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Investigation of the metabolic responses during the cycling phase of an ultraendurance triathlon Laursen, Paul Byron 2000

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INVESTIGATION OF THE METABOLIC RESPONSES DURING THE CYCLING PHASE OF AN ULTRAENDURANCE TRIATHLON By PAUL BYRON LAURSEN B.H.K., University of British Columbia, 1998. A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES School of Human Kinetics We accept this thesis as conforming to the required standards  THE UNIVERSITY OF BRITISH COLUMBIA December, 1999. © Paul B. Laursen, 1999.  In  presenting  degree  this  at the  thesis  in  partial  fulfilment  of  University  of  British  Columbia,  I agree  freely available for copying  of  department publication  this or of  reference  thesis by  this  for  his thesis  and study. scholarly  or  her  for  I further  purposes  gain  shall  permission.  Department  of  \A mywoivs  The University of British Vancouver, Canada  Date  DE-6 (2/88)  V\'\ weAv og>  Columbia  t ^ o o t . » n U J ZH „ I H ^ ^  requirements that  agree  may  representatives.  financial  the  be  It not  is  that  the  Library  permission  granted  by  understood be  for  an  advanced  shall for  the that  allowed without  make  it  extensive  head  of  my  copying  or  my  written  ii  ABSTRACT The purpose of this study was to investigate the premise that ultraendurance triathletes perform the cycling portion of the Ironman Triathlon at an intensity near ventilatory threshold (T  vent  ). Eleven highly-trained ultraendurance triathletes ( x ± SEM:  age = 35.8 ± 1.6 yrs; body fat = 11.7%; V 0  = 67.5 ± 1.0 ml-kg" -min" ) completed two 1  2 m a x  1  randomly assigned trials. The first trial consisted of a ride to volitional fatigue (BiT t) at ven  the subjects T t power output (PO nt) calculated from a preliminary cycling ven  V0  2max  Tve  test. The second trial was a 5 h bike time trial at a self-selected pace (Bi sp)S  The endurance time for the BiT  vent  was 130.7 ± 18.6 min. Significant differences  between trials existed on the measures: power output = 273.6 ± 8.6 vs. 188.0 ± 8.6 W; V0  = 3.61 ± 0.15 vs. 2.64 + 0.09 Lmin' ; 1  2  %T  v e n  tV0  = 110.7 ± 2.6 vs. 80.5 ± 3.3%; HR  2  = 159 ± 3 vs. 130 ± 4 bpm; RER = 0.95 ± 0.01 vs. 0.91 ± 0.01; and V = 103.4 ± 4.7 vs. E  66.7 ± 2.8 Lmin" ; BiT t vs. Bi sp respectively. 1  ven  S  While these results suggest that  ultraendurance triathletes do not perform at their PO nt during the cycling phase, mean Tve  HR data (146 ± 2 bpm) from seven of these subjects during the bike portion of the Canadian Ironman Triathlon (IMC) demonstrate that ultraendurance triathletes do perform at an intensity near their T t HR (150 ± 4 bpm; r = .873; p < 0.05). A treadmill ven  run V 0  2max  subsequent to Bi sp significantly reduced T tspeed (8.9 ± 0.3 mph vs. 8.4 ± S  ven  0.2 mph; p < .05), however, did not improve the ability to predict IMC marathon run pace (IMC marathon = 5.9 ± 0.3 mph; r= .425; p > .05).  iii  TABLE OF CONTENTS ABSTRACT  ii  TABLE OF CONTENTS  ii  LIST OF TABLES  v  LIST OF FIGURES  vi  ACKNOWLEDGEMENT  vu  CHAPTER 1: INTRODUCTION TO THE PROBLEM 1.1 Introduction to the Problem 1.2 Statement of the Problem 1.2.1 Subproblems 1.3 Definitions 1.4 Delimitations 1.5 Limitations 1.6 General Hypothesis 1.6.1 Secondary hypothesis 1.7 Significance of the Study  1 1 3 3 3 4 4 5 5 6  CHAPTER 2: LITERATURE REVIEW: Thresholds and considerations for ultraendurance triathlon performance 2.1 Introduction... 2.2 Historical Development 2.3 Physiological Profile of Triathletes 2.3.1 Triathlon Performance Prediction from Physiological Assessments 2.4 Considerations for Ultraendurance Triathlon Performance 2.4.1 Substrate Utilization 2.4.1.1 Carbohydrate (CHO) 2.4.1.2 Lipid Metabolism 2.4.1.3 Protein Requirements 2.4.2 Fluid and Electrolyte Homeostasis 2.4.3 Cardiovascular Drift 2.4.3.1 Cardiovascular Drift in Triathletes 2.5 The Anaerobic Threshold 2.5.1 Lactate Thresholds 2.5.2 Ventilatory Thresholds 2.5.2.1 Relationship between Lactate and Ventilatory Thresholds 2.5.2.2 Performance at Ventilatory and Lactate Thresholds 2.5.3 Time to Exhaustion at the Anaerobic Threshold 2.6 Thresholds for Long-Distance Performance 2.6.1 Thresholds for Swimming 2.6.1.1 Effects of Swimming on Cycling  7 7 7 8 10 ,11 11 11 13 15 16 17 19 20 21 21 22 22 23 24 24 25  iv  2.6.2 Thresholds for Cycling 2.6.2.1 Effects of Cycling on Running 2.6.3 Thresholds for Running 2.6.4 Thresholds for Triathlon 2.6.5 The Use of Heart Rate Monitors to measure intensity in Ultraendurance Athletes 2.7 A New Paradigm: The Ultraendurance Threshold (UT) 2.8 Conclusions CHAPTER 3: METHODS AND PROCEDURES 3.1 Subjects 3.2 Testing Procedures 3.3 Testing Protocols 3.4 Experimental Design and Data Analysis 3.5 Diagram of Design  27 27 29 29 30 32 35 38 38 38 40 43 44  CHAPTER 4: RESULTS AND DISCUSSION 45 4.1 Results 45 4.1.1 Descriptive Measures 45 4.1.2 V 0 Comparisons 4.1.3 Experimental Findings (Bi nt vs. Bissp) 49 4.1.4 Ironman Canada (IMC) Performance Results 52 4.1.5 Heart Rate Comparisons between Trials 53 4.2 Discussion 59 4.2.1 Descriptive Measures 59 4.2.2 V 0 Comparisons 4.2.3 Relationship of Threshold to Birvent and Bissp 62 4.2.3.1 BiTvent Trial 63 4.2.3.2 Bissp Trial and the UT Hypothesis 66 4.2.3.3 Hematological Comparisons 68 4.2.4 IMC Performance Results and Comparison to Laboratory Trial.. 69 4.2.5 Practical Implications 72 4 6  2max  Tve  6 0  2max  CHAPTER 5: SUMMARY AND CONCLUSIONS 5.1 Summary 5.2 Conclusions 5.3 Recommendations  74 74 76 76  BIBLIOGRAPHY  77  APPENDIX A: Sample calculation for estimation of the ventilatory threshold  91  V  LIST OF TABLES  1. Compilation of physiological attributes of triathletes  9  2. Physiological effects of 800m swimming on 75 min cycling from Kreider et al. (1988a)  26  3. Physiological effects of prior swimming and cycling on 10km running from Kreider etal. (1988b)  28  4. Timeline for testing  44  5. Descriptive data for all subjects  45  6. Primary variables during 7. Cycle ergometry 8. Treadmill running  V0  2 m a x  V0  2 i n a x  tests  47  variable comparisons  48  V0  2 m a x  variable comparisons.  48  9. Comparison of primary variables between trials (BiTvent vs. Bissp)  50  10. Comparison of secondary variables between trials (Bi nt vs. Bissp)  51  11. Estimated and actual run times and paces for the marathon run portion of the IMC  52  12. Comparison of heart rate at T t between trials  54  Tve  ven  vi  LIST OF FIGURES  1. Hypothetical plot of heart rate over time during an ultraendurance event as proposed by OToole et al. (1998)  37  2. Timeline of testing procedures for Bi ent and  44  BI'SSP  Tv  3. Comparison of power output over time for Bi ent and Bi sp  54  4. Comparison of pedaling rate over time for Bi nt and Bissp  55  5. Comparison of heart rate over time for Bijvent, Bissp. and IMC  55  6. Comparison of heart rate over time for Bissp, and IMC  56  7. Comparison of power output, heart rate, and pedaling rate over time for Bissp-  56  8. Hematocrit over time during Bissp  57  9. Respiratory exchange ratio over time during Bissp  57  10.1999 IMC bike course profile  58  11. Heart rate over time during 1999 IMC  58  Tv  S  Tve  vii  ACKNOWLEDGEMENTS Completion of this thesis would not be possible without the assistance from many individuals along the road of life. A heartfelt thanks to all of you for: Dr. Edward C. Rhodes (Supervisor)  your wisdom and direction, but above all else, for allowing me the opportunity to be independent in my studies, which enabled me to complete my Masters degree at my own pace. I am certain our paths will cross again in the future.  Dr.'s Jack E. Taunton, Donald C. McKenzie. (Committee)  your belief in me, your encouragement and support for the past few years, and your insightful contributions to this thesis.  Robert H. Langill  providing invaluable support throughout both my pilot, and thesis projects. The original idea for this thesis stems from you. I could not have done it without you.  Dr. Bill Sheel  motivating me to pursue graduate work, assistance in editing, and by setting an unprecedented example of conduct for all graduate students. You lead by example and are truly a class act.  Dr.'s Kevin Campbell and Peter Hochachka  the provision of hematological equipment, reagents, as well as detailed instruction on their use.  Dr. Alan Chin (my mentor)  inspiring me to pursue graduate work You have supported me in this dream ever since, and I cannot thank you enough. Another step of the ladder has been climbed.  Meghan Donaldson Lisa Shannon Josie Hetyei  your time and effort in assisting me during the lengthy data collection period.  My ultraendurance subjects  the enormous amount of time and hard work you all put into this research (literally blood, sweat and tears!). You've truly inspired me to compete again in the sport of triathlon.  The Simonett's (Judy, John, Kevin, Gillian, JB, Riley, Charlie, Raza, and Bramble).  providing me a home for the last three years at UBC and for your support; financially and emotionally. I could not have made it through two degrees without you. You are all family to me. Special thanks to Kevin for reminding me that life truly is a party! I will miss you all dearly as I continue on to the next phase of my journey.  viii  My parents  your continuous support and guidance throughout my life, and the opportunities you have provided for me. Thanks for trusting me during my decisions, which may have seemed somewhat unorthodox at times. I love you both very much.  My sister, Jana  inspiring me to pursue graduate work through example. You're my little sister, but you have no idea how much I look up to you!  Izabela  My fiance and best friend. For loving me, believing in my dreams, and supporting me day after day.  CHAPTER 1: INTRODUCTION TO THE PROBLEM 1.1 Introduction to the Problem Over the years, researchers have endeavored to describe the factors that contribute to human performance during prolonged endurance exercise. Physiological variables that highly correlate with endurance performance included maximal oxygen uptake (V0 2 m a x ), anaerobic threshold (AT), and economy of motion (Sleivert & Rowlands, 1996; Dengel et al., 1989). However, in activities beyond typical endurance events such as the marathon, termed 'ultraendurance' (i.e.> 4 hours; Hawley & Hopkins, 1995), the relationship between laboratory measured physiological variables fail to correlate strongly with ultraendurance triathlon (UET) performance (OToole et al., 1989; Langill & Rhodes, 1993; Miura et al., 1997). The "endurance triathlon", or Ironman Triathlon, is a three-sport event consisting of a 3.8km swim, a 180km cycle, followed by a 42.2km marathon run. The duration is longer than four hours, and can be considered 'ultraendurance' (Kreider, 1991; Hawley & Hopkins, 1995).  Therefore, a more appropriate name for the race may be an  "ultraendurance triathlon (UET)" and will be referred to throughout this thesis accordingly. The UET is a grueling event that takes between 8 and 17 hours to complete, depending on the calibre of athlete. The successful triathlete is one who has the ability to perform each sequential event at an optimal pace without creating fatigue that will hinder performance in the next event (OToole et al., 1989). However, the duration, intensity, and extreme environmental conditions encountered during UET combine to produce physiological stresses not seen in shorter races such as shorter triathlons and marathons (Hiller, 1989). While the sport of triathlon has received much research  2  attention, an optimum performance intensity has not been established that takes into consideration the specific UET problems. Therefore, competition exercise intensities during UET have been extremely variable (OToole et al., 1987a). It is well established that there are physiological measures of endurance performance we can measure in the laboratory, such as  V 0  2  M  A  X  ,  the AT, and economy  of movement (Wasserman, 1984). Although these physiological measures have been proven reliable predictors of race success in endurance exercise (Petit et al., 1997; Rhodes & McKenzie, 1984; Barlow et al., 1985), they have also been shown to be different than an athlete's performance threshold (Nichols et al., 1997; Hoogeveen & Schep, 1997). Hence, there are limitations to the threshold concept. Nevertheless, this reasoning has lead many authors to develop UET field predictions based upon laboratory assessments (Langill and Rhodes, 1993; Miura et al., 1997). However, these studies reveal that physiological measurements in the laboratory are not related to performance during UETs, as other factors encountered such as hydration and energy homeostasis must first be taken into consideration: A detailed laboratory assessment of highly-trained ultraendurance triathletes, coupled with field considerations will provide further insight as to the optimum intensity that can be maintained for prolonged periods.  If the ultraendurance triathlete could  identify a heart rate (HR) corresponding to a percentage of AT from a laboratory physiological assessment, then theoretically, performing at this intensity could maximize performance. Other "field" factors must also be considered including; the ability of the triathlete to exercise at a high percentage of V 0  2max  for a prolonged period of time, the  effect that a preceding event has on a subsequent event, cardiovascular (CV) drift, fluid homeostasis, and energy balance (OToole et al., 1987a; Kreider et al., 1988; Coyle,  3  1998; Coyle & Montain, 1992). Coupling these factors along with the appropriate HR effect could theoretically maximize performance. 1.2 Statement of the Problem The purpose of this investigation was to determine the intensity ( % V 0  2max  ,  %T nt, %HRmax) that a group of highly-trained ultraendurance triathletes perform at ve  during ultraendurance laboratory trials and during the cycling portion of the Canadian Ironman Triathlon. 1.2.1 Subproblems 1) to determine how cardiac drift affects this intensity. 2) to examine substrate utilization and its affects on HR. 3) to question whether cycling intensity can be optimized to allow subsequently for an optimal marathon run performance. 4) to question if the velocity at T t (determined via excess CO2) during running ven  subsequent to a 5 h cycle time trial can estimate race pace (time) for the marathon run phase of the Ironman Triathlon. 1.3 Definitions 1) Ventilatory threshold - (T t) the point where the aerobic energy response is of ven  insufficient magnitude to supply the tissues energy requirement and there is an increased reliance on anaerobic processes with an accompanying abrupt increase in excess C 0 . 2  4  2) Excess CO2 - nonmetabolic CO2 (EXCO2) formed as a result of the hydrogen ions of lactic acid being buffered by bicarbonate in the following reactions: HLa + NaHCOs <=> NaLa + H C 0 o C 0 + H 0 + NaLa 2  3  2  2  The calculation EXC0 will be based on the formula of Volkov et al. (1975) where: 2  EXC0 = 2  V C 0 - (RERrest * V 0 ) 2  2  1.4 Delimitations This study was delimited by: 1) a sample of triathletes from the Province of British Columbia between the ages of 29 and 44 with a minimum 12 h previous best Ironman Triathlon time. 2) A respiratory gas-sampling rate set at 20-s intervals during ramped protocols, and measured for 5 min every 30 min during prolonged testing. 3) A heart rate sampling rate set at 5 s intervals during ramped protocols, and set at 60 s intervals during prolonged testing. 1.5 Limitations This study will be limited by: 1) The data collection capabilities of the Vmax Metabolic Measurement Cart (V6200, SensorMedics Corporation, Yorba Linda, CA), and the Polar Vantage NV Heart Rate Monitor System (Polar Electro, Finland). 2) The individual metabolic response to the exercise protocols. 3) Race day conditions (terrain, weather, equipment problems, fuels, fluids, etc.)  5  4) Athlete self-selection of ultraendurance workload versus using a calculated workload. [Reasoning: if the workload were set by the evaluator then the athlete runs the risk of either not finishing the trial, or not being appropriately challenged]. 1.6 General Hypothesis This study will provide information for which to calculate an optimal critical ultraendurance intensity, which hereafter is referred to as the ultraendurance threshold (UT). This will be accomplished by observing physiological variables during an UET cycle performance. More specifically, this UT, as determined by a homogenous group of elite ultraendurance triathletes, will correlate significantly with some percentage of Tvent-  1.6.1 Secondary Hypotheses 1) The AT is too great of an intensity to ride at during the UET bike course. 2) An increase in HR (cardiovascular drift) will occur during the initial portion of the prolonged tests. 3) Substrate utilization (decrease in ratio of CHO:FAT), as reflected by respiratory exchange ratio (RER), will cause for significant increases in oxygen consumption ( V 0 ) as well as decreases in HR, yet power output (PO) will be maintained 2  throughout the prolonged tests. 4) A significant difference will exist between treadmill run V 0  2max  measured variables  rested versus post 5 h cycle time trial. 5) A significant difference will exist between treadmill run rested versus post 5 h cycle time trial.  T  ven  t  measured variables  6) Treadmill run velocity at  T  v e n  t  subsequent to a 5 h cycling time trial will correlate  highly with actual performance time for the marathon phase of the Ironman Triathlon. 1.7 Significance of the Study The 3.8km swim portion of an UET represents only 10% of the total duration of the UET (Butts et al., 1991) and is therefore a relatively small feat compared with the remainder of the event. But thereafter, the Ironman triathlete is troubled with deciding on an intensity to be maintained throughout the cycle portion in an attempt to achieve peak performance. During the bike portion of the UET, athletes may be performing at too great of an intensity in the beginning of their 180km cycle race for many reasons. These include the excitement of the day they have trained many months for, on top of the fact that they are rested, tapered, and therefore psychologically "feeling strong". Unfortunately, this surge of energy in the beginning of the cycling event could prove detrimental to their overall performance.  It has been demonstrated that once blood  lactate levels have risen above manageable levels due to exceeding the optimum PO it affects the athlete's ability to continue generating the original PO (Firth, 1998; Wasserman, 1987), and can lead to exhaustion (Urhausen et al., 1994). Therefore, identifying an 'ultraendurance threshold', or a critical intensity, could optimize the performance of the ultraendurance triathlete.  7  CHAPTER 2: Literature Review: Thresholds and Considerations for Ultraendurance Triathlon Performance 2.1 Introduction This review is an examination of the literature pertaining to the physiological factors affecting the second phase of an UET.  The review will examine the  physiological attributes of triathletes, fluid and substrate requirements of prolonged exercise, as well as the anaerobic threshold (AT) concept relating to triathlon and its component sports of swimming, cycling, and running. The review will also identify principles by which HR readings during an ultraendurance event could provide useful information by which the ultraendurance triathlete could maximize their performance. These concepts will be combined to form a new paradigm, which could be called the "ultraendurance threshold (UT)". 2.2 Historical Development Triathlon is an endurance contest where participants compete consecutively in three sports, usually swimming, cycling, and running. It is still a relatively new sport (22 years old) and research studies are needed to identify the physiological mechanisms involved with prolonged and variable event exercise. The UET began in 1978 when the Waikiki Rough Water Swim (3.8km), the Around Oahu Bike Race (180.2 km), and the Honolulu Marathon (42.2 km) were combined to form the Hawaiian Ironman (OToole et al., 1989). This race was previously looked upon as the ultimate in endurance sports in the early 1980's and perhaps thought of as an upper limit to an endurance athlete's capacity (Laursen & Rhodes, 1999). The contest's early years saw very few athletes attempt this endeavor.  However, with the media's exposure of the Hawaiian Ironman, shorter  triathlon distances also began to grow in popularity as people aspired to one day  8  compete at the event. This growth has popularized the sport to a large extent and has helped in leading the Olympic distance triathlon (1.5-km swim, 40-km cycle, 10-km run) to make its debut in the Sydney 2000 Summer Olympic Games. As well, over 10,000 triathletes compete in Ironman Triathlons around the world yearly (Docherty, 1998). This increase in the popularity of UET has also lead to an increase into the scientific inquiry of ultraendurance exercise. 2.3 Physiological Profile of Triathletes Physiological characteristics of triathletes encompass a wide range of endurance performance characteristics that are similar to that of cyclists (OToole et al., 1987). Elite triathletes are generally tall, of average to light weight and have low levels of body fat, and high maximum oxygen uptake ( V 0  2max  ) values (see Table 1). It has been  suggested that the absolute aerobic capacity in triathletes is the critical component to maintain high exercise intensity, especially during the running portion of the triathlon (Zhou et al., 1997). However, V 0  2max  may be, on average, marginally lower than values  previously observed in single event endurance specialists (Sleivert & Rowlands, 1996). V0  2max  in triathletes has been shown to be significantly greater during treadmill running  versus cycle ergometry, and lower during tethered swimming than both cycle ergometry and treadmill running (Schneider et al., 1990; Schneider & Pollack, 1991; Kohrt et al., 1989; OToole et al., 1987). V0  2max  Nevertheless, elite triathletes have significantly higher  values than sub-elite triathletes and high V 0  2max  levels are required for success  in triathlons (Sleivert & Rowlands, 1996). The ability of the triathlete to exercise at a lower percentage of V 0  2max  for a given  submaximal workload might be the most important factor to triathlon success (Burke,  9  1995). This is influenced not only by V 0  2max  itself, but also by AT and economy of  movement (Sleivert & Rowlands, 1996). Table 1. Compilation of physiological attributes of triathletes. Author  Sex  N  Age (years)  Height (cm)  Weight (kg)  AT (% of  % Body  (mlkg" min" )  vo  Fat  V02max 1  1  2max  )  Bunc et al.  F  13  17.1 ± 1.4  168.4 ±2.0  58.8 ±4.7  56.1 ±2.4  83.1± 1.7  10.4 ±2.6  (1996)  M  23  17.7 ±2.2  176.5 ±5.1  66.7 ±7.1  67.9 ±5.9  82.4±2.1  8.2 ±2.3  Zhou et al.  M  10  27.4 ±5.7  181 ±0.06  78.4 ±8.0  63.3 ±9.0  91.1± 1.0  Sleivert &  F  7  28.3 ±2.3  166.4 ±2.1  59.3 ±2.1  51.4 ± 1.3  85.0±2.1  Wenger  M  18  27.7 ± 1.3  180.0 ± 1.5  76.2 ±2.1  63.7 ± 1.6  85.0± 1.3  Kohrt et al.  F  6  29.4 ± 5.1  55.3 ± 1.4  58.4 ± 1.4  = 85  (1989)  M  8  OToole et  M  8  30.5 ±8.8  178.8 ±6.6  74.7 ± 10.0  68.8 ±10.4  9.9 ±3.5  al. (1987a)  F  7  31.3 + 5.6  166.0 ±6.4  58.8 ±5.7  68.1 ±9.4  15.4 ±4.6  Kreider et  M  5  28.6 ±4.6  179.0 ±5.7  74.3 ±2.3  57.9 ± 1.8  M  9  27.0 ±10.6  179.4 ±6.3  72.8 ±6.7  68.1 ±11.9  M  13  29.5 ±4.8  69.8 ±5.6  60.5 ±5.6  OToole et  M  14  40 ± 11  180.2 ± 8  73.7 ± 8  57.4 ±7.5  61 ±2.2  al. (1989)  F  10  31 ± 8  171.0 ± 9  58.0 ± 7  57.5 ±5.6  61 ±2.2  Dengel et  M  11  31.4 ± 1.8  179.9 ± 1.6  74.5 ±2.3  63.2 ± 1.7  65.6 ±1.7  Butts et al.  M  16  22.1 ±3.2  179.0 ±6.4  73.5 ± 10.6  62.0 ± 8.4  12.3 ±4.0  (1991)  F  7  21.0 ±1.0  165.7 ±3.6  59.8 ±4.1  50.7 ±2.6  19.0 ±4.6  Schneider  F  10  25.5 ±0.8  167.6 ± 1.7  59.0 ± 1.8  63.6 ± 1.2  (1997)  (1993)  71.1 ±2.5  15.1 ± 1.4 11.6±0.9  al. (1988b) Kreider et al. (1988a) Kohrt etal. (1987)  8.6 ±0.7  al. (1989)  & Pollack (1991)  74.0 ±2.0  10  2.3.1 Triathlon Performance Prediction from Physiological Assessments Many authors have attempted to predict triathlon race performance from physiological assessments. V0  2 m a x  Some authors have shown significant correlation with  and performance times in moderately trained triathletes (Butts et al., 1991; Kohrt  et al., 1987; Zhou et al., 1997; OToole et al., 1989; Dengel et al., 1989; Langill & Rhodes, 1993). However, as the length of the triathlon increases, other parameters begin to play a large influence on ultraendurance performance, such as thermal regulation and fluid homeostasis, as well as energy balance (Kreider, 1991). Nevertheless, the AT has proven to be the greatest predictor of race performance in endurance cycling (Coyle et al., 1991; Coyle, 1995; Bishop et al., 1998) and endurance running events (Rhodes & McKenzie, 1984; Petit et al., 1997; Farrel et al., 1979; Perronnet et al., 1987). Olympic distance triathlon performance times have also been shown to be highly correlated with the AT measured during cycle ergometry (Zhou et al., 1997). While the V 0  2 m a x  o f the athlete will set the upper limit, the ability of the  triathlete to exercise at a higher fractional utilization of  V0  2 m a x  is crucial to race success  (Zhou et al., 1997; Coyle, 1995). The AT is defined as the V 0 during exercise above which there is a sharp 2  increase in anaerobic energy production resulting in a significant increase in lactic acid levels (Wasserman, 1984). Theoretically then, the AT could be the ultimate intensity at which an ultraendurance triathlete could perform at during the Ironman Triathlon. However, ultraendurance considerations must first be identified to determine the ultraendurance triathlete's true limitations.  11  2.4 Considerations for Ultraendurance Triathlon (UET) Performance The Ironman Triathlon can take anywhere from 8 to 17 hours depending on the calibre of the athlete (Docherty, 1998). This long duration, moderate intensity exercise in the heat creates unique physiological challenges including energy balance, and fluid and electrolyte homeostasis. Caloric expenditure for the UET can range from 8,500 to 11,500 kcals (Kreider, 1991), while sweat rates can reach up to two Lhr" in the heat, 1  creating fluid and electrolyte disturbances  (Coyle,  1994).  Therefore,  during  ultraendurance competition, athletes require fluid and energy replacement to control body temperature and sustain endurance (Laursen & Rhodes, 1999).  It is important to  understand the influence these factors have on the ultraendurance triathlete as they affect variables measured in a laboratory assessment such as HR and AT (De Vito et al., 1995). 2.4.1 Substrate Utilization Substrate utilization during an UET is of great interest to exercise physiologists. The extreme caloric expenditures of these athletes requires significant fueling contribution from all sources including carbohydrate (CHO), fat and protein (Applegate, 1989). 2.4.1.1 Carbohydrate (CHO) Ultraendurance competition requires enormous energy expenditure and the ability to maintain a steady performance depends on an adequate supply of metabolic fuels (Kreider, 1991; Laursen & Rhodes, 1999). V0  2 m a x  )  Intense exercise (i.e. above 60%  can be maintained for prolonged periods, provided that sufficient CHO is  available for energy (Coyle & Montain, 1992). Therefore, CHO should be the main fuel consumed during ultraendurance events to maintain blood glucose levels (Anderson et  12  al., 1994; Case et al., 1995; Evan, 1991; Fallowfield et al., 1995; Raschka et al., 1991). CHO must be replaced because it has a limited storage capacity.  The total CHO  availability from muscle, liver, and blood glucose yields approximately 2000-2500 kcal, or one to two hours aerobic glycolytic exercise (Sherman & Wimer, 1991; Hawley & Hopkins, 1995; Sherman, 1996). Intense exercise performed beyond this time period without a CHO source will cause blood glucose levels to decline and fatigue to occur (Singh et al., 1994). CHO might also reduce fatigue in the central nervous system. This is known as the central fatigue hypothesis (Davis, 1995; Davis et al., 1992; WalbergRankin, 1995). Hence, the goal for the ultraendurance athlete then remains in obtaining enough energy throughout the diet in the form of CHO to balance the constant energy output. Due to the importance of CHO, numerous authors have investigated it's intake immediately prior to or during exercise and concluded that CHO ingestion improves performance during long duration exercise (Applegate, 1989; Lamb et al., 1991; Tarnopolsky et al., 1996; Tsintzas & Williams, 1998; Sherman et al., 1989; Walton & Rhodes, 1997). CHO loading is a well-established and well-practiced ergogenic aid to promote endurance performance (Millard-Stafford et al., 1988; 1990; Brewer et al., 1988; Applegate, 1991; Lindeman, 1992; Singh et al., 1993; Jeukendrup et al., 1996). CHO is also equally important during the event itself.  During prolonged exercise (>1-2 hrs),  CHO should be ingested to prevent fatigue due to inadequate supply of blood glucose. Peters and colleagues (1995) demonstrated in 32 male triathletes that a liquid CHO feeding during exercise (75% V 0 versus a placebo.  2max  ) resulted in significantly higher times to exhaustion  This may occur through the maintenance of blood glucose, or  through the sparing of muscle glycogen (Tsintzas & Williams, 1998). It is also possible  13  that CHO ingestion may lead to a resynthesis of muscle glycogen in non-active muscle fibres during exercise (Walton & Rhodes, 1997). The addition of CHO to fluid replacement beverages is important because it provides CHO late in exercise when there is often an inadequate supply of endogenous CHO to meet the energy requirements of the exercise task (Coyle & Montain, 1992). Maltodextrin has been shown to result in increased endurance cycling performance versus placebo (Langenfeld et al., 1994), and is a commonly used CHO source in commercial sport drinks. Fructose supplementation has been demonstrated to cause gastrointestinal discomfort in large doses during exercise and therefore should be limited (Craig, 1995). Ingestion of approximately 30-70g CHO-h" (Coyle & Montain, 1  1992) or 0.2-0.6 g CHOkg" h" (Applegate, 1989) in the form of a 5%-10% CHO 1  1  solution will generally be sufficient to maintain blood glucose oxidation late in exercise and delay fatigue (Walberg-Rankin, 1995). 2.4.1.2 Lipid Metabolism: Although CHO is the most important fuel to be consumed during ultraendurance exercise, it is important to understand the contribution that lipid makes as an energy substrate during prolonged exercise. Fat is the fuel of choice during exercise bouts of long duration, low intensity exercise (Okano et al., 1996; Romallo & Rhodes, 1998). As intensity increases, sustained exercise at a high PO requires the utilization of both fat and CHO simultaneously (Newsholme, 1981). But even at high work intensities (i.e. 85% V 0  2max  ) , a substantial amount of energy is still derived from fat oxidation, usually  between 25 and 30% (Ranallo & Rhodes, 1998). Because CHO stores are limited, fat becomes a major energy substrate during an ultraendurance event (Kreider, 1991). Theoretically, adipose tissue triglyceride provides sufficient energy for about five days of  14  continuous marathon running (Newsholme, 1981). The use of this energy system has been labeled the aerobic lipolytic energy system (Hawley & Hopkins, 1995). Evidence for the major use of this system is evident from ultraendurance studies. Blood samples drawn immediately following completion of endurance races up to the length of a marathon do not demonstrate a decrease in serum triglycerides (Dufaux et al., 1986; Thompson et al, 1980).  Ultraendurance events, however, have demonstrated this  (Farber et al., 1991; Nagel et al., 1992; Ginsburg et al., 1996). Hence, as exercise increases in duration, athletes depend more on lipid as a major energy substrate. Endurance training increases the size and number of mitochondria to greatly enhance aerobic metabolism and the ability of muscle to use oxygen to metabolize fat and CHO for energy (Hopkins et al., 1996). The ability then to oxidize fat at a very high rate for prolonged periods of time is very advantageous to the ultraendurance triathlete. This premise has lead to a hypothesis whereby "fat loading" prior to an ultraendurance event might increase performance (Hopkins, 1996). Performance, however, is more likely to be impaired by eating fat at the expense of CHO, as fat oxidation cannot support exercise intensities greater than 60% to 65%  V0  2 M A X  (Sherman & Leenders,  1995; Hopkins et al., 1996; Clark et al., 1992). Digestive problems and the lowered preference for this type of fuel lead to a low intake despite the advantage of a higher energy content (Saris et al., 1989). Consequently, the complete reliance on fat as the fuel for ultradistance exercise would significantly compromise performance capacity (Kreider, 1991). Nevertheless, fat is a necessary part of the diet in that it provides essential fatty acids and aids in the absorption of fat-soluble vitamins (Lindeman, 1992). Although fat consumption  during  competition  should  be  limited,  it  is  recommended  that  15  ultraendurance athletes consume 20% to 30% of their total daily energy in the form of fat as desired during a regular training day (Saris et al., 1989; Clark et al., 1992). 2.4.1.2 Protein Requirements: Protein requirements of ultraendurance athletes have not been critically evaluated, but evidence indicates that protein needs of endurance athletes may depend on the intensity and volume of training (Singh et al., 1994). Energy demands from dietary  protein  increase  if  glycogen  becomes  depleted  (Lindeman,  1992).  Ultraendurance studies indicate that athletes consume 5% to 15% of their calories from protein (Clark et al., 1992; Saris et al., 1989). The contribution of protein to total energy expenditure results from a negative energy balance.  Kreider (1991) suggests five  potential reasons for this occurrence: 1) Suppression of appetite and/or boredom of frequent eating 2) the inability to completely replenish muscle and liver glycogen stores within short periods of time 3) the high fiber content of complex CHO providing a sensation of fullness, yet caloric needs may not be met 4) inappropriate food choices 5) the difficulty of consuming 8,000-15,000 kcald"  1  In a recent review, Lemon (1995) states that endurance athletes would benefit from diets containing more protein than the current RDA of 0.8 gkg" day" . 1  1  Current  recommendations for endurance athletes range from 1.0 to 1.5 g k g day" (Clark et al., 1  1  1992, Lemon, 1995). This protein increase covers the increased loss of amino acids oxidized during exercise (greater than 60% V 0  2max  ) , and may provide additional raw  materials to replace exercise-induced muscle damage which has been shown to occur during ultraendurance racing (Lemon, 1995; Case et al., 1995; Armstrong, 1986).  16  Markers such as blood urea nitrogen, potassium, and serum muscle enzyme levels have been demonstrated to increase during an UET, reflecting skeletal muscle permeability or disruption (Farber et al., 1991). In a study of a 1000km running race, Raschka and associates (1991) suggest the absolute protein intake of 1.7-g-kg" -day" 1  1  during the race should be increased in order to diminish the loss of musculature they found during ultraendurance racing. Therefore, prolonged ultraendurance exercise in itself can lead to ultrastructural damage in muscle, which could.contribute to the body's ability to replenish its glycogen stores. Protein requirements may be more important in ultraendurance events than previously thought. 2.4.2 Fluid and Electrolyte Homeostasis The second major consideration resulting from the prolonged nature of triathlon is the maintenance of fluid and electrolyte homeostasis. Heat produced during exercise is primarily dissipated by the evaporation of sweat (Coyle & Montain, 1992; Brouns et al., 1992). Fluids are also lost through the respiratory tract, gastrointestinal tract, and kidneys (Greenleaf, 1992). Therefore, the proper replacement of fluids and electrolytes during prolonged exercise is essential (Applegate, 1989). Dehydration will result without fluid replenishment. Dehydration is a consequence of body water loss due to sweating, which impairs the process of heat dissipation, resulting in elevated deep body (core) temperatures  and reduced endurance  performance (Coyle & Montain, 1992).  Environmental heat exposure will amplify this process. For dehydrated athletes, the continuation of exercise heat stress can result in severe hyperthermia, and potentially a life-threatening thermal injury (Sawka, 1992). Cognitive performance can also be adversely affected by body water deficit (Schoene, 1984).  Dehydration is the most  common reason for a triathlete in the Hawaii Ironman Triathlon to need medical  17  assistance, while hyponatremia, an extracellular sodium imbalance, is the predominant electrolyte disturbance (Hiller, 1989; Laird, 1989). Hence, sodium consumption during an UET is also of particular concern (OToole & Douglas, 1995). Water losses can be as high as two l-h" in hot weather, especially when the 1  exercise intensity is greater than 70%  Vo  2 n ) a x  (Coyle; 1994). Since the average rates of  gastric emptying and intestinal absorption can reach 1 l-h" for water and solutions 1  containing up to 8% CHO, athletes can be supplemented with both CHO and fluids at relatively high rates without compromising either fluid replacement or CHO absorption (over 60 g-h" of CHO and 1 l-h" of fluid) [Coyle & Montain, 1992]. 1  1  2.4.3 Cardiovascular Drift If the objective of this thesis is to determine a HR threshold intensity that would optimize performance during an UET, then it is important to observe the effects that long-duration performance have on HR. A slow but steady increase in HR is witnessed during prolonged endurance exercise at a constant work-rate. For example, Grant and associates (1997) showed HR to increase from 147 to 173 bpm during a two hour ride at the work rate corresponding to 46% V 0  2max  i n eight untrained individuals.  This  phenomenon is known as cardiovascular (CV) drift. CV drift is caused by a progressive decrease in stroke volume (SV), resulting in an increase in HR required to maintain cardiac output (Q) during prolonged exercise (Shaffrath & Adams, 1984; Grant et al., 1997). A rise in plasma catecholamine concentration parallel this rise in HR (Nielsen et al., 1984).  CV drift occurs even more profoundly in conditions that combine high  metabolic and thermal circulatory demands (Heaps et al., 1994). CV drift is augmented by dehydration (Coyle & Montain, 1992b; Heaps et al., 1994), and reduced by fluid replacement (Hamilton et al., 1991). Although not yet scientifically proven, CV drift may  18  occur less in trained individuals versus untrained (Lambert et al., 1998). The mechanisms used to explain CV drift are still being investigated.  The  examination of CV drift in horses indicates that CV drift might be due to increases in core body temperature and lactate levels (Thomas & Fregin, 1990; Coyle, 1998). Human research indicates that reduced blood glucose levels may be related to CV drift. Hamilton and co-workers (1991) discovered that the infusion of an 18% glucose/saline solution during exercise, sufficient to maintain hyperglycemia and prevent dehydration, resulted in the complete elimination of CV drift during two hours of cycling at 70% V0  2 m a x  .  This study amplifies the importance of both fluid and CHO replacement  simultaneously during prolonged exercise (Coyle, 1994). The change in SV during prolonged exercise is equivocal.  Although some  studies have demonstrated SV to be maintained during prolonged exercise with fluid ingestion (Thomas & Fregin, 1990; Hamilton et al., 1991), the majority of author have shown SV to steadily decrease (Shaffrath & Adams, 1984; Coyle & Montain, 1992b; Grant et al., 1997; Coyle, 1998; Gonzalez-Alonso et al., 1998). Approximately one-half of this SV reduction is probably due to the reduced blood volume from dehydration during exercise that produces hyperthermia, while the remaining reduction in SV appears to be related to additional factors such as hyperthermia and the interaction with factors that further reduce ventricular filling, such as heart rate acceleration (Coyle, 1998). Although it was previously felt that an increase in skin blood flow was the direct cause of a CV drift (Freud et al., 1987; Montain & Coyle, 1992a; 1992b), recent evidence has demonstrated that reductions in SV due to dehydration and concomitant hyperthermia are due to reductions in muscle blood flow (Coyle, 1998; Gonzalez-Alonso  19  et al., 1998). In fact, skin blood flow actually declines as skin and systemic vascular resistance increases as the CV system attempts to cope with the severe challenge of large reductions in Q (Coyle, 1998). Sweat rate becomes a problem. CV drift occurs during triathlon events (Guezennec et al., 1996), therefore HR during an UET may be an overestimation of the work rate (OToole et al., 1989). Consequently, attempting to maintain euhydration could theoretically reduce the degree of CV drift during an UET. However, fluid compartment shifts also take place during exercise, even after 10 min (Nielsen et al., 1984). Farber and colleagues (1991) studied the metabolic changes in 11 subjects participating in the Hawaiian Ironman Triathlon. The authors noted an increase in serum albumin without a significant change in body weight to represent a decrease in plasma volume. This might represent the movement of fluid from the extracellular compartment to the skeletal muscle cells.  This effect  would happen secondarily to the development of an osmotic gradient caused by the breakdown of muscle glycogen to lactate during the swim resulting in a lactate concentration that is higher within muscle than in blood (Farber et al., 1991; Armstrong, 1986). Hence, the ultraendurance triathlete can prevent a proportion of the CV drift due to dehydration, but confounding fluid compartment shifts seem uncontrollable at this time. 2.4.3.1 Cardiovascular Drift in Triathletes The scientific literature contains little direct data regarding the extent to which fluid replacement during exercise should match sweat rate to offset CV drift and hyperthermia (Coyle & Montain, 1992). CV drift has been observed during prolonged swimming (Nielsen et al., 1984), cycling (Shaffrath & Adams, 1984; Freund et al., 1987; Hamilton et al., 1991; Montain & Coyle, 1992a; 1992b), running (Westerlind et al., 1992;  20  1994) and during a triathlon (OToole et al., 1987a; 1989; Guezennec et al., 1996). However, swimming CV drift has been found to be not as profound as cycling CV drift, due to both the horizontal and hydrostatic conditions during swimming (Shaffrath & Adams, 1984; Nielsen et al., 1984). Nevertheless, CV drift will already have begun after prolonged swimming during an UET, possibly due to a decrease in plasma volume (McMurray; 1983;Guezennec et al., 1996; Hausswirth et al., 1996). This decrease in plasma volume might not only be due to dehydration (OToole et al., 1987a), but also due to a redistribution of blood volume (Farber et al., 1991). Even if blood volume remained constant, a decrease in venous return due to this redistribution would result in a CV drift. Hence, CV drift has implications for judging UET intensity on the basis of HR. 2.5 The Anaerobic Threshold The AT is defined as the V 0 during exercise above which there is a sharp 2  increase in anaerobiosis where lactate accumulation exceeds removal (Wasserman, 1984). Thus, the AT represents the upper limit of PO where lactate production and removal may attain equilibrium during constant load exercise (Rusko et al., 1986). Higher ATs have been associated with increased aerobic enzyme activity, lower muscle glycogen usage and lower blood lactate concentrations at the same relative workload, resulting in increased performance (Holloszy & Coyle, 1984; Coyle et al., 1988; Coyle et al., 1991; Loftin & Warren, 1994). The AT has proven useful for predicting the ability of athletes to sustain a given work rate for a prolonged period (Rhodes & McKenzie, 1984; Peronnet et al., 1987) and for determining the V 0 above which there is cardiovascular 2  insufficiency in meeting tissue O2 requirements (Wasserman, 1984).  Hypothetical^  then, the AT, as defined by either the lactate threshold (T| ), or the ventilatory threshold ac  21  (T ent) [Weltman, 1995] could be the ultimate intensity at which an ultraendurance V  triathlete could perform at during the Ironman Triathlon. 2.5.1 Lactate Thresholds The lactate concentration is approximately the same at rest in relatively fit adults, in normal sedentary subjects, and in adult patients with heart disease (Wasserman et al., 1994).  But during exercise, the increase of lactate is inversely related to the  physical fitness of the individual (Barlow et al., 1985). During incremental work, the lactate concentration increases initially very little until a distinct metabolic rate is reached at which lactate starts to increase steeply. This point is termed the lactate threshold (Ti ). The two prevalent theories underlying the Ti are the fixed 4.0 mmol/L ac  ac  threshold and the interindividual lactate threshold, which occurs at different points for each individual. The reader is referred to Sjodin & Jakobs (1981) and Stegmann et al. (1981) respectively for an in depth review on each T| . ac  2.5.2 Ventilatory Thresholds Above the Ti , accelerated glycolysis increases muscle lactic acidosis. This ac  acidosis is buffered primarily by bicarbonate which causes an increased alveolar CO2 output relative to 0 uptake (Wasserman et al., 1994). Davis et al. (1976) determined 2  that gas exchange AT was a valid indirect method for the detection of the development of lactic acidosis during incremental exercise.  Several ventilatory parameters have  since been used to assess T t- These include V 0 ven  2 M A X  , ventilation ( V ) , excretion of E  carbon dioxide ( V C 0 ) , and the ratio of ventilation to maximum oxygen consumption 2  ( V / V 0 ) [Davis et al., 1976; Black et al., 1998; Schneider et al., 1993; Loat & Rhodes, E  2  1993; 1996; Anderson & Rhodes, 1989]. T t using the V-slope method (Schneider et ven  22  al., 1993) is determined as the point at which VC0 departs from a line of linearity 2  compared to that of V 0 and can be calculated using visual inspection (Frangolias & 2  Rhodes, 1996) or computerized calculation (Black et al., 1998).  Similarly, the  v / V 0 breakaway point T nt calculation is determined as the point at which VE departs E  2  ve  from a line of linearity compared to that of V 0 (Takano et al., 1991). This has also 2  been proven to be a reliable measure of the A T (Caiozzo et al., 1982). 2.5.2.1 Relationship between Lactate and Ventilatory Thresholds It is equivocal as to whether T| and T t occur at the same exercise intensities ac  (Weltman, 1995). While T i  ac  ven  and T t may occur at the same intensity (Simon et al., ven  1986), Tiac has also been shown to occur at a higher relative exercise intensity to that of Tvent (OToole et al, 1989).  Therefore these two concepts might not necessarily be  related by cause and effect (Simon et al., 1986; Tanaka et al., 1986). Although there are many firm believers in the cause-and-effect relationship of T ent and T i V  a c  (Davis, 1985; Wasserman et al., 1994; Wasserman, 1984) some reviewers  question the phenomena (Brooks, 1985; Stainsby, 1986; Walsh & Banister, 1988). Nevertheless, both T| and T t are widely used and generally accepted measures of ac  ven  endurance performance ability (Loat & Rhodes, 1993; 1997). At the very least, T t ven  provides important information concerning the relative level of T| . ac  2.5.2.2 Performance at Ventilatory and Lactate Thresholds AT as indicated by either T t or T i ven  ac  improves with training (Hill et al., 1987) and  when measured in the appropriate exercise mode has been related to swim, cycle and run performance in the triathlon (Sleivert & Rowlands, 1996). Hence, the ability of the triathlete to exercise at a higher percentage of V o  2max  f o r a given submaximal workload  23  is essential for triathlon success. This is influenced not only by v o  2 m a x  itself, but also by  A T and economy of movement (Sleivert & Rowlands, 1996). To illustrate the importance of training specificity and how it relates to the AT, Mazzeo & Marshall (1989) compared T| and T t in highly trained runners (n=6) and ac  ven  cyclists (n=6) during both treadmill running and cycle ergometry. Although V o  2max  not differ significantly for the cyclists during treadmill running and cycling, both T i  a c  did and  T ent occurred at a relatively earlier workload during the treadmill run. They found the V  opposite was true for the runners (Mazzeo & Marshall, 1989). Triathlon is a unique sporting event requiring high relative ATs in both running and cycling. Therefore, training in all three disciplines is important to influence specific muscle groups causing increases in aerobic enzymes, subsequent increases in AT, and improved performance (Coyle,  1995). Strength training programs have also demonstrated  improvements to both T i  a c  significant  and cycling time to exhaustion at a constant work rate and  are therefore recommended to ultraendurance triathletes as supplemental training (Marcinik et al., 1991, Tanaka & Swensen, 1998). 2.5.3 Time to Exhaustion at the Anaerobic Threshold Laboratory assessments of cycling time to exhaustion at a subjects' AT have been reported to range from 48 to 255 minutes depending on the fitness of the athletes, the supply of exogenous fluid/CHO, and whether T i or T t was used to determine AT a c  ven  (Aunola et al., 1990; Davis et al., 1992; Loat & Rhodes, 1996). These studies indicate that the AT is too high of an intensity to be maintained during an UET, and that factors mentioned earlier (caloric balance, fluid homeostasis, and substrate shifts) cause detriments in prolonged performance.  Thus, an optimum ultraendurance intensity,  24  different than the AT intensity, represented as a percentage of  vo  2max  or AT, is needed  to establish ultraendurance intensity guidelines. 2.6 Thresholds for Long-Distance Performance It is equivocal whether or not v o performance.  2 m a x  and  T nt v e  are good predictors of triathlon  While some researchers have demonstrated a relationship (Zhou et  al.1997; Butts et al., 1991; Kohrt et al., 1987; De Vito et al., 1995), others have not (Dengel et al., 1989; OToole et al., 1989; 1996 Langill et al., 1993, unpublished thesis). These mixed findings may be due to the variability of athlete fitness, athlete experience, as well as uncontrollable environmental factors. This could also be due to the apparent effect that prior exercise has on each subsequent event during a triathlon. For example, it has been demonstrated previously that the AT can be reduced by the glycogen content of the muscles (Friedmann, 1998), substrate manipulation (Ivy et al., 1981; Glass et al., 1997), prior exercise (Black et al., 1984; Neary & Wenger, 1985) and extreme fatigue (Rowbottom et al., 1998). Likewise, rest and tapering have been shown to increase oxidative enzymes and muscle glycogen levels, and subsequently increase PO at  T ent V  (Neary et al., 1992). Nevertheless, the threshold concept has been well  researched and applied in each facet of the triathlon event; swimming, cycling, running, and the triathlon race as a whole. 2.6.1 Thresholds for Swimming Swim times during a triathlon are not related to the physiological variables measured in maximal cycling and running tests (Zhou et al., 1997).  Furthermore,  resistance training does not appear to enhance swimming performance in untrained or competitive swimmers, despite substantial increases in upper body strength (Tanaka & Swensen, 1998). This is largely due to the specific skills and the efficient economy of  25  movement  required for swimming  demonstrates lower values of  vo  2peak  (Sleivert  , and peak  & Rowlands, V  E  1996).  Swimming  versus cycling (Spinnewijn et al.,  1996), which is most likely due to a decreased muscle mass utilization relative to cycling (McArdle, 1985; Medelli et al., 1993). Nevertheless, physical effort during the swim portion of a triathlon is very much required. Rating of perceived exertion (RPE) (Borg, 1982) has been shown to be reached at a lower percent of  Vo  2max  during swimming  versus cycling (Spinnewijn et al., 1996) while blood lactate levels have been demonstrated to be highest in a triathlon during the swim portion (Lavoie, 1982; Pages etal., 1994; Farber etal., 1991). 2.6.1.1 Effects of Swimming on Cycling Performance in swimming does not play the most important role in triathlon performance (Dengel et al., 1989; Margaritis, 1996). Swimming does however elicit a higher relative CHO oxidation rate than cycling during prolonged exercise at the same relative work intensity (Lavoie, 1982). This is primarily due to the larger percentage of fast-twitch muscle fibres that exist in the upper extremities relative to the lower extremities (Farber et al., 1991). Consequently, the preferred energy pathway of fasttwitch muscle fibres is that of glycolysis, which has a byproduct of lactic acid. Thus, it is logical to assume that an increased lactate concentration produced during the swim portion is utilized as substrate during the cycle portion of a triathlon (Farber et al., 1991; Brooks, 1986). Nevertheless, swimming must still be considered to affect subsequent cycling and running bioenergetics (Hausswirth et al., 1996; 1997; Guezennec et al., 1996). Kreider and co-workers (1988) demonstrated that swimming significantly decreased triathlon cycling PO (191 ± 4.2 to 159 ± 7.6 W) compared to control trials in nine male  26  triathletes during a simulated Olympic distance triathlon (see table 2). However, the mean PO of the group indicates that this triathlon population was a moderately trained group. Nevertheless, swimming prior to cycling produced significant differences (p < .05) in most of the measured physiological variables in this moderately trained group (Kreider et al., 1988).  Interestingly, no significant difference in HR was observed  between the control and triathlon cycling trials. The effects of swimming on ensuing cycling performance in elite ultraendurance triathletes has not been published.  However, we (Laursen et al., 1999) recently  demonstrated that 3000m of swimming does not affect 3 h cycling performance (in terms of PO) in eight highly trained ultraendurance triathletes when a CHO/electrolyte beverage was consumed. Presumably the administration of this beverage offset some of the thermoregulatory differences that were apparent in Kreider et al. (1988a), enabling our subjects to maintain a similar PO compared to a control trial during a 3 h self-selected pace cycling time-trial. Physiological effects of 800m swimming prior to 75 min cycling during a  Table 2.  simulated Olympic distance triathlon (Modified from Kreider et al., 1988a). Parameter  Cycling  Swimming prior to Cycling  Mean Difference  P Value  Cycling work output (W)  191 ± 4 . 2  159 ± 7 . 6  -32  < 0.001  V0  3.18 ± 0.10  3.01 ±0.11  -0.17  < 0.001  84.7 ± 4  80.4 ± 4 . 2 1  -4.30  = 0.003  Q (Lmin" )  20.7+1.2  18.9 ± 0 . 8  - 1.8  = 0.002  mean arterial pressure  105 ± 3 . 8  96 ± 7 . 9  -9  = 0.0001  38.2 ± 0 . 2  38.4 ± 0 . 3  + 0.2  = 0.01  V  (Lmin" ) 1  2  (Lmin" ) 1  E  1  (mm Hg) Rectal temperature (°C)  27  2.6.2 Thresholds for Cycling The cyclist's ability to maintain an extremely high rate of energy expenditure for a long duration at a high economy of effort is dependent upon such factors as the individual's AT, muscle fibre type, muscle capillary density and certain anthropometric dimensions (Faria, 1992; Bishop et al., 1988; Coyle, 1995). While cycling time trial distances of 13.5 km, and 20 km have been reported to be performed at levels above the AT (Nichols et al., 1997), distances beyond 40-km have been demonstrated to be performed below the AT (OToole et al., 1987a; Hoogeveen & Schep, 1997). This evidence demonstrates that limitations to the AT concept exist and suggests the need to consider a concept that allows homeostatic exercise demands to be met optimally for prolonged periods at exercise intensities below the AT. 2.6.2.1 Effects of Cycling on Running The effects that both the swimming and cycling segments of the triathlon have on subsequent running performance may be the most important factor to consider when looking at the overall triathlon performance.  Marathon times during an UET are  extremely variable and can range from; approximately 2.5 hours, to over 6 hours (Docherty, 1998). Hence, the ability to run after prolonged swimming and cycling is important to overall triathlon performance, and depends on many factors.  These  include the effects of the prior exercises, as well as the fuel, hydration, and electrolyte status during the marathon. Kreider and co-workers (1988b) demonstrated that triathlon running performed at an identical control PO elicited significant changes in many physiological variables in nine moderately trained triathletes (Table 3).  28  Table 3 . Physiological effects of 800m swimming, and 75 min cycling prior to a 40 min run during a simulated Olympic distance triathlon. Both control and triathlon runs were performed at identical workloads. (Data from Kreider et al., 1988b). Running  Parameter  P Value  Swimming and Cycling  Mean  prior to Running  Difference  Heart Rate (bpm)  161 + 3 . 1  174 ± 3 . 6  + 13  = 0.0001  V0  3.41 ± 0 . 1  3.85 ± 0 . 1  + 0.44  = 0.001  91.3±3.3  104.2 ± 2 . 8  + 12.9  = 0.0001  15.3 ± 0 . 2  17.2 ± 0 . 3  + 1.9  = 0.002  Rectal temperature (°C)  38.3 ± 0 . 2  39.2 ± 0 . 3  + 0.9  = 0.005  Stroke Volume (ml-min" )  138 ± 2 . 4  129 ± 3 . 6  -9  = 0.02  Mean arterial pressure (mm Hg)  102 ± 11.2  89 ± 5.5  -13  = 0.0003  V  (Lmin" ) 1  2  (Lmin" ) 1  E  Arteriovenous 0 Difference 2  (mMOOml" ) 1  1  Hence, prior swimming and cycling caused increases in HR, V o , V , 2  E  a-v02  difference, and rectal temperature, with decreases in SV and arterial pressure. De Vito and collegues (1995) demonstrated vo  2peak  and  T  ven  t  to be reduced by the first two  segments of a triathlon (1.5-km swim, 32-km bike). V0 mlkg" min" while 1  1  T nt v e  decreased from 69 to 64  2peak  decreased from 58 to 51 mlkg" min" . As well, prior swimming 1  1  and cycling were reported to create physiological differences in subsequent running performance during simulated laboratory triathlons (Hausswirth et al., 1996; 1997; Guezennec et al., 1996). The explanation of these physiological effects include dehydration,  fuel  availability  (glycogen),  substrate  utilization,  muscle  fatigue,  cardiovascular fatigue and fluid compartment shifts (OToole & Douglas, 1995). Hence, the impairment of endurance performance induced by the first two segments of a triathlon is well established and is an important aspect to consider when observing triathlon run intensity.  Ultimately, the ability to minimize the effects of the  29  aforementioned proposed mechanisms will hypothetically elicit an optimal triathlon run performance. These factors will be important elements to consider when establishing an ultraendurance threshold (UT). 2.6.3 Thresholds for Running Numerous researchers have confirmed that the AT is related to endurance performance in running events ranging from 10 km to the marathon (Petit et al., 1997; Roecker et al., 1998; Rhodes & McKenzie, 1984; Perronnet et al., 1987). Farrel and associates (1979) demonstrated that runners set a race pace that allows the largest possible V 0 t h a t just avoids the exponential rise in plasma lactate. 2  Sjodin &  Svedenhag (1985) provide further evidence showing that elite marathon runners run their races at an average pace equal to 86% approximately 93% of their 4 mmolL" T| 1  ac  vo  2max  .  This pace represented  (OToole & Douglas, 1995).  marathon runners (finishing times >3hrs) reportedly ran at 65% V 0  2 m a x  Slower  . Therefore, elite  marathon runners were able to sustain higher relative and absolute energy outputs leading to faster finish times. Hence, the capacity to sustain a high fractional utilization of  vo  2max  during distance running is related to endurance running performance.  2.6.4 Thresholds for Triathlon When assessing the AT in triathletes, it is necessary to take into consideration the type of ergometer used as different protocols have been reported to generate different values, usually running  vo  2max  greater than cycling V 0  2 m a x  (Schneider &  Pollack, 1991). The amount of muscle mass, the type and the distribution of active motor units involved in each exercise test might be at the origin of these differences (Medelli et al., 1993). AT also occurs at a lower percent of V 0  2 m a x  i n cycling versus  30  running, however, this may only suggest that triathletes have a greater potential for improvement in cycling. Improvement in event specific AT may be the most important factor to improved performance. Kohrt and co-workers (1989) reported increases of 6% and 10% in PO at T| for cycling and running respectively without an improvement in ac  v  0  2max  • Hence, improvement in triathlon performance is dependent on the ability of the  triathlete to utilize a greater percentage of V 0  2 m a x  .  Studies on longer duration triathlons have not demonstrated the same results. OToole and colleagues (1989) studied the relationship between exercise test variables and bike race times in 24 participants (14 men, 10 women) entered in the 1985 Hawaiian Ironman Triathlon. The researchers found that V 0 values at ATs were not 2  highly related to bike finish times (r = -0.26 to -0.58). Furthermore, % v o %HR ax m  2peak  , HR, and  at thresholds were not related to bike finish times (r = -0.01 to 0.06). This  indicates the importance that other factors such as fuel and hydration homeostasis have on ultraendurance success.  The sport of triathlon, however, has grown immensely  since 1985 and the top triathletes are now more educated in their race strategy. Most triathletes understand the need for proper pacing, as well as the importance of hydration and refueling schedules during an ultraendurance event (Laursen & Rhodes, 1999). This has lead to increased Ironman triathlon performance times over the years (Docherty, 1998). Therefore, it would be valuable to repeat this research with today's ultraendurance triathlete. 2.6.5 The Use of Heart Rate Monitors to Measure Intensity in Ultraendurance Athletes Because little scientific information is available for the use of HR monitors during performance, athletes fail to fully take advantage of physiologic information (OToole et  31  al., 1998). Although HR parameters measured in the laboratory might underestimate those in the field (Kenny et al., 1995), HR measured during a triathlon has been reported to be similar to HR at T t during a physiological assessment (Zhou et al., v e n  1997; OToole et al., 1987a; Roalstad et al., 1987). Thus, HR monitoring may allow for a more precise control of intensity than that of subjective monitoring alone. However, estimated maximal HRs are too variable to be of use to precisely guide training pace during cycling or running (Saldanha et al., 1997). Therefore, a laboratory physiological assessment is important for the ultraendurance triathlete to establish parameters such as HRm , and HR at T t. This provides the athlete with knowledge ax  ven  regarding the approximate HR intensities (or percent of H R  m a x  )  at which to train at, as  well as limitations to long-duration race performance. OToole and associates (1998) suggests that during prolonged (> 6 h) cycling or running, a highly-trained athlete may expect to exercise at an average intensity close to 80% H R  m a x  ,  but should also expect  intensity to decline by 6-7% during the cycle ride or run. This decreased HR near the end of prolonged exercise suggests that intensity declines during ultraendurance events. This may occur due to substrate depletion, altered muscle efficiency, fluid and electrolyte imbalances, thermoregulatory problems, cardiac fatigue, as well as psychological factors (OToole & Douglas, 1995).  Hence, the ability of the  ultraendurance athlete to identify specific reasons for this intensity decline may be important for success in future ultraendurance endeavors (OToole et al., 1998). Roalstad and colleagues  (1987) reported that  ultraendurance  triathletes  maintained average HRs of approximately 75% of their HRm during the bike and run ax  portions of the Hawaii Ironman. Furthermore, the better finishing times were found in triathletes where HRs fluctuated the least during the race. Nevertheless, much remains  32  to be clarified about the HR responses of ultraendurance athletes, particularly in relation to performance and the attainment of individual maximal potential. 2.7 A New Paradigm: The Ultraendurance Threshold (UT) Indeed, the AT has been demonstrated to be a reliable measure to predict the ability of athletes to sustain a given work rate for a prolonged period (Roecker et al., 1998; Rhodes & McKenzie, 1984; Wasserman, 1984). The AT represents the upper limit of PO where lactate production and removal may attain equilibrium during constant load exercise (Rusko et al., 1986). Hypothetical^/ then, the AT could be the optimum intensity at which an ultraendurance triathlete could perform at during the Ironman Triathlon. But this is truly not the case. Athletes have been shown to perform for up to 255 minutes at the AT when supplied intermittently with a CHO/electrolyte beverage (Davis et al., 1992). OToole and co-workers (1987a) demonstrated that ultraendurance triathletes perform at a pace below their AT. Consequently, other factors come into play then that inhibit the ability of the athlete to maintain their AT intensity. These include substrate utilization shifts, plasma volume decline, and muscle recruitment pattern shifts (Farberetal., 1991; OToole et al., 1987a). As exercise increases in duration, CHO supply.from glycogen stores decline and caloric demands require a greater contribution from fat and protein stores (Kreider, 1991). Subsequently, this decreases exercise intensity as fat oxidation reduces the availability of ATP relative to the oxidation of CHO (Gollnick, 1988). Evidence for this is shown as an increased V 0 during prolonged exercise. 2  For example, OToole and  associates (1987b) reported in 5 of 7 world class female ultraendurance triathletes that V 0 increased significantly during the first 2.5 hours of a 5-hour cycle. Because fat 2  metabolism requires approximately 5% more oxygen to produce the same external  33  work, and the increase in V 0 was found to be 8%, this most likely accounts for some of 2  the increase (OToole et al., 1987b). Further evidence for this substrate shift is shown from RER data (0.93 - 0.5hrs, 0.85 - 2.5 hrs, 0.82 - 5hrs). Intensities near the AT require a significant contribution from CHO stores (Gollnick, 1988). It stands to reason that when CHO stores begin to diminish, fat oxidation increases to meet the body's energy demands, and subsequently intensity declines (OToole et al., 1987a).  Furthermore, an increased intensity will produce  higher lactate levels early on in performance.  This racing technique has been  demonstrated to reduce overall endurance performance (Firth, 1998; Wasserman, 1987).  Hence, attempting to complete an UET at the AT would be detrimental to the  overall performance. Although intensities at the AT represent the upper limit of PO where lactate production and removal obtain an equilibrium (Rusko et al., 1986), substrate equilibrium  is out of balance (CHO oxidation > fat oxidation) for  ultraendurance exercise. Therefore, the UT must take into consideration the limited glycogen storage capacity and limited provision of exogenous CHO due to finite gastric emptying rates (Tsintzas & Williams, 1998; Coyle & Montain, 1992), in an attempt to maintain a more balanced fuel utilization. Certainly, CHO utilization during the first two hours will be out of proportion, as glycogen stores are initially high, and glycogen promotes its own usage at high concentrations (Gollnick, 1988). However, beyond this two to three hour period of exercise, fueling contribution obtains more of an equilibrium (OToole et al., 1987b). Hence, the UT is an exercise intensity that maintains a more balanced fuel contribution leading to increased performance. Dehydration decreases exercise intensity due to decreases in Q. This can be prevented by fluid ingestion. Nevertheless, it seems that fluid compartment shifts also  34  .  occur during ultraendurance events resulting in decreases in SV (Farber et al., 1991). However, Q might still be maintained by an increase in HR (OToole et al., 1987b). Hence, the UT might be affected by these compartment shifts even under homeostatic hydration conditions. Therefore, HR intensity would have to be adjusted accordingly to the individual's plasma volume response to prolonged exercise.  More research is  required to understand the fluid compartment shifts during prolonged ultraendurance exercise. It has been shown that the neuromuscular system adapts during prolonged exercise by recruiting different muscle groups (OToole et al., 1987b). As the muscles begin to fatigue, technique and recruitment patterns can be altered to accomplish the same work output (Sjogaard et al., 1986). This adaptation changes the economy of motion requiring greater V 0 a t the same PO (Sleivert & Rowlands, 1996; OToole et 2  al., 1987b). These changes in muscle recruitment patterns also happen naturally during triathlons as exercise mode changes from swimming, to cycling, to running.  The  influence that the preceding event has on subsequent events has been demonstrated (Kreider et al., 1988; Laursen et al., 1999). Therefore, the UT intensity must take the preceding event into consideration. For example, running after prolonged cycling might change HR parameters due to the increased use of relatively rested muscle fibres during the initial stages of the marathon. Hence, just as V 0  2max  and AT are specific to  the event protocol, so would be the UT. For example, Dengel and colleagues (1989) calculated event-specific % v u percent V 0  2max  2max  f o r swimming, cycling, and running and found the  used during the submaximal tests was significantly related to swimming  (r=0.91), cycling (r=0.78), and running (r=0.86) times during a Half-lronman triathlon. Hence, the UT is specific to each event.  35  When the majority of these possible hypotheses for the demise of the intensity at the AT are taken into account, a new intensity can be reestablished. This new intensity would have to take into consideration the aforementioned factors allowing for adequate substrate, fluid  and electrolyte, and neuromuscular  homeostasis  to be met.  Accordingly, I offer that a unique physiological paradigm be proposed for the ultraendurance athlete that accompanies the aforementioned considerations that the ultraendurance athlete encounters during prolonged ultra-distance exercise.  This  paradigm would be called the ultraendurance threshold, and would be defined as the optimum intensity that an ultraendurance athlete can perform at during an ultra-distance event. 2.8 Conclusions This review has outlined considerations for the development of an UT where the UT could be defined as the optimum maintainable exercise intensity during ultraendurance performance. It has been outlined that the UT can be monitored by HR readings, and that after HR reaches a steady state, a slow but steady increase occurs representing the effects of CV drift. Over time, intensity may decline due to substrate shifts and neuromuscular fatigue by 6% - 7% (OToole et al., 1998). Hence, the graph of mean HR over time for ultraendurance athletes may appear similar to that of Figure 1. The UT is a unique paradigm to other threshold concepts in that it must take into consideration the unique complications of prolonged ultraendurance exercise. These complications include substrate utilization, fluid and electrolyte homeostasis and the effects of dehydration and plasma volume shifts on cardiovascular function.  Other  considerations include the effect that the preceding event has on subsequent events, as  36  well as neuromuscular fatigue. These considerations will all affect the ability to maintain performance at the AT. Although, the UT will exist at an intensity below the AT, it may prove to be proportionate.  For example, subjects with higher ATs may have higher  UTs. Evidence for this concept has been previously provided. OToole and associates (1987a) demonstrated that a metabolic rate exists below the AT that defines an individual's maximal ultraendurance steady state for the cardiorespiratory and metabolic response to exercise. The study reported a moderate correlation (r = 0.61; p < .05) between percent v o  2peak  at 10W below mean T t work rate and bike finish times in the ven  Hawaiian Ironman. Hence, here lies evidence that an UT exists at a relative rate below the AT. Consequently, further research is required to determine adequately whether a critical intensity exists relative to V0  2max  and the AT in ultraendurance triathletes. This  intensity will also take into account the unique considerations of ultraendurance events. This relative intensity could be defined as the ultraendurance threshold.  37  Figure 1.  A hypothetical plot of HR over time during an ultraendurance event  (according to data suggested by OToole et al., 1998).  Hypothetical Plot of HR over Time During Ultraendurance Exercise  HR at A T  38  CHAPTER 3: METHODS AND PROCEDURES 3.1 Subjects Eleven male ultraendurance triathletes were selected from the province of British Columbia to participate in this study.  This sample size is similar to previous UET  studies (OToole et al., 1987a; 1989; Farber et al., 1991). through  an  advertisement  placed  on  the  Ironman  Subjects were solicited Canada  web  page  (http://www.ironman.ca) and in the British Columbia Triathlon Association newsletter (TriBC Word).  The inclusion criteria included a cycling V o  2max  o f score of 60  ml-kg" -min" , and having completed a minimum of one prior Ironman Triathlon distance 1  1  event in under 12 h. Approximately the top 20% of all male finishers finish within this time period (Docherty, 1989). The exclusion criteria were (1) not being able to complete any of the testing procedures, (2) not being able to complete the bike portion of the Ironman Triathlon in less than six hours, or (3) not being able to complete the Ironman race. Before testing, all risks and benefits were thoroughly explained to the subjects and written informed consent was obtained in accordance with the Guidelines for Ethical Review at the University of British Columbia. 3.2 Testing Procedures All laboratory testing was performed in the J.M. Buchanan Exercise Science Laboratory at the University of British Columbia. Subjects were asked to prepare for all testing in the same manner they would prepare for an ultraendurance race. Subjects were instructed to refrain from heavy exercise 24 hours prior to all tests. Individuals were informed of the intent of the study, hypotheses and experimental protocols. Prior to the first session, consent forms were signed, followed by baseline measures of height, weight and percent body fat (Going, 1996). During session #1 (BiV0 max1), a 2  39  maximal oxygen consumption test ( V 0  2 m a x  )  was performed on a cycle ergometer to  determine whether or not athletes were to be included in the study, and also to establish threshold calculations. Session  # 2 (TrV02max1)  of 48 hrs separated the v o any carry-over effects.  2max  consisted of a V 0  2max  t e s t on the treadmill. A minimum  tests from any subsequent test in an attempt to prevent  Session  fatigue at the athletes calculated  #3  (Bi-r nt)  P O  at  ve  T  v e n  consisted of a cycling ride to volitional  t (PO  T v e  nt)-  The main purpose of this test  was to establish whether or not the AT is a reasonable intensity to be maintained during the cycle portion of the UET. Session #4 (Bissp) consisted of an ultraendurance cycling 5 h ride at the athletes' self-selected P O performed on the cycle ergometer. Athletes were asked to mimic the pace that they would choose to ride at during the Ironman Triathlon bike course. P O was blinded to the athlete during both experimental sessions. A second treadmill run V0  2max  t e s t (Session #5; TrV0 max2) immediately followed Bissp. The rationale for this 2  test was to determine if running speed at T nt could better predict marathon run ve  performance during the Ironman compared to that of TrV0 max12  The Bi ent trial and Tv  Bissp trial were completed in random order so as to avoid training effects. Session  # 6 (BiV0 2 max2),  a cycle v o  2max  t e s t , consisted of an identical procedure  to that of BiV0 max1 and took place approximately two weeks pre-event to ensure that 2  V0  2 m a x  , Tvent  BiV0 a 12m  X  and baseline measures did not change significantly compared to those of During this test, hematolgical status was determined through measured  hemoglobin (Hb) and hematocrit (Hct) levels.  40  Session #7 (IMC) consisted of HR measurements during the Canadian Ironman Triathlon, in Penticton, British Columbia, on August 29 , 1999. This was accomplished th  using computer downloadable portable HR monitors (Polar Vantage NV, Polar Electro, Finland). 3.3 Testing Protocols During all laboratory testing sessions, expired gases were collected and analyzed using the Vmax metabolic cart (V6200, SensorMedics Corporation, Yorba Linda, CA). HR was measured using a Polar Vantage NV HR monitor (Polar Electro, Finland), and cycling PO was calculated using a electronically braked cycle ergometer (SensorMedics 800 Ergometer, SensorMedics Corporation, Yorba Linda, CA). All capillary blood samples were collected from fingertips in 25-u.L heparinized capillary tubes.  All sessions were preceded with an explanation of the testing procedures  followed by a physiological warm-up with all the equipment in place against a light resistance load. This provided the subjects with an opportunity to become familiar with the equipment and the actual process for gathering data during the test. During the  vo  2max  tests, volitional fatigue was defined by the following criteria:  1. The oxygen consumption ceases to increase linearly with rising workload and approaches a plateau or drops slightly, the last two values agreeing within ± 2 ml-kg" -min" . 1  1  2. Attainment of 90% of age predicted H R  max  3. Respiratory exchange ratio (RER) is greater than 1.10 Tvent was  calculated using the excess CO2 (EXCO2) elimination curve (Frangolias  & Rhodes, 1996) by visual inspection by two independent reviewers for identification of  41  the PO and running speed at which CO2 showed a sudden and sustained increase (i.e. Tvent)-  In the event of a disagreement, the V / V o curve (Takano et al., 1991) was used E  2  to clarify the actual threshold point. Session # 1 - Bike  1 V0  2 m  ax  Test  (BiV0 max1) 2  The electronically braked cycle ergometer was used with the protocol starting at an initial workload of 100W and having progressive increases of 30W each minute. Volitional fatigue was defined by either the inability to maintain a minimum cadence of 40rpm or the subject's own termination of the test. Session #2 - Treadmill V 0  2  m  a x  Test  (TrV02max1)  This procedure involved a continuous (zero grade) treadmill run protocol started at an initial velocity of 3.5 mph and increased 0.5 mph each minute.  After the  attainment of 10 mph, the grade was increased by 2% each minute. Volitional fatigue was defined by the athlete no longer being able to maintain the treadmill velocity. This protocol created difficulties in representing peak speed numerically for statistical analysis. Therefore, time on the treadmill was used as a maximum speed/power value, called maximum treadmill time (MTT). From that, a percentage of maximum treadmill time (%MTT) was calculated from the speed at which T  v e n  t  occurred (%MTT-T ). vent  Session #3 - Ventilatory Threshold Ride to Volitional Fatigue Baseline  levels  of weight,  blood  lactate  (Lac")  (Bi ent) Tv  (Accusport,  Boehringer  Mannheim), blood glucose (Glu) (One Touch II, Lifescan Canada Ltd., Burnaby, B.C.), and hematocrit (Hct) were recorded. Hct determinations were made by centrifugation for 5 min using a microcapillary centrifuge (Drummond Scientific Co., Broomall, PA.). After warming up and becoming familiar with the testing procedures, the subject began riding  42  at POivent that was calculated during BiV0 max12  After 5 min riding to obtain steady  state, expired gases were collected for 5 min, and thereafter for 5 min at the top and bottom of each hour thereafter. When the athlete felt he could maintain his cadence for less than 5 min, a final gas collection procedure occurred until volitional fatigue. Lac", Glu, and Hct were also recorded at the top of each hour of exercise, and at exhaustion. Borg's rating of perceived exertion (RPE) (Borg, 1982) was inquired every 30 min throughout.  Subjects received unlimited access to water, and a CHO/electrolyte  beverage (Shaklee Performance™) during this test to maximize their time to exhaustion (Davis et al., 1992).  Quantities of each were recorded. Volitional fatigue was defined  as the athlete unable to maintain a cadence of 40 rpm or the subject's own termination of the test. Weight was measured post-test to determine fluid loss/gain. Session #4 - Five-Hour Cycling Time Trial at Self-Selected Pace (Bi sp) S  A minimum of one week separated the experimental trials. Bissp protocol was identical to that used during Bi ent with one exception; that being the ability to increase Tv  or decrease PO according to what the subject felt was a pace they would ride at during the Ironman Triathlon bike course.  Although PO during the ride could be either  increased or decreased at the request of the subject, the subject was encouraged to choose a PO that they would be challenged by, while at the same time being able to maintain for the 5 h duration. Because of the duration of Bissp, and potentially Bi nt, Tve  athletes were permitted to use the toilet as required. The required time off the bike was recorded and adjusted so that the subject would have to complete the full 5 h of cycling during Bi sp- Immediately following Bissp- athletes performed a transition (standardized S  at 5 min) into run apparel to complete session #5 (TrV02max2), which was identical in procedure to that of BiV02max1 •  43  Session # 6 - Bike V 0 a x Test (BiV0 ax2) 2m  A v o  2  max  2m  test, identical to the BiV0 x1 occurred approximately two-weeks prior 2rria  to I M C to ensure that V 0  2max  a n d T t did not change significantly from BiV0 m 1 due ven  2  ax  to training effects. At this point, descriptive hematolgical parameters were determined in duplicate. Hemoglobin (Hb) concentrations were measured colorimetrically (540nm) after conversion to cyanmethemoglobin, using Sigma Diagnostics test reagents. (Sigma Diagnostic assay kit #525), while Hct determinations were made by centrifugation for 5 min. Descriptive measures of weight and body composition were measured again. Session # 7 - The Canadian Ironman Triathlon, Penticton, B.C. August 2 9 , 1 9 9 9 (IMC). HR was recorded at 60-second intervals during the race using downloadable Polar HR monitors. Watches were removed from the athletes and information was downloaded at the earliest possible convenience. All timing during the race was done electronically by SportStats, the official timers for I M C . 3.4 Experimental Design and Data Analysis A repeated measure analysis of variance (ANOVA) was used to compare the dependent variables, V 0 , % V 0 2  2 m a x  , %T t, %PO nt, RER, V , PO, Lac", Glu, Hct, ven  Tve  RPE, and pedaling rate (PR) during Bi nt and Bi spTve  S  E  The comparison of individual  variables between trials was conducted using Hotelling T . 2  HR during I M C was  compared with HR during both Biivent and Bissp using trend analysis to compare the pattern of change over time. A one-way ANOVA was used to compare the dependent variables V 0  2 m a x  , T  ven  t , HR at T  ven  t (HR ent), percent of HR Tv  max  at T t ( % H R m T v e n t ) , ven  a x  44  v  Emax  , and R E R p e a k for B i V C W I ,  BiV0  2m  ax2, TrV0  2m  ax1  and T r V 0  2 m a  When the  x2.  ANOVA revealed a significant difference, Tukey's Post Hoc test was used to specify where the difference occurred. Hotelling T was used to examine differences between 2  the two run V0  2 m a x  2 m a x  tests (MTT,  T  ven  speed,  t  %MTT-T  tests; peak PO (PPO), percent of PPO at T  vent  ven  and the two cycling  t),  (%PPO-T  ven  t),  and PO at  Pearson Product correlation examined the relationship between  (POivent)-  and  V0  TrV0  2 m a x  predictions of I M C marathon run time, and actual  2  IMC  TrV0  T  2 m a  ven  t  x1  marathon run  time. Pearson Product correlation matrix was also used to examine the relationship between  BiV0 m 1 2  ax  and B i V 0  2 m a x  2 HR ent Tv  and mean HR during  All statistics were run on SPSS 8.0 for Windows.  Bi  Tve  nt,  Bissp, and  IMC.  The alpha level was set at .05.  Results are expressed as a mean ± the standard error of the mean ( x ± S E M ) . 3.5 Diagram of Design Random Group Design  Table 4. Time Line For Testing  June 1 - 1 5  June 1 5 - 3 0  July 1 - 3 1  August 10-20  August 29  BiV0  2max  1  Biivent  BiV0  IMC  TrV0  2max  1  Bissp TrV0  2max  Time 0  RPE  I  I  1 hour  5min 5 min Gas  Height, Weight Resting Glucose Lactate, HR, Hct  t 5 min Gas  t  RPE RPE  I  +  5 min 5 min Gas Gas Glucose Hct Lactate  RPE  I  2 hour  t  2  2  Figure 2. Timeline of Testing Procedure for B i RPE  2max  RPE  I  t  5 min 5 min Gas Gas Glucose Hct Lactate  Tve  nt  and Bissp-  RPE  RPE  I I I  3 hour  t  +  5 min 5 min Gas Gas Glucose Hct Lactate  RPE 4 hour  t  RPE RPE  4 . -andA PTiwer throughout 5 hour  t  5 min 5 min Gas Gas Glucose Hct Lactate  t  5 min Gas Glucose Hct Lactate  •Unlimited access to water, CHO/electrolyte beverage, CHO bars throughout  45  CHAPTER 4: RESULTS AND DISCUSSION 4.1 Results 4.1.1 Descriptive Measures Ten of the eleven subjects in the study were focussing on competition at the 1999 Ironman Canada Triathlon (August 29 ), while one subject, on a similar training th  regimen was focussed on competition in the 1999 Florida Ironman Triathlon (November 4 ). This single subject's test data was only included for comparison of V 0 th  2 m a x  results  and experimental testing, however, when comparisons were made for IMC, his data was omitted from the analysis. Descriptive data of the subject pool is listed in Table 5. Hematological measures of oxygen carrying capacity (Hb and Hct) were within normal ranges (Bodary et al., 1999). Age was higher than in most Olympic distance triathlon studies (Bunc et al., 1996; Zhou et al., 1997; Sleivert & Wenger, 1993; Kreider et al., 1988a; 1988b) however, was typical of UET studies (OToole et al., 1987a; 1989). Training status during the testing period and prior to the 1999 Canadian Ironman Triathlon was 16.3 ± 1.0 hrwk" (2.7 ± 0.5 hrwk" swimming, 8.5 ± 0.6 hr-wk" cycling, 1  4.5 ± 0.5 hr-wk" running). 1  1  1  All subjects satisfied the criteria of having previously  completed an Ironman distance race in less than 12 hr (mean time = 10.73 ±0.17 hr). Table 5. Descriptive measures: age, height (Ht), weight (Wt), percent body fat (%BF), hemoglobin (Hb), and Hematocrit (Hct).  X  SEM  age  Ht  Wt  %BF  (yr)  (cm)  (kg)  (%)  Hct  Hb  (9-dL- ) (%) 1  35.8 176.7 68.9  11.7  16.9  43.9  2.2  1.2  0.2  0.4  1.6  2.3  46  4.1.2. V(X, Comparisons 2 max  The variables of HR, V 0 , and PO were measured as an absolute value at T t 2  ven  and as a relative percentage of their maximum (i.e. T nt/V0 ve  BiV0 ax2, TrV0 max1, and TrV0 2m  V0  2  2max  2max  a x  v e n  t, T  ven  t  TrV0  2max  absolute, V0  2max  relative, H R m , HR ent, a x  Tv  ven  E m a x  hoc test clarified the differences on v 2inax  2max  absolute, T t relative (all p > .05; Table 6). However, the ANOVA  revealed significant differences on v  running V0  ) for BiVC>2max1,  2. No significant differences were found during the  tests on the following variables: V0  %HRm -T  2max  , and R E R  Emax  Pea  k (p < 05; Table 6). Tukey's post  to exist between BiV0 ax2 and both treadmill 2m  tests (p < .05), while the significant differences in RER k were between  2 and both cycling V0  Pea  2max  tests (p < .05).  47  Table 6. Primary Variables. Comparison of the following variables over time between the maximal tests: absolute and relative oxygen uptake  ( V 0  ventilatory threshold (T t), maximum heart rate ( H R ven  max  2  ),  M  A  X  ) ,  absolute and relative  heart rate at ventilatory  threshold (HR nt), percent of maximum heart rate at T nt (%HR ax-T ent)- maximum Tve  ventilation  (v  Emax  ve  m  ) , and peak respiratory exchange ratio (RER k)pea  V  (t = Significant  difference between tests; p < .05).  BiV0 max1  x ± S E M , N=11  2  BiV0 max2 2  TrV0  2max  1  Bissp followed by  TrV0 4.57 ± 0 . 1 6  (L-min- ) 1  V 0  2  M  A  X  V 0  2  M  A  X  4.68 ± 0 . 1 6 4.74 ± 0 . 1 7  2max  2  4.45 ± 0 . 1 9  64.4 ± 1 . 0  67.5 ± 1.0  67.0 ± 1.4  63.3 ± 1.5  3.20 ± 0 . 1 2  3.30 ± 0 . 0 8  3.43 ± 0 . 1 3  3.24 ± 0.14  70.0 + 1.4  70.8+1.4  72.4 ± 1.1  73.2 ± 1.9  HRmax (beatsmin" )  179.2 ± 3 . 7  176.2 ± 3 . 3  185.3 ± 3 . 2  177.5 ± 2 . 2  HRivent (beatsmin" )  150.3 + 3.7  148.7 + 3.4  151.4 + 3.2  144.9 ± 2 . 6  %HR x-Tvent  83.9 + 1.6  84.5 ± 1.4  81.7 ± 1 . 2  81.7+1.1  171.1 ± 6 . 3  188.4 + 6.4  161.4 ± 5 . 2  153.6 ± 4 . 9  1.15 ± 0 . 0 2  1.15 ± 0 . 0 2  1.10±0.02  1.08 ± 0 . 0 2  (mlkg" -min" ) 1  1  T nt (L-min" ) 1  ve  Tvent (%V02max) 1  1  ma  v  (L-min" ) t 1  Emax  RERpeak +  48  No significant difference was found between P P O , POivent, and % P P O - T t ven  between BiV0 max1 and BiV0 ax2 (p > .05; Table 7). 2  2m  Furthermore, no significant  difference was found between %MTT-T t (p > .05; Table 8). However, TrV0 m 2 T t ven  2  ax  ven  speed and MTT was significantly less than TrV0 x1 (p < 05; Table 8). 2ma  Table 7. Within protocol comparison of measures during maximal cycle ergometer tests (BiV0  2max  1 vs. BiV0  2max  2): peak power output (PPO), power output at T t (PO nt), ven  Tve  percent of peak power output at T nt (%PPO-T t) (All p > .05). ve  x ± S E M , N=11 P P O (W)  ven  BiV0  BiV0 max1 2  2 m a x  2  420 ± 18  437 ± 18  T entPO (W)  274 ± 9  287 ± 9  %PPO-T t  65.7+1.1  66.1 ± 1.4  V  ven  Table 8. Within protocol comparison of measures during maximal treadmill run tests (TrV0 max1 vs. T r V 0 2  2max  2 ) : maximum treadmill time (MTT), speed at T nt (T t Speed), ve  ven  T ent expressed as a percent of maximum treadmill time (%MTT-T nt)- (t = Significant V  ve  difference between tests; p < .05). x ± S E M , N=11 MTT (min) t Tvent Speed (mph) t %MTT-T t (%) ven  TrV0  2max  1  16.25 ± 0 . 4 4  TrV0 x2 2ma  15.21  ±0.44  8.9 ± 0 . 3  8.4 ± 0 . 2  65.8 ± 2 . 1  64.2 + 1.6  49  4.1.3. Experimental Findings (Bi nt vs. Bi sp) Tve  S  During Bi nt, subjects #1, #5, and #11, could not perform at their POivent for Tve  longer than one hour (13, 38, and 45 min respectively). Therefore, their results were omitted for the statistical comparison between Bi nt and Bissp (N=8). The endurance Tve  time (ET) for the Bi ent trial equated to 2 h 10.7 ± 18.6 min, whereas all subjects Tv  completed the 5 h Bissp trial. In an attempt to decipher this apparent dichotomy (those that cycled for a long versus a short duration), the subject pool (N=11) was divided into those that performed less than 2 h (ET| = 49.1 ± 6.7 min; N=6), and those that performed greater than 2 h 0W  (ET  high  = 2 h 49.4 ± 1 2 . 1 min; N=5). Although a trend towards a higher CV and  metabolic rate relative to T t did exist in all parameters (ET| ven  0W  vs. ET h), the hig  differences were not statistically significant (p > .05). Pearson Product Correlation Matrix identified %PO-r entto have a significant relationship with ET (r = -.570; p < .05). V  The submaximal rides were completed at an average PO of 273.6 ± 8.6 W and 188.0 ± 8.6 W which corresponded to 65.7 ± 1 . 1 % and 45.3 ± 2.0% P P O for Bi ent and Tv  Bissp respectively (p < .05; Figure 3). Significant differences between trials existed on the following variables averaged over time: HR (Figure 5), V 0 absolute, %V0 max, 2  %T nt, %PO nt, RER, V (p < .05; Table 9). ve  Tve  E  2  vo did not significantly increase overtime 2  during Bissp (p > 05; Figure 8), however, RER significantly decreased over time (p < .05; Figure 9).  Table 9. Comparison of selected variables over time between the ventilatory threshold to volitional fatigue trial (Bi nt) and the five hour self-selected pace time trial (BiSSP): Tve  oxygen uptake  (V0 ), 2  percent of maximum oxygen uptake  ventilatory threshold  (%T t),  maximum heart rate  (%HRm ),  ven  ax  percent of  T  ven  t  power output  (%V0  2 m a x  percent of  ),  (%PO-rvent),  percent of  and minute ventilation (V ). (All p < .05 between trials) E  (t = significantly different over time; p < .05; N = 8). 5  30  60  Final  Mean  3.61 ±0.15  3.62 ±0.15  3.60 ±0.15  3.52 ±0.14  3.61 ±0.15  2.46 + 0.12  2.64 ±0.12  2.74 ±0.12  2.73 ± 0.06  2.64 ± 0.09  75.6 ± 4.1  75.8 ± 4.1  75.5 ± 4.0  73.8 ± 3.9  75.6 ± 4.1  51.6 ±5.0  55.2 ± 4.6  57.5 ± 4.3  57.1 ± 2.2  55.4 ±3.5  BiTvent  110.7 ±2.9  111.0±2.6  110.4 ±2.4  108.2 ±2.4  110.7 ±2.6  Bissp  75.9 ± 3.9  81.2 ±3.5  84.3 ± 3.0  84.8 ± 4.6  80.5 ± 3.3  BJTvent  100.0 ±0.0  100.0 ±0.0  100.0 ±0.0  100.0 ±0.0  100.0 ±0.0  Bissp  60.3 ± 3.2  66.7 ± 3.6  70.9 ± 3.7  69.3 ± 3.5  67.1 ±3.2  BiTvent  0.98 ± 0.01  0.95 ± 0.01  0.95 ±0.01  0.91 ± 0.02  0.95 ± 0.01  Bissp  0.93 ± 0.01  0.92 ±0.01  0.91 ± 0.01  0.89 ± 0.00  0.91 ± 0.01  97.8 ± 3.9  103.5 ±4.6  108.4 ±5.9  104.0 ±4.5  103.4 ±4.7  60.9 ± 2.9  66.4 ±3.2  69.2 ± 2.6  70.1 ±2.5  66.7 ± 2.8  Trial V o (Lmin" ) 1  2  Biivent  Bissp  %vo  2 m a x  Biivent  Bissp %T nt ve  %PO vent T  RER  V  t  (Lmin" ) t 1  E  BJTvent  Bissp  51  Hct and Lac" were significantly different between  Bi ent Tv  and Bissp over time (p <  .05; Table 10). However, Glu was not significantly different between trials or over time (p > .05; Table 10).  Table 10. Comparison of blood glucose (Glu), blood lactate (Lac), and hematocrit (Hct) levels over time during the ventilatory threshold to volitional fatigue trial  (Bi ent) Tv  and the  five hour self-selected pace time trial (Bi sp): (t = significantly different between trials; p S  < .05; N = 8). Rest  60  Final  Mean  BiTvent  5.9 ± 0.6  5.2 ± 0.2  5.6 ±0.4  5.6 ± 0.4  Bissp  6.3 ± 0.4  5.6 ±0.3  5.3 ±0.2  5.7 ± 0.3  BJTvent  2.2 ± 0.3  6.7 ±0.8  4.9 ± 0.4  4.6 ± 0.5  Bissp  2.4 ± 0.4  2.8 ± 0.4  4.0 ± 0.9  3.1 ±0.6  BiTvent  43.3 ± 0.4  44.0 ± 0.7  44.4 ± 0.8  43.9 ± 0.6  Bissp  42.8 ± 0.5  43.1 ± 0.7  40.9 ± 0.6  42.3 ± 0.6  Trial Glu (mmol-L ) 1  Lac" (mmol-L" ) 1  Hct (%)  t  t  Significant differences between trials also existed on the following variables averaged overtime: R P E = 16.6 ± 0.4 vs. 13.5 ± 0.5; pedaling rate (PR) = 70.7 ± 3.7 vs. 82.5 ± 2.0 rpm for  Bi nt Tve  vs. Bissp respectively (p < .05; figure 4). Trend analysis  revealed R P E , HR, V E , and Lac" to increase significantly over time, while P R and R E R  52  decreased significantly over time (p < .05). Furthermore, PR, V 0 , Lac", and Hct 2  demonstrated significant interaction effects (p < .05), therefore displaying different patterns of change over time. Subjects lost 0.5 ± 0.2 and 0.3 ± 0.3 kg during Bi nt and Bissp respectively which Tve  was not significantly different between trials or from baseline measurements (p > .05). Subjects ingested 1.99 ± 0.52 L and 4.92 ± 0.33 L of fluids which provided 175.7 ± 42.5 g and 498.8 ± 25.0 g of CHO, or in relative terms, 14.9 ± 1.6 and 3.5 ± 0.2 ml-kg" 1  hr" , and 1.4 ± 0.1 and 14.1 ± 0.4 gkg" -hr" CHO for Bi nt and Bissp respectively (p < 1  1  1  Tve  .05).  4.1.4. Ironman Canada (IMC) Performance Results Subjects completed the Ironman Canada (IMC) performance in a time of 677.2 ± 15.9 min (swim = 67.3 ± 1.7 min, bike = 331.3 ± 3.7 min, run = 270.4 ± 12.2 min). Of all  the physiological measures, only PPO during BiV0 max2 correlated significantly with 2  IMC performance (r = -.567, p < .05).  Using the treadmill velocity at T t during ven  TrV0 max1 and TrV0 max2, an estimated time (min) and pace (mph) for the marathon 2  2  component was developed and compared to the actual time and pace for the triathlon (Table 11). An explanation of the development of the run estimation is presented in Appendix A.  Table 11. Estimated and actual run times and paces for the marathon run portion of the Ironman Canada Triathlon (IMC). Estimated from TrV0 x1 Estimated from TrV0 x2 Actual IMC Marathon Run Time 2ma  2ma  Time (min) 178.0 ± 5 . 3  Pace (mph) Time (min) 8.9 ± 0 . 3  189.2 ± 4 . 7  Pace (mph)  Time (min)  Pace (mph)  8.4 ± 0 . 2  270.4 ± 12.2  5.9 ± 0 . 3  53  4.1.5. Heart Rate Comparisons between Trials In order to compare the HR responses between  BiTvent,  Bissp, and IMC, the  sample size was reduced to N = 5 due to either the subject not completing a minimum of 60 min on the Bi vem trial, or loss of HR data due to HR monitor malfunction. As T  before, comparison between the three performance trials could only be made for 60 min. HR showed significant differences between trials, over time, and interactively (trial x time) (p < .05; Figure 5). HR nt Tve  during both cycling V 0  2 m a x  tests (BiV0 ax1 and B i V 0 x 2 ) demonstrated 2m  2ma  significant relationships with mean IMC HR, Bissp HR, and  BiTvent  HR (Table 12).  However, non-significant relationships were demonstrated in amongst the three performance trials (p > .05). Table 12 displays the comparison of HRTvent between the mean HR during each of the three performance trials. Interestingly, HR during IMC most closely matched HR nt during B i V 0 a 2 Tve  2m  X  (%diff  = -1.1 ± 1.5%),  and correlated  strongly (r = .866; p < .05). Figure 6 compares the HR response between Bisspand five hours of the 180-km IMC cycle portion. Because of the loss of data due to HR monitor malfunction, the sample size for HR comparison between the trials was reduced to N = 7.  HR was  significantly different between the trials (p < .05; Figure 6), however, not over time (p > .05). Furthermore, there was a significant interaction effect (trial x time; p < .05).  54  Table 12. Comparison of mean heart rate (HR), mean percent of maximum heart rate (%HR ax), m  mean difference (diff) and mean percent difference (%diff) during the  performance trials in relation to the graded cycling V 0 correlation (r) to B i V 0  2max  2max  t e s t (BiV02max2). The  1 and BiV02max2 are also presented, ( t = Significant  correlation; p < .05).  x HR X % HRmax  x diff (bpm) x %diff  IMC  BJTvent  Bissp  (N=7)  (N=11)  (N=11)  146.3 ± 2 . 4  159.2 ± 2 . 9  129.9 ± 3 . 7  84.6 ± 1.3% 88.9 ± 0.7% -2.2 ± 2 . 7  r= .873  t  BiV0  r= .866  t  2 m a x  2  -20.3 ± 2 . 7  - 1.1 ± 1.5% + 5.0 ± 1.6% - 11.4 ± 1.5%  BiV0 max1 2  + 8.9 ± 2 . 9  72.5 ± 1.3%  r= .825  t  r= .662  r= .770  t  r= .799  t  Figure 3 . Comparison of power output (PO) over time for the ventilatory threshold ride to volitional fatigue trial (Bi ent) versus the five hour self-selected pace cycling time trial Tv  (Bissp). Significantly different between trials (p <.05). PO over Time  - • — BiTvent o  30  40 Time (min)  END  BiSSP  55  Figure 4. Comparison of pedaling rate (PR) over time for the ventilatory threshold ride to volitional fatigue trial (Bi ent) versus the five hour self-selected pace cycling time trial Tv  (Bissp)- Significantly different between trials and over time (p < .05). Pedaling Rate over Time  » BiSSP - BiTvent  END  Figure 5. Comparison of heart rate (HR) over time for the ventilatory threshold ride to volitional fatigue trial  (BiTvent).  the five hour self-selected pace cycling time trial (Bissp),  and the cycling portion of the Ironman Canada (IMC). All significantly different between trials and over time (p < .05). HR over Time (N=5)  l~  I I  E £ 140  r  1  1  1  I I T -~]r — 1 — 1 > -«[-•  T  - *  i  i  i- — «  r-""""  -  ' •  - BiTwnt -IMC  1  1  -  40  Time (min)  END  BiSSP  56  Figure 6. Comparison of heart rate (HR) over time for the five hour self-selected pace cycling time trial (Bissp). and the first 300 min of the cycling portion of the Ironman Canada (IMC). Significantly different between trials (p < .05; N = 7). IMC Cycle Portion vs. BiSSP over Time  \— 1M  •  V  Figure 7. Comparison of power output (PO), heart rate (HR), and pedaling rate (PR) over time for the five hour self-selected pace cycling time trial (Bissp), (N = 11). Comparison of PO, HR, and PR over Time for BiSSP trial  150 Time (min)  57  Figure 8. Hct over time during Bissp (significant decrease over time; p < .05). Hct over Time  Time (min)  Figure 9. RER over time during Bi sp (significant decrease over time; p < .05). S  RER over Time  0.980  cc UJ  CC  0.880 0.860 0.840 50  100  150 Time (min)  200  250  300  58  Figure 10. 1999 Ironman Canada Bike Course Profile (Wolf Infosystems, 1999).  3000 T  Yellow Lake Rienter Pass  2000 4  180  100  Kilometers  Figure 11. HR overtime during the 1999 Ironman Canada (N=7). Average HR over Time for IMC 170  BiV0 max2  TrV0 max2  TyentHR  TyentHR  2  2  110  100 100  SWIM  200  00  300  BIKE  Time (min)  500  600  RUN  700  59 4.2 Discussion  Ultraendurance performance is an endeavor in which the athlete attempts to adjust the factional utilization of v o  2  during performance in order to obtain maximal  benefits (i.e. the greatest speed) without exceeding a critical PO level that cannot be maintained for the duration of the event. Therefore, it is not surprising that athletes, coaches, and exercise physiologists have investigated various strategies to try to establish  an optimal exercise  performances.  Although  intensity  controversy  sustainable does  exist  during training with  respect  and race  to detection,  nomenclature, interpretation, and mechanisms (Brooks, 1985; Davis, 1985) strong relationships have been demonstrated between AT and endurance performance. The AT has demonstrated a relationship with endurance cycling (Coyle et al., 1991; Coyle, 1995; Bishop et al., 1998) endurance running (Rhodes & McKenzie, 1984; Petit et al., 1997; Farrel et al., 1979; Perronnet et al., 1987), as well as Olympic distance triathlon performance (Zhou et al., 1997).  However, in longer duration events, this strong  relationship between the AT and performance begins to decline (OToole et al., 1989; Langill and Rhodes, 1993; Miura et al., 1997). Nevertheless, ultraendurance triathletes will still strive to perform at some critical intensity, which might be relative to the AT (OToole etal., 1987a). 4.2.1 Descriptive Measures  The subjects in this study appear to be similar to other groups of triathletes (Zhou et al., 1997; Sleivert & Wenger, 1993; OToole et al., 1987a; 1989; Kreider et al., 1988a; 1988b). The subjects were slightly older than in most Olympic distance triathlon studies (Bunc et al., 1996; Zhou et al., 1997; Sleivert & Wenger, 1993; Kreider et al., 1988a; 1988b), however, they were comparable to UET studies (OToole et al., 1987a; 1989).  60  This may reflect the physiological and psychological experience it takes to compete over longer, more demanding distances. Height, weight, and percent body fat were also within expected ranges (OToole et al, 1987b). The training status of the triathletes prior to IMC was 8 ± 2 km-wk" swimming, 270 ± 18 kmwk" cycling, and 50 ± 5 km-wk' 1  1  1  running. This represented 2.7 ± 0.5 hrwk" swimming, 8.5 ± 0.6 hrwk" cycling, and 4.5 1  1  ± 0.5 hrwk" running, respectively, which is consistent with other UET studies (OToole, 1  1989; OToole etal., 1989). 4.2.2 V 0  2max  Comparisons  The AT has been demonstrated to be reduced by the glycogen content of the muscles (Friedmann, 1998), substrate manipulation (Ivy et al., 1981; Glass et al., 1997), prior exercise (Black et al., 1984; Neary & Wenger, 1985) and extreme fatigue (Rowbottom et al., 1998). Likewise, rest and tapering have been shown to increase oxidative enzymes and muscle glycogen levels, and subsequently increase PO at T t ven  (Neary et al., 1992). Hence, our findings of non-significant differences in V 0  2max  and  Tvent between TrV0 max1 and TrV0 ax2 (both relative and absolute) were surprising. 2  2m  These findings disagree with those of De Vito et al. (1995) where both v o  2 p e a k  and T t ven  were significantly reduced by the first two segments of a short-course triathlon (1.5-km swim, 32-km bike). This disparity may be related to differences in cycling intensity prior to the treadmill V0  2max  test.  In all likelihood, the Bissp trial would be performed at a  lower exercise intensity than in De Vito et al.'s (1995) 32-km bike time trial due to differences in duration. Hence, it is possible that the lower intensity during Bissp in the present study coupled with CHO ingestion during the ride may have lead to glycogen synthesis in some active (and inactive) muscle fibers (Palmer et al., 1999). This would  61  allow for the availability of adequate glycogen stores to produce similar excess CO2 for the detection of T tven  A non-significant RER k (p > 05) between T r V 0 pea  2max  1 and  TrV0 max2 further supports this hypothesis. Nevertheless, a declining trend did exist 2  (Table 6). V 0  2 m a x  declined (although not statistically) from 4.74 ± 0.17 to 4.45 ±0.19  Lmin" , while T t declined (although not statistically) from 3.43 ± 0.13 to 3.24 ± 0.14 1  ven  Lmin" , TrV0 x1 to T r V 0 1  2ma  2max  2 respectively.  Furthermore, T r V 0  TventSpeed were significantly reduced relative to T r V 0 Bissp trial did have some effect. T r V 0  2max  2max  2 T t estimation subsequent to Bissp ven  ven  2max  2 MTT and  1 (p < .05), indicating that the  significantly reduced T tSpeed, however, only marginally (TrV0 mph, T r V 0  2max  2max  1 T nt = 8.9 ± 0.3 ve  2 T t = 8.4 ± 0.2 mph; p < .05). This reduction did not improve the ven  ability to predict IMC marathon run pace (IMC marathon = 5.9 ± 0.3 mph; r = .425; p > .05).  One limitation to this finding, however, is that T r V 0  order in comparison to T r V 0 running treadmill V 0  2max  2max  2max  1 occurred first in time  2 . This was to ensure that subjects were familiar with a  t e s t prior to engaging in that activity subsequent to Bissp-  Hence, there exists the potential for a training effect to have occurred, T r V 0 TrV0  2max  2max  1 to  2 , that could have lessened the magnitude of these results.  Treadmill running will generally elicit a greater V 0  2 m a x  score than cycle ergometry  due to an increase in active muscle mass (McArdle et al., 1986; Medelli et al., 1993). While V 0  2 m a x  and T t were not significantly different between cycling and running (p > ven  .05), there was a percent difference in V 0  2max  equal to 3.9% (BiV0  2max  1 vs. T r V 0  2max  1),  which is consistent with other triathlon study's (Kohrt et al., 1987; OToole et al., 1987b; Kreider et al., 1988a; Schneider et al., 1990). Hence, our finding of a modest decline, in  62  comparison to single sport athletes, where the maximums are 9 to 11% less (Roalstad, 1989; Faulkner et al., 1971), is likely due to training specificity (OToole, 1989). 4.2.3 Relationship of Threshold to Bi ent and Bissp Tv  The AT is defined as the V o during exercise above which there is a sharp 2  increase in anaerobiosis where lactate accumulation exceeds removal (Wasserman, 1984). This may represent the upper limit of PO during constant load exercise (Rusko et aL, 1986). Strong relationships have been demonstrated between AT and endurance performance.  For example, Rhodes & McKenzie (1984) demonstrated a strong  correlation (r = 0.94) between run velocity at T t and marathon performance time. ven  However, in longer duration events, this strong relationship between the AT and performance begins to decline (OToole et al., 1989; Langill and Rhodes, 1993; Miura et al., 1997).  For example, Langill and Rhodes (1993) demonstrated a moderate  correlation (r = 0.76) between run velocity at T nt and IMC marathon performance using ve  the identical protocol. As well, OToole et al. (1989) determined that the relationship between exercise test variables and bike race times in the 1985 Hawaiian Ironman Triathlon were not highly related to bike finish times (r = -0.26 to -0.58). % v o  2peak  , HR,  and %HRmax at thresholds were also not related to bike finish times (r = -0.01 to 0.06). This decreased relationship may be due to the apparent effect that prior exercise has on each subsequent event during a triathlon (Kreider et al., 1989a; Laursen et al., 1999). It may also be due to the variability of athlete fitness, athlete experience, as well as uncontrollable environmental factors. Nevertheless, it makes sense to assume that the ultraendurance triathlete will still strive to perform at some critical intensity, which might be relative to the AT.  63  4.2.3.1 Biivent Trial  The purpose of the experimental trials was to test the hypothesis that ultraendurance triathletes perform at T nt during the bike portion of the Ironman ve  triathlon. This hypothesis seemed questionable as previous AT cycles to exhaustion have demonstrated times to volitional fatigue ranging from 48 to 255 min at a PO corresponding to AT (Aunola et al., 1990; Davis et al., 1992; Loat & Rhodes, 1996). Hence, this seemed too great an intensity to be maintained during the bike portion of an UET. Fuel requirements and thermoregulatory considerations (Kreider, 1991; Laursen and Rhodes, 1999) would likely prevent most athletes from performing at this PO intensity for the duration necessary. Of the 11 athletes, three subjects could not perform the Biivent trial for longer than 60 min (32 ±5.1 min) and were subsequently removed from the statistical analysis. The remaining subjects (N=8) performed at their PO ent for 2 h, 10.7 ± 18.6 min, whereas all Tv  subjects completed the 5 h Bissp trial. With the exception of Glu, significant differences existed on all measured variables when comparing Biivent to Bissp (Table 9, 10, Figure 35). Hence, this data suggests that ultraendurance triathletes do not choose to perform at the PO that corresponds to T t on a ramped cycling protocol. ven  In retrospect, it may have been more appropriate to use a fixed HR or v o  2  t  instead of a fixed PO.  vo  2  and HR during Bi ent were both higher than V 0 T t (+298 2  Tv  ven  ± 62ml) and HR ent (+9 ± 3 bpm) during BiV02max1- Hence, the actual intensity during Tv  Biivent corresponded to 110.7 ± 2.6% V0 T ent, and 104.8 + 2.1% HR 2  V  Tven  t, or 7.3 ± 1.5%  above V0 T nt, and 3.8 ± 1.7% above HRivent- These results bring to question the 2  ve  ability of a 30 W-min" ramped cycling protocol to accurately calculate the PO that 1  corresponds to whole body T tven  It might be suggested that a slower ramped PO  64  protocol would result in a more accurate determination, however, Hoogeveen & Schlep (1997) recently performed this (beginning at 2.5 Wkg" and increasing by 40W every 4 1  min) and the predictive value of the plasma lactate response in relation to 40km cycling performance was negligible.  Conversely, running studies have shown excellent  relationships between A T and performance (Petit et al., 1997; Roecker et al., 1998; Rhodes & McKenzie, 1984; Perronnet et al., 1987; Roecker et al., 1998). These physiological disparities are unexplainable, but it has been suggested that a ramp protocol during cycling might alter, in some unknown way, the classical mechanism of diffusion of Lac" and/or H+ through the sarcolemma (Chicharro et al., 1997) causing a lag time in Lac" or EXC0 detection. In any case, POivent was clearly above the levels 2  of the metabolic and CV T t markers. When exercise occurs above T ven  vent  , v o d o e s not 2  level off, but continues to rise for several minutes until either a delayed but elevated steady state is attained, or exhaustion occurs (Jones et al., 1999). This additional increase in v o  2  has been referred to as the v o  2  slow component (Barstow and Mole,  1991; Xu and Rhodes, 1999), and may be the result of an increased recruitment of Type II motor units during heavy exercise (Barstow et al., 1996). Hence, questions exist regarding the specific meaning of "exercise intensity".  If exercise intensity refers to  whole-body physiological stress, this might be reflected metabolically in V 0 , and 2  cardiovascularly in HR (Jeukendrup & Van Diemen, 1998).  Conversely, exercise  intensity could also refer to the mechanical PO of the athlete (McLellan & Cheung, 1992). However, as has been demonstrated, these two concepts do not necessarily run parallel during a ramped cycle ergometry V 0  2max  t e s t (Boulay et al., 1997).  While  ultraendurance athletes may perform at a metabolic or CV intensity that corresponds to Tvent, it is unlikely based on the present findings and that of others (Aunola et al., 1990;  65  Davis et al., 1992; Loat & Rhodes, 1996) that ultraendurance triathletes perform at their POivent-  Boulay et al. (1997) recently demonstrated decreases in PO, V , VC0 and Lac" E  2  when HR was kept constant at 5 bpm below HR nt for 90 min. Hence, these findings Tve  and ours, appear to refute the critical power concept. Critical power represents the highest metabolic rate at which a steady state response can be achieved during prolonged exercise (Monod & Schierrer, 1965), and may be similar to the POivent (Moritani et al., 1981). This may explain why three subjects could not perform past 60 min at POivent, and why three others could not perform past 80 min. Hence, important interindividual differences must exist when performing to volitional fatigue at POiventFurthermore, the large variability subject to subject (range = 12.0 to 3 h 39.6 min) demonstrates the limitation of the EXC0 T t determination during a graded cycling 2  V0  2max  ven  t e s t to predict a homogenous ET (at least in ultraendurance triathletes). A trend  did exist towards a higher CV and metabolic rate relative to T t in ET| versus ET i h, ven  0W  h g  although this was not statistically significant (p > .05). It is tempting to speculate that athletes in the ET|  0W  group may have been overtrained at that particular time in the  testing, as testing took place during training for an UET. Urhausen et al. (1998) noted a 27% decrease in time to volitional fatigue at 110% of the IAT in athletes that were in an overtrained state. Furthermore, it has been reported that 65% of all endurance athletes develop symptoms of overtraining at some time in their competitive career (Margan et al., 1987; see also review by McKenzie, 1999).  Nevertheless, the potentiality of  overtraining to explain some of the variance in ET is purely speculative, and this variance is likely related also to other factors.  66  4.2.3.2 Bissp Trial and the Ultraendurance Threshold (UT) Hypothesis The Bissp trial was performed at an intensity equating to 55.4 ± 3.5% V0  2 m a x  which compares almost identically to the lab based 5 h ultraendurance cycling  rides of OToole et al. (1987a), but that their cycle was followed by an identical selfselected pace 3 h treadmill run. Interestingly, the self-chosen pace of OToole et al.'s (1987a) male triathletes (N=8) was 6 mph, which resembles the 5.9 ± 0.3 mph IMC marathon pace in the present study.  Perhaps one limitation to this method of self-  selected pace is that adjustments of intensity do not rely on physiological measures, but on the athlete's perception of the effort. Hence, we cannot clearly ascertain that the intensity chosen during Bissp would be representative of the cycle portion of IMC. Nevertheless, in a performance setting, athletes will chose to perform according to their perception of the effort. This perception of effort during Bissp equated to a RPE score of 15.0 ± 0.4 during the final measurement, indicating that the athletes perceived this effort to be considerable. Athletes chose a significantly higher PR when cycling during Bissp (82.5 ± 2.3 rpm) than when cycling at the PO-r ent (62.9 ± 3.7 rpm) (p < .05; Figure 4). This V  increased PR in Bissp may be a result of a reduction in the activation of the vastus lateralis muscle (Takaishi et al., 1994) due to the decrease in force application and connected to a reduction in V 0 (Hagberg et al., 1981). In the present study, PR was 2  increased 31.1% in Bisspvs. Bijvent (p < 05), whereas V 0 was reduced by 26.8% (p < 2  .05). Therefore the higher observed PR may be associated with a reduction in the forces applied on the pedals, the latter eliciting the recruitment of a higher percentage of slow-twitch fibers which have a lower recruitment threshold, a larger oxidative capacity, and a better mechanical efficiency for contraction (Takaishi et al., 1994; Coyle et al.,  67  1991). Hence, in the Bi ent trial, the progressive recruitment of additional motor units Tv  and/or the higher firing rate of recruited motor units was required to compensate for the deficit in contractility provoked by the alteration of fatigued motor units (Takaishi et al., 1994). This would help explain the lower chosen PO intensity during the Bissp versus Biivent- Lower Lac" values obtained during Bissp (p < 05; Table 10) also suggest that  the UT pace requires the majority of metabolism in its aerobic component, enabling triathletes to save energy to continue their prolonged effort either cycling or running. By reducing exertion in the cycling phase, triathletes may be more willing to push themselves in the running segment. This has been recently demonstrated in shortcourse triathletes, where drafting during the cycle enabled increased performances during the final run phase (Hausswirth et al., 1999). This was demonstrated in the present study as TrV0 ax2 was not significantly different than TrV0 max1 in terms of 2m  V0  2max  2  (p > .05), indicating that the UT pace still enabled a significant contribution from  glycolytic metabolism to produce subsequent Lac" (as indicated by EXC0 ) during 2  TrV0  2max  2.  RER data further supports the UT hypothesis whereby fuel oxidation (CHO relative to fat) is more in equilibrium. During earlier ultraendurance laboratory studies (OToole et al., 1987b), RER demonstrated a large decline (0.93 to 0.82). Our study demonstrated a modest decline (Figure 9).  Presumably, the ingestion of adequate  quantities of fuels and fluids would aid this balance (Palmer et al., 1999). Most notably, OToole et al. (1987b) allowed fluids only during their 5 h cycles, whereas in the present study, triathletes were permitted any types of fuels or fluids. High CHO "sport gels" were used, in addition to solid CHO and CHO/electrolyte beverages. The comparison of OToole et al.'s (1987a) RER data to the present study suggests that the large quantities of these high CHO sources (14.1 ± 0.4 gkg" hr" 1  1  CHO) allowed for an  68  increase in CHO oxidation, presumably from blood glucose (Palmer et al., 1999). This further helps to explain the non-significant  V0  2 m a x  scores in TrV0 max2 versus 2  TrVC>2max1- This finding may represent the increase of applied physiological knowledge in ultraendurance triathletes. 4.2.3.3 Hematological Comparisons  Resting hematological measures of Hb and Hct were both higher than previously reported in UET studies. Hb levels (16.9 ± 0.2 g-dL" ) were higher than in sedentary 1  norms (Berne and Levy, 1983), which is unusual in ultraendurance triathletes. In fact, OToole et al. (1988) reported anemia (Hb < 14gdL" ) in 39% of male Ironman 1  triathletes. Hct levels in the present study (43.9 ± 0.4%) were within normal ranges but were somewhat higher than the 42.5% reported in a large sample size by OToole et al. (1999). Normally, ultraendurance triathletes exhibit a pseudoanemia, which is generally attributed to a training-induced increase in plasma volume which is greater than that in the red cell volume (Convertino, 1991). differences is unknown.  The reasons for these hematological  Hct levels significantly declined during Bissp yet increased  significantly during Biivent, thus demonstrating a significant interaction effect (p < .05; Figure 8, Table 10). These findings fall in line with OToole et al. (1999) where although Hct generally increases due to a decrease in plasma volume with prolonged exercise, the variability is quite large (range = -7.1 to +10.0%).  Hence, it appears that some  individuals hemoconcentrate during triathlons while others hemodilute (OToole et al., 1999). Our findings of a significant interaction suggests that intensity and duration may play a factor in hemodynamics (Wells et al., 1987). Fluid dynamics, fluid intake, sodium loss, and intra/extravascular proteins may also play a role (Neutians and Gaehtgens, 1994).  69  4.2.4 IMC Performance Results and Comparisons to Laboratory Trials The mean finishing time of subjects in IMC was 11.3 ± 0.3 h, which was slower than the mean of their personal best times of 10.7 ± 0.2 h. Of the ten subjects entered in IMC, two achieved personal best times, one was 15 min off his personal best, and seven were greater than 30 min off their personal best.  This increase was mainly  attributable to the run where the average time was 32.1 ± 11.0 min greater than their IMC marathon personal best, while previous swim and bike times were nearly identical to their personal bests.  Large variability occurred during the latter portion of the  marathon run (Figure 11) where successful triathletes were able to maintain a high HR intensity, while less successful triathletes were not.  Subjective comments for the  decline in marathon time included gastrointestinal complaints, extreme leg cramping and even an anaphylactic reaction from a bee sting. IMC marathon run times strongly correlated with IMC overall times (r = .982; p < .05), suggesting that the run phase of the UET is critical to successful performance in experienced ultraendurance triathletes. Nevertheless, overexertion during the swim and cycle phases has the potential to create problems during the run phase (Kreider et al., 1989a; Laursen et al., 1999). HR response during the triathlon (Figure 6 and 11) supports OToole et al.'s (1987a) finding that ultraendurance triathletes perform the bike portion of the Ironman at the HR corresponding to T t. Although CV drift was evident during Bissp, it was not ven  during IMC (Figure 6 and 11), as HR obtained its peak during the swim portion only 30 min into the race. This is most likely due to psychological factors due to the excitement of the day (Selley et al., 1995). This finding, however, is contrary to previous studies that have demonstrated the horizontal position in swimming combined with water immersion to elicit lower HRs compared to cycling and running at the same relative  70  intensity (Shaffrath & Adams, 1984; Nielsen et al., 1984). Nevertheless, HR during IMC began its slow decline after 30 min, and by the cycle portion, fluctuated around BiV0 max2 HR vent- These HR fluctuations tracked the IMC elevation chart (Figure 10), 2  T  with the two distinguishable peaks in HR (Figure 6, 11) matching the two major elevation climbs (Richter Pass and Yellow Lake). Furthermore, as the race progressed, HR readings declined (p < .05). Mean HR during the run segment declined 5.5% compared to the cycle phase, similar to the 6 to 7% decline in HR intensity suggested by OToole et al. (1998) during ultraendurance exercise performed greater than 6 h. As previously mentioned, this decline may reflect substrate depletion, altered muscle efficiency, fluid and electrolyte imbalances, thermoregulatory problems, cardiac fatigue, as well as psychological factors (OToole & Douglas, 1995). The longer the competition distance, the more substrate availability and glycogen storage quantity are considered to be performance-determining factors (Roecker et al., 1998). Substrate utilization was altered significantly during Bissp(P < 05) and may have been further altered had a swim preceded it (Laursen et al., 1999). Declining thermoregulatory and CV efficiencies while running attributable to prior swimming and cycling has also been documented (Kreider etal., 1988b). Both Roalstad et al. (1987) and OToole et al. (1987a) independently reported that the cycling portion of the Hawaii Ironman is performed at an exercise intensity of approximately 75% of HR xma  OToole et al. (1987a) also found that 75% H R  max  corresponded to T nt suggesting that athletes perform the cycling portion of the Ironman ve  at an intensity which approximates HR ntTve  Our subjects performed at 84.6 ± 1.3%  HRmax which closely matched HR nt during BiV0 ax2 (%diff = -1.1 ± 1.5%), and Tve  2m  showed a strong relationship (r = .866; P < .05). Hence, over the course of the IMC bike phase, our triathletes performed at the HR intensity that corresponds to their  71  HRivent- Therefore, although the PO-rvent did not match the physiological T t measures, ven  HRjventdoes seem to be a realistic average HR to perform at during the cycle portion of the Ironman triathlon. Unfortunately, we can not conclude that this is an "optimal" HR intensity to maintain during an UET as only two often subjects achieved a personal best time. It is interesting to note, however, that one of these subjects achieved the highest relative V 0  2 m a x  score, suggesting that a high V 0  2max  is required to maintain a high  exercise intensity for prolonged periods (Sleivert & Rowlands, 1996). However, this field based HR intensity may not be representative of a lab-based intensity. HR has been demonstrated to be higher during a race when compared to HR at the same running speed under non-competitive laboratory controlled conditions (Selley et al., 1995). Hence, the psychological fact of being in a race environment versus a controlled lab environment can alter physiological responses to exercise. In the current study, HR during Bissp was significantly less than HR during the cycle portion of the IMC (p < .05; Figure 6), and subjects were asked to mimic their Ironman cycle intensity. Furthermore, it has been estimated that for every 1% loss in body mass due to dehydration, HR increases by 7 bpm (Coyle and Montain, 1992). Therefore, in a hot environment (i.e. 22.4 to 30.2 °C during the bike portion of IMC), dehydration/plasma volume shifts can change the HR-intensity relationship drastically.  This would explain further the  difference between these two trials. Hence, if athletes use HR monitors as a gauge of their racing pace, they may perform at a lesser PO than expected during a race, should a racing target HR be calculated on a HR determined during training or a physiological assessment (Lambert et al., 1998). CV drift occurs with increasing exercise duration (Lambert et al., 1998). Therefore, HR during the later stages of the IMC cycle portion might not be indicative of the expected PO. If indeed HR remained relatively constant during the IMC bike phase,  72  we might expect the PO to decline. This decrease in PO was recently demonstrated by Boulay et al. (1997) where HR was kept constant at 5 bpm below T t during a 90 min ven  performance trial.  This trend was demonstrated during Bissp as HR increased  significantly over time (p < .05), while PO was shown to decline somewhat after 2h 10 min (Figure 7). Another difference that exists between IMC and Bissp is the relatively steady PO during Bi sp versus the undulating PO during IMC due to terrain and wind. S  However, Palmer et al. (1999) recently demonstrated non-significant metabolic and CV differences in an undulating PO cycle versus a steady state PO ride; each eliciting identical mean POs.  Nevertheless, certain factors have been shown to change  submaximal HRs during cycling. These include bike setup (Jeukendrup & Van Diemen, 1998) and the aerodynamic (aerobar) cycling position (Sheel et al., 1996). 4.2.5 Practical Implications One of the purposes of this thesis was to provide some practical information for ultraendurance triathletes. It has been demonstrated previously (OToole et al., 1987a; Roalstad et al., 1987), and now in an experienced and well-trained group that ultraendurance triathletes perform at a mean HR intensity which is close to HR entTv  Therefore, it may be valuable for an ultraendurance triathlete to obtain a physiological assessment including a cycling V 0  2max  t e s t in order to establish HRivent-  Hence, if  uncertainties in HR intensity exist during the cycle portion of the race, an observation of a portable HR monitor may provide some confidence that the athlete is performing near optimal physiological performance. In this sense, HR monitors may provide a more accurate index of exercise intensity than speed (Jeukendrup & Van Diemen, 1998). Environmental and physiological factors such as wind, air temperature, air density, humidity and terrain have a large impact on cycling speed (Jeukendrup & Van Diemen, 1998). In fact, HR monitors may even represent 'ergogenic aids' (Lambert et al., 1998)  73 as they can motivate athletes to work at high intensities at or above T t (Jeukendrup & ven  Van Diemen, 1998). Finally, this study has demonstrated the importance of the run portion on overall triathlon performance. Hence, training for UETs should focus on the run phase, and specifically on running subsequent to cycling. It is hoped this study will provide important information to the ultraendurance triathlete, coach, and exercise physiologist intent on improving UET performance.  74  CHAPTER 5: SUMMARY AND CONCLUSION 5.1 Summary Physiological measurements such as economy of motion, V 0 have been demonstrated to predict endurance performance.  2 m a x  , and the AT  However, when these  concepts are extended to ultraendurance sports (i.e. > 4 h), predictibility of these measurments declines (OToole et al., 1989; Langill and Rhodes, 1993; Miura et al., 1997). The potential reasons for this decline are numerous and include: fuel utilization, fluid and electrolyte homeostasis, the effects of dehydration and plasma volume shifts on CV function, the effect that the preceding component has on subsequent components, as well as neuromuscular fatigue. (Farber et al., 1991; OToole et al., 1987a; 1987b; Kreider, 1991). Nevertheless, it is logical to assume that ultraendurance triathletes will attempt to maintain some critical intensity during the UET, which may similarly be related to T t (OToole et al., 1987a). The findings from the present study ven  demonstrate that ultraendurance triathletes do not perform at their PO nt. ET during Tve  Biivent was 2 h 10.7 ± 18.6 min, with great variability (range = 12.0 min to 3 h, 39.6 min).  This variability creates questions about the ability of a 30 W-min" ramped protocol to 1  estimate the AT as defined as the upper limit of PO where Lac" production and removal attain equilibrium during constant load exercise (Rusko et al., 1986).  Bi nt was Tve  performed at 7.3 + 1.5% above v o T n t > and 3.8 ± 1.7% above HRjvent, suggesting 2  ve  limitations of the EXCO2 elimination curve to estimate a POivent equating to metabolic and CV T t- Conversely, Bisspwas performed at 18.5 ± 2.9% below V0 T nt and 16.4 2  ven  ve  ± 2.0% below HR-r ent. Hence, the critical intensity chosen by ultraendurance triathletes V  during a five hour cycling time trial is performed so that metabolism is largely in its aerobic component.  Nevertheless, the ramped protocol did find considerable  75  agreement between the HR nt during BiV0 max2 and the mean HR performed at during Tve  2  the cycle portion of IMC (-1.1 ± 1.5% difference, r = .866; p < .05). This relationship has been previously demonstrated in other UET studies (OToole et al. 1987a; Roalstad et al. 1987a). The present study has also demonstrated the limitation of a lab based UET cycling simulation to resemble a similar effort in the field (IMC).  The significant  difference in HR measurement (129.9 ± 3.7 vs. 146.3 ± 2.4 bpm; Bi sp vs. IMC S  respectively; p < .05) is most likely due to the psychological effects of a race environment (Selley et al., 1995), potential effects of the swim prior to cycling (Kreider et al., 1988a; Laursen et al., 1999), as well as the increased effects of dehydration and plasma volume shifts due to increasing temperature resulting in a CV drift (Coyle & Montain, 1992). Nevertheless, the final RPE measurement during the Bissp trial was 15.0 ± 0.4, indicating that the athletes perceived this effort to be considerable. TrV02max2 T ent estimation subsequent to Bissp significantly reduced T ntSpeed, ve  V  however, only marginally (TrV0 max1 T t = 8.9 ± 0.3 mph, TrV0 2  ven  2ma  x2 T t = 8.4 ± 0.2 ven  mph; p < .05). This did not significantly improve the ability to predict IMC marathon run pace (IMC marathon = 5.9 ± 0.3 mph; r = .425; p > .05). These findings are in opposition to those demonstrated in an Olympic distance triathlon (De Vito et al., 1995), and are likely related to differences in intensity and duration (Roecker et al., 1998). From a CV standpoint, ultraendurance triathletes perform the second phase of an UET at their HR ntTve  Metabolically (in terms of the fractional utilization of V 0 ) and 2  mechanically (in terms of PO), it appears they do not. A number of confounding variables serve to increase HR to the level of HR nt during IMC, however, it is unlikely Tve  that the fractional utilization of V 0 , and subsequent PO, follow a similar pattern. 2  76  5.2 Conclusions 1. The ET for Bi nt trial equated to 2 h. 10.7 ± 18.6 min, whereas all subjects Tve  completed the 5 h Bissp trial indicating that ultraendurance triathletes do not perform the Ironman bike phase at their POivent- As well, significant differences between Biivent and Bissp existed on all physiological measures except Glu. 2. HRivent during BiVC>2max2 was similar to IMC mean HR (-1.1 ± 1 . 5 % difference) and  showed a strong relationship (r= .866; p < .05). 3. A treadmill  run V 0  2 m a x  (TrV0 ax2) 2m  subsequent to Bissp significantly reduced  T v e n t S p e e d (8.9 ± 0.3 mph vs. 8.4 ± 0.2 mph; p < .05), however, did not improve the ability to predict IMC marathon run pace (IMC marathon = 5.9 ± 0.3 mph; r = .425; p > .05).  5.3 Recommendations It would be valuable to repeat the Bi nt portion of this study by having subjects Tve  perform to volitional fatigue at their V0 T nt, and at their HR nt, thus adjusting P O 2  ve  Tve  accordingly, similar to the study protocol of Boulay et al. (1997). This would determine if indeed ultraendurance triathletes are able perform metabolically at a level of intensity corresponding to T t during the second phase of an UET. ven  77  BIBLIOGRAPHY Anderson GS, Rhodes EC: A review of blood lactate and ventilatory methods of detecting transitions thresholds. Sports Med. 8(1): 43-55, 1989. Anderson M, Bergman EA, Nethery VM. Preexercise meal affects ride time to fatigue in trained cyclists. J Am. 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Correlations between short-course triathlon performance and physiological variables determined in laboratory cycle and treadmill tests. J. Sports Med. Phys. Fitness 37(2): 122-30, 1997.  91  APPENDIX A Sample calculation for the estimation of T t in either the running or cycling ven  V0  2 m a x  tests.  35  o -I 0.0  ,  .  .  >  '  '  •  •  '  ^  2.0  4.0  6.0  8.0  10.0  12.0  14.0  16.0  18.0  20.0  TIME (min)  The corresponding time at the breakaway point in the graph of excess C 0 vs. time was 2  used to determine T t point. This point in time would correspond to a specific cycling ven  power output, or a specific treadmill velocity. For example, in this case: minute 13 = 10.0 mph  

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