Figure 9 – Threshold Training (10)
February 23, 2013
An evidence-based triathlon training protocol: a case study and narrative review
· LT1 (lactate threshold 1) = VT1 (ventilatory threshold 1) = AeT (aerobic threshold)
· LT2 (lactate threshold 2) = VT2 (ventilatory threshold 2) = AnT (anaerobic threshold) = MLSS (maximal lactate steady state)
· VO2max = maximal oxygen consumption
· LIT = low intensity training
· MIT = moderate intensity training
· HIT = high intensity training
The goal of any high-performance training program is to increase an athlete’s performance by producing physiological, neurological and metabolic changes that promote success in their particular sport. With respect to physiological adaptations, training can induce both central (cardiac) and peripheral (skeletal muscle) changes. Central adaptations (changes that affect the left ventricle) increase stroke volume and ultimately cardiac output. These changes are most important when considering oxygen consumption, as the limiting factor for increasing VO2max is the body’s ability to supply oxygen to exercising muscles (1). Peripheral adaptations (changes to the structure of skeletal muscle itself) improve VO2max by increasing the body’s ability to uptake and utilize oxygen at the cellular level.
Recently, it has become clear that performance is not directly related to VO2max, but rather the ability to compete as close to VO2max as possible. In endurance sports, the highest workload at which an athlete can race is considered to be their MLSS (2). MLSS is the highest blood lactate concentration that can be maintained without a progressive accumulation of lactate in the body (2). Therefore, it is important for an endurance coach to not only increase an athlete’s VO2max but also to increase their MLSS to a point as close to their VO2max as possible.
Currently, there are a number of studies that describe the effects of different programs of various training intensity distributions on endurance athletes, but none of these studies are specifically directed at triathlon. Also, most studies on aerobic training include training periods of 4-weeks up to 6-months. The case study presented here provides the results of an evidence-based, triathlon training protocol from two consecutive training cycles (Training Cycle 1 – 2012 pre-season and the beginning of Training Cycle 2 – 2013 pre-season, approximately 12-months). The reasoning behind including the two training cycles is to show the effectiveness of this training protocol from one season to the next. This will establish the validity of the protocol by demonstrating continued improvement in athletic performance. This is meaningful because it is more challenging to increase the fitness level of a highly trained athlete than of an untrained or moderately trained individual.
The athlete included in the case study is a moderately trained, 28 year old male triathlete. He has been training and competing in triathlon for approximately 7 years. Baseline values were taken prior to the beginning of the training program and include the athlete’s height (184 cm), weight (82.7kg) and BMI (24.4). VO2max was 57ml/kg/min and was determined using a cycle ergometer. It is also important to note that this athlete also works full time (approximately 50 hours/week).
In this study, LIT was performed at LT1; MIT was performed at MLSS; and HIT was performed as intervals sets above LT2. The protocol in both training cycles included approximately 8 to 10- weeks of LIT followed by 6-weeks of polarized training (approximately 80% LIT, 5-10% MIT, and 10-15% HIT). The weekly training volume was between 9 and 13 hours each week. Each week included 3 to 4 swim sessions, 3 to 4 bike sessions and 4 run sessions.
Figure 1 – Physiological Intensity Zones (3)
The results below only include the data collected from the cycling component of the training program.
Table 1 – Training Cycle 1 (2012 Season Preparation)
Table 2 – Training Cycle 2 (2013 Season Preparation)
Table 3 – Total Training period (~12 months)
Figure 2 – Power (watts) at LT1 – Training Cycle 1
Figure 3 – Power (watts) at LT1 – Training Cycle 2
Figure 4 – Power (watts) at MLSS – Training Cycle 1
Figure 5 – Power (watts) at MLSS – Training Cycle 2
Figure 6 – Efficiency (watts/beat) at MLSS – Training Cycle 2
Figure 7 – Power (watts) above LT2 – Anaerobic Intervals – Training Cycle 2
Figure 8 – Power (watts) above LT2 – Aerobic Intervals – Training Cycle 2
An adequate training stimulus is required in order for the desired physiological adaptations to take place. Currently, there are conflicting views in the literature about which method of training (LIT, MIT, or HIT) is optimal for improving performance. In recent years, a significant amount of research has been published that demonstrates how HIT can improve performance, and that it can do so with significantly less training volume compared to LIT. These results are quite impressive, however, it is important to consider the mechanism by which these improvements occur.
High intensity training performed through repeated intervals has been shown to initiate peripheral adaptations. Duscha et al 2012 conducted a randomized controlled trial comparing different doses of high intensity intervals in untrained men and women (4). The results of the study demonstrated an increase in aerobic enzymes, as well as in muscle capillary density (4). Iaia et al 2009 demonstrated similar improvements in mitochondrial and capillary density in endurance-trained male runners following 4-weeks of speed endurance training (5). Another study performed by Creer et al 2004 showed that 4-weeks of high-intensity sprint interval training increased muscle fibre recruitment (6).
The results from these studies explain how HIT can lead to peripheral changes, however they do not address the mechanisms by which central adaptations occur. Macpherson et al 2011 conducted a controlled trial on ten trained men and women that compared the effects of LIT and HIT on cardiac output (7). The results from the 6-week trial demonstrated a significant (p < 0.01) increase of 2.1L/min (9%) in cardiac output following LIT, however, no changes in cardiac output following HIT (7). Since both groups showed a significant (p < 0.001) increase in VO2max (7), it is likely that the improvement in the HIT group was not associated with central adaptations.
There is still limited high-quality evidence available that analyzes the mechanisms by which central and peripheral adaptations occur. The evidence discussed provides some insights into the appropriate exercise intensities (LIT for central adaptations and HIT for peripheral adaptations) used to elicit physiological changes. Further research in this area is required to help establish a better understanding of these mechanisms.
The previous section explains how LIT and HIT can improve the physiological markers associated with aerobic performance. Race pace efforts are performed at approximately MLSS, therefore, it is reasonable for a coach to assume that a large percentage of training time should be completed at MLSS. However, a prospective cohort study on top class marathon runners revealed that approximately 78% of their total training volume was spent below LT1 (8). Another study conducted by Seiler et al 2006 on junior male cross country skiers demonstrated that 75 ± 3% of training time was spent below LT1; 8 ± 3% between LT1 and LT2; and 17 ± 4% above LT2 (3). Since these were both observational studies, it is impossible to determine if improvements in performance were as a result of the specific training program or if changes were simply as a result providing a training stimulus.
Neal et al 2013 conducted a randomized controlled trial that compared the effects of threshold training and polarized training on well-trained, male competitive cyclists (See Figures 9 and 10 for examples of both polarized and threshold training). The polarized training group included 80% of the total training volume at LT1 and 20% of total training above LT2. The threshold-training group performed 57% of total training volume at LT1 and 43% of total training volume between LT1 and LT2 (9). The results of the study demonstrated that there was a significant (p < 0.05) increase in power at lactate threshold (18 ± 18 watts) and peak power output (27 ± 18 watts) from pre- to post-training (9). There was no significant change in the threshold-training group for power at LT1 (4 ± 31 watts) or for peak power output (9 ± 17 watts) (9).
The training protocol used in this case study incorporates a similar protocol to that of the Neal et al 2013 study with some minor differences. The protocol included two phases. The first phase was a general preparation phase that consisted of 8-10 weeks of training only at LT1. The second phase was a specific preparation phase that consisted of 6-weeks that included ~80% of training time spent at LT1, ~10-15% of training time well above LT2, and ~5-10% of training time at MLSS. Based on the results of the Neal et al 2013 study there were no physiological benefits to training at or near MLSS. The reason for incorporating training at MLSS into this training protocol was to provide the athlete with the physical and psychological benefits of exercising at race pace.
Figure 9 – Threshold Training (10)
Figure 9 – Threshold Training (10)
Figure 10 – Polarized Training (10)
Distribution and duration of Interval Sessions
The previous section describes the appropriate distribution of LIT and HIT with respect to total training volume; however, it does not specify how the various intensities should be distributed throughout a weekly training plan. A study conducted by Parra et al 2000 compared the effects of a 24- and 48-hour recovery period between HIT interval sets on markers of performance in 10 healthy male students (11). The results of the study demonstrated that the group that had a 48-hour recovery period improved in both maximum peak power (20%) and mean power (14%), and that this improvement was significantly (p < 0.05) greater than the 24-hour recovery group (11).
Another vital aspect to consider when incorporating HIT into a training protocol is the duration of the intervals themselves. Sanbakk et al 2012 performed a randomized controlled trial on 21 highly-trained cross-country skiers to compare the effects of moderate duration intervals (2 to 4 minutes) and long duration intervals (5 to 10 minutes) (12). Both interval groups demonstrated a significant increase in VO2max from pre- to post-training, however, only the long duration interval group showed a significant (p = 0.004) increase in oxygen uptake (5.8 ± 3.3%) at LT2 (12). As discussed in the introduction, it is the athlete’s ability to exercise as close to their VO2max as possible for them to optimize their performance. Therefore, it appears more beneficial to use long duration training intervals moderate duration intervals.
A similar study conducted by Zuniga et al 2011 analyzed the effects of short duration training intervals (30 seconds) and moderate duration intervals (3 minutes) on 12 recreationally competitive male and female triathletes (13). The results of the study revealed that the short duration interval group had longer total interval times as well as a greater total oxygen consumption during the training session than the moderate duration interval group (13). This may suggest that the short duration intervals provide a greater exercise stimulus than the moderate duration intervals.
A possible explanation for why moderate duration training intervals were less effective, is that a 2-3 minute time period may not provide the right stimulus to allow for one energy system (anaerobic vs. aerobic) to dominate. Therefore, the protocol in this case study incorporated two interval sessions a week; one session of short duration intervals and one of long duration intervals. The athlete was instructed to perform the interval sets at maximum effort for the duration of the session, taking into account the number and duration of the intervals included in the set. Also, HIT days were separated by a minimum of 48-hours to provide optimal recovery between training sessions, as suggested by the study by Parra et al 2000.
This case study demonstrates the benefits of an evidence-based coaching approach on athletic performance in triathlon. The training protocol led to a 41% increase in power output (watts) at LT1 and a 27% increase in power output (watts) at MLSS over a 12-month period. These improvements can be attributed to incorporating the sport-science aspects of coaching with an athlete-centred approach. By considering both of these components, a coach can promote athletic success.
1. Nogami Y. Cardiac function as the limiting factor of exercise. Adv Exerc Sports Physiol. 2010;15(4):127–30
2. Faude O, Kindermann W, Meyer T. Lactate threshold concepts. Sports Med. 2009;39(6): 469–90
3. Seiler S, Kjerland G. Quantifying training intensity distribution in elite endurance athletes: is there evidence for an “optimal” distribution? Scand J Med Sci Sports. 2006;16(1):49–56
4. Duscha B, Annex B, Johnson J, Huffman K, Houmard J, Kraus W. Exercise does response in muscle. Int J Sports Med. 2012;33:218–23
5. Iaia F, Hellsten Y, Nielsen J, Fernstrom M, Sahlin K, Bangsbo J. Four weeks of speed endurance training reduces energy expenditure during exercise and maintains muscle oxidative capacity despite a reduction in training volume. J Appl Physiol. 2009;106:73–80
6. Creer A, Ricard M, Conlee R, Hoyt G, Parcell A. Neural, metabolic, and performance adaptations to four weeks of high intensity sprint-interval training in trained cyclists. Int J Sports Med. 2004;25:92–8
7. Macpherson R, Hazell T, Olver D, Paterson D, Lemon P. Run sprint interval training improves aerobic performance but not maximal cardiac output. Med Sci Sports Exerc. 2011;43(1):115–22
8. Billat V, Demarle A, Slawinski J, Paiva M, Koralsztein J. Physical and training characteristics of top-class marathon runners. Med Sci Sports Exerc. 2001;33(12):2089–97
9. Neal C, Hunter A, Brennan L, O'Sullivan A, Hamilton D, DeVito G, et al. Six weeks of a polarized training-intensity distribution leads to greater physiological and performance adaptations than a threshold model in trained cyclists. J Appl Physiol. 2013;114:461–71
10. Seiler S, Tonnessen E. Intervals, thresholds, and long slow distance: the role of intensity and duration in endurance training. Sportsci. 2009;13:32–53
11. Parra J, Cadefau J, Rodas G, Amigo N, Cusso R. The distribution of rest periods affects performance and adaptations of energy metabolism induced by high-intensity training in human muscle. Acta Physiol Scand. 2000;169:157–65
12. Sandbakk Ø, Sandbakk S, Ettema G, Welde B. Effects of intensity and duration in aerobic high-intensity interval training in highly-trained junior cross-country skiers. J Strength Cond Res. 2012;Published Ahead of Print
13. Zuniga J, Berg K, Noble J, Harder J, Chaffin M, Hanumanthu V. Physiological responses during interval training with different intensities and duration of exercise. J Strength Cond Res. 2011;25(5):1279–84.