (HR) and oxygen consumption (V02) during laboratory based activiti.es of a moderate intensity, and the effect that an adjustment for age and fitness level had on the validity of using HR to predict energy expenditure (EE). This adjustment was accomplished by using a percent of heart rate reserve (%HRR) and a percent ofV02 reserve (%V02R), in the placeof HR
and V02 data in the EE prediction equation. Sixty-one subjects, 31 men (age 41 ± 13 yr), and 30 women (age 40 ± 12 yr) were used in the study. Subjects performed a varying number of activities outside of and inside of the laboratory. Outside of the laboratory, while at home, subjects vacuumed, swept, cooked and other normal household tasks; and outside of the home participated in yard work, softball, doubles tennis and other types of moderate activities. While in the Universities laboratory, subjects walked at 67 m/min and 93.8 m1min while carrying items weighing 6.8 kg, unloaded boxes and stretched.
While outside of the laboratory, subjects walked at about 78 m1min and at 100 m/min on an outdoor track. All activities were performed for 15 min while wearing a portable indirect calorimetry system and a polar HR monitor. The individual subject's mean HR and V02 values were computed from 5-15 minutes for each activity. The mean individual subject values were pooled and a linear regression analysis was performed to determine the HR V02 relationship. The correlation of the HR V02 relationship was r=
0.6, SEE = 18.23 mllkg/min. The relationship between measured EE and estimated EE 44 (using %HRR and %VOzR prediction equation) was r = 0.87, SEE 0.76 METs. The mean error across a large range of intensities (measured EE - estimated EE) was 0.04
METs. It was concluded that when estimating individual EE from a HR VOzlinear regression equation based on measured and subsequently pooled means, HR is a moderate physiological indication of VOz (r= 0.68, SEE = 18.23 ml/kg/min). If HR and
VOz values are adjusted for age and fitness levels (using %HRR and %VOzR prediction equation), HR becomes a strong predictor of EE (r = 0.87, SEE 0.76 METs).
Ekelund et al. (2001) examined in 127 adolescents (60 boys, 67 girls, 14.8 ± 0.3 yrs.) absolute heart rates (HR) and percentages of maximal HR (%HRmax) corresponding to 40%,60% and 80% of peak oxygen uptake (PVOz). The absolute and relative
(%PVOz) oxygen uptakes (V0z), corresponding to absolute HR values of 120,140, and
160 bpm and the effect of fitness and fatness on the HR - VOz relationship were also
studied. During an incremental Bruce protocol VOZmax test, HR and VOz data were collected by EeG and open circuit spirometry, respectively. Individual linear regression equations describing HR-VOz and %VOz - %HR in both absolute and relative (%HRmax'
%PVOz) data were determined for each subject. An analysis of covariance using sex, fitness and fatness as covariates was performed on the predicted HR corresponding to
40%,50%,60% and 80% of PVOz, and performed on the predicted VOz at absolute HR values of 120,140, and 160 bpm. In respect to absolute HR- VOz relationship, a 45 significant difference was found between the sexes, although no significant differences were found between slopes using relative values (%HRmax-%PV02). The inter-subject
CV for slopes describing the HR-VOz relationship were 25% for boys and 17% for girls.
Sex, fitness and fatness had no effect on predicted HR at 40%,60% and 80% of PV02.
In respect to absolute VOz-HR relationship, a significant difference was found between the sexes, although no significant differences were found between slopes using relative values (PV02%-%HRmax)' The inter-subject CV for the slopes ofV02-HR relationships were 33% for boys and 34% for girls. Absolute and percent peak VOz predicted from
HR in boys were significantly higher than in girls. A highly significant fitness effect was found at all HR when predicting VOz in ml·kg-1·min-1. The author concluded that the most important finding of this paper was that predicted V02 ml·kg-1·min-t, at absolute
HR of 120, 140, and 160 bpm were significantly higher in boys. This suggests that absolute HR data collected to assess physical activity in young people should be converted to relative values (%HRmax), when attempting to estimate oxygen consumption if an individual calibration for HR- VOz can not be established.
HiiIIoskorpi et aI. (2003) studied the accuracy of different heart rate (HR) based prediction equations, which used HR and oxygen uptake (VOz) relationships to predict energy expenditure (EE) from low to high activity levels. Forty-two men (mean age 36.5
[SD 7.6]) and 47 women (mean age 37.5 [SD 9.5]) performed a low-activity exercise test consisting of activity around 1-3 metabolic equivalents (MET) and high activity test 46 consisting of a maximal uphill treadmill walking test. General prediction equations were established based upon the individual HR and VOz relationships obtained by indirect calorimetry and electrocardiography during the two tests. Three general prediction equations were created: the first used normal HR values in the equation, the second used % of HR reserve (lOO*[(activity HR - resting HR)/(maximal HR - resting
HR)], (HRR), and the third used the difference between activity HR and resting HR
(HRnet). All three equations used body weight (BW), age, gender, and exercise intensity as predictors. The standard error of estimate (SEE) for the three equations were 1.41 kcal-min-\ 1.01 kcal-min-l and 1.08 kcal-min-\ respectively. The results show that using a percent of HHR provided the most accurate estimation of EE.
Summary: The factors that influence the HR - VOz relationship and energy expenditure groups are summarized together. There is no distinct line separating the studies in these two sections. With the advent of watch type HR monitors, collecting valid HR data in the field has become simple and thus makes the use of Heart rate VOz relationships to estimate energy expenditure increasingly common (Cessay et at. 1989, Laukkanen et al.
1998, Strath et at. 2000, Achten et at. 2003). The linear regression of the HR - VOz relationship is an accurate model of the data through most exercise intensities. During very low intensity activities that illicit heart rates below 100 b-min- l or activities causing the HR to rise above ventilatory threshold, the relationship becomes non-linear (Spur et at. 1988, Cesay et al. 1989, Achten et at. 2003). The HR measured during the field tests 47 fell within this linear range. The literature within this section clearly supports the use of individual HR - V02 relationships to estimate individual energy expenditure in the field. APPENDIX A. RAW DATA TABLES
Abbreviations:
RER: Respiratory Exchange Ratio
RPE $: Rating of Perceived Exertion Support Leg
RPE K: Rating of Perceived Exertion Kicking Leg
RPE C: Rating of Perceived Exertion Chest
RPE 0: Rating of Perceived Exertion Overall
RPE L: Rating of Perceived Exertion Leg
SKF: Skin fold
%BF: Percentage of Body Fat
PM: Fat Mass
LBM: Lean Body Mass 1 V02 L'min- Stages Subjects 1 2 3 4 5 6 7 8 9 10
1 1.8 2.2 2.2 2.2 2.2 2.5 2.6 2.8 2.9 3.3 2 1.3 1.7 1.9 2.0 2.1 2.2 2.4 2.5 2.6 2.8 3 1.6 1.9 1.9 1.9 2.2 2.4 2.4 2.3 4 1.6 2.0 1.9 2.0 2.0 2.2 2.1 2.3 2.4 2.5 5 1.9 2.1 2.2 2.3 2.5 2.8 2.8 6 1.5 1.6 1.8 1.8 1.8 2.1 2.1 2.2 2.3 2.4 7 1.6 2.0 2.1 2.1 2.3 2.5 2.5 2.6 2.8 3.0 8 1.9 2.4 2.6 2.6 2.8 2.9 3.0 3.2 9 1.7 2.0 2.1 2.2 2.4 2.5 2.6 2.7 2.9 10 1.9 2.3 2.5 2.6 2.8 2.9 3.2 3.4 3.6 3.7
Mean 1.7 2.0 2.1 2.2 2.3 2.5 2.6 2.7 2.8 2.9 SD 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.5
+: \0 VOz (Allometrically Scaled) Stages Subjects 1 2 3 4 5 6 7 8 9 10
1 93.5 114.3 115.3 116.5 118.5 129.9 137.5 148.8 153.5 174.4 2 79.5 101.1 110.1 115.4 124.0 129.8 143.0 146.7 153.7 162.5 3 95.5 111.5 112.6 113.0 127.1 143.5 143.8 134.6 4 99.0 122.2 120.4 121.8 125.6 137.9 130.8 144.9 148.0 153.3 5 112.3 121.6 125.6 136.0 145.8 160.9 164.5 6 83.0 92.0 102.9 102.9 100.5 120.7 119.0 125.6 132.9 138.0 7 90.9 108.9 115.1 117.6 125.3 138.7 137.6 145.8 155.4 163.2 8 92.8 118.5 128.2 129.8 137.2 144.3 147.8 156.9 9 %.3 114.0 122.7 128.7 137.6 146.3 153.4 159.7 169.5 10 97.9 116.8 124.8 130.1 143.0 148.5 160.3 171.5 182.3 189.2
Mean 94.1 112.1 117.8 121.2 128.5 140.1 143.8 148.3 156.5 163.4 SD 9.0 9.4 8.0 10.0 13.3 11.4 0.3 13.6 15.7 17.5
I..n o Heart Rate Stages Subjects 1 2 3 4 5 6 7 8 9 10
1 107 119 124 125 128 135 141 150 153 162 2 118 136 142 148 155 161 170 173 179 184 3 128 137 147 159 160 169 179 174 4 120 140 142 145 151 158 159 165 169 172 5 152 160 170 175 180 202 194 6 105 119 125 129 135 144 147 154 159 162 7 117 131 140 145 153 160 167 172 176 182 8 111 124 135 143 150 159 164 176 9 140 154 163 170 178 183 187 192 196 10 105 121 128 134 144 149 160 168 174 177
Mean 120 134 141 147 153 162 167 169 172 173 SD 16 14 15 16 16 19 17 12 14 10
V1 I-' RER Stages Subjects 1 2 3 4 5 6 7 8 9 10
1 0.93 0.93 0.94 0.92 0.94 0.94 1.00 1.04 1.02 1.07 2 0.80 0.87 0.87 0.87 0.89 0.90 0.91 0.92 0.94 0.98 3 0.93 0.98 1.00 1.00 0.98 1.03 1.06 0.99 4 0.87 0.91 0.94 0.93 0.96 0.96 0.97 0.99 0.97 0.98 5 0.99 0.98 0.98 1.03 1.06 1.07 1.09 6 0.79 0.81 0.81 0.84 0.87 0.86 0.86 0.87 0.90 0.89 7 0.90 0.90 0.95 0.95 0.98 1.00 1.01 1.04 1.05 1.09 8 0.84 0.86 0.90 0.94 0.93 0.95 0.96 0.98 9 0.92 0.95 0.95 0.93 0.98 0.97 1.00 1.02 1.01 10 0.90 0.89 0.88 0.92 0.90 0.91 0.92 0.94 0.93 0.96
Mean 0.89 0.91 0.92 0.93 0.95 0.96 0.98 0.98 0.97 0.99 SD 0.06 0.06 0.06 0.05 0.06 0.06 0.07 0.06 0.06 0.07
\J1 N RPES Stages Subjects 1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 11 15 12 12 12 11 10 10 11 10 7 11 13 15 15 16 17 18 19 20 20 8 12 13 14 14 14 14 14 15 9 12 13 14 14 15 15 17 18 19 10 10 14 14 16 15 16 16 17 17 17
Mean 11 14 14 14 14 15 15 16 17 16 SD 0.8 0.9 1.1 1.5 1.5 2.3 3.2 3.6 4.0 5.1
\Jl Vol RPEK Stages Subjects 1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 6 6 6 7 7 8 7 7 7 8 7 7 9 10 10 12 11 13 12 14 16 8 7 8 8 10 10 11 10 11 9 9 10 12 12 12 12 13 14 16 10 7 8 9 11 11 11 12 14 14 15
Mean 7 8 9 10 10 11 11 12 13 13 SD 1.1 1.5 2.2 1.9 2.1 1.5 2.5 2.9 3.9 4.4
V1 ~ · RPEC Stages Subjects 1 2 3 4 5 6 7 8 9 10
1 9 10 12 12 13 13 14 15 15 18 2 9 11 11 11 12 12 13 14 14 15 3 4 8 9 12 10 11 11 13 13 12 17 5 9 12 12 14 16 16 17 6 7 7 7 7 7 8 7 7 7 8 7 7 7 7 7 8 9 9 10 12 14 8 7 8 9 10 9 10 10 11 9 7 8 10 10 11 12 12 13 14 10 9 9 10 11 12 13 13 14 14 15
Mean 8.0 9.0 10.0 10.2 11.0 11.6 12.0 12.1 12.6 14.5 SD 1.0 1.7 2.0 2.2 2.7 2.4 3.0 2.6 2.7 3.5
\J1 \J1 RPEO Stages Subjects 1 2 3 4 5 6 7 8 9 10
1 10 12 14 13 13 14 15 16 16 18 2 9 11 11 11 12 12 13 14 14 15 3 4 8 11 11 13 13 14 14 16 14 17 5 9 12 13 15 17 15 17 6 10 10 10 7 8 9 8 9 9 9 7 9 10 11 12 14 13 15 16 17 19 8 7 8 9 10 11 11 11 12 9 9 12 12 11 13 13 13 15 17 10 9 11 11 13 13 14 15 15 15 15
Mean 8.9 10.8 11.3 11.7 12.7 12.8 13.4 14.1 14.6 15.5 SD 0.9 1.3 1.5 2.3 2.4 1.9 2.7 2.5 2.8 3.6
VI (]'I RPEL Stages Subjects 1 2 3 4 5 6 7 8 9 10
1 13 13 14 14 14 15 16 17 17 20 2 10 12 12 14 14 15 16 17 16 17 3 4 9 12 13 14 15 16 16.5 18 18 18 5 12 13 16 17 18 20 20 6 7 8 9 10
Mean 11.0 12.5 13.8 14.8 15.3 16.5 17.1 17.3 17.0 18.3 SD 1.8 0.6 1.7 1.5 1.9 2.4 1.9 0.6 1.0 1.5
\Jl "-J Subject Data SUbjects. Sum Skate Height Weight FM LBM Gender Age of7 %BF Board Test V02max (cm) (kg) (kg) (kg) (ml-kg-1-min-1) SKF HRlV02 r 1 male 182.9 80.5 27 72.0 10.1 8.2 72.3 0.990 59 2 female 175.3 68.4 23 103.8 20.9 14.3 .54.1 0.999 52.2 3 male 169.9 68.1 25 84.0 11.7 8.0 60.2 0.930 49.3 4 female 169.4 63.4 21 120.7 23.3 14.8 48.6 0.980 58.8 5 male 168.9 69.5 21 60.2 7.6 5.3 64.3 0.970 56.3 6 male 175.6 72.7 27 68.3 9.6 7.0 65.8 0.980 .54.2 7 male 187.0 75.2 21 42.5 4.8 3.6 71.6 0.990 45.2 8 male 183.7 89.1 28 93.0 13.4 11.9 77.2 0.980 51.5 9 male 170.9 69.5 29 63.3 9.0 6.3 63.2 0.990 49.2 10 male 178.4 85.2 23 40.7 4.7 4.0 81.2 0.997 61.4
Mean 176.2 74.2 24.5 74.8 11.5 8.3 65.8 0.981 53.7 SD 6.6 8.3 3.1 25.7 6.2 4.0 10.1 0.020 5.2
\J1 (Xl Individual subject and mean values from the 3Q-minute skateboarding field-test. Total Total Average % Distance Average estimated estimated Subjects Field Test VO kcaUmin Traveled Speed Zmax VOzL kcal HR (miles) (mph) (30 min) (30 min)
1 137.7 53.8 77 372.6 12.4 2 153.2 58.3 62 303.6 10.1 3 158.5 62.7 63 307.3 10.2 4 125.0 44.6 SO 242.7 8.1 4.8 9.6 5 154.2 SO. 1 59 286.2 9.5 4.8 9.6 6 136.4 49.5 59 284.9 9.5 6.4 12.8 7 144.3 63.6 65 315.1 10.5 5.3 10.6 8 136.2 54.7 75 366.1 12.2 5.3 10.6 9 162.1 61.1 63 305.2 10.2 5.8 11.7 10 112.1 39.6 62 302.1 10.1 4.8 9.6
Mean 142.0 53.8 64 308.6 10.3 5.3 10.6 SD 15.7 7.9 8 37.9 1.3 0.6 1.2
V1 \0 Field Test Heart Rates in beats-min-l at Five Minute Intervals Five Minute Periods Subjects 5 10 15 20 25 30 Mean SD
1 122.8 138.6 147.0 145.4 138.8 133.4 137.7 8.8 2 133.6 157.0 160.0 155.4 155.0 158.2 153.2 9.8 3 156.0 160.6 160.2 160.6 155.2 158.5 158.5 2.4 4 126.6 132.8 118.0 122.4 123.8 126.2 125.0 4.9 5 146.0 154.0 155.0 158.2 158.0 153.8 154.2 4.4 6 116.4 129.2 128.4 143.8 140.8 159.8 136.4 15.1 7 131.4 146.0 144.6 145.2 149.0 149.4 144.3 6.6 8 121.8 141.0 137.0 138.4 139.6 139.4 136.2 7.2 9 158.6 169.8 168.2 155.2 162.2 158.4 162.1 5.8 10 99.8 105.6 119.2 115.2 119.8 113.0 112.1 7.9
Mean 131.3 143.5 143.8 144.0 144.2 145.0 142.0 7.3 SD 18.2 18.5 -17.7 15.1 14.3 16.3 15.7 3.5
0" o Individual subject values, means and standard deviations of40% 1 and 50% V02 (ml"kg'min- ) reserve and the average V02 1 (ml'kg'f:l!in- ) estimated from the 30 minute field test.
2 2 40% V0 1 50% V0 1 Average Field Test Subjects (ml'kg'min- ) (mtkg'min- ) V0 (ml'kg'min- 1) reserve reserve 2
1 25.7 31.3 31.7 2 23.0 27.9 30.4 3 21.8 26.4 30.9 4 25.6 31.2 26.2 5 24.6 29.9 28.2 6 23.8 28.9 26.9 7 20.2 24.3 28.7 8 22.7 27.5 28.2 9 21.8 26.4 ·30.1 10 26.7 32.5 24.3
Mean 23.6 28.6 28.6 SD 2.1 2.6 2.3
(J'I ~ Field Test Estimated V02 L-min-\ at Five Minute Intervals Five Minute Periods Subjects 5 10 15 20 25 30 Mean SD
1 2.2 2.6 2.8 2.8 2.6 2.4 2.6 0.2 2 1.7 2.2 2.2 2.1 2.1 2.2 2.1 0.2 3 2.1 2.1 2.1 2.1 2.1 2.1 2.1 0.0 4 1.7 1.8 1.6 1.6 1.6 1.7 1.7 0.1 5 1.8 2.0 2.0 2.0 2.0 2.0 2.0 0.1 6 1.6 1.8 1.8 2.1 2.0 2.3 2.0 0.3 7 1.9 2.2 2.2 2.2 2.3 2.3 2.2 0.1 8 2.2 2.6 2.5 2.6 2.6 2.6 2.5 0.1 9 2.0 2.3 2.2 1.9 2.1 2.0 2.1 0.1 10 1.8 1.9 2.2 2.1 2.3 2.1 2.1 0.2
Mean 1.9 2.1 2.2 2.2 2.2 2.2 2.1 0.1 SD 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.1
0\ N Field Test Estimated Total V02 in Liters at Five Minute Intervals Five Minute Periods Subjects 5 10 15 20 25 30 Total
1 10.8 12.9 14.0 13.8 12.9 12.2 76.6 2 8.4 10.8 11.1 10.6 10.6 10.9 6204 3 lOA 10.7 10.7 10.7 103 10.5 63.2 4 8.5 9.0 7.8 8.1 8.2 8.4 49.9 5 9.0 9.8 9.9 10.2 10.2 9.8 58.9 6 8.1 9.2 9.1 lOA 10.1 11.7 58.6 7 9.6 11.0 10.8 10.9 11.3 11.3 64.8 8 11.2 13.0 12.6 12.8 12.9 12.8 75.3 9 10.1 11.3 11.1 9.7 10.5 10.1 62.8 10 8.9 9.6 11.2 10.7 11.3 10.5 62.1
Mean 9.5 10.7 10.8 10.8 10.8 10.8 63.5 SD 1.1 104 1.7 1.6 104 1.3 7.8
0"1 W Field Test Estimated Total Kcalat Five Minute Intervals Five Minute Periods Subjects 5 10 15 20 25 30 Total
1 52.7 62.7 68.0 67.0 62.8 59.4 372.6 2 40.7 52.5 54.0 51.7 51.5 53.1 303.6 3 50.3 52.0 51.9 52.0 49.9 51.1 307.3 4 41.1 43.5 37.7 39.4 40.0 40.9 242.7 5 44.0 47.6 48.1 49.5 49.4 47.5 286.2 6 39.3 44.5 44.2 50.5 49.3 57.1 284.9 7 46.5 53.3 52.7 53.0 54.7 54.9 315.1 8 54.6 63.1 61.4 62.0 62.5 62.4 366.1 9 49.1 54.9 54.1 47.3 50.9 49.0 305.2 10 43.2 46.6 54.5 52.2 54.9 50.9 302.1
Mean 46.1 52.1 52.6 52.5 52.6 52.6 308.6 SD 5.4 6.9 8.4 7.5 6.7 6.2 37.9
~ ~ Field Test Estimated Kcal·min-I at Five Minute Intervals Five Minute Periods Subjects 5 10 15 20 25 30 Mean SD
1 10.5 12.5 13.6 13.4 . 12.6 11.9 12.4 1.1 2 8.1 10.5 10.8 10.3 10.3 10.6 10.1 1.0 3 10.1 10.4 10.4 10.4 10.0 10.2 10.2 0.2 4 8.2 8.7 7.5 7.9 8.0 8.2 8.1 0.4 5 8.8 9.5 9.6 9.9 9.9 9.5 9.5 0.4 6 7.9 8.9 8.8 10.1 9.9 11.4 9.5 1.2 7 9.3 10.7 10.5 10.6 10.9 11.0 10.5 0.6 8 10.9 12.6 12.3 12.4 12.5 12.5 12.2 0.6 9 9.8 11.0 10.8 9.5 10.2 9.8 10.2 0.6 10 8.6 9.3 10.9 10.4 11.0 10.2 10.1 0.9
Mean 9.2 10.4 10.5 10.5 10.5 10.5 10.3 0.7 SD 1.1 1.4 1.7 1.5 1.3 1.2 1.3 0.3
0\ V1 APPENDIX B. FORMS AGREEMENT TO PARTICIPATE IN 67 An Analysis of the Caloric Costs of Skateboarding
Ian Hunt 953 Honokahua Place Honolulu, HI 96825 395-6630
1) Description:
This is a graduate level research project designed to determine the caloric costs of skateboarding. A short interview will be conducted in which questions about your skateboarding skill level will be asked, and two routine medical questionnaires will be given to you prior to your participation in the protocol. This experiment requires skateboarding on a treadmill. In order to insure your safety, you will be required to attend a training session in which instruction will be given on how to safely skateboard on the treadmill. If the researchers feel that your skill level is not adequate, you will be given one more training session. If you are still not able to safely perform the task, you will not be allowed to participate in the experiment If you are able to demonstrate a satisfactory skill level, you will be asked to participate in two treadmill tests. One of the tests will be used to determine your maximal oxygen uptake. This first test involves a progressive protocol that starts at a slow walking speed (1.7 mph) at 10% grade. Every three minutes the speed and grade will increase in small increments (Bruce Protocol) until you can no longer continue (volitional exhaustion). The second treadmill test will be used to establish a relationship between heart rate and oxygen uptake while skateboarding on a treadmill. The second test like the first involves a progressive protocol. Each stage will consist of3 minutes of skateboarding followed by 30 seconds of rest The first stage will consist of a warm up at 5 mph and 0% grade. The second stage will consist of skateboarding at 5 mph at a 1.5% grade. Following stage 2, the grade will remain at 1.5%, while the speed will increase in 0.5 mph increments. Lastly, you will also be asked to participate in one 30 minute field test During this time period, you will be required to wear a heart rate monitor, which will be used to estimate the amount of calories expended during that half-hour.
2) Procedures:
a. When you come in for the first treadmill test and all others, you will be given time to stretch. During all treadmill tests, you will have four electrodes attached to your chest to allow for the recording of your heart rate by an electrocardiograph machine. During all treadmill tests, you will also be required to breathe through a mouthpiece, so that your respiratory gasses can be analyzed. The test lasts less than 21 minutes, and depending on your fitness will probably last between 12 to 18 minutes. The test ends when you tell me that you do not wish to continue.
The stages are as follows: 1. 1.7 mph @ 10% grade 2. 2.5 mph @ 12% grade 3. 3.4 mph @ 14% grade 4. 4.2 mph @ 16% grade 5. 5.0 mph @ 18% grade 6. 5.5 mph @ 20% grade 7. 6.0 mph @ 22% grade 68 Cool down: walking at 0% grade for at least 5 minutes
b. The second treadmill test is similar to the first. You will be required to breathe through a mouthpiece and have electrodes attached to your chest. During this test you will be asked to skateboard on the treadmill. You will only be allowed to kick with one leg. Each stage will consist of three minutes of pushing and thirty seconds of rest. The rest will be accomplished by placing both feet on the skateboard and holding onto the treadmill's side rails. You may end the test at any time.
The stages are as follows: 1. 5.0 mph @ 0% grade 2. 5.0 mph @ 1.5% grade 3. 5.5 mph @ 1.5% grade 4. 6.0 mph @ 1.5% grade 5. 6.5 mph @ 1.5% grade 6. 7.0 mph @ 1.5% grade 7. 7.5 mph @ 1.5% grade 8. 8.0 mph @ 1.5% grade 9. 8.5 mph @ 1.5% grade 10. 9.0 mph @ 1.5% grade Cool down: walking at 0% grade for at least 5 minutes
c. You will also be asked to participate in one field test It will consist of a 30-minute period ofskateboarding. During this half-hour you will be required to wear a polar heart rate monitor. This consists of a wristwatch and a plastic transmitter that straps to your chest During the field test you will also be required to wear proper safety gear. The test consists of continuous skateboarding around the outer concourse of the Stan Sheriff Center.
3) Confidentiality:
The entire protocol will be held confidential. The researchers and you will be the only persons present in the laboratory while the test is being administered, and your name or identity will not be shown or indicated on any report of these data. This exercise is strictly voluntary and you may withdraw your participation from the research at anytime without prejudice.
4) Benefits:
You willieam your own level of aerobic fitness (V02max), ventilatory threshold, and maximal heart rate. These can be used to create your own exercise program. You will also gain a better understanding of the amount of energy you expend when skateboarding. If you choose to use skateboarding as a mode of exercise, you will better be able to plan your diet and exercise routine with this knowledge. 69 5) Risks:
As a result of participating in any of the treadmill exercise tests, it is possible that you may feel some discomfort. This might include one or more of the following: fatigue, distress, irritation, anxiety, stitch in the side, breathlessness, lightheadedness, dizziness, faintness, nausea, weakness, cramps, or an "unwell" feeling.
A small blood sample (two or three drops of blood) will be obtained via a finger prick during both treadmiJl tests to determine blood lactate concentrations. The risks are minimal and are only those of having blood drawn. This might include mild pain or a bruise at the place where the blood was taken. The risk of infection is slight, because a new, sterile, disposable lance will be used and discarded after each sample. This procedure is considered safe and all appropriate precautions will be taken to protect you from infection. Occasionally a person may faint or feel faint when blood is drawn.
Because ofthe high levels ofphysical activity involved, there is always a risk of injury, and, although very remote, the risk ofa cardiac event In the event ofa physical injury from the research procedure, only immediate and essential medical treatment is available. You should understand that if you are injured in the course of this research procedure, you alone may be responsible for the costs oftreating your injuries.
Certification:
I certify that I have read and that I understand the foregoing, that I have been given satisfactory answers to my inquiries concerning project procedures and other matters and that I have been advised that I am free to withdraw my consent and to discontinue participation in the project or activity at any time without prejudice.
I understand that ifI am injured in the course ofthis research procedure, I alone may be responsible for the costs of treating my injuries.
I herewith give my consent to participate in this project with the understanding that such consent does not waive any ofmy legal rights, nor does it release the principal investigator or the institution or any employee or agent thereof from liability for negligence.
Signature of Participant: Date: _
Signature of Investigator: Date: _
If you cannot obtain satisfactory answers to your questions or have comments or complaints about your treatment in this study, contact: Committee on Human Studies, University of Hawaii. 2540 Maile Way, Honolulu, HI 96822.
Phone: (808) 956-5007 70 MEDICAL HISTORY FORM Name ._ Date of Birth _
Name of contact person _ Relationship _ Home Phone Work Phone _
Physician _ Office Phone _
Hospital Preference __• . Phone _
MEDICAL HISTORY , Please identify any illness or condition that you have or had that might restrict your participation in physical activity. If you answer yes to any item, please indicate whether any aid requirements are needed. '
Condition Circle One Circle One or Both
Fainting Spells YES NO PAST PRESENT Headache YES NO PAST PRESENT Convulsion { Epilepsy YES NO PAST PRESENT Asthma YES NO PAST PRESENT High Blood Pressure YES NO PAST PRESENT High Blood Cholesterol YES NO PAST PRESENT Kidney Problems YES NO PAST PRESENT Intestinal Disorder YES NO PAST PRESENT Hernia YES NO PAST PRESENT Diabetes YES NO PAST PRESENT Heart Disease YES NO PAST PRESENT Angina YES NO PAST PRESENT Dentalplate YES NO PAST PRESENT Poor Vision YES NO PAST PRESENT Poor Hearing YES NO PAST PRESENT Skin Disorder YES NO PAST PRESENT Metabolic Disorder YES NO PAST PRESENT Stroke YES NO PAST PRESENT Allergies YES NO PAST PRESENT specify . Joint Dislocation YES NO PAST PRESENT
specify Other --YES NO PAST PRESENT specify _
Aid Requirements? 71
MEDICAL HISTORY FORM
Please identify any injury that you hnve or had that might restrict your participation in physical activity. If you answer yes to any item, please indicate whether any aid requirements are needed.
Injury Circle 'One Circle One or Both
Toes YES NO PAST PRESENT Feet YES NO PAST PRESENT Ankles YES NO PAST PRESENT LowerLegs YES NO PAST PRESENT Knees YES NO PAST PRESENT Thighs YES NO PAST PRESENT Hips YES NO PAST PRESENT Lower Back YES NO PAST PRESENT Upper Back YES NO PAST PRESENT Ribs YES NO PAST PRESENT Abdomen YES NO PAST PRESENT Chest YES NO PAST PRESENT Neck YES NO PAST PRESENT Fingers YES NO PAST PRESENT Hands YES NO PAST PRESENT Wrist YES NO PAST . PRESENT Forearms YES NO PAST PRESENT Elbows YES NO PAST PRESENT Upper Arms YES NO PAST PRESENT Shoulders YES NO PAST PRESENT Head YES NO PAST PRESENT
specify Other YES NO PAST PRESENT
specify
Are you currently taking any medication? YES NO
If yes, please describe medication, amount and reason taking. ------
----.,------Do you have any adverse reaction Ie, medication? YES NO
If yes, what medications and what re-actions? ------Has a physician placed any restrictions on your present activity? YES NO
If yes, please explain.
2 72
Medical Evaluation and the Graded Exercise Test 53
,,~jul -'ctMty Relldil'lftl =,0;;:.-"''1 PAR-Q & YOU (A Questionnaire for People Aged 1S to 69) Regular physical aClivity is fun and healthy, and increasingly more people are staning to become more active every day. Being more active is very safe for most people. However, some people should check with their doctor before they stan becoming much more physically active. 'I If you are planning to become much more physically active than you are now, stan by answering the seven questions in the box below. If 'I you are between the ages of 1Sand 69. the PAR.Q will tell you if you should check with you doctor belore you start If you are over 69 years of age, and you are not used to being very active, check with your doctor. Common Sense is your best guide when you answer these questions. Please read the questions carefully and answer each one honestly: check YES or NO.
YES NO o 0 1. Has your doctor ever said that you have a hean condition and that you should only do physical activity recommended by a doctor? o 0 2. Do you feel pain in your chest when you do physical activity? o 0 3. In the past month, have you had chest pain when you were not doing physical activity' o 0 4.00 you lose your bal<3nce because of dizziness or do you ever, lose consciousness' o 0 5. Do you have a bone or joint problem that could be made worse by a change in your physical activity' o 0 6. Is your doctor currently prescribing drugs (for example, water pills) for your blood pressure or heart condition' o 0 7. Do you know of any other reason why you should not do physical activity'
, YES to one or more questions If Talk with your doctor by phone or in person BEfORE you start becoming much more physically active or BEfORE you have a fitness appraisal Tell your doctor about the PAR·Q and which questions you answered YES. you • You may be able to do any activity you wanl-as long as you start slowly and build up gradually Or. you may need to restrict your activities to those which are safe for you. Talk with your doctor about the kinds of activities you wish to participate in and follow hislher advice. answered • find out whiCh community programs are safe and helpful for you.
~ DELAY BECOMING MUCH MORE ACTtVE: NO to all questions • If you are not feeling well because of a temporary ill· 11 you answered NO honestly 10 al/ PAR·Q questions. you can be ness such as a cold or a fever-wait until you iee\ bet· reasonably sure that you can: ter; or • If you are or may be pregnant-talk to your doctor • start becoming much more physically active-begin slowly before you start becoming more active. and build up gradually. This is the safest and easiest way to go, • take part in the fitness appraisal-this is an excellent way Pleas~ n~te:lfyo~; healU;cha~9es· SO that you then to determine your basic fitness so that you can plan the answer YES to any of the above questions, tell your fitness best way for you to live actively. .or,~~alth ?r.otl!SsiOl)a~~k.~~~r~ushoUI~C~ange, yo~r.; .p~~l,al:tl~~ ~Ia~~,..;,\... .;,:"::;;";';';"': .''.:'
Informed Use of the PAR·P· The Canadian Society for ElCercise Physiology, Health Canada, and their agents aSSume no liability lor perSons who undertak.e ph~ical activity, and .if in doubt after completing this queSlionnaire, consult your doctor prior to physical activity You are encouraged to copy the PAR-Q but only if you use the entire form.
Note: If the PAR-O is being given to a penon before he or she participates in a physical activity program or a fitness appraisal. this section may be used for lega' or administrative purposes I have read, understood and completed this questionnaire. Any questions I had were answered to my lull satisfaction NAME SIGNATURE DATE _ SIGNATURE Of PARENT WITNESS or GUARQIAN (lor participant'i under the age of majority) C Canadian Society for tlCerci\e Physiology Health Sante Sod~t~ canadienne de physiologie de I'exercice Supponed by: Canada Canada
Reprinted from the 1994 revised version of the Ph)1.kal Activity Readiness Questionnaire lPAR·Q and YOU). The PAR·Q and YOU is a copyrighted, pre-exefcise screen owned by the Canadian Society lot Exe'cise Ph)1.i~09Y.
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Figure 3.2 The Physical Activity Readiness Questionnaire (PAR-Q) offers an easy, brief evaluation prior to starting an exercise program.
....,"."._. ;ec._yew;,.•,::l,D co +'",...... :::::::EtiliieI.+§-£ waARW;'.; - 73
Skateboarding Skill Assessment Interview Questions
1. How long have you been skateboarding?
2. Are you comfortable skating on a Halfpipe?
3. Are you comfortable skating on a street course?
4. Can you ollie?
5. Do you feel that you could skateboard for one hour without taking a long break?
6. What tricks can you do? 74
Dear Subject, Thank you for agreeing to participate in this research study. This is a short list of thingsyou should do before the test and what to bring to the test:
1) You'll need to fast for 12 hours before the test. This means that if the test is at 7 in the morning you shouldn't eat after 7 p.m. the night before. This is to insure that the readings we get from the test are accurate. 2) In the morning before the test you should drink only water. Please do not drink any caffine containing beverages, such as coffee or diet colas. They can artificially elevate your heart rate and again give us inacurate readings. 3) Please do not participate in any type of strenuous exercise the night before or morning before the test. This includes both resistance training and endurance tra.ining. 4) Please wear appropriate running attire, including running or some type of athletic shoes, and shorts. Please bring a towel and some water.
Directions: The Lab is located in room 100 of the Stan Sheriff Stadium, which is located on the lower UH Manoa campus. APPENDIX C. STATISTICS 1st five subs, RPE repeated measures, rpeo=1, rpec=2, rpel=3 1 09:16 Sunday, April 13, 2003
The GLM Procedure
Number of observations 5
NOTE: Observations with missing values will not be included in this analysis. Thus, only 4 observations can be used in this analysis.
\ :: 'RpE- 0 ~ ::Rf\3- C 3 ::- ert::- .t-
'-J 0\ 1st five subs, RPE repeated measures, rpeo=1, rpec=2, rpel=3 2 09:16 Sunday, April 13, 2003
The GLM Procedure Repeated Measures Analysis of Variance
Repeated Measures Level Information
Dependent Variable rpe1 rpe2 rpe3
Level of rpe 2 3
...... 1st five subs, RPE repeated measures, rpeo=1, rpec=2, rpel=3 3 09:16 Sunday, April 13, 2003
The GLM Procedure Repeated Measures Analysis of Variance Univariate Tests of Hypotheses for Within Subject Effects
Source OF Type III SS Mean Square F Value Pr > F
rpe 2 23.16666667 11.58333333 32.08 0.0006 Error(rpe) 6 2.16666667 0.36111111
Adj Pr > F Source G - GH-F
rpe 0.0022 0.0006 Error(rpe)
Greenhouse-Geisser Epsilon 0.7752 Huynh-Feldt Epsilon 1.4494
-....J 00 1st five subs, RPE repeated measures, rpeo=1, rpec=2, rpel=3 4 09:16 Sunday, April 13, 2003
The GLM Procedure Repeated Measures Analysis of Variance Analysis of Variance of Contrast Variables rpe_N represents the contrast between the nth level of rpe and the 1st
Contrast Variable: rpe_2
Source OF Type III SS Mean Square F Value Pr > F
Mean 1 25.00000000 25.00000000 75.00 0.0032 Error 3 1.00000000 0.33333333
Contrast Variable: rpe_3
Source OF Type III SS Mean Square F Value Pr > F
Mean 1 42.25000000 42.25000000 46.09 0.0065 Error 3 2.75000000 0.91666667
-....I \0 1st five subs, RPE repeated measures, rpeo=1, rpec=2, rpel=3 5 09:16 Sunday, April 13, 2003
The GLM Procedure Repeated Measures Analysis of Variance
Repeated Measures Level Information
Dependent Variable rpe1 rpe2 rpe3
Level of rpe 2 3
(Xl o 1st five sUbs, RPE repeated measures, rpeo=1, rpec=2, rpel=3 6 09:16 Sunday, April 13, 2003
The GLM Procedure Repeated Measures Analysis of Variance Univariate Tests of Hypotheses for Within Subject Effects
Source OF Type III SS Mean Square F Value Pr > F rpe 2 23 . 16666667 11.58333333 32.08 0.0006 Error(rpe) 6 2.16666667 0.36111111
Adj Pr > F Source G-GH-F
rpe 0.0022 0.0006 Error(rpe)
Greenhouse-Geisser Epsilon 0.7752 Huynh-Feldt Epsilon 1.4494
00 t-' 1st five subs, RPE repeated measures, rpeo=1, rpec=2, rpel=3 7 09:16 Sunday, April 13, 2003
The GLM Procedure Repeated Measures Analysis of Variance Analysis of Variance of Contrast Variables rpe_N represents the contrast between the nth level of rpe and the 2nd
Contrast Variable: rpe_1
Source OF Type III SS Mean Square F Value Pr > F
Mean 1 25.00000000 25.00000000 75.00 0.0032 Error 3 1.00000000 0.33333333
Contrast Variable: rpe_3
Source OF Type III SS Mean Square F Value Pr > F
Mean 1 2.25000000 2.25000000 2.45 0.2152 Error 3 2.75000000 0.91666667
The GLM Procedure Number of observations 5 last five sUbjects RPE repeated measures trend analysis RPEs, RPEk, RPEo a 12 08:44 Sunday, April 13, 2003 The GLM Procedure Repeated Measures Analysis of Variance Repeated Measures Level Information Dependent Variable rpe1 rpe2 rpe3 rpe4 Level of rpe 2 3 4 00 ~ last five subjects RPE repeated measures trend analysis RPEs, RPEk, RPEo a 13 08:44 Sunday, April 13, 2003 The GLM Procedure Repeated Measures Analysis of Variance Univariate Tests of Hypotheses for Within Subject Effects Source OF Type III SS Mean Square F Value Pr > F rpe 3 27.60000000 9.20000000 6.53 0.0072 Error(rpe) 12 16.90000000 1.40833333 Adj Pr > F Source G - GH-F rpe 0.0250 0.0072 Error(rpe) Greenhouse-Geisser Epsilon 0.6102 Huynh-Feldt Epsilon 1.0992 <:Xl U1 86 r/ \ 1',. 'V' --;.- ~ last five subjects RPE repeated measures trend analysis RPEs, RPEk, RPEo a 14 08:44 Sunday, April 13, 2003 The GLM Procedure Repeated Measures Analysis of Variance Analysis of Variance of Contrast Variables rpe_N represents the contrast between the nth level of rpe and the 1st Contrast Variable: rpe_2 Source OF Type III SS Mean Square F Value Pr > F Mean 1 28.80000000 28.80000000 12.52 0.0240 Error 4 9.20000000 2.30000000 Contrast Variable: rpe_3 Source OF Type III SS Mean Square F Value Pr > F Mean 1 33.80000000 33.80000000 18.78 0.0123 Error 4 7.20000000 1.80000000 Contrast Variable: rpe_4 Source OF Type III SS Mean Square F Value Pr > F Mean 1 45.00000000 45.00000000 11.25 0.0285 Error 4 16.00000000 4.00000000 last five subjects RPE repeated measures trend analysis RPEs, RPEk, RPEo a 15 08:44 Sunday, April 13, 2003 The GLM Procedure Repeated Measures Analysis of Variance Repeated Measures Level Information Dependent Variable rpe1 rpe2 rpe3 rpe4 Level of rpe 2 3 4 (Xl -....J last five sUbjects APE repeated measures trend analysis APEs, RPEk, APEo a 16 08:44 Sunday, April 13, 2003 The GLM Procedure Repeated Measures Analysis of Variance Univariate Tests of Hypotheses for Within Subject Effects Source OF Type III SS Mean Square F Value Pr > F rpe 3 27.60000000 9.20000000 6.53 0.0072 Error(rpe) 12 16.90000000 1.40833333 Adj Pr > F Source G-GH-F rpe 0.0250 0.0072 Error(rpe) Greenhouse-Geisser Epsilon 0.6102 Huynh-Feldt Epsilon 1.0992 00 00 89 ~ " ,,'V " ., last five subjects RPE repeated measures trend analysis RPEs, RPEk, RPEo a 17 08:44 Sunday, April 13, 2003 The GLM Procedure Repeated Measures Analysis of Variance Analysis of Variance of Contrast Variables rpe_N represents the contrast between the nth level of rpe and the 2nd Contrast Variable: rpe_1 ~ V~ \ Source OF Type IIISS Mean Square F Value pr > F Mean 1 28.80000000 28.80000000 12.52 0.0240 Error 4 9.20000000 2.300000Q() Contrast Variable: rpe_3 Source OF Type III SS Mean Square F Value Pr > F Mean 1 0.20000000 0.20000000 0.05 0.8276 Error 4 14.80000000 3.70000000 Contrast Variable: rpe_4 Source OF Type III SS Mean Square F Value Pr > F Mean 1 1.80000000 1.80000000 0.42 0.5529 Error 4 17.20000000 4.30000000 last five subjects RPE repeated measures trend analysis RPEs, RPEk, RPEo a 18 08:44 Sunday, April 13, 2003 The GLM Procedure Repeated Measures Analysis of Variance Repeated Measures Level Information Dependent Variable rpe1 rpe2 rpe3 rpM Level of rpe 2 3 4 I.C o last five sUbjects RPE repeated measures trend analysis RPEs, RPEk, RPEo a 19 08:44 Sunday, April 13, 2003 The GLM Procedure Repeated Measures Analysis of Variance Univariate Tests of Hypotheses for Within Subject Effects Greenhouse-Geisser Epsilon 0.6102 Huynh-Feldt Epsilon 1.0992 \0 ~ 92 last five subjects RPE repeated measures trend analysis RPEs, RPEk, RPEo a 20 08:44 Sunday, April 13, 2003 The GLM Procedure Repeated Measures Analysis of Variance Analysis of Variance of Contrast Variables rpe_N represents the contrast between the nth level of rpe and the 3rd Contrast Variable: rpe_1 Source OF Type III SS Mean Square F Value Pr > F Mean 1 33.80000000 33.80000000 18.78 0.0123 Error 4 7.20000000 1.80000000 Contrast Variable: rpe_2 Source OF Type III S8 Mean Square F Value Pr > F Mean 1 0.20000000 0.20000000 0.05 0.8276 Error 4 14.80000000 3.70000000 Contrast Variable: rpe_4 Source OF Type III SS Mean Square F Value Pr > F Mean 1 0.80000000 0.80000000 1.00 0.3739 Error 4 3.20000000 0.80000000 93 REFERENCES Achten, J., and A. 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