Entries in VO2 Max (9)

Tuesday
Dec062011

Exercise Science and Coaching: Correcting Common Misunderstandings About Endurance Exercise

By: Andrew N. Bosch, PhD
UCT/ MRC Research Unit for Exercise Science and Sports Medicine.
Department of Human Biology, University of Cape Town and Sports Science Institute of South Africa
From: International Journal of Sports Science & Coaching Volume 1 • Number 1 • 2006


Many coaches who work with endurance athletes still believe in old concepts that can no longer be considered correct. Prime amongst these are the understanding, or misunderstanding, of the concepts of maximal oxygen uptake (VO2 max), lactate threshold, training heart rate, and dehydration and fluid requirements during prolonged exercise.

Knowing the VO2 max of an athlete is not particularly useful to the coach, and the exact VO2 max value of any particular athlete can vary considerably as fitness changes. Race performance is a more useful measure on which to base training schedules.

Lactic acid production, far from being an undesirable event, is of great importance and is actually beneficial to the athlete. The lactate concentration during exercise, and the lactate turnpoint, are both widely measured. The nature of the information that these measures can provide about training and training status, however, is still based on information from the 1980s, although more current information is available and many of the original concepts have been modified.

Heart rate is often used to prescribe training intensity, but it is important to understand the limitations inherent in its use. If used correctly, it is a useful tool for the coach.
Similarly, many athletes and coaches still believe that it is necessary to maintain a high fluid intake to avoid dehydration and prevent associated collapse. These beliefs are incorrect, but modern exercise science has been able to advance the knowledge in this area and provide more accurate information.
Exercise science continues to progress and can offer much to the coach willing to accept new and changing ideas.

Key words: Anaerobic threshold; Endurance training; hydration; lactic acid; maximal oxygen uptake; training heart rate

Introduction

Sports science knowledge has progressed tremendously in the last 20 years in terms of the understanding of many of the underlying concepts in exercise physiology and human performance. Many coaches, however, have failed to take cognisance of the new information and still believe in old and out-dated concepts, many of which frankly are wrong. And it is this incorrect understanding that is then applied to the coaching of athletes. In the following article, some of these misconceptions related to endurance performance are highlighted, specifically those around maximal oxygen uptake (VO2 max), lactate threshold, training heart rate, dehydration, and fluid requirements during prolonged exercise. Although runners are most often referred to in the discussion that follows, the principles are applicable to all genre of endurance athlete.

VO2 Max

Every so often a request is received from the coach of a runner or cyclist wanting to know ifit would be possible to measure the VO2 max of one of their athletes. I explain that it is, indeed, possible, but then go on to ask why they want to have the VO2 max of the athlete measured? There is usually one of two replies. Firstly, I am told, by knowing his or her VO2 max the runner will know the esoteric time that he or she is ultimately capable of running for some particular race distance, and therefore their ultimate potential as a runner. Secondly, once their VO2 max is known it will be possible to prescribe the ultimate personalised training schedule. Unfortunately, knowing the VO2 max of a runner does not answer either question.

It is widely believed by those involved in endurance sports that the VO2 max is genetically determined and never changes, and that an individual is born with either a high or low VO2 max. Generally, someone with a high VO2 max value is considered to have a cardiovascular system capable of delivering large amounts of oxygen to the working muscle and is able to exercise at a maximum aerobic work output that is determined by the exercise intensity that can be sustained by this supply of oxygen [1]. In this paradigm it does not appear to matter whether a runner or cyclist is unfit or superbly fit, the VO2 max value obtained in a test is theoretically the same. However, it is intuitively obvious that when fit, the athlete can run much faster on the treadmill than when unfit. Thus, since VO2 max is genetically determined and does not change, VO2 max would be reached at a relatively slow running speed when a runner is unfit compared to when very fit, when a much higher speed or workload can be reached. This means that in a totally unfit world class runner we would measure a high VO2 max (for example, 75 ml/kg/min or higher, a reasonable VO2 max value for an elite runner) at a speed of maybe 17 km/hr in a testing protocol in which the treadmill remains flat during the test. When very fit the same athlete will reach the same VO2 max, but now the speed reached on the treadmill will be around 24 km/hr (a reasonable speed for an elite athlete in such a test). The problem is that such a high VO2 max is never measured at a speed of just 17 km/hr, or thereabout. This would be almost impossibly inefficient [2]. The theory of a genetically set and unchanging VO2 max, regardless of work output therefore begins to appear a little shaky.

This concept of VO2 max evolved originally from misinterpretation of the data of early experimental work [1; 3-5]. It was believed that as an athlete ran faster and faster during a treadmill test, an increasing volume of oxygen was needed by the muscles, a process which continued until the supply of oxygen became limiting, or the ability of the muscle to utilise oxygen was exceeded. At this point there would be no further increase in oxygen uptake, despite further increases in running speed [1]. The plateau in oxygen utilisation was regarded as the VO2 max of the runner. If high, then the athlete had great genetic potential. This has been termed the cardiovascular/ anaerobic model by Noakes [1] and needs revision, although others adhere to the concept [6]. However, 30% of all runners and cyclists tested in exercise laboratories never show a plateau in their oxygen uptake [4; 7]. Instead, the oxygen uptake is still increasing when the athlete cannot continue the test. The conventional view of VO2 max now appears to be even more suspect.

Consider a different possibility. The muscles of a runner require a certain amount of oxygen to sustain contraction at a given speed. When the speed is increased, the muscles have to work harder and there is therefore a corresponding increase in the volume of oxygen needed to run at the higher speed. As the runner runs faster and faster, it follows that there is a concomitant increase in the oxygen required, until ultimately something other than oxygen supply to the muscle prevents the muscle from being able to work harder and to sustain a further increase in running speed.

The brain may be the ultimate subconscious controller, by sensing a pending limitation in the maximum capacity of the coronary blood flow to supply oxygen to the heart as exercise intensity increases, and then preventing a further increase in muscle contractility to prevent damage to the heart during maximal exercise [1].

The volume of oxygen being used by the muscle when maximum running speed has been reached is termed the VO2 max. With this theory, the increase in oxygen requirement merely tracks the increase in running speed, until a peak running speed and therefore peak oxygen requirement (VO2 max) is attained. It is easy to see why the VO2 max value will change (which it does) as a runner gets fitter and becomes capable of running faster. Within this framework, the genetically determined limit of VO2 max is actually determined by the highest running speed that the contractility of the muscles can sustain [8] before the brain limits performance to protect the heart, as described above [1]. Of practical importance, is that the exercise scientist and coach cannot use the VO2 max test as a predictor of future performance in someone who still has the capacity to improve their running by utilising a scientifically designed training programme. A great training-induced increase in running speed will result in a substantial change in VO2 max. Only when widely disparate groups of athletes are tested can a VO2 max value be used to distinguish between athletes (i.e. very fast and very slow [2; 9; 10]). In a group of athletes with similar ability, the VO2 max value cannot distinguish between the faster and slower runners i.e. their race performance. Neither is the knowledge of a VO2 max value going to assist in the construction of a training programme, other than by indirectly giving an indication of the time in which a race may currently be completed, by the use of various tables that are available [11]. Indeed, current race performance provides the most useful information for the coach on which to base training prescription [11].

There are, however, some potential uses of a VO2 max test for a coach. When constructing a training programme for someone who has not run any races and who therefore has no race times from which to determine current ability, a VO2 max test will help by giving an indication of the current capability of the athlete on which to base training schedules. If done at regular intervals, the test can provide information about the efficacy of a training programme [11] as laboratory conditions are very reproducible with regard to temperature and absence of wind. However, the peak speed attained in the test is probably the best indicator of current ability [1; 12-14] and not the actual VO2 max value. Race times remain the most useful measure on which to prescribe running speed in training schedules [11].

Lactic Acid

Most athletes and coaches still believe that lactic acid is released during hard or unaccustomed exercise and that this is what limits performance, as well as being the cause of stiffness. Neither is correct. Furthermore, the terminology “lactic acid,” is not correct.

Lactic acid does not exist as such in the body - it exists as lactate at physiological pH [15], and it is this that is actually measured in the blood when “lactic acid” concentration is measured, as is done when a “lactate threshold” is determined in an athlete. This distinction is important not only for the sake of correctness, but more importantly, because lactate and lactic acid would have different physiological effects.

The first misconception is that lactic acid is the cause of the stiffness felt after an event such as a marathon. Stiffness is due to damage to the muscle [1], and not an accumulation of lactic acid crystals in the muscle [1; 16], as is commonly believed.

The second misconception is that lactate is responsible for acidifying the blood, thereby causing fatigue. To the contrary, the production of lactate is actually important for two reasons. Firstly, when lactate is produced from pyruvate in the muscle, a hydrogen ion is “consumed” in the process [15]. Consequently the production of lactate actually reduces the acidity in the muscle cells and is thus a beneficial process. Secondly, lactate is an important fuel that is used by the muscles during prolonged exercise [17; 18]. It can be produced in one muscle cell and utilized as a fuel in another, or it can be released from the muscle and converted in the liver to glucose, which is then used as an energy source. So rather than cause fatigue, lactate production actually helps to delay fatigue [19].

Anaerobic Threshold

Closely allied to the thinking that lactate production is bad for performance, is the concept of measuring the blood lactate concentration to determine the so-called “anaerobic threshold” or “lactate threshold.”. The origin of this belief can probably be traced to the early studies of Fletcher and Hopkins [20]. Thus we see photographs of athletes at the track or at the side of the pool having a blood sample taken, with an accompanying caption indicating that the workout is being monitored by measuring “lactic acid.” The supposed rationale is that as speed is increased, a point is reached at which there is insufficient oxygen available to the muscle and energy sources that do not require oxygen (oxygen independent pathways, previously termed the anaerobic energy system) then contribute to the energy that is needed. This supposedly results in a disproportionate increase in the blood lactate concentration, a point identified as the “anaerobic” or “oxygen deficient” threshold. This is also known as the lactate threshold or lactate turnpoint.

There are two problems with this concept. First of all, the muscle never becomes anaerobic; there are other reasons for the increase that is measured in blood lactate concentration [21]. Secondly, the so-called disproportionate increase causing a turnpoint is not correct, in that the increase is actually exponential [22-24]. This is seen when many samples are taken, as in the exercise laboratory, where a blood sample can be drawn every 30 seconds as an athlete runs faster and faster.

Although a graph showing a “breakpoint” in lactate concentration as speed increases cannot be drawn as the breakpoint does not exist, a graph can nevertheless be drawn depicting the curvilinear increase in blood lactate concentration as running speed or exercise intensity increases. This curve changes in shape (shifts to the right) as fitness level changes. Particularly, the fitter a runner gets, the more the curve shifts to the right on the graph, meaning that at any given lactate concentration the running speed or work output is higher than before. A shift in the lactate curve to a higher workload or percentage VO2 max occurs due to a reduced rate of lactate production by the muscles and an increased ability of the body to clear the lactate produced [25; 26]. Often, the running speed at a lactate concentration of 4mmol/l is used as a standard for comparison. It is sometimes suggested that this can be used as a guide for training speed (i.e. a runner could do some runs each week at the speed corresponding to the 4mmol/l lactate concentration, some runs above this speed, and recovery runs at a lower speed). Of course, as fitness changes and the curve shifts, these speeds will change, and so a new curve will have to be determined. In concept this works well, but the problem is that neither exercise scientists nor coaches know how much running should be done below, at, and above the 4mmol/l concentration. The 4 mmol/l concentration referred to is a somewhat arbitrarily chosen concentration. It could just as well have been 3.5 mmol/l or 4.5 mmol/l, which would result in different training speeds for the athlete utilizing this system. Indeed, Borch et al [27] suggest 3 mmol/l as the lactate concentration representing an average steady state value. Measuring the maximal steady state lactate concentration may be useful, but requires 4-5 laboratory visits. Thus the real value in determining a ‘lactate curve’ is to monitor how it shifts with training. The desirable shift is one in which a faster running speed is achieved at the same lactate concentration. This regular testing can be done in the laboratory, with the athlete running on a treadmill or on a track, in which running speed can be carefully controlled, such as by means of pace lights.

Training Heart Rate

In recent years the concept of using heart rate while training as an indicator of the correct training intensity, has gained in popularity. Specifically, various heart rate “training zones” have been suggested, and ways to calculate these proposed. This approach has been described in many articles written for coaches and runners [27-29] and does have potential for being a precise way to regulate running intensity in training, particularly for novice runners. However, at present there are no scientific data to support an ideal specific heart rate for different types of training, and much of what is written is based on anecdotal experiences. There is no doubt that future studies will refine this area, making the prescription of training heart rate a more exact science.

Probably the greatest value in heart rate in training is for the coach to use it as a way of ensuring that an athlete does not train too hard on those days when nothing more than an easy training session is prescribed. The use of heart rate for more absolute prescription has the risk of the athlete training at the wrong intensity as a result of the large daily variability in heart rate due to influence of diurnal variation, temperature differences, sleep patterns, and stress [30]. All these can result in the prescribed training heart rate being either too high or too low on a given day. Thus the athlete may train too easily on one day, but on another day when more recovery is needed from a prior hard training session, the training intensity may be too high. The coach is probably better able to assess the most suitable intensity for the athlete. Nevertheless, training intensity based on heart rate may have some value [28].

The use of heart rate as a monitoring tool during training, as opposed to being used to dictate training intensity is a useful aid that coaches can use to assess the training response of an athlete. A progressive decline (over weeks) in heart rate for a given training session would indicate appropriate adaptive response by the athlete; a progressive increase in normal training heart rate would indicate a failure in the adaptive process and that the training load should be adjusted. Similarly, an abnormally high heart rate for a given training session may indicate approaching illness or failure to adapt to the training load and impending overtraining. The athlete would then be well-advised to train only lightly, or to rest [30].

Post-Run Stiffness

In the section on lactic acid, it was stated that the stiffness and muscle pain felt after a marathon or hard workout is not caused by lactic acid. While this was believed to be the case some decades ago, it is now known that lactic acid is not the cause of muscle stiffness, but is the result of damage to the muscle cells, connective tissue and contractile proteins [31-33].

Although the precise cause of delayed onset muscle soreness remains unknown, all runners and coaches are aware that the degree of pain depends on the intensity, duration and type of workout. For example, there is more muscle pain after a long or hard downhill run than after running over flat terrain (i.e. if eccentric muscle actions are emphasised [34]). In fact, it is this phenomenon that begins to exclude a build-up of lactic acid as a cause of the pain. In downhill running, the concentration of lactate in the blood and muscle will be low compared to running at the same speed on the flat. Thus, the most painful post-race stiffness can occur when the lactate concentration is lowest.

If a blood sample is taken from a runner the day after a marathon, especially an ultra- marathon, the concentration of an enzyme, creatine kinase, will be high [35-37]. This is an indication that muscle damage has occurred, as this particular enzyme “leaks” from damaged muscle. The “damage” referred to is minute tears or ruptures of the muscle fibres [38; 39]. This trauma to the muscle can be visualised if a sample of the muscle is examined microscopically. However, it is not just the muscle that is damaged. By measuring the amino acid hydroxyproline, it is possible to show that the connective tissue in and around the muscles is also disrupted [40]. What this shows is that stiffness results from muscle damage and breakdown of connective tissue.

Running fast or running downhill places greater strain on the muscle fibres and connective tissue compared with running on the flat. Downhill running is particularly damaging because of the greater eccentric muscle actions that occur. It is this simultaneous contracting of the muscle while being forced biomechanically to lengthen that is most damaging to muscle fibres.

What does this mean for the runner and coach? From a training and racing point of view, after the muscles have recovered from the damage that caused the stiffness and the adaptive process is complete, the muscle is more resistant to damage from subsequent exercise for up to six weeks [41]. From a coaching point of view, hard training sessions should be withheld when there is muscle pain, as further damage could result. It would be better to allow the appropriate physiological adaptations to take place before resuming hard training sessions. Weight training to increase the strength of the muscle [1] may be beneficial. It has been suggested that vitamin E may help to reduce muscle soreness, but there is little evidence to support this idea [42]. Vitamin E is thought to act as an antioxidant that may blunt the damaging action of free radicals, which attack the cell membrane of the muscle fibre.

It has also been suggested that stretching the painful muscle or muscles may be beneficial, but this has not consistently been shown to alleviate delayed onset muscle soreness. Neither is there any evidence that massage or ultrasound speed up recovery [43]. Similarly, an easy “loosening up” run “to flush out the lactic acid” is unlikely to speed up recovery, although it is also unlikely to result in further damage.

The real cause of muscle stiffness after a hard run is clearly not due to lactic acid in the muscle. Coaches will be in a better position to manage the return to normal training of their athletes after training or racing that has induced muscle soreness, if they understand the effects of type, intensity, and volume of training on muscle stiffness after exercise.

Dehydration, Heat Exhaustion and Heat Stroke

Historically, the understanding has been that runners collapse (most often at the end of races) due to dehydration. This is popularly thought to be more likely when the environmental temperature is high and dehydration more severe. “Heat exhaustion” has been incorrectly thought to be associated with dehydration, yet there is no evidence to support this [1]. “Heat stroke” is an entirely different condition, associated with an increase in body temperature.

There are a number of critical errors in the traditional thinking on the issue of dehydration. Firstly, and possibly most importantly, rectal temperatures are not abnormally elevated in collapsed runners suffering from “dehydration” [44; 45]. Secondly, there is no published evidence that runners with dehydration/ heat exhaustion will develop heat stroke if left untreated [46; 47]. And thirdly, the question must be asked why these runners nearly always collapse at the finish of the race and not during the race. Thus we must look for another explanation as to why the runners collapse.

The explanation is found in a condition called postural hypotension [44; 47-50]. While running, the high heart rate and rhythmic contraction of the leg muscles maintain blood pressure and aids in the return of blood from the legs. When running ceases, the pump action of the leg muscles stops and the heart rate drops rapidly. This results in pooling of the blood in the veins of the lower limb, which in turn causes blood pressure to decrease. It is the lowered blood pressure that results in collapse. Secondly, there is an increase in peripheral blood flow to regulate body temperature. This is more pronounced in hot conditions, and results in a reduction in the pressure of blood filling the heart [51]. Treatment is therefore very simple: If the runner lies down with the legs elevated, the return of blood from the legs is aided, blood pressure is restored and after a short while the runner will have recovered. Cooling the legs may be beneficial. As a preventive measure, it is a good idea to continue to walk after the finish line has been crossed. A second possibility is to lie down as soon as possible and elevate the legs slightly, with cooling of the legs as an additional option.

Heat exhaustion as a result of dehydration does not, therefore, exist and is not a condition that coaches need to be concerned about. This contrasts with heat stroke, in which the body temperature becomes very high (rectal temperature above 41°C) and is a potentially dangerous condition. Even after the athlete has stopped, either voluntarily or because of collapse, the temperature remains elevated because of physiological and biochemical abnormalities in the muscles. Thus the athlete must be cooled as quickly as possible, using methods such as fans, to bring the body temperature down to below 38 degrees Celsius.
Heat stroke develops as a result of a combination of a number of factors. Particularly, a high environmental temperature (>28°C) is more likely to result in the problem than when conditions are cooler. If the humidity is also high, there is an additional heat load on the runner because the sweating mechanism of the body is rendered ineffective. Sweat running off the body, as it does when the humidity is high, does not result in cooling. To cool the surface temperature of the skin, the sweat must evaporate. In addition, and also very importantly, the metabolic heat produced by the runner must be high. Thus, it is the faster athletes who are at risk, who are exercising at a high intensity. It is also, therefore, in races shorter than the marathon in which there is a high likelihood of heat stroke because of the much higher running intensity in shorter races such as cross country (on a hot day) or a 10 km race [46; 47; 52]. Thirdly, it appears that some runners are more susceptible to the development of heat stroke than others [53].

Contrary to popular belief, dehydration is not a major cause of the development of heat stroke. Although adequate fluid replacement during racing in the heat may reduce the risk of heat injury, it is not the only factor and may not even be the most important factor [46; 47; 54; 55]. Arunner can develop heat stroke without being dehydrated. Conversely, a runner can be dehydrated, but not develop heat stroke. If the recommended guidelines for fluid ingestion are followed (~600 ml/ hour), it is very unlikely that fluid deficit will play a role in the development of heat stroke.

Fluid Intake During Exercise

During events such as marathon running, one often reads recommendations suggesting that more than 1L of fluid should be ingested every hour. Ingestion of such a high volume is unnecessary, however, and probably impossible for faster runners to adhere to.

The rate at which fluid ingested during exercise empties from the stomach before being absorbed in the small intestine is influenced by a number of factors. These include the temperature of the fluid, the volume of fluid ingested, and the concentration of any carbohydrate such as glucose, fructose, sucrose or glucose polymer in the water. Thus it is important that athletes follow the correct regimen to ensure optimal fluid and carbohydrate replacement. This consists of ingesting 500-600 ml per hour of a fluid containing 7-10% carbohydrate [56]. This serves two purposes. It supplies a source of carbohydrate to maintain blood glucose concentration, as well as all the fluid replacement that is necessary during prolonged exercise, except possibly under extreme environmental conditions.

Ingestion of too much water during prolonged exercise is not only unnecessary, but can be harmful. In some susceptible people, ingesting large volumes of water can result in a condition called “water intoxication” or hyponatraemia. This occurs when the body’s normal sodium concentration becomes significantly diluted, because the amount of water or sports drink ingested is far in excess of what is needed during exercise to maintain hydration [46; 54; 57; 58]. As with heat stroke, in extreme cases this condition can be life threatening, in this case due to cerebral oedema.

Conclusions

VO2 max testing can be of some limited use to a coach when constructing a training programme for someone who has not run any races. If done regularly, the test can provide information about the efficacy of a training programme. However, the peak speed attained in the test is probably the best indicator of current ability, but race times are the most useful measure on which to prescribe running speed in training schedules.

Rather than cause fatigue, the process of lactate production helps to delay fatigue. In addition, it is important as a fuel substrate. The real value in determining a ‘lactate curve’ is to monitor how it shifts with training, the desirable shift being one in which a faster running speed is achieved at the same lactate concentration.

Heart rate during training is a useful monitoring tool, but should not be used to dictate training intensity. Rather, training heart rate information, together with knowledge of current race speeds and training-induced fatigue, should be used by the coach to determine training intensity. Ultimately, the influence of various parameters that effect heart rate response will be well researched and the coach will then be able to prescribe a specific heart rate for different types of training.

Muscle stiffness after a hard run is not due to lactic acid in the muscle. Return to normal training should be prescribed based on the knowledge that soreness is due to muscle damage.

Dehydration is not a major cause of the development of heat stroke. Heat stroke can occur without dehydration, and conversely, dehydration can occur without heat stroke. If the recommended guidelines for fluid ingestion are followed, it is very unlikely that fluid deficit will play a role in the development of heat stroke.

Ingestion of too much water during prolonged exercise is not only unnecessary, but can be harmful. In some susceptible people, ingesting large volumes of water can result in a condition called “water intoxication” or hyponatraemia.

Despite the exponential increase in knowledge in exercise physiology in the last two decades, the process of exercise physiologists and coaches changing old ideas and concepts and accepting new ones has been slow. Both should examine the new information available and use it to proceed with the next series of research studies and coaching concepts, respectively.

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Thursday
Sep292011

Intervals, Thresholds, and Long Slow Distance: the Role of Intensity and Duration in Endurance Training

Sportscience - sportsci.org
Perspectives / Training

Stephen Seiler1 and Espen Tønnessen2
Sportscience 13, 32-53, 2009 (sportsci.org/2009/ss.htm)
1 University of Agder, Faculty of Health and Sport, Kristiansand 4604, Norway.  
2 Norwegian Olympic and Paralympic Committee National Training Center, Oslo,  Norway.
Reviewers: Iñigo Mujika, Araba Sport Clinic, Vitoria, Spain; Stephen Ingham, English Institute of Sport, Loughborough University, Leicestershire, LE11 3TU, UK.


Abstract:

Endurance training involves manipulation of intensity, duration, and frequency of training sessions.   The relative impact of short, high-intensity training versus longer, slower distance training has been studied and debated for decades among athletes, coaches, and scientists.  Currently, the popularity pendulum has swung towards high-intensity interval training.  Many fitness experts, as well as some scientists, now argue that brief, high-intensity interval work is the only form of training necessary for performance optimization.   Research on the impact of interval and continuous training with untrained to moderately trained subjects does not support the current interval craze, but the evidence does suggest that short intense training bouts and longer continuous exercise sessions should both be a part of effective endurance training.  Elite endurance athletes perform 80 % or more of their training at intensities clearly below their lactate threshold and use high-intensity training surprisingly spar-ingly.  Studies involving intensification of training in already well-trained ath-letes have shown equivocal results at best.  The available evidence suggests that combining large volumes of low-intensity training with careful use of high-intensity interval training throughout the annual training cycle is the best-practice model for development of endurance performance. KEYWORDS: lactate threshold, maximal oxygen uptake, VO2max, periodization.

Content:

Interval Training: A long History
Exercise Intensity Zones
Training Plans and Cellular Signaling
Training Intensities of Elite Endurance Athletes
Units for Trainong Intensity
The 80-20 Rule for Intensity
Training Volume of Elite Athletes
Intensified-Training Studies
Intensity for Recreational Athletes:
- Case 1-From Soccer Pro to Elite Cyclist
- Case 2 From Modern Pentathete to Runner
Valid Comparisons of Training Interventions
Conclusions
References

The evening before the start of the 2009 European College of Sport Science Congress in Oslo, the two of us were sitting at a doctoral dissertation defense dinner that is part of the time honored tradition of the “doctoral disputas” in Scandinavia. One of us was the relieved disputant (Tønnessen) who had successfully defended his dissertation. The other had played the adversarial role of “førsteopponent.” Tønnessen’s research on the talent development process included extensive empirical analyses of the training characteristics of selected world champion female endurance athletes. His career case-study series systematized training diary logs of over 15,000 training sessions from three World and/or Olympic champions in three sports: distance running, cross-country skiing, and orienteering. Common for all three champions was that over their long, successful careers, about 85 % of their training sessions were performed as continuous efforts at low to moderate intensity (blood lactate ?2 mM). Among the 40 guests sat coaches, scientists, and former athletes who had been directly or indirectly involved in winning more endurance sport Olympic gold medals and world championships than we could count. One guest, Dag Kaas, had coached 12 individual world champions in four different sports. In his toast to the candidate he remarked,  ”My experience as a coach tells me that to become world champion in endurance disciplines, you have to train SMART, AND you have to train a LOT. One without the other is insufficient.”

So what is smart endurance training? The question is timely: research and popular interest in interval training for fitness, rehabilitation, and performance has skyrocketed in recent years on the back of new research studies and even more marketing by various players in the health and fitness industry. Some recent investigations on untrained or moderately trained subjects have suggested that 2-8 wk of 2-3 times weekly intense interval training can induce rapid and substantial metabolic and cardiovascular performance improvements (Daussin et al., 2007; Helgerud et al., 2007; Talanian et al., 2007). Some popular media articles have interpreted these findings to mean that long, steady distance sessions are a waste of time. Whether well founded or not, this interpretation raises reasonable questions about the importance and quantity of high- (and low-) intensity training in the overall training process of the endurance athlete. Our goal with this article is to discuss this issue in a way that integrates research and practice.

In view of the recent hype and the explosion in the number of studies investigating interval training in various health, rehabilitation, and performance settings, one could be forgiven for assuming that this training form was some magic training pill scientists had devised compara-tively recently. The reality is that athletes have been using interval training for at least 60 years.  So, some discussion of interval training research is in order before we address the broader question of training intensity distribution in competitive endurance athletes.

Interval Training: a Long History

International running coach Peter Thompson wrote in Athletics Weekly that clear references to “repetition training” were seen already by the early 1900s (Thompson, 2005).  Nobel Prize winning physiologist AV Hill incorporated intermittent exercise into his studies of exercising humans already in the 1920s (Hill et al., 1924a; Hill et al., 1924b).  About this time, Swede Gosta Holmer introduced Fartlek to distance running (fart= speed and lek= play in Swedish).  The specific term interval training is attributed to German coach Waldemer Gerschler. Influenced by work physiologist Hans Reindell in the late 1930s, he was convinced that alternating periods of hard work and recovery was an effective adaptive stimulus for the heart. They apparently adopted the term because they both believed that it was the recovery interval that was vital to the training effect. Since then, the terms intermittent exercise, repetition training, and interval training have all been used to describe a broad range of training prescriptions involving alternating work and rest periods (Daniels and Scardina, 1984). In the 1960s, Swedish physiologists, led by Per Åstrand, performed groundbreaking research demonstrating how manipulation of work duration and rest duration could dramatically impact physiological responses to intermittent exercise (Åstrand et al., 1960; Åstrand I, 1960; Christensen, 1960; Christensen et al., 1960). As Daniels and Scardina (1984) concluded 25 years ago, their work laid the foundation for all interval training research to follow. In their classic chapter Physical Training in Textbook of Work Physiology, Åstrand and Rodahl (1986) wrote, “it is an important but unsolved question which type of training is most effective: to maintain a level representing 90 % of the maximal oxygen uptake for 40 min, or to tax 100 % of the oxygen uptake capacity for about 16 min.” (The same chapter from the 4th edition, published in 2003, can be read here.)  This quote serves as an appropriate background for defining high intensity aerobic interval training (HIT) as we will use it in this article: repeated bouts of exercise lasting ~1 to 8 min and eliciting an oxygen demand equal to ~90 to 100 % of VO2max, separated by rest periods of 1 to 5 min (Seiler and Sjursen, 2004; Seiler and Hetlelid, 2005). Controlled studies comparing the physiological and performance impact of continuous training (CT) below the lactate turnpoint (typically 60-75 % of VO2max for 30 min or more) and HIT began to emerge in the 1970s. Sample sizes were small and the results were mixed, with superior results for HIT (Henriksson and Reit-man, 1976; Wenger and Macnab, 1975), superior results for CT (Saltin et al., 1976), and little difference (Cunningham et al., 1979; Eddy et al., 1977; Gregory, 1979). Like most published studies comparing the two types of training, the CT and HIT interventions compared in these studies were matched for total work (iso-energetic). In the context of how athletes actually train and perceive training stress, this situation is artificial, and one we will return to.

McDougall and Sale (1981) published one of the earliest reviews comparing the effects of continuous and interval training, directed at coaches and athletes. They concluded that both forms of training were important, but for different reasons. Two physiological assumptions that are now largely disproven influenced their interpretation. First, they concluded that HIT was superior for inducing peripheral changes, because the higher work intensity induced a greater degree of skeletal muscle hypoxia. We now know that in healthy subjects, increased lactate accumulation in the blood during exercise need not be due to increased muscle hypoxia (Gladden, 2004). Second, they concluded that since stroke volume already plateaus at 40-50 %VO2max, higher exercise intensities would not enhance ventricular filling. We now know that stroke volume continues to rise at higher intensities, perhaps even to VO2max, in well trained athletes (Gledhill et al., 1994; Zhou et al., 2001). Assuming a stroke volume plateau at low exercise intensity, they concluded that the benefit of exercise on cardiac performance was derived via stimulation of high cardiac contractility, which they argued peaked at about 75 %VO2max. Thus, moderate-intensity continuous exercise over longer durations and therefore more heart beats was deemed most beneficial for enhancing cardiac performance. While newer research no longer supports  their specific conclusions, they did raise the important point that there are underlying characteristics of the physiological response to HIT and CT that should help explain any differential impact on adaptive responses.

Poole and Gaesser (1985) published a citation classic comparing 8 wk of 3 × weekly training of untrained subjects for either  55 min at 50 %VO2max, 35 min at 75 %VO2max, or 10 × 2 min at 105 %VO2max with 2-min recoveries.  They observed no differences in the magnitude of the increase in either VO2max or power at lactate threshold among the three groups. Their findings were corroborated by Bhambini and Singh (1985) in a study of similar design published the same year. Gorostiaga et al. (1991) reported findings that challenged McDougall and Sale's conclusions regarding the adaptive specificity of interval and continuous training. They had untrained subjects exercise for 30 min, three days a week either as CT at 50 % of the lowest power eliciting VO2max, or as HIT, alternating 30 s at 100 % of power at VO2max and 30 s rest, such that total work was matched. Directly counter to McDougall and Sales conclusions, they found HIT to induce greater changes in VO2max, while CT was more effective in improving peripheral oxidative capacity and the lactate profile. At the beginning of the 1990s, the available data did not support a consensus re-garding the relative efficacy of CT vs HIT in inducing peripheral or central changes related to endurance performance.
Twenty years on, research continues regarding the extent to which VO2max, fractional utilization of VO2max, and work efficiency/economy are differentially impacted by CT and HIT in healthy, initially untrained individuals. Study results continue to be mixed, with some studies showing no differences in peripheral and central adaptations to CT vs HIT (Berger et al., 2006; Edge et al., 2006; Overend et al., 1992) and others greater improvements with HIT (Daussin et al., 2008a; Daussin et al., 2008b; Helgerud et al., 2007). When differences are seen, they lean in the direction that continuous work at sub-maximal intensities promotes greater peripheral adaptations and HIT promotes greater central adaptations (Helgerud et al., 2007).

Controlled studies directly comparing CT and HIT in already well-trained subjects were essentially absent from the literature until recently. However, a few single-group design studies involving endurance athletes did emerge in the 1990s. Acevedo and Goldfarb (1989) reported improved 10-km performance and treadmill time to exhaustion at the same pace up a 2 % grade in well-trained runners who increased their training intensity to 90-95 %VO2max on three of their weekly training days. In these already well-trained athletes, VO2max was unchanged after 8 wk of training intensification, but a right shift in the blood lactate profile was observed. In 1996 -97, South African sport scientists published the results of a single group intervention involving competitive cyclists (Lindsay et al., 1996; Weston et al., 1997). They trained regionally competitive cyclists who were specifically selected for study based on the criteria that they had not undertaken any interval training in the 3-4 months prior to study initiation. When 15 % of their normal training volume was replaced with 2 d.wk-1 interval training for 3-4 wk (six training sessions of six 5-min high intensity work bouts), 40-km time trial performance, peak sustained power output (PPO), and time to fatigue at 150 %PPO were all modestly improved. Physiological measurements such as VO2max and lactate profile changes were not reported. Stepto and colleagues then addressed the question of interval-training optimization in a similar sample of non-interval trained, regional cyclists (Stepto et al., 1999). They compared interval bouts ranging from 80 to 175 % of peak aerobic power (30 s to 8 min duration, 6-32 min total work). Group sizes were small (n=3-4), but the one group that consistently improved endurance test performance (~3 %) had used 4-min intervals at 85 % PPO. These controlled training intensification studies essentially confirmed what athletes and coaches seemed to have known for decades: some high-intensity interval training should be integrated into the training program for optimal performance gains. These studies also seemed to trigger a surge in interest in the role of HIT in athlete performance development that has further grown in recent years.

If doing some HIT (1-2 bouts per week) gives a performance boost, is more even better? Billat and colleagues explored this question in a group of middle distance runners initially training six sessions per week of CT only. They found that a training intensification to four CT sessions, one HIT session, and one lactate threshold (LT) session resulted in improved running speed at VO2max (but not VO2max itself) and running economy. Further intensifi-cation to two CT sessions, three HIT sessions and one LT session each week gave no additional adaptive benefit, but did increase subjective training stress and indicators of impending overtraining (Billat et al., 1999). In fact, training intensification over periods of 2-8 wk with frequent high-intensity bouts (3-4 sessions per week) is an effective means of temporarily compromising performance and inducing overreaching and possibly overtraining symptoms in athletes (Halson and Jeukendrup, 2004).  There is likely an appropriate balance between high- and low-intensity training in the day-to-day intensity distribution of the endurance athlete. These findings bring us to two related questions: how do really good endurance athletes actually train, and is there an optimal training intensity distribution for long-term performance development?

While arguments can be made that tradition, resistance to change and even superstition may negatively influence training methods of elite endurance athletes, sports history tells us that athletes are experimental and innovative. Observing the training methods of the world's best endurance athletes represent a more valid picture of “best practice” than we can develop from short-term laboratory studies of untrained or moderately trained subjects.  In today’s per-formance environment, where promising athletes have essentially unlimited time to train, all athletes train a lot and are highly motivated to optimize the training process. Training ideas that sound good but don't work in practice will fade away. Given these conditions, we argue that any consistent pattern of training intensity distribution emerging across sport disciplines is likely to be a result of a successful self-organization (evolution) towards a “population optimum.” High performance training is an individualized process for sure, but by population optimum, we mean an approach to training organization that results in most athletes staying healthy, making good progress, and performing well in their most important events. 

Exercise Intensity Zones

To describe intensity distribution in endurance athletes we have to first agree on an intensity scale. There are different intensity zone schemes to choose from. Most national sport governing bodies employ an intensity scale based on ranges of heart rate relative to maximum and associated typical blood lactate concentration range.  Research approaches vary, but a number of recent research studies have identified intensity zones based on ventilatory thresholds.  Here we will examine an example of each of these scales.
Table 1 shows the intensity scale used by all endurance sports in Norway. A valid criticism of such a scale is that it does not account for individual variation in the relationship between heart rate and blood lactate, or activity specific variation, such as the tendency for maximal steady state concentrations for blood lactate to be higher in activities activating less muscle mass (Beneke and von Duvillard, 1996; Beneke et al., 2001).

Several recent studies examining training intensity distribution (Esteve-Lanao et al., 2005; Seiler and Kjerland, 2006; Zapico et al., 2007) or performance intensity distribution in multi-day events (Lucia et al., 1999; Lucia et al., 2003) have employed the first and second venti-latory turnpoints to demarcate three intensity zones (Figure 1). The 5-zone scale in the table above and the 3-zone scale below are reasonably super-imposable in that intensity Zone 3 in the 5-zone system coincides well with Zone 2 in the 3-zone model. While defining five “aerobic” intensity zones is likely to be informative in training practice, it is important to note that they are not based on clearly defined physiological markers. Note also that 2-3 additional zones are typically defined to accommodate very high intensity sprint, anaerobic capacity, and strength training. These zones are typically defined as “anaerobic” Zones 6, 7, and 8.

Training Plans and Cellular Signaling

Athletes do not train at the same intensity or for the same duration every day. These va-riables are manipulated from day to day with the implicit goals to maximize physiological capacity over time, and stay healthy. Indeed, the former is quite dependent on the latter. Training frequency is also a critical variable manipulated by the athlete. This is particularly evident when comparing younger (often training 5-8 times per week) and more mature athletes at peak performance level (often training 10-13 sessions per week). Ramping up training frequency (as opposed to training longer durations each session) is responsible for most of the increase in yearly training hours observed as teenage athletes mature. Cycling might be an exception to this general rule, since cycling tradition dictates single daily sessions that often span 4-6 h among professionals. The ultimate targets of the training process are individual cells.  Changes in rates of DNA transcription, RNA translation, and ultimately, synthesis of specific proteins or protein constellations are induced via a cascade of intra-cellular signals induced by the training bout. Molecular exercise biologists are unraveling how manipulation of intensity and duration of exercise specifically modifies intracellular signaling and resulting protein synthetic rates at the cellular or whole muscle/myocardial level (Ahmetov and Rogozkin, 2009; Hoppeler et al., 2007; Joseph et al., 2006; Marcuello et al., 2005; McPhee et al., 2009; Yan, 2009). About 85 % of all publications involving gene expression and exercise are less than 10 y old, so we do not yet know enough to relate results of Western blots to the specific training of an athlete.

The signaling impact of a given exercise stress (intensity×duration) almost certainly decays with training (Hoppeler et al., 2007; Nordsborg et al., 2003).  For example, AMP activated protein kinase a2 (AMPK) activity jumps 9-fold above resting levels after 120 min of cycling at 66 %VO2max in untrained subjects.  However, after only 10 training sessions,  almost no increase in AMPK is seen after the same exercise bout (McConell et al., 2005). Manipulating exercise intensity and duration also impacts the systemic stress responses associated with training. Making this connection is further complicated by recent findings suggesting that muscle glycogen depletion can enhance and antioxidant supplementation can inhibit adaptations to training (Brigelius-Flohe, 2009; Go-mez-Cabrera et al., 2008; Hansen et al., 2005; Ristow et al., 2009; Yeo et al., 2008). It seems fair to conclude that while we suspect important differences exist, we are not yet able to relate specific training variables (e.g., 60 min vs 120 min at 70 %VO2max) to differences in cell signaling in a detailed way. Our view of the adaptive process remains limited to a larger scale. We can still identify some potential signaling factors that are associated with increased exercise intensity over a given duration (Table 2) or increased exercise duration at a given sub-maximal intensity (Table 3). Some of these are potentially adaptive and others maladaptive.  There is likely substantial overlapping of effects between extending exercise duration and increasing exercise intensity.

It may be a hard pill to swallow for some exercise physiologists, but athletes and coaches do not need to know much exercise physiology to train effectively. They do have to be sensitive to how training manipulations impact athlete health, daily training tolerance, and performance, and to make effective adjustments. Over time, a successful athlete will presumably organize their training in a way that maximizes adaptive benefit for a given perceived stress load. That is, we can assume that highly successful athletes integrate this feedback experience over time to maximize training benefit and minimize risk of negative outcomes such as  illness, injury, stagnation, or overtraining.

Training Intensities of Elite Endurance Athletes

Empirical descriptions of the actual distribution of training intensity in well-trained athletes have only recently emerged in the literature. The first time one of us (Seiler) gave a lecture on the topic was in 1999, and there were few hard data to present, but a fair share of anecdote and informed surmise. Carl Foster, Jack Daniels and Seiler published a book chapter the same year, “Perspectives on Correct Approaches to Training” that synthesized what we knew then (read chapter here via Google books). At that time, much of the discussion and research re-lated to the endurance training process focused on factors associated with overtraining (a training control disaster), with little focus on what characterized “successful training.” The empirical foundation for describing successful training intensity distribution is stronger 10 years later. 
Robinson et al. (1991) published what was according to the authors “the first attempt to quantify training intensity by use of objective, longitudinal training data.”  They studied training characteristics of 13 national class male, New Zealand runners with favorite distances ranging from 1500 m to the marathon. They used heart rate data collected during training and related it to results from standardized treadmill determinations of heart rate and running speed at 4-mM blood lactate concentration (misnamed anaerobic threshold at the time). Over a data collection period of 6-8 wk corresponding to the preparation phase, these athletes reported that only 4 % of all training sessions were interval workouts or races. For the remaining training sessions, average heart rate was only 77 % of their heart rate at 4-mM blood lactate. This heart rate translates to perhaps 60-65 % of VO2max. The authors concluded that while their physiological test results were similar to previous studies of well trained runners, the training intensity of these runners was perhaps lower than optimal, based on prevailing recommendations to perform most training at or around the lactate/anaerobic threshold.

In one of the first rigorous quantifications of training intensity distribution reported, Mujika et al. (1995) quantified the training intensity distribution of national and international class swimmers over an entire season based on five blood-lactate concentration zones. Despite specializing in 100-m and 200-m events requiring ~60 to 120 s, these athletes swam 77 % of the 1150 km completed during a season at an intensity below 2 mM lactate.  The intensity distribution of 400- and 1500-m swim specialists was not reported, but was likely even more weighted towards high-volume, low-intensity swimming.

Billat et al. (2001) performed physiological testing and collected data from training diaries of French and Portuguese marathoners. They classified training intensity in terms of three speeds: marathon, 10–km, and 3–km. During the 12 wk preceding an Olympic trials mara-thon, the athletes in this study ran 78 % of their training kilometers at below marathon speed, only 4 % at marathon race speed (likely to be near VT1), and 18 % at 10–km or 3–km speed (likely to be > VT2). This distribution of training intensity was identical in high-level (<2 h 16 min for males and <2 h 38 min for females) and top-class athletes (<2 h 11 min and <2 h 32 min). But the top-class athletes ran more total kilometers and proportionally more distance at or above 10–km speed.

Kenyan runners are often mythologized for the high intensity of their training. It is therefore interesting that with data from another study by Billat et al. (2003), we calculated that elite male and female Kenyan 5- and 10-km runners ran ~85 % of their weekly training kilometers below lactate-threshold speed.

The first study on runners to quantify training intensity using three intensity zones was that of Esteve-Lanao et al. (2005). They followed the training of eight regional- and national-class Spanish distance runners over a six-month period broken into eight, 3-wk mesocycles. Heart rate was measured for every training session to calculate the time spent in each heart-rate zone defined by treadmill testing. All told, they quantified over 1000 heart-rate recordings. On average these athletes ran 70 km.wk-1 during the six-month period, with 71 % of running time in Zone 1, 21 % in Zone 2, and 8 % in Zone 3. Mean training intensity was 64 %VO2max. They also reported that performance times in both long and short races were highly negatively correlated with total training time in Zone 1. They found no significant correlation between the amount of high-intensity training and race performance.

Rowers compete over a 2000-m distance requiring 6-7 min. Steinacker et al. (1998) reported that extensive endurance training (60- to 120-min sessions at <2 mM blood lactate) dominated the training volume of German, Danish, Dutch, and Norwegian elite rowers. Rowing at higher intensities was performed ~4-10 % of the total rowed time. The data also suggested that German rowers preparing for the world championships performed essentially no rowing at threshold intensity, but instead trained either below 2 mM blood lactate or at intensities in the 6-12 mM range.

Seiler collaborated with long time national team rower, coach, and talent development coordinator Åke Fiskerstrand to examine historical developments in training organization among international medal winning rowers from Norway (Fiskerstrand and Seiler, 2004). Using questionnaire data, athlete training diaries, and physiological testing records, they quantified training intensity distribution in 27 athletes who had won world or Olympic medals in the 1970s to 1990s.  They documented that over the three decades: training volume had increased about 20 % and become more dominated by low-intensity volume; the monthly hours of high-intensity training had dropped by one-third; very high intensity overspeed sprint training had declined dramatically in favor of longer interval training at 85-95 %VO2max; and the number of altitude camps attended by the athletes increased dramatically. Over this 30-y timeline, VO2max and rowing ergometer performance improved by ~10 % with no change in average height or body mass.  Most of the changes occurred between the 1970s and 1980s, coinciding with major adjustments in training intensity.

Most recently, Gullich et al. (2009) described the training of world class junior rowers from Germany during a 37-wk period culminating in national championships and qualification races for the world championships. These were very talented junior rowers, with 27 of 36 athletes winning medals in the junior world championships that followed the study period. Remarkably, 95 % of their rowing training was performed below 2 mM blood lactate, based on daily heart-rate monitoring and rowing ergometer threshold determinations performed at the beginning of the season.  This heavy dominance of extensive endurance training persisted across mesocycles. However, the relatively small volume of Zone 2 and Zone 3 work shifted towards higher intensities from the basic preparation phase to the competition phase. That is, the intensity distribution became more polarized. It is important to point out that time-in-zone allocation based on heart-rate cut-offs (the kind of analysis performed by software from heart watch manufacturers) underestimates the time spent performing high-intensity exercise and the impact of that work on the stress load of an exercise session (Seiler and Kjerland, 2006). Although the outcomes are biased by this problem, there was still a clear shift in the intensity distribution towards large volumes of low- to moderate-intensity training. We also evaluated retrospectively whether there were any differences in junior training characteristics between a subgroup of rowers who went on to win international medals as seniors within three years (14 of 36 athletes) and the remainder of the sample, who all continued competing at the national level. The only physical or training characteristic that distinguished the most successful rowers from their peers was a tendency to distribute their training in a more polarized fashion; that is, they performed significantly more rowing at very low aerobic intensities and at the highest intensities. We concluded that the greater polarization observed might have been due to better management of intensity (keeping hard training hard and easy training easy) among the most successful athletes. This polarization might protect against overstress.

Professional road cyclists are known for performing very high training volumes, up to 35,000 km.y-1. Zapico and colleagues (2007) used the 3-intensity zone model to track training characteristics from November to June in a group of elite Spanish under-23 riders. In addi-tion, physiological testing was performed at season start and at the end of the winter and spring mesocycles.  There was an increase in total training volume and a four-fold increase in Zone 3 training between the winter and spring mesocycles (Figure 2), but there was no further improvement in power at VT1, VT2 or at VO2max between the end of the winter and spring mesocycles (Figure 3), despite the training intensification. Anecdotally, this finding is not unusual, despite the fact that athletes feel fitter. It may be that VT2 and VO2max determi-nation using traditional methods can miss an important increase in the duration that can be maintained at the associated workloads.


 

Individual and team pursuit athletes in cycling compete over about 4 min. The event ap-peals to sport scientists because the performance situation is highly controlled and amenable to accurate modeling of the variables on both sides of the power balance equation. Schumacher and Mueller (2002) demonstrated the validity of this approach in predicting “gold medal standards” for physiological testing and power output in track cycling. However, less obvious from the title was the detailed description of the training program followed by the German cyclists monitored in the study, ultimately earning a gold medal in Sydney in world-record time. These athletes trained to maintain 670 W in the lead position and ~450 W when following using a training program dominated by continuous low to moderate intensity cycling on the roads (29-35,000 km.y-1). In the 200 d preceding the Olympics, the athletes performed “low-intensity, high-mileage” training at 50-60 % of VO2max on ~140 d. Stage races took up another ~40 d. Specific track cycling at near competition intensities was performed on less than 20 d between March and September.  In the ~110 d preceding the Olympic final, high-intensity interval track training was performed on only 6 d.

Units for Training Intensity

Cross country skiers have rather legendary status in exercise physiology circles for their aerobic capacity and endurance capacity in arms and legs. Seiler et al. (2006) studied 12 competitive to nationally elite male 17–y old skiers from a special skiing high school in the region. The mean VO2max for the group was 72 ml.kg-1min-1. They were guided by coaches with national team coaching experience and were trained along similar lines to the seniors, but with substantially lower volumes of training. Like Esteve-Lanao (2005) did with runners, we used heart-rate monitoring to quantify all endurance sessions and determined three aerobic intensity zones based on ventilatory turn points. We also recorded the athletes' rating of perceived exertion (RPE) using the methods of Foster et al. (1996; 1998; 2001a) for all training bouts. Finally, we collected blood lactate during one training week to relate heart rate and perceived exertion measurements to blood lactate values.

When comparing the three different intensity quantification methods, we addressed the issue of how training intensity is best quantified. Heart-rate monitoring is clearly appealing. We can save heart rate data, download entire workouts to analysis software, and quantify the time heart rate falls within specific pre-defined intensity zones. Using this “time-in-zone” approach, we found that 91 % of all training time was spent at a heart rate below VT1 intensity, ~6 % between VT1 and VT2, and only 2.6 % of all 15-s heart rate registrations were performed above VT2. We then quantified intensity by allocating each training session to one of the three zones based on the goal of the training and heart rate analysis. We called this the “session-goal approach”. For low-intensity continuous bouts, we used average heart rate for the entire bout. For bouts designed to be threshold training we averaged heart rate during the threshold-training periods. For high-intensity interval-training sessions, we based intensity on the average peak heart rate for each interval bout. Using this approach, intensity distribution derived from heart rate responses closely matched the session RPE (Figure 4), training diary distribution based on workout description, and blood-lactate measurements. The agreement between the session-by-session heart-rate quantification and session RPE-based assignment of intensity was 92 %. In their training diaries, athletes recorded 30-41 training sessions in 32 d and described 75% of their training bouts as low intensity continuous, 5% as threshold wor-kouts, and 17% as intervals.

We have also recently observed the same time-in-zone mismatch when quantifying intensity distribution in soccer training (unpublished data). It seems clear that typical software-based heart-rate analysis methods overestimate the amount of time spent training at low intensity and underestimate the time spent at very high workloads compared to athlete perception of effort. We think this mismatch is important, because the unit of stress perceived and responded to by the athlete is the stress of the entire training session or perhaps training day, not minutes in any given heart-rate zone. 

The 80-20 Rule for Intensity

In spite of differences in the methods for quantifying training intensity, all of the above studies show remarkable consistency in the training distribution pattern selected by successful endurance athletes.  About 80 % of training sessions are performed predominantly at inten-sities under the first ventilatory turn point, or a blood-lactate concentration <=2mM. The remaining ~20 % of sessions are distributed between training at or near the traditional lactate threshold (Zone 2), and training at intensities in the 90-100 %VO2max range, generally as interval training (Zone 3). An elite athlete training 10-12 times per week is therefore likely to dedicate 1-3 sessions weekly to training at intensities at or above the maximum lactate steady state. This rule of thumb coincides well with training studies demonstrating the efficacy of adding two interval sessions per week to a training program (Billat et al., 1999; Lindsay et al., 1996; Weston et al., 1997). Seiler and Kjerland (2006) have previously gone so far as say that the optimal intensity distribution approximated a “polarized distribution” with 75-80 % of training sessions in Zone 1, 5 % in Zone 2, and 15-20 % in Zone 3. However, there is considerable variation in how athletes competing in different sports and event durations distribute their training intensity within Zones 2 and 3. 

Why has this training pattern emerged?  We do not have sufficient research to answer this question, but we can make some reasonable guesses. One group of factors would involve the potential for this distribution to best stimulate the constellation of training adaptations required for maximal endurance performance. For example, large volumes of training at low intensity might be optimal for maximizing peripheral adaptations, while relatively small volumes of high intensity training fulfill the need for optimizing signaling for enhanced cardiac function and buffer capacity. Technically, lots of low intensity training may be effective by allowing lots of repetitions to engrain correct motor patterns. On the other side of the adaptation-stress equation is the stress induced by training. Athletes may migrate towards a strategy where longer duration is substituted for higher intensity to reduce the stress reactions associated with training and facilitate rapid recovery from frequent training (Seiler et al., 2007). Interestingly, Foster and colleagues reported a very similar intensity distribution by professional cyclists during the 3 wk and 80+ racing hours of the grand tours, such as the Tour de France. Perhaps this distribution represents a form of pacing that emerges over the months of elite training (Foster et al., 2005).

”Low intensity”–between 50 %VO2max and just under the first lactate turnpoint–represents a wide intensity range in endurance athletes. There is probably considerable individual varia-tion in where within this range athletes accumulate most of their low-intensity training volume. Technique considerations may play in: athletes have to train at a high enough intensity to allow correct technique. For example, Norwegian Olympic flat-water kayak gold medalist Eric Verås Larsen explained that the reason most of his Zone 1 continuous endurance training tended to be closer to his lactate threshold than normally observed was that he could not paddle with competition technique at lower intensities (Verås Larsen, personal communication).  These qualifiers aside, we conclude that a large fraction of the training within this zone is being performed at ~60-65 %VO2max, We note that this intensity is about the intensity associated with maximal fat utilization in trained subjects (Achten and Jeukendrup, 2003), but it is unclear why optimizing fat utilization would be important for athletes competing over 3-15 min.

Training Volume of Elite Athletes

Obviously, training intensity distribution and training volume together will determine the impact of training. Elite athletes train a lot, but to be more specific requires some common metric for comparing athletes in different sports. Runners and cyclists count kilometers, swimmers count thousands of meters, and rowers and cross-country skiers count training hours.  With a few reasonable assumptions, we can convert these numbers to annual training hours. This physiological metric is appropriate, since the body is sensitive to stress duration. 

Training volume increases with age in high-level performers, mostly through increased training frequency in sports like running and cross-country skiing, but also through increases in average session duration, particularly in cycling. A talented teenage cyclist training five days a week might accumulate 10-15 h.wk-1. A professional cyclist from Italy performing a 1000-km training week will likely be on the bike between 25 and 30 h.

Cycling 30-35,000 kilometers a year at, say, ~35 km.h-1 with occasional sessions of strength training, will add up to ~1000 h.y-1.  An elite male marathoner would likely never run more than about 15 hours in a week. At an average running speed of 15 km.h-1, that would be at most 225 km.  Former world record holder in the 5 km, 10 km, and marathon, Ingrid Kristiansen trained 550 h.y-1 when she was running (Espen Tønnessen, unpublished data). At a younger age, when she competed in the Olympics for Norway as a cross country skier, she actually trained 150 more h.y-1. Bente Skari, one of the most successful female cross country skiers ever, recorded peak annual training loads of 800 h.y-1 (Espen Tønnessen, unpublished data). Annual training volume measured in hours is around 1000 among world class rowers. For example, Olaf Tufte recorded 1100 training hours in 2004, when he took his first gold medal in the single scull event (Aasen, 2008). His monthly training volume for that year is shown in Figure 5. Of these hours, about 92 % were endurance training, with the remainder being primarily strength training. An Olympic champion swimmer like Michael Phelps may record even higher annual training volumes, perhaps as much as 1300 h (a reasonable guess based on training of other swimming medalists).

The Kenyan marathoner, Italian cyclist, Norwegian rower and American swimmer are all at the top of their sport, but when we measure their training volume in hours, they seem quite different, with international success being achieved with a two-fold or larger range in hours per year (Figure 6). What can explain this difference?  One explanation is that the muscle, tendon, and joint loading stress of the different movements vary dramatically. Running imposes severe ballistic loading stress that is not present in cycling or swimming.

There seems to be a strong inverse relationship between tolerated training volume and degree of eccentric or ballistic stress of the sport. Swimming, rowing, and cross-country skiing are all highly technical events with movement patterns that do not draw on the genetically pre-programmed motor pathways of running.  Thus high volumes of training may be as important for technical mastery as for physiological adaptation in these disciplines. Rowers and speed skaters do less movement-specific training than most other athletes, but they accumulate substantial additional hours of strength training and other forms of endurance training.


Intensified-Training Studies

Is the “80-20” training intensity distribution observed for successful athletes really optimal, or would a redistribution of training intensity towards more threshold and high intensity interval training and less long slow distance training stimulate better gains and higher perfor-mance? Proponents of large volumes of interval training might invoke the famous pareto principle and propose that in keeping with this “rule” of effects vs causes, these athletes are achieving 80 % of their adaptive gains with 20 % of their training and wasting valuable training energy. In the last 10 y, several studies have been published addressing this question.

Evertsen et al. (1997; 1999; 2001) published the first of three papers from a study involving training intensification in 20 well-trained junior cross-country skiers competing at the national or international level. All of the subjects had trained and competed regularly for 4-5 years. In the two months before study initiation, 84 % of training was carried out at 60-70 %VO2max, with the remainder at 80-90 %VO2max.  They were then randomized to a moderate-intensity (MOD) or a high-intensity training group (HIGH). MOD maintained essentially the same training-intensity distribution they had used previously, but training volume was increased from 10 to 16 h.wk-1. HIGH reversed their baseline intensity distribution so that 83 % of training time was performed at 80-90 %VO2max, with only 17 % performed as low-intensity training.  This group trained 12 h.wk-1. The training intervention lasted five months. Intensity control was achieved using heart-rate monitoring and blood-lactate sampling.

Despite 60 % more training volume in MOD and perhaps 400 % more training at lactate threshold or above in HIGH, physiological and performance changes were modest in both groups of already well-trained athletes. Findings from the three papers are summarized in Table 4.

Gaskill et al. (1999) reported the results of a 2-y project involving 14 cross-country skiers training within the same club who were willing to have their training monitored and manipu-lated. The design was interesting and practically relevant. During the first year, athletes all trained similarly, averaging 660 training hours with 16 % at lactate threshold or higher (nominal distribution of sessions). Physiological test results and race performances during the first year were used to identify seven athletes who responded well to the training and seven who showed poor VO2max and lactate-threshold progression, and race results. In the second year, the positive responders continued using their established training program. The non-responders performed a markedly intensified training program with a slight reduction in training hours. The non-responders from Year 1 showed significant improvements with the intensified program in Year 2 (VO2max, lactate threshold, race points). The positive responders from Year 1 showed a similar development in Year 2 as in Year 1.

It is interesting in this context to point out that many elite athletes now extend the  peri-odization of their training to a 4-y Olympic cycle. The first year after an Olympics is a “recovery season”, followed by a building season, then a season of very high training volume, culminating with the Olympic season, where training volume is reduced and competition specificity is emphasized more.  Variation in the pattern of training may be important for maximal development, but these large scale rhythms of training have not been studied.

Esteve-Lanao et al. (2007) randomized 12 sub-elite distance runners to one of two training groups (Z1 and Z2) that were carefully monitored for five months. They based their training intensity distribution on the 3-zone model described earlier and determined from treadmill testing. Based on time-in-zone heart-rate monitoring, Z1 performed 81, 12, and 8 % of training in Zones 1, 2, and 3 respectively. Z2 performed more threshold training, with 67, 25, and 8 % of training performed in the three respective zones. That is, Group Z2 performed twice as much training at or near the lactate threshold. In a personal communication, the authors reported that in pilot efforts, they were unable to achieve a substantial increase in the total time spent in Zone 3, as it was too hard for the athletes. Total training load was matched between the groups. Improvement in a cross-country time-trial performed before and after the five-month period revealed that the group that had performed more Zone 1 training showed significantly greater race time improvement (-157 ± 13 vs  122 ± 7 s).

Most recently, Ingham et al. (2008) were able to randomize 18 experienced national standard male rowers from the UK into one of two training groups that were initially equiva-lent based on performance and physiological testing. All the rowers had completed a 25-d post-season training-free period just prior to baseline testing. One group performed “100 %” of all training at intensities below that eliciting 75 %VO2max (LOW). The other group per-formed 70 % training at the same low intensities as well as 30 % of training at an intensity 50 % of the way between power at lactate threshold and power at VO2max (MIX). In practice, MIX performed high intensity training on 3 d.wk-1. All training was performed on a rowing ergometer over the 12 wk. The two groups performed virtually identical volumes of training (~1140 km on the ergometer), with ±10 % individual variation allowed to accommodate for variation in athlete standard. Results of the study are summarized in Table 5.

Sixteen of 18 subjects set new personal bests for the 2000-m ergometer test at the end of the study. The authors concluded that LOW and MIX training had similar positive effects on performance and maximal oxygen consumption. LOW training appeared to induce a greater right-shift in the blood-lactate profile during sub-maximal exercise, which did not translate to a significantly greater gain in performance. If MIX training enhanced or preserved anaerobic capacity more than LOW, this may have compensated for the observed differences in blood-lactate profile.

Intensity for Recreational Athletes

Elite endurance athletes train 10-12 sessions and 15-30h each week.  Is the pattern of 80 % below and 20 % above lactate threshold appropriate for recreational athletes training 4-5 times and 6-10 hours per week?  There are almost no published data addressing this question. Recently Esteve-Lanao (personal communication) completed an interesting study on recreational runners comparing a program that was designed to reproduce the polarized training of successful endurance athletes and compare it with a program built around much more threshold training in keeping with the ACSM exercise guidelines.  The intended intensity distribution for the two groups was: Polarized 77-3-20 % and ACSM 46-35-19 % for Zones 1, 2, and 3. However, heart-rate monitoring revealed that the actual distribution was: Polarized 65-21-14 % and ACSM 31-56-13 %.

Comparing the intended and achieved distributions highlights a typical training error com-mitted by recreational athletes.  We can call it falling into a training intensity “black hole.”  It is hard to keep recreational people training 45-60 min a day 3-5 days a week from accumulating a lot of training time at their lactate threshold. Training intended to be longer and slower becomes too fast and shorter in duration, and interval training fails to reach the desired intensity. The result is that most training sessions end up being performed at the same threshold intensity. Foster et al. (2001b) also found that athletes tend to run harder on easy days and easier on hard days, compared to coaches' training plans.  Esteve Lanao did succeed in getting two groups to distribute intensity very differently. The group that trained more polarized, with more training time at lower intensity, improved their 10-km performance significantly more at 7 and 11 wk. So, recreational athletes could also benefit from keeping low- and high-intensity sessions at the intended intensity.

Interval training can be performed effectively with numerous combinations of work duration, rest duration, and intensity. We have found that when subjects self-select running speed based on a standard prescription, 4-min work duration and 2-min recovery duration combine to give the highest physiological response and maintained speed (Seiler and Sjursen, 2004; Seiler and Hetlelid, 2005). However, perceptual and physiological response differences across the typical work and recovery spectrum are fairly small and performance enhancement differences are unclear at best. Some researchers have proposed that specific interval regimes (e.g., 4 × 4 min at 95 %VO2max) may be superior for achieving adaptive gains (Helgerud et al., 2007; Wisloff et al., 2007), but other research studies and our observations of athlete practice suggest that a variety of combinations of work and rest duration are effective for long-term development. Table 6 shows typical combinations of intensity and effective duration used by elite endurance athletes for workouts in the different aerobic training zones described earlier. All the examples are taken from the training diaries of elite performers. The effective durations for the different zones are utilized by highly trained athletes. For those without the same training base, similar workouts would be performed but with less total effec-tive duration.

Case Studies of Training Manipulation

Case studies are the weakest form of scientific evidence. But, for coaches and high performance athlete support teams, each elite athlete is a case study.  So, we present here two case studies that we think are instructive in demonstrating the potential physiological impact of successfully manipulating training  volume and intensity distribution variables at the individual level. Both cases involve Norwegian athletes who were followed closely by one of the authors (Tønnessen).  Both would be considered already highly trained prior to the training reorganization.

Case 1–From Soccer Pro to Elite Cyclist

Knut Anders Fostervold was a professional soccer player in the Norwegian elite league from 1994 to 2002.  A knee injury ended his soccer career at age 30 and he decided to switch to cycling.  Knut had very high natural endurance capacity and had run 5 km in 17:24 at age 12.  After 15 y of soccer training at the elite level, he adopted a highly intensive training regime for cycling that was focused on training just under or at his lactate threshold and near VO2max; for example, 2-3 weekly training sessions of 4-5 × 4 min at 95 %VO2max.  Weekly training volume did not exceed 10 h.

After 2.5 years of this high-intensity, low-volume training, Fostervold initiated cooperation with the Norwegian Olympic Center and his training program was radically reorganized.  Weekly training volume was doubled from 8-10 h to 18-20.  Training volume in Zone 2 was reduced dramatically and replaced with a larger volume of training in Zone 1.  Training in Zone 5 was replaced with Zones 3 and 4, such that total training volume at intensities at or above lactate threshold was roughly doubled without overstressing the athlete. The typical effective duration of interval sessions increased from ~20 min to ~ 60 min (for example 8 × 8 min at 85-90 %HRmax with 2-min recoveries).  The intensity zones were initially based on heart rate but later adjusted relative to lactate and power output measurements made in the field.  Table 7 shows the training intensity distribution and volume loading for the athlete during the season before and after the change in training to a high-volume program. Table 8 shows the outcome.

  

 

 

 

The athlete responded well to the training load amplification and reorganization.  During the 2005 season, after 2.5 y performing a low-volume, high-intensity program, a season training with higher volume and lower average intensity resulted in marked physiological and performance improvement. Although the athlete’s training de-emphasized both training near his lactate threshold intensity and training at near VO2max, both of these physiological anchors improved markedly.

Fostervold won a bronze medal in the Norwegian national time-trial championships, seconds behind former world under-23 time trial champions and Tour de France stage win-ners Thor Hushovd and Kurt Asle Arvesen.  His failure to perform even better, given his exceptionally high VO2max, was attributed to poorer cycling efficiency and aerodynamics and a lower fractional utilization at lactate threshold compared to the best professionals with many years of specific training. In 2006 and 2007 he represented Norway in the world cham-pionship time trial. His absolute VO2max in 2005 was equal to the highest ever measured in a Norwegian athlete. 

Case 2–From Modern Pentathlete to Runner

Prior to 2003, Øystein Sylta was a military pentathlete (European champion in 2003).  In the Fall of 2003 he decided to focus on distance running and is now nationally competitive, with personal bests for 3000-m steeplechase, 5000-m, and 10000-m of 8:31, 14:04 and 29:12 respectively.  His case is interesting due to the dramatic change in training volume and intensity distribution he undertook from 2003 to 2004 and associated changes in physiolog-ical test results.

Prior to 2003, Sylta trained using a high-intensity, low-volume training structure.  When he agreed to try a new approach, emphasis was placed on increasing training volume with low-intensity sessions and changing his interval training.  He either trained long slow distance or long intense interval sessions. However, his total training distance at intensities above his lactate threshold was reduced and redistributed.  From 2002/2003 to 2003/2004 he increased his total running distance from 3,500 to 5,900 km.  He also reduced his strength training from 100 annual hours to 50.  Table 9 shows a typical hard training week in the Fall of 2003 and Fall of 2004, and Table 10 summarizes the running specific training.  His physiological adaption to the first year of restructured training is documented in Table 11.

From 2003 to 2009, Sylta’s threshold running speed increased from 16.9 to 19.5 km.h-1. From 2002 to 2009,  his 10-km time improved from 31:44 to 29:12, and 3000-m steeplechase from 9:11 to 8:31.  In the first five months of training reorganization, his 3000-m steeple result improved by 30 s.

 

 

 

Both these case studies demonstrate that even in already well trained athletes, meaningful improvements in physiological test results and performance may occur with appropriate training intensity and volume manipulation.  Both athletes showed clear improvements in physiological testing despite reductions in HIT training.  Both seemed to respond positively to an increase in total training volume and specifically, more low-intensity volume.

Valid Comparisons of Training Interventions

Matching training programs based on total work or oxygen consumption seems sensible in a laboratory.  As we noted earlier, this has been the preferred method of matching when com-paring the effects of continuous and interval training in controlled studies. Unfortunately, it is not realistic from the view of athletes pursuing maximal performance. They do not compare training sessions or adjust training time to intensity in this manner. A key issue here is the non-linear impact of exercise intensity on the manageable accumulated duration of intermittent exercise. We have exemplified this in Table 12 by comparing some typical training sessions from the training of elite athletes.

The point we want to make is that the athlete’s perception of the stress of performing 4 × 15 min at 85 %VO2max is about the same as that of performing 6 × 4 min at 95 %VO2max, even though total work performed is very different. To answer a question like, “is near VO2max interval training more effective for achieving performance gains in athletes than training at the maximal lactate steady state?”, the matching of training bouts has to be realistic from the perspective of perceived stress and how athletes train. Future studies of training intensity effects on adaptation and performance should take this issue of ecological validity into account.

Conclusions

Optimization of training methods is an area of great interest for scientists, athletes, and fitness enthusiasts. One challenge for sport scientists is to translate short-term training intervention study results to long-term performance development and fitness training organi-zation. Currently, there is great interest in high-intensity, short-duration interval training programs. However, careful evaluation of both available research and the training methods of successful endurance athletes suggests that we should be cautious not to over-prescribe high-intensity interval training or exhort the advantages of intensity over duration.
Here are some conclusions that seem warranted by the available data and experience from observations of elite performers:

• There is reasonable evidence that an ~80:20 ratio of low to high intensity training (HIT) gives excellent long-term results among endurance athletes training daily.
• Low intensity (typically below 2 mM blood lactate), longer duration training is effective in stimulating physiological adaptations and should not be viewed as wasted training time.
• Over a broad range, increases in total training volume correlate well with improvements in physiological variables and performance.


• HIT should be a part of the training program of all exercisers and endurance athletes. However, about two training sessions per week using this modality seems to be sufficient for achieving performance gains without inducing excessive stress.
• The effects of HIT on physiology and performance are fairly rapid, but rapid plateau effects are seen as well. To avoid premature stagnation and ensure long-term development, training volume should increase systematically as well.
• When already well-trained athletes markedly intensify training with more HIT over 12 to ~45 wk, the impact is equivocal.
• In athletes with an established endurance base and tolerance for relatively high training loads, intensification of training may yield small performance gains at acceptable risk.
• An established endurance base built from reasonably high volumes of training may be an important precondition for tolerating and responding well to a substantial increase in training intensity over the short term.
• Elite athletes achieve periodization of training with reductions in total volume, and modest increases in volume of training above the lactate threshold. An overall polarization of training intensity characterizes the transition from preparation to competition mesocycles. The basic intensity distribution remains similar throughout the year.

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Friday
Sep232011

Skeletal muscle: master or slave of the cardiovascular system?

By: Russell S. Richardson, Craig A. Harms, Bruno, Grassi, and Russell T. Hepple
Department of Medicine, University of California, San Diego, La Jolla, CA; Department of Kinesiology, Kansas State University, Manhatten, KS; and Istituto di Tecnologie Biomediche Avanzate, National Research Council, Milano, ITALY.

From: Skeletal muscle: master or slave of the cardiovascular system?

RUSSELL S. RICHARDSON, CRAIG A. HARMS, BRUNO, GRASSI, and RUSSELL T. HEPPLE. Skeletal muscle: master or slave of the cardiovascular system? Med. Sci. Sports Exerc., Vol. 32, No. 1, pp. 89–93, 1999.

ABSTRACT 

Skeletal muscle and cardiovascular system responses to exercise are so closely entwined that it is often difficult to determine the effector from the affector. The purpose of this manuscript and its companion papers is to highlight (and perhaps assist in unraveling) the interdependency between skeletal muscle and the cardiovascular system in both chronic and acute exercise. Specifically, we elucidate four main areas: 1) how a finite cardiac output is allocated to a large and demanding mass of skeletal muscle, 2) whether maximal muscle oxygen uptake is determined peripherally or centrally, 3) whether blood flow or muscle metabolism set the kinetic response to the start of exercise, and 4) the matching of structural adaptations in muscle and the microcirculation in response to exercise. This manuscript, the product of an American College of Sports Medicine Symposium, unites the thoughts and findings of four researchers, each with different interests and perspectives, but with the common intent to better understand the interaction between oxygen supply and metabolic demand during exercise.

Key Words: GAS EXCHANGE KINETICS, BLOOD FLOW DISTRIBUTION, LACTIC ACID, INTRACELLULAR PO2, CARDIAC OUTPUT, MUSCLE PLASTICITY, V˙O2MAX

Although recognizing the numerous physiological systems and the many interactions during exercise, still perhaps the most significant interplay is between the cardiorespiratory system and skeletal muscle, which determines both O2 supply and demand (Fig. 1). At the beginning of exercise, the integrated response of the pulmonary, cardiovascular, and muscular systems characterize the V˙O2 on-kinetics. This kinetic response is highly sensitive to aerobic training (31) and can be measured both at the mouth and across a muscle (10). However, the role that each system plays in determining the V˙O2 on-kinetics continues to be the subject of considerable debate (4,18).

Beyond this transitional period, we encounter the issue of blood flow distribution, which is the appropriate distribution of a finite cardiac output among essential organs such as the brain, heart, intestines (48), and the metabolically very active skeletal muscle involved in the exercise (32). Which area of demand takes precedence as the metabolic requirements increase and the limits of cardiac output are approached (11)? The introduction of isolated skeletal muscle models (2,51) has highlighted this issue of skeletal muscle perfusion under conditions of maximal cardiac output versus a small muscle mass where central components are less taxed, allowing a greater level of skeletal muscle perfusion to be achieved (41,47). Additionally, these skeletal muscle models have proved fruitful in another long standing area of study: the determinants of maximal metabolic rate (V˙O2max), specifically whether V˙O2max is governed by O2 supply or O2 demand (35,43). Finally, the study of the structural interface between the cardiovascular system and skeletal muscle can be a powerful approach to elucidating the interplay between these two systems. It can be experimentally demonstrated that O2 conductance from blood to muscle cell plays an important role in determining V˙ O2max (37,52), suggestive of a passive role played by the muscle itself. However, when exposed to a repeated exercise stimulus, skeletal muscle now takes a very active role and demonstrates a remarkable plasticity (17) that positively affects exercise capacity (16).

Thus, here again the issue of who is the master and who the slave in the relationship between the cardiovascular system and skeletal muscle is open to debate.

Muscular Perfusion: Determined by Muscular Demand or Cardiovascular Supply?

The greatest demand for cardiac output during exercise is from skeletal muscle, as nearly 85% of total blood flow is directed to the working legs during maximal cycle ergometry (20,32). Several investigations have examined how different groups of skeletal muscle compete for the cardiac output during exercise and whether a “steal” phenomenon exists. Although Secher et al. (50) observed a decrease in leg blood flow when arm exercise was added to two legged cycle ergometry, more recent investigations have failed to corroborate these findings (36,44,49). However, the majority of data suggest that some degree of leg vasoconstriction or an attempt to vasoconstrict, as determined from norepinephrine spillover, occurs when arm exercise is added to leg exercise (44,49). Recently, a set of experiments have been conducted to determine whether a different group of skeletal muscles, those associated with breathing, influence cardiac output and its distribution during maximal exercise (11–13,56). These reports have demonstrated that respiratory muscles demand a significant portion of the cardiac output, primarily through stroke volume and total V˙O2, approximating 14–16% of the total (12). Additionally, it was shown that during heavy exercise, this metabolic demand from the respiratory muscles affects the distribution of cardiac output between the respiratory muscles and the legs such that leg vascular conductance and blood flow increases with respiratory muscle unloading and decreases with respiratory loading (11). Exercise performance may also be affected by the work of breathing during heavy exercise due to redistribution of blood flow between the chest wall and the locomotor muscles (56). Therefore, it appears that, in contrast to arm versus leg exercise, respiratory muscle work normally encountered during maximal exercise significantly influences cardiac output and its distribution.

V˙O2max: Governed by Oxygen Supply or Demand?

It has now been repeatedly demonstrated that an increase in O2 delivery can increase V˙O2max (1,3,5,21,30,34,38,43,55), which suggests that O2 supply limitation exists. As the isolated human quadriceps exercise does not approach the upper limits of cardiac output, this exercise paradigm has previously unveiled a skeletal muscle metabolic reserve and results in the highest mass specific V˙O2 and work rates recorded in man (37,41,46). This observation in of itself is evidence of O2 supply limitation of muscle V˙O2max. In a recent human knee-extensor study, the V˙O2max increased with an elevated O2 delivery (hyperoxia) demonstrating that in normoxic conditions even in the highly perfused isolated quadriceps, muscle V˙O2max is not limited by mitochondrial metabolic rate, but rather by O2 supply (35).

Although it is clear that in many scenarios an increase in O2 delivery can increase V˙O2max, it has also been demonstrated that this is not the sole determinant; in fact, the interaction between the convective and diffusive components of O2 transport may ultimately set the maximal metabolic rate (52). In the isolated canine gastrocnemius preparation, infusion of the allosteric modifier of hemoglobin RSR13 (Allos Therapeutics, Denver, CO) significantly increased P50, and at a constant arterial O2 delivery resulted in an increase in O2 extraction and a consequent increase in muscle V˙O2max (43). This indicates, for the first time, that the canine gastrocnemius muscle is normally O2 supply-limited, even when the animal is breathing 100% O2. In addition, the increase inV˙ O2max was proportional to the increase in venous PO2. Taken together, these findings support the concept that the diffusion of O2 between the red cell and the mitochondria plays a role in determining V˙O2max.

The insinuation that the production of lactate with progressively intense muscular work is evidence of inadequate intramuscular oxygenation has been long lived (15). Since then, the term “anaerobic threshold” has been used to describe the point at which lactate begins to accumulate in the blood, thought to indicate the inadequacy of O2 supply for the metabolic demand (54). Magnetic resonance spectroscopy, utilizing myoglobin as an endogenous probe of intracellular PO2 (29,53), in combination with the isolated human quadriceps model (38) has revealed that in hypoxic or normoxic exercise conditions net muscle lactate efflux is independent of intracellular PO2. The former increases whereas the latter remains constant during progressive incremental exercise (39). However, in hypoxia intracellular PO2 is systematically decreased in comparison to normoxia, whereas the changes in intracellular pH and muscle lactate efflux are accelerated. Whereas the latter observations indicate that a role for intracellular PO2 as a modulator of metabolism cannot be ruled out, arterial epinephrine levels are closely related to skeletal muscle lactate efflux in both normoxia and hypoxia and thus may be a major stimulus for the observed rise in muscle lactate efflux during progressively intense exercise and for the elevated lactate efflux in hypoxia. We would postulate that it is systemic and not intracellular PO2 that increases catecholamine responses in hypoxia and is therefore responsible for the correspondingly higher net lactate efflux (39).

Recently, evidence supporting the importance of intracellular PO2 in determining skeletal muscle V˙O2max has come to light (38). Studies of intracellular PO2 in trained human skeletal muscle with varied FIO2 suggest that in hyperoxia there is the expected rise in intracellular PO2 (due to increased mean capillary PO2), but this elevated O2 availability is now in excess of mitochondrial capacity (40). Indicating that intracellular PO2 is a determinant of V˙O2max in each FIO2 (12, 21, and 100% O2) but that in the latter case the increased intracellular PO2 results in diminishing returns with respect to an increase in V˙O2max. These observations are consistent with cellular metabolism that is moving toward a transition between O2 supply and O2 demand as a determinant of V˙O2max. It seems that further increases in intracellular PO2, beyond those recorded in hyperoxia, may have smaller effects upon V˙O2max until a plateau is reached and V˙O2max becomes invariant with intracellular PO2. From this point, intracellular PO2 may no longer be a determinant of skeletal muscle V˙O2max. This hyperbolic relationship, perhaps stemming from the origin, between intracellular O2 tension and cellular respiration is similar to data previously presented by Wilson et al. (57) in which the metabolic rate of isolated kidney cells was demonstrated to be O2 supply dependent below a certain O2 availability. Again, these myoglobin-associated PO2 data fit with the supply dependence of V˙O2max in healthy exercise trained human skeletal muscle (35,37).

V˙O2 On-Kinetics: Set by Blood Flow or Muscle Metabolism?

Upon a step transition from rest to exercise, or from a lower to higher workload, O2 uptake (V˙O2) lags behind the power output increase, following a time course usually termed V˙O2 on-kinetics. The mechanism(s) determining this kinetic response has been a matter of considerable debate between those who consider it mainly related to the rate of adjustment of O2 delivery to the exercising muscles and those supporting the concept that the V˙O2 on-kinetics is mainly set by an inertia of intramuscular oxidative metabolism.

In recent years, experiments in both exercising humans (9,10) and in the isolated in situ dog gastrocnemius preparation (7,8) have provided evidence in favor of the “metabolic inertia” hypothesis. Specifically, the transition from unloaded-to-loaded pedalling (below the “ventilatory threshold”) was studied in humans. 

Blood flow to one of the exercising limbs was determined continuously by a modified constant-infusion thermodilution technique, andV˙O2 across the limb was determined every ;5s by the Fick principle. Leg blood flow rose rapidly upon the change in work intensity, whereas arteriovenous O2 concentration difference across the limb did not increase during the first 10–15 s of the transition (10). During this type of metabolic transition, therefore, muscle O2 utilization kinetics lag behind the kinetics of bulk O2 delivery to muscle.

Heart transplant recipients show a slower V˙O2 on-kinetics compared with healthy controls. This slower V˙O2 onkinetics may be attributed to a slower adjustment of heart rate, cardiac output, and O2 delivery to muscles. In a group of heart transplant recipients, a “warm-up” exercise, performed before a rest-to-50-W transition, resulted in a slightly faster adjustment of cardiac output and more favourable conditions as far as O2 delivery to exercising muscles but did not speed up the V˙ O2 on-kinetics (9). Again, indicative of the lag in O2 uptake originating in the muscle itself.

By utilizing the isolated in situ dog gastrocnemius preparation, the metabolic transition from rest-to-electrically stimulated tetanic contractions corresponding to ;70% of V˙O2max was studied (7). The delay in the adjustment of convective O2 delivery to muscle was completely eliminated by pump-perfusing the muscle, at rest and during contractions, at a constant level of blood flow corresponding to the steady state value obtained during contractions in preliminary trials conducted with spontaneous adjustment of muscle blood flow (muscle perfused via the contralateral femoral artery). Adenosine was infused intra-arterially to prevent any vasoconstriction associated with the elevated muscle blood flow. Elimination of delay in convective O2 delivery did not affect muscle V˙O2 on-kinetics, which was not different to that observed in control conditions (7).

Finally, another study was conducted on the isolated in situ dog gastrocnemius preparation, during the same metabolic transition described above. Peripheral O2 diffusion was enhanced by having the dogs breathe a hyperoxic gas mixture and by the administration of RSR 13 (Allos Therapeutics), which right-shifts the oxy-hemoglobin dissociation curve. Mean capillary PO2 (PcapO2) was estimated by numerical integration. Hyperoxic breathing and RSR 13 significantly increased PcapO2 (i.e., the driving force for peripheral O2 diffusion) at rest and during contractions but did not affect muscle V˙O2 on-kinetics (8). Taken together, the results of this study and the previous one indicate that, in this experimental model, neither convective nor diffusive O2 delivery to muscle fibers affects muscleV˙ O2 on-kinetics, supporting the hypothesis that the latter is mainly set by an inertia of muscle oxidative metabolism. These conclusions appear in agreement with observations obtained by other authors in humans during step transitions to workloads lower than the “ventilatory threshold” (6,24). It should be noted, however, that these authors indicate that during step transitions to workloads higher than the “ventilatory threshold” the kinetics of O2 delivery to muscle appears to be a critical factor in determining the V˙O2 on-kinetics.

Plasticity of Skeletal Muscle: Microcirculatory Adaptation to Metabolic Demand?

The issue of whether skeletal muscle is master or slave of the cardiovascular system depends on frame of reference. Although acute manipulations of convective O2 delivery clearly show that O2 supply sets the upper limit of mitochondrial respiratory rate (42), interspecies comparisons (23) and study of adaptation to chronic conditions such as physical training show that capillarization (14,19) and mitochondrial development (28,45) are key components of the adaptive response in systemic V˙O2max. In addition, adaptations in the structural capacity for aerobic metabolism in skeletal muscle are closely regulated (e.g., close matching of capillary supply and fiber mitochondrial content) (26,33) and are maintained in proportion to the aerobic capacity of the whole organism (17). The study of adaptive variation in skeletal muscle structure within and between species has revealed design features that are uniform throughout muscles of widely varying metabolic demand. One of these features is that the size of the capillaryto- fiber interface rather than diffusion distance relates most closely to the structural capacity for O2 flux into muscle fibers (27). Recent studies have also shown that the size of the capillary-to-fiber interface is matched to mitochondrial volume/ fiber length with adaptation to training (33), electrical stimulation (26), and chronic hypoxia (25). These observations suggest another regulated design feature in skeletal muscle is matching the structural capacity for O2 flux to fiber metabolic demand (33).

Changes in capillarization and fiber mitochondrial content are important parts of the adaptive response to exercise training. In older humans, both high-intensity resistance training and aerobic training increase the size of the capillary-to-fiber interface (14). Furthermore, the change in V˙O2max is related to changes in the size of the capillary-to-fiber interface rather than capillary density, suggesting an increase in the structural capacity for O2 flux is an important feature of the adaptation in V˙O2max with both modes of training in this population (14).

Similarly, mitochondrial electron transport chain (ETC) capacity appears important to muscle V˙O2max. Poisoning of complex III (NADH-cytochrome c reductase) of the ETC results in a stepwise reduction in peak muscle O2 (27) and reduces peak muscle V˙O2 to pretraining levels in trained rat hindlimb muscle (45). It is noteworthy that this occurs even when muscle metabolism, blood flow, and convective O2 delivery are markedly lower than seen during maximal exercise in vivo (22).

In conclusion, there appears to be a paradox between the well-known increase in V˙O2max that occurs with increased O2 delivery and the proportional alterations in V˙O2max that accompany manipulations in mitochondrial oxidative capacity at submaximal O2 delivery and submaximal metabolic demand.

This, in conjunction with the observation that adaptation in skeletal muscle structural capacity for O2 flux (e.g., increased capillarization and fiber mitochondrial content) occurs in response to alterations in metabolic demand through exercise training and chronic hypoxia, supports an independent role of skeletal muscle in determining systemic V˙O2max.

SUMMARY

It is clear that both on a functional and structural level the response of the cardiovascular system and skeletal muscle are closely linked. Here we have addressed the issue of which of these systems is dominant and which more submissive.

Although we offer insight to this question, perhaps the most striking observation is that a single answer would not be appropriate as the role of each system appears to be highly dependent upon a multitude of factors that together create the scenario under investigation. A change in one of these variables, for example, acute exercise becoming chronic exercise, will markedly alter the relationship between the cardiovascular system and skeletal muscle and change the answer to the question of control.

Funding was provided by NIH 17731, RR02305, and HL-15469, and Dr. Richardson and Dr. Harms were supported by Parker B. Francis Fellowships in Pulmonary Research.
Address for correspondence: Russell S. Richardson, Ph.D., Department of Medicine, University of California, San Diego, La Jolla, CA 90293-0623. E-mail: rrichardson@ucsd.edu.

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Sunday
Sep182011

Elite Rowing: Maintaining Maximum Condition

By: Dr Richard Godfrey and Greg Whyte
From: Elite Rowing: Maintaining Maximum Condition
 

Dr Richard Godfrey is a Senior Research Lecturer at Brunel University and has previously spent 12 years working as a chief physiologist for the British Olympic Association

Greg Whyte FACSM is director of science and research at the English Institute of Sport


Life at the top – how are elite rowers tested and monitored?

Elite rowers subject their bodies to incredibly high levels of physiological stress. So what kind of testing and monitoring is needed to maintain maximum condition during rowing training without complete breakdown? Richard Godfrey and Greg Whyte explain. 

Olympic rowing events are conducted over a 2,000m course. The event lasts about 320 seconds (s) to 460s, depending upon the number of rowers in the boat and upon competition classification eg heavyweight (now more commonly referred to as ‘open weight’), lightweight, men or women, sculling or rowing. Furthermore, performance, as measured on the water, also depends on external factors, including the environmental conditions ie water temperature, wind speed and direction, and air temperature.
 
The advent of rowing ergometers has facilitated training by providing a controllable and repeatable tool in the assessment of rowing performance. Performance over 2,000m on a rowing ergometer is dependent upon the functional capacity of both the aerobic and anaerobic energy pathways, with the relative amount of energy derived from anaerobic metabolism being 21-30%(1).
 
The study of physiological characteristics of rowers has revealed that power at VO2max, VO2 at lactate threshold (LT), maximum power production and power at a blood lactate of 4mmol.L-1 are the most important predictors of 2,000m rowing ergometer performance in elite rowers(2). (The use of power output at 4mmol·L-1 blood lactate level has been used by a number of coaches and is widely agreed to be important predictor of performance.) However, of the measures listed it is generally agreed that power at VO2max is the strongest aerobic correlate of performance (a finding similar to that seen for endurance running). 

Of the short-term maximal effort tests, maximum force and power production are the strongest correlates of rowing performance. Elite rowers sustain, on average, 77% of maximum power during a 2,000m time trial(1). Thus, if all other determinants remain the same, the greater the maximum power, the greater the average power and resultant speed.
 
The results of ‘off-water’ ergometer studies indicate the importance of higher intensity parameters (power at VO2max and maximum power) in rowing performance. Given this fact, it is perhaps surprising to note that most international teams utilise vast volumes of low intensity training for competition preparation(3). It must be remembered however that sub-maximal economy is important in underpinning power at VO2max, and thus the importance of training that is focused on improving economy and sub-maximal parameters should not be ignored. This type of training typically consists of a number of sessions per week dedicated to lactate threshold training, which has the dual advantage of improving submaximal economy, and improving the power output that can be sustained.

Weight and gender differences

There are significant performance differences between male and female and between heavyweight and lightweight rowers. On the ergometer, researchers have shown that male rowers were on average 7.7% faster than their female counterparts(2). Results from World Championships and World Cup single scull events, suggest that this difference is increased to 10.9% on-water (there are subtle relationships between technique and power delivery which make on-water rowing harder than ergometer rowing, but why the difference is greater between ergometer and on-water rowing in women is not known).
 
The difference between heavyweight and lightweight rowers was 5.5% on-ergometer compared to 4% on-water. While heavyweights are faster than lightweights, research suggests that any increase in body mass should be primarily composed of functional (lean) mass to effect a change in ergometer/boat speed. This is particularly true for lightweight rowers and requires the right combination of diet, rowing-specific ergometer and on-water work, coupled with weight training, which ensures the development of an appropriate functional mass.
 
In describing the physiological components that are necessary for good rowing performance it must be remembered that anthropometric (ie height, limb length), technical (ie stroke length, stroke rate) and psychological factors are also crucial elements of that performance. Assessing the physiological aspects of performance is important in the profiling of athletes, as this allows the design of better training programmes, which in turn improves adaptation.
 
The physiological assessment of the rower should aim to test the range of physiological requirements of rowing performance, both aerobic and anaerobic. The following section outlines the range of tests employed by physiologists to assess elite rowers in laboratory and field (on-water or on ergometers in the boathouse or gym) settings. 

Laboratory testing for rowers

Rowing is a strength-endurance sport with a large aerobic component. A number of endurance sports have been proposed as the ‘most aerobic’, including cross-country skiing and running. But when scaling is used (that is a mathematical technique to allow individuals of different sizes and weights to be compared) then heavyweight rowers come out on top (4,5).
 
Heavyweight rowers are large individuals with an average height of 1.93m and average weight of 93kg. Although their body fat values tend to be slightly higher than their lightweight team-mates, they still carry considerable muscle mass.
 
Elite rowers require the ability to generate moderate to high forces and sustain efforts for six minutes (the average time to complete 2,000m in competition at World Championships or Olympic games). Physiology support in the laboratory is therefore designed to examine the current conditioned state of the individual with respect to body composition, muscle power and force, aerobic power and sustainable percentage of maximal aerobic power.
 
Body composition testing is particularly important for lightweight rowers because they cannot afford to be carrying excess ‘non-functional’ weight (ie body fat).
As mentioned previously, it is important to measure maximal aerobic power (VO2max) and the percentage of maximal aerobic power that can be sustained. To do this the discontinuous incremental protocol (commonly referred to as a ‘step-test to max’ and shown in figure 1) is the usual test used.
 
In the lab, testing occurs on a Concept 2 Model C rowing ergometer, the kind of rowing machine found in most health clubs. There is a difference however, as (unlike the standard rowers) the lab ergometer is also fitted with a special force transducer at the handle, so that the force produced by the rower can be directly and very accurately measured.
 
On this equipment, a test is first carried out to examine strength and power. Before the test begins the rower performs a 10-minute warm-up followed by some light stretching. A specific warm-up is then completed using hard efforts of two, three, and four strokes prior to starting the test. For the test itself, the rower is instructed to carry out seven strokes as hard as possible at a rate of 30 strokes per minute. From this test, work (in joules), mean force (in newtons), mean power (in watts), stroke rate (strokes per minute, spm) and stroke length (in metres) are reported from the last five strokes.
 
Elite rowers are often asked to perform 2,000m time trials on the ergometer in training, and so will have a recent 2,000m time. If a young rower visits the lab for the first time it can be difficult to know what intensity to start the step test at. However, a means of determining this has been devised.
 
The time for 2,000m should be converted into a 500m split time. For heavyweight men and women add 15 seconds to this time and you have the split for the third stage of the step-test. For the power output that equates to the time for stage 3, subtract 25 watts to get the power output (and split time) for stage 2 and subtract 50 watts for stage 1. For stage 4 add 25 watts and for stage 5 add 50 watts. For lightweight men and women, also add 15 seconds to the calculated 500m split time to find the split for the third stage. However, it may be more appropriate to use 15-20 watt increments (rather than a 25 watt increment) to calculate subsequent stage workloads(5).
 
During the step test the rower wears a heart rate monitor and a mouthpiece for collection and analysis of expired air, and every four minutes the rower stops to have an earlobe blood sample taken for blood lactate analysis.
 
The heart rate associated with LT can be used to determine a number of heart rate zones that can be used for training, and, after a few weeks, improvements in endurance are detected as a rightward shift of the lactate curve.
 
For the final stage of testing, the individual is asked to cover the furthest distance possible (at a relatively even pace) in four minutes. Traditionally, laboratory-based blood lactate measuring equipment such as Analox, Yellow Springs or Eppendorf lactate analysers have been preferred, as their validity and reliability has been tested and is well known. Although it is possible to use new ‘palm top’ lactate analysers, their validity and reliability continue to be questioned.
 
The data collected and calculated from the step test includes VO2max, power at VO2max, the percentage of maximum that can be sustained (ie at lactate threshold as a percentage of VO2max), power at LT and power at reference blood lactate vales of 2 and 4mmol.L-1

Field-testing for rowers

Many elite sports routinely enjoy a physiology support programme and hence, coaches and athletes have greater experience of sports science. As a result, coaches in many sports are increasingly demanding that field-based testing replace laboratory-based testing. However, coaches and athletes rarely have the training and experience of professional sports scientists and, while many physiologists are not averse to an increase in the use of field-testing, it is very difficult to justify the elimination of laboratory-based testing altogether.
 
Laboratory-based testing provides an objective set of data collected under standardised conditions(5). This level of standardisation and objectivity could never be achieved in the field. However, field-based data has greater sports specificity, something which is very difficult, or is impossible, to achieve in a laboratory-based simulation of the sport. Accordingly, GB elite rowers are still lab tested two to three times per year with 4-5 field-based (step-test) sessions. To supplement this, the coach also carries out some performance tests such as, 18km, 30minute, 2km or 250m rows. On some occasions blood samples can be taken (by a physiologist) at the end of such rows, or the 18km row can be broken into 3 x 6km rows with a 30-60 second rest interval for blood samples to be taken.
 
At field camps overseas, early morning monitoring is routinely carried out prior to daily training. This involves the measurement of urine concentration to monitor hydration status, blood urea, body mass and resting heart rate to examine how the athlete is coping with the physical stress of exposure to a new, often extreme, environment, coupled with normal training. All of these measures are viewed in combination with a psychological inventory and some discussion with the coach and athlete. As a result, the coach decides on whether any modification of training is required for certain individuals as a consequence of this plus on-water and gym-based data.

Altitude camps

Originating in Eastern Europe, the use of altitude training camps in rowing has become commonplace. Elite rowers may ascend to altitude for training camps lasting up to 3 weeks on as many as three occasions per year. Altitude results in a lower availability of oxygen to the working muscles, due to lower barometric pressures, and this reduced availability of oxygen results in an increased physiological stress both at rest and during exercise.
 
The primary purpose of altitude training is to capitalise on the adaptations associated with this increased physiological stress, which is suggested to increase red cell mass and haemoglobin concentration and hence, increase oxygen carrying capacity.
 
Unfortunately, these adaptations come at a price; altitude has a number of undesirable effects that can affect the health and performance of the rower including; sleep disturbance, dehydration, glycogen depletion, immune suppression and an increased incidence of illness including upper respiratory tract infections and gastrointestinal upsets. Altitude training can even lead to a reduction in performance due to a relative deconditioning associated with an enforced lowering of training intensity(6).
 
It is for these reasons that monitoring rowers at altitude is crucial to optimise the beneficial effects and reduce the adverse effects of low oxygen availability. Physiological monitoring of the rower at altitude is based upon assessing sleep quality, recovery, hydration and training intensities. Recent advances in the simulation of high altitude environments at sea level by reducing partial oxygen pressure (ie reduced O2 concentration) in chambers, tents and face masks has led to new opportunities in the use of hypoxia (low oxygen) for training and competition(6).

Summary

The functional capacities of the aerobic and anaerobic energy systems are important in 2,000m rowing, and performance and power at VO2max, VO2 at lactate threshold, power at a blood lactate of 4mmol.L-1 and maximum power production are the most important predictors of 2,000m rowing ergometer performance in elite rowers. Laboratory-based testing is centred on step and maximum power tests and body composition assessment, while field-testing includes ‘on-water’ tests such as 18km, 30minute, 2km or 250m rows and lactate measurement following set pieces.
 


Thursday
Sep152011

Training Methods and Intensity Distribution of Young World Class Rowers 

By Arne Guellich (1), Stephen Seiler (2), and Eike Emrich (3)
1 Department of Sports Sciences, University of Kaiserslautern, GERMANY
2 Faculty of Health and Sport, University of Agder, Kristiansand, NORWAY
3 Institute of Sports Sciences, University of the Saarland, Saarbruecken, GERMANY

From: International Journal of Sports Physiology and Performance, 2009, 4, 448-460


Abstract

Purpose: To describe the distribution of exercise types and rowing intensity in successful junior rowers and its relation to later senior success. Methods: 36 young German male rowers (31 international, 5 national junior finalists, 19.2 ± 1.4 yr, 10.9 ± 1.6 training sessions.wk-1) reported the volumes of defined exercise and intensity categories in a diary over 37 weeks. Training categories were analysed as aggregates over the whole season and also broken down to defined training periods. Training organisation was compared between juniors who attained national and international senior success three years later. Results: Total training time consisted of 52% rowing, 23% resistance exercise, 17% alternative training, and 8% warm-up programs. Based on heart rate control, 95% of total rowing was performed at intensities corresponding to <2 mmol.L-1, 2% at 2-4 mmol.L-1, and 3% at >4 mmol.L-1 blood lactate. Low-intensity work remained widely unchanged at ~95% throughout the season. In the competition period the athletes exhibited a shift within <2mmol-exercise towards lower intensity and within the remaining ~5% of total rowing towards more training near maximal oxygen consumption (VO2max) intensity. Retrospectively, among subjects going on to international success three years later had their training differed significantly from their peers only in slightly higher volumes at both margins of the intensity scope. Conclusion: The young world-class rowers monitored here exhibit a constant emphasis on low intensity steady-state rowing exercise, and a progressive polarization in the competition period. Possible mechanisms underlying a potential association between intensity polarization and later success require further investigation. 

Keywords: high performance, training analysis, intensity distribution, endurance, rowing

Introduction

Elite endurance athletes subject themselves to very high training loads in pursuit of maximal performance. For example, world class senior rowers compete over a 2000m distance requiring ~6-7 minutes; yet invest a training volume in a season equivalent to many hours for each minute of an international competition. A key question that occupies the minds of athletes and coaches is how best to utilize this training investment. For numerous reasons, systematic intervention for research purposes is constrained in elite sport and experimental studies are lacking to identify any “optimal” training organization for maximizing both physiological and technical adaptations. We contend that the international competition environment is a quite effective experimental arena, in a Darwinistic sense. Extreme performance standards stimulate the emergence of self-organizing processes where athletes, national teams, and governing bodies pursue the training structure which gives the most consistent success. This process together with inter- and intra-individual method iteration, evaluation, and adjustments presumably drives changes in training over time that correspond with continued performance improvements. For example, one of the major changes in the training evolution of international medal winning Norwegian rowers over three decades was an increase in total training volume associated with a substantial shift in intensity distribution from higher to lower intensities.2 Accurate descriptions of the training characteristics of highly successful athlete groups have value in furthering our knowledge about performance improvement in endurance sport and catalyzing experimental studies.

Also, within an elite athlete generation fairly small improvements in performance may be critical to success. Top performers approximate the margin of individual load tolerance in training, and minor variation in the balance of beneficial adaptation and maladaptive load-related stress reaction may account for critical differences in performance development. The day-to-day and seasonal distribution of training intensity appears to be a crucial variable in training organization for endurance athletes. Following the 3-intensity zone structure representing exercise intensity below the first ventilatory threshold (VT1; where the ventilatory equivalent for O2 breaks from linearity, without an increase in the ventilatory equivalent for CO2; typically < 2 mmol.L-1 blood lactate), from VT1 to VT2 (where the ventilatory equivalent for CO2 also begins to increase; ~2-4 mmol.L-1), and above VT2 (> 4 mmol.L-1),3-5 it has previously been proposed that two basic intensity distribution patterns emerge from the research literature.5,6 The “threshold training model” emerges from some short-termed studies demonstrating that training at the lactate threshold intensity evokes significant physiological improvements among untrained subjects.7-10 A contrasting “polarized training model” has been proposed based on observations from a number of studies describing the distribution of work intensity among elite athletes in marathon running, rowing, track cycling, and cross-country skiing.2, 5,11-16 One consistent observation from these studies is that successful endurance athletes perform 75% or more of their training (sessions, distance, time) at intensities below VT1. In addition, about 10 to 20% of training volume is reported to be clearly above VT2, (i.e. 6-10 mmol.L-1 blood lactate).2,5,11,15,17 Consequently, remarkably little training is executed at the traditional lactate threshold. Thus, the training is apparently “polarized away” from the work range characterised by moderately hard intensity. If training intensity distribution is critical for optimal performance, we might expect to see quantifiable differences in organization between highly successful and less successful athletes with similar performance potential.

Recent longitudinal observations in quasi-experimental post-hoc and experimental designs support the value of low intensity training in achieving desired physiological adaptations and performance enhancement.3,4,18,19

In the present study we extend these findings by reporting 1) a detailed description of the distribution of the exercise types and of the intensity distribution within the specific rowing workout, 2) their alteration over a complete training season from autumn until summer in a large group of internationally successful junior age rowers, and 3) a comparison of the training characteristics of the junior rowers who reached international senior finals three years later to those who did not attain this success level.

Methods

Study Design

The present study builds on the complete reported daily training data provided by 36 athletes from the men’s German junior national rowing squad. This study was approved by the German Federal Institute of Sports Science including the subjects’ informed, written consent for their training data to be used for research purposes.

All national squad members were requested to document their executed daily individual training in a standardized digital training diary and submit it to the national coach. Individual heart rate (HR) ranges for defined intensity categories in training were determined during a centralized rowing ergometer ramp protocol (Concept CIIC; 3 min stages, 20 W steps) in the first week of each training year. In addition, rowing power (watts) at 4 mmol.L-1 venous blood lactate (PLa4) was calculated from the blood lactate/rowing ergometer power relationship. The national rowing governing body did not perform standardized, centralized VO2 max testing on junior rowers. Therefore information regarding the maximal oxygen consumption of these athletes is not available. Individual heart-rate ranges were prescribed for each of the rowing intensity categories based on the stable blood lactate-heart rate relationship determined during ramp protocol rowing ergometry performed at the beginning of the training season.23 Heart rate was controlled during all rowing sessions via online HR-monitoring (Polar, Kempele, Finland).

Training monitoring

Prior to the training, athletes were briefed as to the desired training composition by the coach and provided a reporting scheme. Training was categorized as defined by the national federation (see Table 1). The training data reported here represents the executed, not the planned training for a complete training season (37 weeks, t1). In addition competitive senior success for the entire sample was followed up 3 years later (t2).

The intensity definitions used for training documentation closely correspond to the physiological 3-zone model used in a previous study of rowing intensity distribution.2 The categories Compensation and Extensive Endurance (<80% race pace; HR <160 b.min-1; [La-] <2 mmol.L-1; Table 1) correspond with work below VT1 (“zone 1”). Intensive Endurance (75-85% race pace; HR 156-168 b.min-1; [La-] 2-4 mmol.L-1) corresponds with work intensity between VT1 and VT2 (“zone 2”). The categories Highly Intensive Endurance, Race-Specific Velocity-Endurance, and Velocity Training (85-112% race pace; HR >180 b.min-1; [La-] >4 mmol.L-1) correspond with work intensity above VT2 (“zone 3”). This three intensity zone scheme has been previously described and used in both experimental and descriptive studies of endurance exercise intensity distribution.5,20-22

Training was recorded from the beginning of the training season (15th October) until the national trials for the junior world championships (30th June; 37 weeks in total). The 37 weeks were divided into 3 training periods: basic preparation period (BPP) 1st to 15th training week, specific preparation period (SPP) 16th to 25th week, and (early) competition period (CP) 26th to 37th training week. SPP culminated in the national small-boat championship regatta which is obligatory for all squad members. The CP recording concluded with the national trials.

To evaluate the reliability of athletes’ training documentation, diary figures reported to the national coach were compared to data reported directly to our research group (as “neutral” addressees) by 29 athletes participating in an anonymous postal survey after the referred season. Subjects were re-identified for this analysis based on birth date and success. The data from the training diary and from the postal survey correlated with r=0.88 (training frequency; p<0.01) and r=0.84 (training time; p<0.01). The diary figures deviated from those in the postal survey by 4.0 ± 8.5% in training frequency and –10.4 ± 12.3% in expended training time. No systematic relation between this deviation and performance achievement was observed (p>0.05, in each case).

Senior Success

The 36 athletes in this study continued rowing at a high level. We therefore retrospectively compared the junior training characteristics of 14 athletes who reached senior world championships and/or Olympic finals three years after the junior training registration period with the 22 who attained success ‘only’ at national level within the same period.

Statistical Analysis

All statistical analyses were performed using SPSS version 14.0. Physical, physiological, and training characteristics are presented as means and standard deviations. Training intensity distribution and other training characteristics were compared across the three defined training periods using Repeated Measures ANOVA. Comparison of the junior age training characteristics of internationally successful and less successful senior rowers was performed using Independent Samples T-tests. A p value of < 0.05 was considered statistically significant.

Results

All 36 athletes remained members of the national junior squad throughout the observed training period (2001; t1) and became finalists at the national junior championships. Of these, 31 also reached the finals at the junior world championships, 27 attained a medal, and 15 became junior world champion. The athletes were 19.2 ± 1.4 years, 91.0 ± 6.0 kg and 193.3 ± 5.3 cm at t1. They performed a mean of 10.9 ± 1.6 training sessions and 12.8 ± 2.5 hours of (net) training time per week. Their PLa4 value during rowing ergometry ramp protocol at the beginning of the training season was 373 ± 29 W. Three years after the training registration season (t2), all 36 athletes were finalists at the national senior championships. Of these, 14 reached the finals at the Olympic Games (Athens 2004) and/or senior world championships, nine won medals.

Rowing specific activities made up 52% of total junior training time (Table 2). The remaining training time was devoted to resistance exercise (23%), general athletic training like jogging, strengthening gymnastics, and game play (17%), and warm-up programs (8%). Strength training was dominated by “power endurance” training with high repetitions performed with moderate loads (76%). The overall distribution of rowing specific training intensity is also provided in Table 2. Interestingly, ~95% of rowing specific training was performed at intensities corresponding to < 2 mmol.L-1 blood lactate (below VT1, zone 1; Compensation and Extensive Endurance range).

Weekly training frequency increased from 10.3 ± 2.5 in the Basic Preparation Period (BPP) to 11.3 ± 1.7 in the Specific Preparation Period (SPP; p<0.01) and was reduced again to 10.6 ± 1.8 sessions.wk-1 in the (early) Competition Period (CP; p<0.01). Figure 1 shows an approximate doubling in rowing specific training volume from BPP to CP. This doubling was achieved via both an increase in total training volume and a decrease in strength training and alternative training. The relative contribution of low intensity (zone 1) work to total rowing training remained almost constant throughout the entire season, but the higher intensity work became significantly more intense (Figure 2). Low intensity zone 1 endurance training made up 96% of all rowing volume during the BPP and only decreased to 94% in the CP. During the CP, there was also a small but significant shift within zone 1 rowing represented by a lowered volume of Extensive Endurance range (BPP 89%, SPP 88%; p>0.05; CP 84%; p<0.01) and an increase in the amount of very low intensity Compensation range rowing performed (BPP 7.1%, SPP 6.5%; p>0.05; CP 10.1%; p<0.01). The remaining 4-6% of rowing training distance shifted first towards a transiently higher volume of the Intensive Endurance range (“zone 2” lactate threshold intensity work) from BPP to SPP and then towards an enhancement of the highest intensity ranges (“zone 3”) of Race-Specific Velocity-Endurance and Velocity during CP (Figure 2). While high intensity training remained a small percentage of total training volume throughout the season, the 141% increase of the share of total rowing at race pace or higher intensity from BPP to CP (p<0.01) represents an enhancement of the absolute distance rowed at this intensity range by about 3-fold.

 

 

Among 14 athletes who reached the finals at the Olympics and/or senior world championships three years after the training registration period (t2), and 22 who did not, 12 (86%) and 19 (86%), respectively, had reached the finals at the junior world championships (t1), 10 (71%) and 17 (77%) had medalled, and 5 (36%) and 10 (45%) had been junior world champion. The respective groups did not differ systematically in age (19.0 ± 1.3 and 19.4 ± 1.4 years; M ± SD), weight (91 ± 6 and 91 ± 6 kg), height (193 ± 5 and 193 ± 6 cm), or PLa4 (368 ± 28 and 376 ± 30 W) at t1 (all p>0.05).

Table 3 compares the junior-age training characteristics between internationally and nationally successful athletes. The rowers reaching international success as seniors did not differ systematically (p>0.05) as juniors in total training frequency or volume, distribution of expended training time, or their time distribution among different training modes. However, small but statistically significant differences were exhibited within the intensity distribution of their specific rowing endurance training. The international finalists completed more distance in both the lowest intensity Compensation range and the highest intensity Race-Specific Velocity-Endurance range.

Discussion

An underlying premise for describing the training organization of highly successful athletes is that they are successful, in part, because of how they train. In this context, we believe the most important finding in this study is that, based on time-in-zone heart rate monitoring, internationally successful junior rowers performed 95% of all specific rowing training over a 37 week training period in “zone 1,” at a heart rate corresponding to blood lactate concentration under 2 mmol.L-1. In comparison, the same time-in-zone, 3-intensity zone method applied to a group of well-trained, non-elite distance runners showed that 71% of their training was in zone 1, 21% in zone 2 and 8% in zone 3.3 Accepting that this well established intensity quantification method tends to overestimate time spent at low training intensity,5 these findings still demonstrate a marked emphasis on basic endurance training throughout the training season. In the present group of rowers, the remaining 4-6% of rowing specific training volume quantified at higher intensities, progression from the basic preparation period to the competition period was associated with a shift from emphasis on moderately high intensity “lactate threshold” training, towards more race pace intensity training at near maximal oxygen consumption (VO2max) intensity. That is, the intensity distribution became more polarized in the competition period.

This was a quite homogenous group of talented rowers who had reached national elite level in a very strong rowing nation. Their physique (mean 91 kg, 193 cm) clearly exceeded previously published descriptions of rowing finalists at junior world championships,24 consistent with the fact that 15 of the subjects in the sample became junior world champions during the season training data was collected. The range in performance between “more successful” and “less successful” athletes as defined here is very small. Also, this study did not compare effects of different training programs on performance and thus does not establish a causal relationship between intensity distribution and performance. It was an ex post facto analysis of common variation between characteristics of junior training and later senior success. Based on a 3-year follow-up analysis, the only significant difference in training volume or organization observed between the most successful and less successful rowers in this sample was a modest but significant increase in the degree of intensity polarization observed in the most successful athletes. Athletes who went on to senior international success had, as juniors, tended to perform slightly more of their total rowing endurance exercise at very low intensity and at very high intensity compared to their peers. We can only speculate what advantages this increase in intensity polarization might have provided. It might be that the increased polarization observed merely demonstrates a form of intensity management discipline (keeping hard training hard and easy training easy) among the most successful athletes that could prove protective against overstress.

The present findings are consistent with previous studies demonstrating that low intensity (below LT1 or VT1) training dominates the total training volume of successful endurance athletes in a variety of sports.2,11-16 However, the extreme emphasis on low intensity, steady state training seen in these elite junior rowers has not been reported in the research literature previously. The 2000 meter rowing distance requires ~6 minutes to complete in a large team boat and is performed at 100-110% of VO2 max intensity.25 Clearly this distribution violates conventional wisdom regarding training intensity specificity; these athletes train relatively little at competition intensity. Recently, Ingham and colleagues compared 12 weeks of training at low intensity only (98% of total training performed at <75% of VO2 peak) with a regimen of 70% low intensity and 30% high intensity training (>84% VO2 peak). They found that in the British national standard rowers involved, both training regimes gave similar improvements in VO2 max and rowing test performance, but that low intensity only training actually improved blood lactate responses at sub-maximal intensity to a greater extent.19 No indicators of overreaching were present in the mixed intensity training group, making it unclear why the mixed training model failed to induce a greater performance improvement.

One of us has previously concluded that elite endurance athletes in running, cycling, cross-country skiing, and rowing often perform surprisingly little of their total training at intensities typically described as lactate threshold training, but instead tend to polarize their training away from this moderate intensity, training both a great deal at below VT1 and a significant amount above VT2 intensity.22 The present descriptive study of internationally successful rowers, and the recent experimental study on rowers by Ingham and colleagues,19 both suggest that marked performance adaptations and very high level performances in rowing can be elicited with a regiment of training that is dominated by low intensity, high volume work, with relatively little race pace, high intensity training. These findings run contrary to accepted theories that substantial high intensity training is critical for optimizing centrally limited oxygen delivery capacity in endurance athletes.26,27

Anecdotally, the training intensity distribution reported here is not unique to German rowers, but is also observed in other highly successful international programs. We propose that there are several unique characteristics of rowing specifically, as well as the elite training process in general that may explain the training distribution employed.

Expansion of total training volume generally is achieved at the expense of the high intensity work proportion. High performance athletes expose themselves to voluminous training load, mostly involving multiple daily sessions, and they approximate (at least temporarily) the margin of what is tolerable. Athletes attempt to balance loads evoking maximal positive adaptations (gene expression, synthesis of mitochondrial and other relevant proteins, cardiovascular performance, buffering capacity, technical efficiency at near race velocity) while avoiding excessive sympathetic stress leading to overtraining. Consistent with the evolution of training organisation among international rowing medallists over recent decades and with reports from elite athletes in other endurance sports,2,11-16 achieving this balance apparently favors the selection of a training intensity distribution characterised by voluminous low-intensity rowing below the lactate threshold with only intermittent highly intensive bouts.

Rowing power is a function of mean stroke force and stroke frequency. In trained rowers, peak forces during a rowing stroke remain quite consistent across rowing frequency,28 with rowing stroke rate (i.e. duty cycle) being the primary intensity control variable. We might speculate from this that extensive training at low intensities remains effective in recruiting a large proportion of available motor units, and achieves the specific muscular adaptations necessary to row at high power outputs as well. Elite rowers may therefore gravitate towards training below the first ventilatory threshold in order to stabilize technical aspects of the rowing stroke while still achieving desired physiological adaptations and perhaps avoiding excessive stress reactions.22 It is also important to point out that although the relative percentage of high intensity rowing was low, during the competition period, these athletes were still performing ~20 minutes of rowing weekly at heart rates corresponding to high intensity. Because a heart rate based “time-in-zone” approach to intensity classification will tend to underestimate the actual time (and physiological stress) of rowing at high work intensity due to delays in heart rate responses, the actual high intensity work duration each week is perhaps 30 minutes or more.

Rowing also differs from endurance sports like running and cycling in that substantial volumes of non-rowing training are performed. While almost all training time may be movement specific among road cyclists and distance runners, little more than 50% of the total training time of these rowers was rowing. Traditionally, rowing training often incorporates a significant strength training component, which reduced the relative time spent on rowing specific training. Rowing ranged from 40% during the basic preparation phase to 65% of total training time during the early competition phase. Previously, it has been suggested that 70% of total training volume of rowers should be specific.29 However, the lower value reported here is consistent with the fact that junior rowers often do not have the same access to good on-water conditions during the late fall and winter. In contrast, elite senior rowers are more likely to live in or travel to locations affording year-around access to on-water training.

Because a large proportion of total training volume in these elite junior rowers was not rowing, it is worthwhile to consider the impact of this training on the overall training intensity distribution of the rowers. Heart rate was not monitored during non-rowing activities such as stretching, game play, and jogging, but they were always performed at low intensity according to coaches and therefore would likely contributed almost exclusively to the low intensity volume. Strength training made up 23% of total training time. It is likely that some strength training sessions induced transient periods where local muscle metabolic rates and muscle and blood lactate values were consistent with training in zone 2 or zone 3. The potential contribution of this training to power output and fatigue resistance at race pace in rowing is unclear.

We contend that the reported observations prompt further research on training intensity distribution with particular attention to highly selective samples of extraordinary performers. Future goals are 1) to describe training load in more detail, including physiological responses and 2) to examine the effects of varying intensity distributions on physiological capabilities and performance.

Acknowledgment

The authors wish to express their sincere thanks to Michael Mueller, performance director of the German Rowing Federation, and Dieter Altenburg, national junior coach, for fruitful cooperation and helpful suggestions in this project.

References

1. Hopkins WG, Hawley JA, Burke LM. Design and analysis of research on sport performance enhancement. Med. Sci. Sports Exerc. 1999: 31: 472–485.

2. Fiskerstrand A and Seiler KS. Training and performance characteristics among Norwegian International Rowers 1970-2001. Scand. J. Med. Sci. Sports 2004: 14: 303-310.

3. Esteve-Lanao J, San Juan AF, Earnest CP, Foster C, Lucía A. How do endurance runners actually train? Relationship with competition performance. Med. Sci. Sports Exerc. 2005 (37): 3: 496-504.

4. Esteve-Lanao J, Foster C, Seiler S, Lucía A. Impact of training intensity distribution on performance in endurance athletes. Journal of Strength and Conditioning Research 2007, 21(3), 943-949.

5. Seiler KS, Kjerland GØ. Quantifying training intensity distribution in elite endurance athletes: is there evidence for an ‘‘optimal’’ distribution? Scand. J. Med. Sci. Sports 2006: 16: 49-56.

6. Seiler S, Hetlelid K. The impact of rest duration on work intensity and RPE during interval training. Med. Sci. Sports Exerc. 2005: 37: 1601-1607.

7. Denis C, Dormois D, Lacour JR. Endurance training, VO2 max, and OBLA: a longitudinal study of two different age groups. Int. J. Sports Med. 1984: 5: 167–173.

8. Gaskill SE, Walker AJ, Serfass RA, Bouchard C, Gagnon J, Rao DC, Skinner JS, Wilmore JH, Leon AS. Changes in ventilatory threshold with exercise training in a sedentary population: the HERITAGE Family Study. Int. J. Sports Med. 2001: 22 (8): 586-92.

9. Kindermann W, Simon G, Keul J. The significance of the aerobic-anaerobic determination of work load intensities during endurance training. Eur. J. Appl. Physiol. 1979: 42: 25-34.

10. Londeree BR. Effect of training on lactate/ventilatory thresholds: a meta analysis. Med. Sci. Sports Exerc. 1997: 29: 837-843.

11. Billat VL, Demarle A, Slawinski J, Paiva M, Koralsztein JP. Physical and training characteristics of top-class marathon runners. Med. Sci. Sports Exerc. 2001: 33: 2089-2097.

12. Kellmann M, Altenburg D, Lormes W, Steinacker JM. Assessing stress and recovery during preparation for the World Championships in rowing. The Sports Psychologist 2001 (15): 151-167.

13. Schumacher YO, Müller P. The 4000-m team pursuit cycling world record: theoretical and practical aspects. Med. Sci. Sports Exerc. 2002: 34: 1029-1036.

14. Schumacher YO, Müller P, Keul J. Development of peak performance in track cycling. J. Sports Med. Phys. Fitness 2001 (41): 2: 139-146.

15. Steinacker JM, Lormes W, Lehmann M, Altenburg D. Training of rowers before world championships. Med. Sci. Sports Exerc. 1998: 30: 1158-1163.

16. Steinacker JM, Lormes W, Kellmann M, Liu Y, Reißnecker S, Opitz-Gress A, Baller B, Günther K, Petersen KG, Kallus KW, Lehmann M, Altenburg D. Training of junior rowers before world championships. Effects on performance, mood state, and selected hormonal and metabolic responses. J. Sports Med. Phys. Fitness 2000: 40: 327-335.

17. Billat V, Lepretre PM, Heugas AM, Laurence MH, Salim D, Koralsztein JP. Training and bioenergetic characteristics in elite male and female Kenyan runners. Med. Sci. Sports Exerc. 2003; 35(2):297-304.

18. Zapico AG, Calderón FJ, Benito PJ, Gonzáles CB, Parisi A, Pigozzi F, Di Salvo V. Evolution of physiological and haematological parameters with training load in elite male road cyclists: a longitudinal study. J. Sports Med. Phys. Fitness 2007 (47): 2: 191-196.

19. Ingham SA, Carter H, Whyte GP, Doust JH. Physiological and performance effects of low- versus mixed-intensity rowing training. Med. Sci. Sports Exerc. 2008; 40(3): 579-584.

20. Lucía A, Pardo J, Durantez A, Hoyos J, Chicharro JL. Physiological differences between professional and elite road cyclists. Int. J. Sports Med. 1998: 19: 342–348.

21. Lucía A, Hoyos J, Carvaljal A, Chicharro JL. Heart rate response to professional road racing: the Tour de France. Int. J. Sports Med. 1999: 20: 167–172.

22. Seiler S, Haugen O, Kuffel E. Autonomic recovery after exercise in trained athletes: Intensity and duration effects. Med. Sci. Sports Exerc. 2007 (39): 8: 1366-1373.

23. Foster C, Fitzgerald DJ, Spatz P. Stability of the blood lactate-heart rate relationship in competitive athletes. Med. Sci. Sports Exerc. 1999 (31): 4: 578-582.

24. Bourgois J, Claessens AL, Vrijens J, Philippaerts R, Renterghen BV, Thomis M, Janssens M, Loos R, Lefevre J. Anthropometric characteristics of elite male junior rowers. Br. J. Sports Med. 2000: 34: 213-216.

25. Hagerman FC. Applied physiology of rowing. Sports Med. 1984, 1 (4): 303-326.

26. Billat VL, Flechet B, Petit B, Muriaux G, Koralsztein JP. Interval training at VO2max: effects on aerobic performance and overtraining markers. Med. Sci. Sports Exerc. 1999: 31:156-163.

27. Laursen PB, Jenkins DG. The scientific basis for high-intensity interval training: optimising training programmes and maximising performance in highly trained endurance athletes. Sports Med. 2002; 32(1): 53-73.

28. McGregor AH, Bull AMJ, Byng-Maddick R. A comparison of rowing technique at different stroke rates: a description of sequencing, force production and kinematics. Int. J. Sports Med. 2004; 25: 465-470.

29. Mäestu J, Jürimäe J, Jürimäe T. Monitoring of performance and training in rowing. Sports Med. 2005; 35(7): 597-617.


Wednesday
Sep072011

Training The Energy Systems

By Dr. Fritz Hagerman

PDF link: Training the energy system.


Dr Fritz Hagerman: Background

Dr. Fritz Hagerman, a world-renowned expert in exercise physiology, has been educating and improving rowers and coaches for over 30 years. Fritz's groundbreaking research in rowing physiology began in the late 60s with New Zealand's National team, and he has continuously worked with the U.S. National team since 1972. The results of his research have positively impacted the performance of our national teams by teaching athletes how to improve their training regimens as well as helping coaches to identify those with the best physiological potential. He has been working closely with U.S. Men's Coach Mike Teti since 1997. Fritz is a Professor of Physiology at Ohio University and also serves as the Head of FISA's Sports Medicine Commission. irow.com is extremely honored to have "THE MAN" in rowing physiology share his knowledge with us.

TRAINING THE ENERGY SYSTEMS: Part I

It was emphasized in "Defining the Energy Systems" that the interaction among the three energy systems - ATP-PC and Lactic Acid Systems (anaerobic), and the Oxygen System (aerobic) - during rowing training and competition represents several complex biochemical processes. It should, therefore, be of no surprise to any of our previous or more recent on-line viewers to learn that it is difficult to blend these three systems into an effective training program that will maximize the use and development of each system and result in improved rowing performance.

Before discussing specific recommendations to improve the effectiveness of each energy system, it is important to review the basic principles of training. Training should be mostly task specific, and when not rowing, the athlete should exercise to simulate the rowing stroke, whether in part or as a whole, including resistance or weight training.

The only exceptions would be off-season cross-training or alternative training due to an injury caused or aggravated by rowing. Overload the physiological systems, but don’t concentrate this overload; follow the 10% rule when starting a training program, meaning an increase of no more than 10% per week in training frequency, duration, and intensity. As training progresses, then the weekly increase can be reduced to as low as 5%.

Also, don’t forget that rest and recovery are vital ingredients in the best training recipe; a failure to plan for these can produce disastrous results, including peaking at the wrong time, overtraining, or chronic fatigue. Remember, under-training is usually never a problem for the motivated rower. If you are unusually tired, injured, or sick, then taking a day or two off should not be considered a serious training set-back.

Instead, abstinence of training under any of these conditions is a wise choice. Because most interruptions of training are due to respiratory infections, it is recommended that training be reduced if the respiratory problem is above the neck and cancelled if it is below the neck.

Consistency of training is one of the most important training principles; you must use it, or lose it, and as you know, it is far easier to maintain a highly trained state than to achieve one. Individualize your training program based on your skill and fitness levels, availability of training facilities and equipment, and the amount of time you have available. There is no "best time" of the day to train, as it has been shown conclusively that the body doesn’t "care" when you decide to train. However, very early morning time (1-4am) and training immediately before bedtime or following a large meal should be avoided. An increase in training should also be accompanied by an increase in the quantity and quality of food intake, a higher intake of calories will be necessary to fuel the energy systems.

Part II: Peaking

Probably the most difficult job for any coach or self-trained athlete is to design a training program that will permit “peaking” at the right time. This goal is sometimes further complicated by the need to “peak” more than once in a period of only a few months which is often the case of U.S. Olympic qualifiers.

Successful and competitive performances are dependent on carefully planned comprehensive training programs that usually span several weeks or months including up to a year or more. Periodicity of training provides planning for long-term periods (macrocycles) which, in turn, are divided into number of training sessions, days, or weeks (microcycles).

Macrocycles are often represented by an out-of-competition period, a preparation period, and a competitive period and for rowers who live north of the equator, these periods would include approximately September through December, January through April, and May through August respectively. Furthermore, training can be categorized as either specific or non-specific. Specific training includes all work done on the water, rowing ergometry, and tank exercises whereas non-specific (supplemental) training can include weight training, flexibility exercises, or any form of cross training such as cycling, swimming, running, or cross country skiing.

A well-planned training program is based on four specific training factors: type of training (specific and non-specific), frequency (number of sessions per day, week, or cycle), duration (length of time for each training session), and intensity of training (rate of doing work). The intensity of work is the most critical factor in planning a program which will culminate in your best performance. It is well known that the timing of increasing or decreasing intensity determines whether an athlete “peaks” at the desired time or not. In addition, if intensity is increased at too high a rate it can lead to overtraining, injury, and fatigue. The selection of the right mixture of the four training factors is the basis of successful conditioning.

As you train it is good advice to learn and remember how the body responds to exercise and as you plan a training schedule, record it (computer, audio, or written); don’t go on the water, enter the weight room, or sit on the ergometer without a plan. When you complete each training session, again record what you have done, compare the results with your intended plan, and immediately note how your body reacted to the training session. Modifying or changing training programs may be necessary and comparing your specific training regimens with your competitive performances over time will permit you to more objectively make accurate modifications.

Part III: The ATP-PC System

Although certain training recommendations will tend to benefit one energy system more than another, their close relationship insures an energy continuum. Despite emphasizing one energy system with a specific training stimulus, it is likely you will always have some overlap among systems, especially when you consider the variable time frames and weather conditions in which rowing, training, and competition take place.

It is also important to point out that there are a number of different ways to train each of the energy systems and a wealth of training information is now available in several different forms; video and audio tapes, the internet, live symposia, and the old stand-by, the written word. If anything, hopefully the information presented here will help you to make better and more intelligent training choices.

You may recall the description of the three energy systems available to the rowing muscles from the previous presentation on this website; the ATP-PC System, the Lactic Acid System, and the Oxygen System. With the exception of the few seconds of an exercise when our muscles must rely on the ATP-PC System for energy, the use of the other energy systems depends on the duration and intensity of the exercise.

The Adenosine Triphosphate-Phosphocreatine (ATP-PC) System

Because of only a limited contribution of this system to rowing and because it is used most effectively during the first few seconds of any exercise, it is not necessary to devote much of your training time, if any, to the improvement of this system. Our earlier research indicated that this system contributes less than 5% of the energy needed to row a highly competitive 2000m race.

Recent research seems to tell us that insignificant changes occur in this system despite regular performance of high intensity bouts of exercise that last between 5 and 15 seconds. If you want to train the ATP-PC System, it is suggested that multiple intermittent work bouts of less than 20 seconds be performed, e.g., racing starts, with recovery periods of 40-60 seconds between each work bout. In this way the work bouts are too brief to provide much stimulation to anaerobic glycolysis (Lactic Acid System), and the relative long recovery periods permit adequate restoration of ATP and PC. This also means less lactic acid is produced, thus lowering the prospect of acute fatigue associated with this by-product of anaerobic metabolism. Training at or greater than 100% of maximum effort (see accompanying training intensity table) will stimulate this energy system.

Although some athletes appear to be blessed with more powerful ATP-PC systems, the quickness and explosiveness of a rower are also determined by other factors such as muscle fibre type distribution and complex neuromuscular relationships. There is no difference in the biochemical machinery of this system between men and women, however, men tend to have higher absolute energy outputs because of their larger skeletal muscle mass. To suggest that a rower cannot get faster or react more quickly, with training, is incorrect, but it would be more productive to concentrate on developing skill and technique at higher velocities than attempting to design training sessions concentrating solely on improvement of the ATP-PC System.

It is interesting to note that probably the most widely used ergogenic aid in sports today is phosphocreatine (PC). This compound has gained popularity because it is not found as part of any sports federation banned or illegal substance list, it is suggested to be effective in improving performance, and, at least for now, there appears to be no known acute or chronic side effects. If PC is effective, then it would be for only short periods. A recent avalanche of reports concerning PC has tumbled out of both the scientific and non-scientific communities, and the results are equivocal.

Although short bouts of repetitive muscular efforts have been shown to improve using isolated muscle groups as a result of PC ingestion, sports performances following PC use, both actual and simulated, are less impressive. There seems to be a strong relationship between the amount of PC stored in the working muscle and the ability to perform repetitive anaerobic work bouts, but it is difficult to assess the PC storage capacity or content of muscle and this capacity and content apparently vary from one individual to the next. PC may be similar to our electrolyte use; if we are low in calcium then exercise performance may be impaired.

However, it would be unwise to simply consume large amounts of calcium without knowing what its concentration is in the body; calcium is relatively easy to measure in the body, PC is not. There are also no reports of the long-term effects of PC use and it will be some time before these data are available. Although the distributors of PC are recommending that all sports will benefit from its use, there is no reliable evidence that this is the case and nor is there valid evidence that increased muscular concentrations of PC spare or delay the use of the other energy systems, thus contributing to a possible larger and more efficient energy pool.

Part IV: Anaerobic Glycolysis – Lactic Acid System (LAS)

Although this energy system accounts for only about 15 to 20% of the energy contribution during a 2000m race, the timing of its contribution is critical. Because elite rowers generate their highest power outputs in the first 500m of a race, significant amounts of lactic acid are produced during the first 90 seconds. In fact, our research has shown that blood lactate concentrations reach maximal levels within the first 2 minutes of a 2000m race.

Therefore, the rower usually tolerates a very high lactate load for an additional 3-4 minutes until the sprint, when the Lactic Acid System is once again challenged to make a significant energy contribution. Venous blood lactate values in excess of 20 mmol/L of blood have been observed for elite rowers following 2000m competitive efforts and, when compared with responses of elite aerobic athletes in other sports, the rower’s responses have been among the highest. As a result, one can appreciate the physical discomfort a rower experiences during and immediately following a race.

It is important to note that measuring blood lactate does not reflect the total amount of lactate produced by the working muscles. Instead it is more of a residual concentration of lactate left over following a complex series of biochemical cellular reactions that involve lactate production, transport, clearance, buffering and resynthesis to ATP and glycogen. Maximal lactate concentrations are quite variable among individuals, but tend to be more consistent following sub maximal efforts. The Lactic Acid System’s (LAS) range of maximum energy production is 60-90 seconds during high intensity exercise.

Although there are several training schemes designed to improve this energy system, it is recommended that any training intensity above anaerobic threshold (AT) will improve the LA System (see intensity table). There is also evidence to indicate that this system, among the three energy systems, probably has the greatest capacity to change with training. Repeated rowing efforts of 1-3 minutes above AT and using a work: recovery ratio 1:3 or 1:2 will permit sufficient time for large amounts of lactate to be cleared and resysnthesized.

In other words, if you row 3 minutes, then your recovery time between exercise bouts will double or triple the exercise time. This is not only an effective way to train the Lactic Acid System, but if exercise duration is extended, the cardiovascular transport system will also greatly benefit. Any work performed at or above AT will teach the athlete lactate tolerance and, as the exercise increases in intensity, so will the learning effect. The AT seems as receptive to change as the LAS.

It is not uncommon for an elite rower to improve AT from 70-75% of maximal heart rate during the off-season to 85-90% during the competitive period. Anaerobic Threshold training should include a work: recovery ratio of 1:1. Because training intensities above AT are almost totally dependent on glucose and glycogen for fuel, it is recommended that 36- 48 hours should separate any of these higher intensity workouts. Even a diet high in carbohydrate will be challenged to replenish muscle glycogen stores during these recovery times. I have often referred to AT as that point during high intensity exercise where an untrained person will stop exercising and where a trained athlete will begin to think about quitting; the latter being precisely the state of mind you want your opponent to be in with 250-500m to go in the race.

Part V: The Oxygen System

The Oxygen System, or aerobic metabolism, makes the most significant contribution of energy during a 2000m race and also for most training rows. Although more active biochemical changes seem to occur in the muscle cell as a result of aerobic training compared to only minimal changes attributed to anaerobic training, the actual increase in VO2 max is proportionally less than measurable responses of anaerobic factors due to specific training methods. Although it appears that VO2 max is primarily determined by hereditary factors, it can be significantly improved with training. However, its capacity for change is considerably less than the potential for change in the anaerobic response.

For many years, exercise scientists have suggested that VO2 max is the single most limiting factor in performing high intensity aerobic work that extends beyond 3 minutes. Although there is a strong relationship between VO2 max and a rower’s performance, our more recent research has shown that there is an even stronger relationship between a rower’s ability to work for 5-7 minutes at a higher percentage of their VO2 max and their performance.

The most revealing physiological response to predict rowing performance at the international level is the rower’s ability to maintain their metabolic rate at or above AT. Any aerobic athlete who can significantly elevate their AT can perform high intensity exercise more efficiently (aerobic metabolism means more ATP molecules) and the by-products of the O2 system, CO2 and H2O, are easy to deal with. This is not the case when anaerobic metabolism dominates.

Oxygen, or aerobic training, can be divided into either high intensity or low intensity workouts and both can use either continuous or intermittent training sessions. High intensity aerobic training seems more conducive to intermittent work, which should range from about 75-90% of maximal heart rate (see table of training intensities) with a work recovery ratio of either 1:0.5 or 1:0.25. In other words, if you row 10 minutes in this intensity range, your recovery period should range from 2.5 to 5 minutes. The high intensity form should not only represent the majority of your aerobic training but should also be the largest contributor to total training time.

Most low intensity aerobic training should be continuous and, if done intermittently, it should not be for any length of time less than 10 minutes. Rest or recovery periods for low intensity aerobic rowing should range between 30-60 seconds; the shorter the duration of exercise, the shorter the recovery period needed. Low intensity aerobic training is often referred to as “conversational” pace and thus you should be able to talk easily during an exercise of this intensity.

Although both forms of aerobic training permit a rower to reach and maintain an aerobic base, do not interpret the value of aerobic training in only quantitative terms. Every workout, even of a low intensity, must always stress quality, and as the physical condition of the rower improves, both exercise intensity and skill level need to be elevated. Many coaches and athletes are convinced that 60-120 minutes of continuous low intensity or steady-state rowing is an important part of developing and maintaining an adequate aerobic base. We have convincing data, including muscle biopsy histochemical and biochemincal indicators, which support that rowing continuously at a low steady state intensity for 60 minutes or longer for any calibre of rower, is not more effective in maintaining aerobic capacity than 30 minutes of rowing at the same work intensity.

Not only do these results apply to a single bout of rowing, but also to 5, 10, 15, and 20 week training responses after the aerobically-trained subjects had completed a total of 20, 40, 60 and 80 training sessions respectively. Furthermore, performing 2 intermittent 30 minute exercise bouts of relatively high aerobic work intensity (10-20 % more average power than for the low intensity work) with a 7-10 minute recovery period between the 30 minute work bouts is a much stronger aerobic training stimulus than lower intensity continuous rowing.

This higher work intensity for continuous rowing could not be tolerated by most subjects for more than 32-36 minutes and still maintain a steady-state. The increased energy expenditure of the intermittent high intensity work not only proved significantly more effective than either 30 or 60 minutes of rowing in the improvement of aerobic capacity, but it was also more neuromuscularly task specific.

Comparative videotape, coaching evaluations, and metabolic data confirmed those rowers performing intermittent high intensity training bouts rowed more efficiently at all exercise intensities than those rowers who trained for longer time periods and at lower intensities, especially as stroke rating and power output increased to beyond AT, including maximum power output.

This presentation has discussed training of all three basic energy systems, including AT training with supporting research data to validate my recommendations. Regardless of your present skill level or physical conditioning state or your competitive aspirations, optimal training of the energy systems requires a comprehensive training program. In future irow.com presentations, the importance of comprehensiveness will be emphasized by discussions dealing with such topics as resistance training, cross training, artificial and actual altitude training, restricted breathing training, high oxygen training, ionization training, electrical stimulation of muscle, and muscle and blood boosting using creatine, human growth hormone, erythropoietin (EPO), and oxygen “kickers” such as flurocarbons, oxygen breathing, and oxygenated water.


Saturday
Jul302011

The Lactate Threshold

By: Sports Advisor.
Site link: Sports Advisor.
Article Link: The Lactate Threshold


If VO2 max is your aerobic endurance potential then your lactate threshold plays a significant role in how much of that potential you are tapping.

Lactate threshold has been defined as:

The point during exercise of increasing intensity at which blood lactate begins to accumulate above resting levels, where lactate clearance is no longer able to keep up with lactate production. (3)

During low intensity exercise, blood lactate remains at or near to resting levels. As exercise intensity increases there comes a break point where blood lactate levels rise sharply (4,5). Researchers in the past have suggested that this signifies a significant shift from predominantly aerobic metabolism to predominantly anaerobic energy production.

Several terms have been used to describe this shift and many coaches and athletes believe it is the same phenomenon:

  • Lactate threshold
  • Anaerobic threshold
  • Aerobic threshold
  • Onset of blood lactate accumulation (OBLA)
  • Maximal lactate steady state

Although these terms are used interchangeably, they do not describe the same thing. Lactate accumulation only determines the balance between lactate production and its clearance and suggests nothing about the availability or lack of oxygen so the terms aerobic and anaerobic become a bit misleading.

The reasons for lactate accumulation are complex and varied and not yet fully understood. For more information on this topic see the lactic acid article.

OBLA

At a slightly higher exercise intensity than lactate threshold a second increase in lactate accumulation can be seen and is often referred to as the onset of blood lactate accumulation or OBLA. OBLA generally occurs when the concentration of blood lactate reaches about 4mmol/L (6,7). The break point that corresponds to lactate threshold can often be hard to pinpoint and so some Exercise Physiologists often prefer using OBLA.

Maximal Lactate Steady State

Maximal lactate steady state is defined as the exercise intensity at which maximal lactate clearance is equal to maximal lactate production (8). Maximal lactate steady state is considered one of the best indicators of performance perhaps even more efficient than lactate threshold (8,9). 

Lactate Threshold as a Percentage of VO 2 Max

The lactate threshold is normally expressed as a percentage of an individuals VO2 max. For example, if VO2 max occurs at 24 km/h on a treadmill test and a sharp rise in blood lactate concentration above resting levels is seen at 12 km/h then the lactate threshold is said to be 50% VO2 max.

In theory, an individual could exercise at any intensity up to their VO2 max indefinitely. However, this is not the case even amongst elite athletes. As the exercise intensity draws closer to that at VO2 max, a sharp increase in blood lactate accumulation and subsequent fatigue occurs the lactate threshold is broken. In world-class athletes lactate threshold typically occurs at 70-80% VO2 max. In untrained individuals it occurs much sooner, at 50-60% VO2 max (10,11).

Generally, in two people with the same VO2 max, the one with a higher lactate threshold will perform better in continuous-type endurance events. See the graph below:

Although both Athlete 1 and Athlete 2 reach VO2 max at a similar running speed, Athlete 1 has a lactate threshold at 70% and Athlete 2 has a lactate threshold at 60%. Theoretically, Athlete 1 can maintain a pace of about 7.5 mph (12 km/h) compared to Athlete 2s pace of about 6.5 mph (10.5km/h).

VO2 max has been used to predict performance in endurance events such as distance running and cycling but the lactate threshold is much more reliable. Race pace has been closely associated with lactate threshold (11).

There are several non-invasive methods used to determine the lactate or anaerobic threshold. For more information see How to Determine Your Anaerobic Threshold.

Lactate Threshold and Training

With training, lactate threshold as a percentage of VO2 max can be increased. Even if there are no improvements in maximal oxygen uptake, increasing the relative intensity or speed at which lactate threshold occurs will improve performance. In effect, proper training can shift the lactate curve to the right:

Following training, the reductions in lactate concentration at any given intensity may be due to a decrease in lactate production and an increase in lactate clearance (12). However, Donovan and Brooks (13) suggest that endurance training affects only lactate clearance rather than production.

Blood lactate levels after an intense exercise bout are also lower following training. For example, immediately after a 200m swim at a fixed pace, blood lactate may be as high as 13-14 mmol/L. Following 7 months of training these levels can decrease to under 4mmol/L (14). Before training, a swim leading to such high levels of lactate would force the swimmer to slow down dramatically or stop after the 200m. But following training, lactate levels of under 4mmol/L would probably allow the swimmer to continue after 200m, at the same pace, indefinitely.

Studies have shown that training at or slightly above the lactate threshold can increase the relative intensity at which it occurs (4,13).

References

1) Baechle TR and Earle RW. (2000) Essentials of Strength Training and Conditioning: 2nd Edition. Champaign, IL: Human Kinetics

2) McArdle WD, Katch FI and Katch VL. (2000) Essentials of Exercise Physiology: 2nd Edition Philadelphia, PA: Lippincott Williams & Wilkins

3) Wilmore JH and Costill DL. (2005) Physiology of Sport and Exercise: 3rd Edition. Champaign, IL: Human Kinetics

4) Davis JA, Frank MH, Whipp BJ, Wasserman K. Anaerobic threshold alterations caused by endurance training in middle-aged men. J Appl Physiol. 1979 Jun;46(6):1039-46

5) Kindermann W, Simon G, Keul J. The significance of the aerobic-anaerobic transition for the determination of work load intensities during endurance training. Eur J Appl Physiol Occup Physiol. 1979 Sep;42(1):25-34

6) Sjodin B, Jacobs I. Onset of blood lactate accumulation and marathon running performance. Int J Sports Med. 1981 Feb;2(1):23-6

7) Tanaka K, Matsuura Y, Kumagai S, Matsuzaka A, Hirakoba K, Asano K. Relationships of anaerobic threshold and onset of blood lactate accumulation with endurance performance. Eur J Appl Physiol Occup Physiol. 1983;52(1):51-6

8) Beneke R. Anaerobic threshold, individual anaerobic threshold, and maximal lactate steady state in rowing. Med Sci Sports Exerc. 1995 Jun;27(6):863-

9) Foxdal P, Sjodin B, Sjodin A, Ostman B. The validity and accuracy of blood lactate measurements for prediction of maximal endurance running capacity. Dependency of analyzed blood media in combination with different designs of the exercise test. Int J Sports Med. 1994 Feb;15(2):89-95

10) Cerretelli P, Ambrosoli G, Fumagalli M. Anaerobic recovery in man. Eur J Appl Physiol Occup Physiol. 1975 Aug 15;34(3):141-8

11) Farrell PA, Wilmore JH, Coyle EF, Billing JE, Costill DL. Plasma lactate accumulation and distance running performance. Med Sci Sports. 1979 Winter;11(4):338-44

12) Bergman BC, Wolfel EE, Butterfield GE, Lopaschuk GD, Casazza GA, Horning MA, Brooks GA. Active muscle and whole body lactate kinetics after endurance training in men. J Appl Physiol. 1999 Nov;87(5):1684-96

13) Donovan CM, Brooks GA. Endurance training affects lactate clearance, not lactate production. Am J Physiol. 1983 Jan;244(1):E83-92

14) Costill DL, Thomas R, Robergs RA, Pascoe D, Lambert C, Barr S, Fink WJ. Adaptations to swimming training: influence of training volume. Med Sci Sports Exerc. 1991 Mar;23(3):371-7


Saturday
Jul302011

How To Determine Lactate / Anaerobic Threshold

By: Sports Advisor.
Site link: Sports Advisor.

There are several methods used to determine an athletes lactate or anaerobic threshold. While the most accurate and reliable is through the direct testing of blood samples during a graded exercise test, this is often inaccessible to most performers.

There are several field tests that can also be used to estimate lactate threshold. They vary in their reliability but some offer an acceptable alternative for most amateur athletes.

Several terms such as onset of blood lactate accumulation and maximal lactate steady state are used interchangeably with anaerobic threshold. Technically, they do not describe precisely the same thing. In fact, although lactate threshold and anaerobic threshold occur together under most conditions, strictly speaking even these two terms are not the same (1). For this article however, lactate threshold and anaerobic threshold will be used interchangeably. See the lactate threshold article for more details on this topic.

It is also worth bearing in mind that blood lactate and lactic acid are not the same substance. Blood lactate production is actually thought to be beneficial to endurance performance and may delay fatigue. Nevertheless, its accumulation still remains a good marker for the onset of fatigue. 

Laboratory Testing of Anaerobic Threshold

The most accurate way to determine lactate threshold is via a graded exercise test in a laboratory setting (2). During the test the velocity or resistance on a treadmill, cycle ergometer or rowing ergometer is increased at regular intervals (i.e. every 1min, 3min or 4min) and blood samples are taken at each increment. Very often VO2 max, maximum heart rate and other physiological kinetics are measured during the same test (3).

Blood lactate is then plotted against each workload interval to give a lactate performance curve. Heart rate is also usually recorded at each interval often with a more accurate electrocardiogram as opposed to a standard heart rate monitor.

Once the lactate curve has been plotted, the anaerobic threshold can be determined. A sudden or sharp rise in the curve above base level is said to indicate the anaerobic threshold. However, from a practical perspective this sudden rise or inflection is often difficult to pinpoint.

Assuming the inflection is clear (as in the graph above), the relative speed or workload at which it occurs can be determined. In this example, the athletes anaerobic threshold occurs at about 12km/h. This means, in theory they can maintain a pace at or just below 2km/h for a prolonged period, indefinitely. Of course, this is purely hypothetical as there are many other factors involved in fatigue not least the amount of carbohydrate stores an athlete has in reserve (1). A crossover to fat metabolism will significantly reduce the athletes race pace (2).

By recording heart rate data alongside workload and blood lactate levels, an athlete can use a heart rate monitor to plan and complete training sessions. Although monitoring heart rate is never completely reliable and varies greatly between and within individuals (1,2,3) combining it with lactate measurements is probably more reliable than using the Conconi test (see below) for example.

Confirmatory Test

When anaerobic threshold is read from the lactate curve, an additional test can be used to verify its accuracy. Using the example above, the athletes threshold is thought to occur at about 12km/h on the treadmill. The confirmatory test involves running for 15 minutes at a pace just below threshold, 15 minutes at threshold and 15 minutes at a pace just above threshold. See the curves below of three athletes whose thresholds have all been determined to occur at approximately 12kmh.

Notice that for Athlete 1, blood lactate remains steady at their estimated anaerobic threshold (12km/h) and lactate begins to accumulate when the pace is increased to 13km/h in the final 15 minutes. For athlete 1, this is confirmation that their anaerobic threshold pace is reasonably accurate.

For Athlete 2, lactate begins to accumulate during the middle 15minute segment (their estimated threshold) and continues to do so during the final 15 minutes. For this athlete, anaerobic threshold occurs at a slightly slower pace than was determined originally.

Finally, Athlete 3s lactate curve does not rise significantly even during the final 15 minutes segment. Anaerobic threshold for them occurs at a slightly higher pace then was originally determined.

Assuming, you dont have access to facilities that directly monitor your or your athletes lactate response, are there other acceptable alternatives?

Portable Lactate Analyzer

Portable lactate analysers are becoming more popular amongst coaches and athletes at all levels. A good portable analyzer should have the same validity and reliability as laboratory testing equipment. The Accutrend Lactate Analyzer for example, has been tested using guidelines of the European Committee for Clinical Laboratory Standards and is cleared for sports medicine use by the Federal Drug Administration in the United States.

Needless to say a portable analyser is only one half of the equation. A suitable and sport-specific exercise test is still required and selecting the most appropriate protocol takes knowledge and experience. Any physiological test is only as reliable as the testers ability to follow a set protocol. Even when a suitable assessment has been chosen, numerous variables must be kept constant for the test to remain accurate and reliable.   

Conconi Test

In 1982 Conconi et a (4) stated that the anaerobic threshold correlated to a deflection point in the heart rate. Essentially, heart rate and exercise intensity is linear i.e. as exercise intensity increases so will heart rate. However, Conconi et a found that in all their tested subjects, including those in a follow up test (5), heart rate reached a plateau at near maximal exercise intensities.

Although this is a relatively simple field test that would be useful for coaches and athletes at all levels, its accuracy has been contested by subsequent researchers (6,7,8). Studies have found that the deflection point or plateau in heart rate only occurs in a certain number of individuals and that when it does, it significantly overestimates directly measured lactate threshold. Conconi and co-workers (9) themselves acknowledge this controversy and cite studies that both support and contradict their original findings. 

10km Run, 30Km Cycle, 30 Min Time Trial

More experienced athletes often run a 10km race or cycle 30km race at or close to anaerobic threshold. By simulating a race in training and recording heart rate, the anaerobic threshold may be determined. Alternatively, exercising for 30 minutes at the fastest sustainable pace can be used. The key is to sustain a steady pace which is why this test is more suited to experienced athletes who can gauge how fast to set off. A heart rate monitor with split time facility is required to record heart rate at each 1-minute interval. Take the average heart rate over the final 20 minutes as the heart rate corresponding to anaerobic threshold.  

Heart Rate Percentage

A very simply method for estimating the anaerobic threshold is to assume anaerobic threshold occurs at 85-90% maximum heart rate (220-age). As mentioned earlier, heart rate varies greatly between individuals and even within the same individual so this is not a reliable test.

The Lactate Threshold Debate

Some researchers have questioned the validity of determining the lactate or anaerobic threshold even in laboratory settings (10,11). Yet more researchers question whether a definite point or threshold exists at all (10,12,13,14). Instead they suggest blood lactate accumulation is continuous in nature and no specific point can be determined.

Rather than get bogged down in the debate it is sensible to remember that regardless of the underlying mechanisms, the physiological changes that accompany lactate accumulation have important implications for endurance athletes. Any delay in the blood lactate accumulation that can be achieved through training is beneficial to performance.

References

1) Wilmore JH and Costill DL. (2005) Physiology of Sport and Exercise: 3rd Edition. Champaign, IL: Human Kinetics

2) McArdle WD, Katch FI and Katch VL. (2000) Essentials of Exercise Physiology: 2nd Edition Philadelphia, PA: Lippincott Williams & Wilkins

3) Maud PJ and Foster C (eds.). (1995) Physiological Assessment Of Human Fitness. Champaign, IL: Human Kinetics

4) Conconi, F., M. Ferrrari, P. G. Ziglio, P. Droghetti, and L. Codeca. Determination of the anaerobic threshold by a noninvasive field test in runners. J. Appl. Physiol. 1982, 52: 862-873

5) Ballarin, E., C. Borsetto, M. Cellini, M. Patracchini, P. Vitiello, P. G. Ziglio, and F. Conconi. Adaptation of the "Conconi test" to children and adolescents. Int. J. Sports Med. 1989, 10: 334-338

6) Parker, D., R. A. Robergs, R. Quintana, C. C. Frankel, and G. Dallam. Heart rate threshold is not a valid estimation of the lactate threshold. Med. Sci. Sports Exerc. 1997, 29: S235

7) Tokmakidis, S. P., and L. A. Leger. Comparison of mathematically determined blood lactate and heart rate "threshold" points and relationship to performance. Eur. J. Appl. Physiol. 64: 309-317

8) Vachon JA, Bassett Jr DR and Clarke S. Validity of the heart rate deflection point as a predictor of lactate threshold during running. J Appl Physiol. 1999, 87: 452-459

9) Conconi, F., G. Grazze, I. Casoni, C. Guglielmini, C. Borsetto, E. Ballarin, G. Mazzoni, M. Patracchini, and F. Manfredini. The Conconi test: methodology after 12 years of application. Int. J. Sports Med. 1996, 17: 509-519

10) Yeh MP, Gardner RM, Adams TD, Yanowitz FG, Crapo RO. "Anaerobic threshold": problems of determination and validation. J Appl Physiol. 1983, Oct;55(4):1178-86

11) Gladden LB, Yates JW, Stremel RW, Stamford BA. Gas exchange and lactate anaerobic thresholds: inter- and intraevaluator agreement. J Appl Physiol. 1985 Jun;58(6):2082-9

12) Hughson RL, Weisiger KH, Swanson GD. Blood lactate concentration increases as a continuous function in progressive exercise. J Appl Physiol. 1987 May;62(5):1975-81

13) Campbell ME, Hughson RL, Green HJ. Continuous increase in blood lactate concentration during different ramp exercise protocols. J Appl Physiol. 1989 Mar;66(3):1104-7

14) Dennis SC, Noakes TD, Bosch AN. Ventilation and blood lactate increase exponentially during incremental exercise. J Sports Sci. 1993 Oct;11(5):371-5; discussion 377-8 

Friday
Jul292011

VO2 Max, Aerobic Power & Maximal Oxygen Uptake

By: Sports Advisor.
Site link: Sports Advisor.

VO2 max has been defined as:

"the highest rate of oxygen consumption attainable during maximal or exhaustive exercise" (3).

As exercise intensity increases so does oxygen consumption. However, a point is reached where exercise intensity can continue to increase without the associated rise in oxygen consumption. To understand this in more practical terms, take a look at the diagram below:

The point at which oxygen consumption plateaus defines the VO2 max or an individual's maximal aerobic capacity. It is generally considered the best indicator of cardiorespiratory endurance and aerobic fitness. However, as well discuss in a moment, it is more useful as an indicator of a person's aerobic potential or upper limit than as a predictor of success in endurance events.

Aerobic power, aerobic capacity and maximal oxygen uptake are all terms used interchangeably with VO2 max.

VO2 max is usually expressed relative to bodyweight because oxygen and energy needs differ relative to size. It can also be expressed relative to body surface area and this may be a more accurate when comparing children and oxygen uptake between sexes.

One study followed a group of 12-year-old boys through to the age of 20 - half of which were trained, the other half untrained but active. Relative to bodyweight no differences in VO2 max were found between the groups suggesting that training had no influence on maximal oxygen uptake. However, when VO2 max was expressed relative to body surface area, there was a significant difference between groups and maximal oxygen uptake did indeed increase in proportion to training (4).

VO2 Max In Athletes and Non Athletes

VO2 max varies greatly between individuals and even between elite athletes that compete in the same sport.

The table below lists normative data for VO2 max in various population groups:

Genetics plays a major role in a persons VO2 max (11) and heredity can account for up to 25-50% of the variance seen between individuals. The highest ever recorded VO2 max is 94 ml/kg/min in men and 77 ml/kg/min in women. Both were cross-country skiers (16).

Untrained girls and women typically have a maximal oxygen uptake 20-25% lower than untrained men. However, when comparing elite athletes, the gap tends to close to about 10% (3). Taking it step further, if VO2 max is adjusted to account for fat free mass in elite male and female athletes, the differences disappear in some studies. Cureton and Collins (29) suggest that sex-specific essential fat stores account for the majority of metabolic differences in running between men and women.

Training & VO2 Max

In previously sedentary people, training at 75% of aerobic power, for 30 minutes, 3 times a week over 6 months increases VO2 max an average of 15-20% (6). However, this is an average and there are large individual variations with increases as wide ranging as 4% to 93% reported (6).

Amongst groups of people following the same training protocol there will be responders - those who make large gains, and non-responders - those who make little or no gains (14,9). This was originally put down to a simple issue of compliance but more recent research suggests that genetics plays a role in how well any one individual responds to an endurance training program (13).

The extent by which VO2 max can change with training also depends on the starting point. The fitter an individual is to begin with, the less potential there is for an increase and most elite athletes hit this peak early in their career. There also seems to be a genetic upper limit beyond which, further increases in either intensity or volume have no effect on aerobic power (5). This upper limit is thought to be reached within 8 to 18 months (3).

Crucially, once a plateau in VO2 max has been reached further improvements in performance are still seen with training. This is because the athlete is able to perform at a higher percentage of their VO2 max for prolonged periods (2). Two major reasons for this are improvements in anaerobic threshold and running economy.

Resistance training and intense 'burst-type' anaerobic training have little effect on VO2 max. Any improvements that do occur are usually small and in subjects who had a low level of fitness to begin with (17). Resistance training alone does not increase VO2 max (30,31,32) even when short rest intervals are used between sets and exercises (33).

Considerable training is required to reach the upper limit for VO2 max. However, much less is required to maintain it. In fact peak aerobic power can be maintained even when training is decreased by two thirds (18). Runners and swimmers have reduced training volume by 60% for a period of 15-21 days prior to competition (a technique known as tapering) with no loss in VO2 max (19,20,21).

VO2 Max as a Predictor of Performance

In elite athletes, VO2 max is not a good predictor of performance. The winner of a marathon race for example, cannot be predicted from maximal oxygen uptake (15).

Perhaps more significant than VO2 max is the speed at which an athlete can run, bike or swim at VO2 max. Two athletes may have the same level of aerobic power but one may reach their VO2 max at a running speed of 20 km/hr and the other at 22 km/hr.

While a high VO2 max may be a prerequisite for performance in endurance events at the highest level, other markers such as lactate threshold are more predictive of performance (3). Again, the speed at lactate threshold is more significant than the actual value itself.

Think of VO2 max as an athletes aerobic potential and the lactate threshold as the marker for how much of that potential they are tapping.

Factors Affecting VO2 Max

There are many physiological factors that combine to determine VO2 max but which of these are most important? Two theories have been proposed:

Utilization Theory

This theory maintains that aerobic capacity is limited by lack of sufficient oxidative enzymes within the cell's mitochondria (3). It is the body's ability to utilize the available oxygen that determines aerobic capacity. Proponents of this theory point to numerous studies that show oxidative enzymes and the number and size of mitochondria increase with training. This is coupled with increased differences between arterial and venous blood oxygen concentrations (a-vO2 difference) accounting for improved oxygen utilization and hence improved VO2max.

Presentation Theory

Presentation theory suggests that aerobic capacity is limited not predominantly by utilization, but by the ability of the cardiovascular system to deliver oxygen to active tissues. Proponents of this theory maintain that an increase in blood volume, maximal cardiac output (due to increased stroke volume) and better perfusion of blood into the muscles account for the changes in VO2max with training.

So what plays the greater role in determining an athlete's VO2 max - their body's ability to utilize oxygen or supply oxygen to the active tissues?

In a review of the literature, Saltin and Rowell (7) concluded that it is oxygen supply that is the major limiter to endurance performance. Studies have shown only a weak relationship between an increase in oxidative enzymes and an increase in VO2 max (8,9,10). One of these studies measured the effects of a 6-month swim training program on aerobic function. While oxidative enzymes continued to increase until the end, there was no change in VO2 max in the final 6 weeks of the program (10). 

Determining VO2 Max

VO2 max can be determined through a number of physical evaluations. These tests can be direct or indirect. Direct testing requires sophisticated equipment to measure the volume and gas concentrations of inspired and expired air. There are many protocols used on treadmills, cycle ergometers and other exercise equipment to measure VO2 max directly.

One of the most common is the Bruce protocol often used for testing VO2 max in athletes or for signs of coronary heart disease in high risk individuals.

Indirect testing is much more widely used by coaches as it requires little or no expensive equipment. There are many indirect tests used to estimate VO2 max. Some are more reliable and accurate than others but none are as accurate as direct testing. Examples include the multistage shuttle run (bleep test), 12 minute walk test and 1.5 mile run.

VO2 Max at Altitude

VO2 max decreases as altitude increases above 1600m (5249ft) or about the altitude of Denver, Colorado. For every 1000m (3281ft) above that, maximal oxygen uptake decreases further by approximately 8-11% (3). Anyone with a VO2 max lower than 50 ml/kg/min would struggle to survive at the summit of Everest without supplemental oxygen.

The decrease is mainly due to a decrease in maximal cardiac output. Recall that cardiac output is the product of heart rate and stroke volume. Stoke volume decreases due to the immediate decrease in blood plasma volume. Maximal heart rate may also decrease and the net effect is that less oxygen is "pushed" from the blood into the muscles (2).

Effects of Aging on VO2 Max

VO2 max decreases with age. The average rate of decline is generally accepted to be about 1% per year or 10% per decade after the age of 25. One large cross sectional study found the average decrease was 0.46 ml/kg/min per year in men (1.2%) and 0.54 ml/kg/min in women (1.7%) (22,23).

However, this deterioration is not necessarily due to the aging process. In some cases the decease may be purely a reflection of increased body weight with no change in absolute values for ventilation of oxygen. Recall, that VO2 max is usually expressed relative to body weight. If this increases, as tends to happen with age, and aerobic fitness stays the same then VO2 max measured in ml/kg/min will decrease.

Usually, the decline in age-related VO2 max can be accounted for by a reduction in maximum heart rate, maximal stoke volume and maximal a-vO2 difference i.e. the difference between oxygen concentration arterial blood and venus blood (2).

Can training have an affect on this age-related decline?

Vigorous training at a younger age does not seem to prevent the fall in VO2 max if training is ceased altogether. Elite athletes have been shown to decline by 43% from ages 23 to 50 (from 70 ml/kg/min to 40 ml/kg/min) when they stop training after their careers are over (24). In some cases, the relative decline is greater than for the average population - as much as 15% per decade or 1.5% per year (27,28).

However in comparison, master athletes who continue to keep fit only show a decrease of 5-6% per decade or 0.5-0.6% per year (25,26,27,28). When they maintain the same relative intensity of training, a decrease of only 3.6% over 25 years has been reported (28) and most of that was attributable to a small increase in bodyweight.

It seems that training can slow the rate of decline in VO2 max but becomes less effective after the age of about 50 (3).

References

1) Baechle TR and Earle RW. (2000) Essentials of Strength Training and Conditioning: 2nd Edition. Champaign, IL: Human Kinetics

2) McArdle WD, Katch FI and Katch VL. (2000) Essentials of Exercise Physiology: 2nd Edition Philadelphia, PA: Lippincott Williams & Wilkins

3) Wilmore JH and Costill DL. (2005) Physiology of Sport and Exercise: 3rd Edition. Champaign, IL: Human Kinetics

4) Sjodin B, Svedenhag J. Oxygen uptake during running as related to body mass in circumpubertal boys: a longitudinal study. Eur J Appl Physiol Occup Physiol. 1992;65(2):150-7

5) Costill DL. (1986) Inside Running: Basics of Sports Physiology. Indianapolis: Benchmark Press

6) Pollock ML. (1973). Quantification of endurance training programs. Exercise and Sport Sciences Reviews. 1,155-188

7) Saltin B, Rowell LB. Functional adaptations to physical activity and inactivity. Federation Proceeding. 1980 Apr;39(5):1506-13

8) Gollnick PD, Armstrong RB, Saubert CW 4th, Piehl K, Saltin B. Enzyme activity and fiber composition in skeletal muscle of untrained and trained men. J Appl Physiol. 1972 Sep;33(3):312-9

9) Saltin B, Nazar K, Costill DL, Stein E, Jansson E, Essen B, Gollnick D. The nature of the training response; peripheral and central adaptations of one-legged exercise. Acta Physiol Scand. 1976 Mar;96(3):289-305

10) Costill DL, Thomas R, Robergs RA, Pascoe D, Lambert C, Barr S, Fink WJ. Adaptations to swimming training: influence of training volume. Med Sci Sports Exerc. 1991 Mar;23(3):371-7

11) Bouchard C, Dionne FT, Simoneau JA, Boulay MR. Genetics of aerobic and anaerobic performances. Exerc Sport Sci Rev. 1992;20:27-58

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