Increased participation in recreational and competitive triathlons over the last decade has been accompanied by an increase in the number of athletes sustaining injuries (9). Studies investigating factors relating to levels of training that contribute to injury identified that training for or competing in the running component of the triathlon resulted in the greatest number of, and often the most severe, injuries (9,28). Specifically, risk of injury increased with increased weekly training distances, especially for running (9,28). In contrast, a growing body of literature points to mean training intensity over a season as the key factor for performance improvement (8,20). A clear example for endurance sports was reported by Billat et al. (4) who showed that male Kenyan runners training at higher speeds had a significantly better 10-km performance than Kenyan athletes training at lower speeds, despite the elite status of both groups.
As a training method that leads to a reduction in weekly running distances and an increase in mean running intensity without impairing athletic performance, high-intensity interval training (HIIT) is considered one of the most effective forms of exercise for improving the physical performance of athletes (2,3,7,8,20). Although there is no universal definition, HIIT generally refers to repeated short to long bouts of high-intensity exercise—performed at close to 100% maximal oxygen uptake (V̇o2max)—interspersed with recovery periods.
The HIIT protocol is well documented (8), and various types of HIIT programs have been shown to improve endurance performance in runners (1,12,17) and cyclists (10,19). However, despite the reported benefits of training at a high intensity, endurance athletes continue to train mostly at low intensities (13); thus, more evidence is needed to “convince” coaches and athletes of the importance of HIIT for endurance performance. Finally, all of these studies have been performed in a single sport, by replacing a part of their training programs and reducing, in a variable percentage (0–50%), the average training distance. Nevertheless, to date, no previous studies have proposed any strategy to insert and apply the HIIT methodology to a triathlon.
Taken together, the aim of this study was to examine the effect of a 5-week HIIT-based running plan on the athletic performance of triathletes and to compare the physiological and neuromuscular responses during a sprint-distance triathlon race before and after this high-intensity and low-volume intervention period. The authors hypothesize that a low-volume HIIT-based running plan, combined with the already high training volumes of these triathletes in swimming and cycling, might be a more efficient training program for improving the performance of triathletes than the typically performed high-volume and low-/moderate-intensity exercise.
Experimental Approach to the Problem
This study analyses the effect of incorporating HIIT on muscle power measurement and simulated sprint triathlon performance. Using a between-group design (experimental group [EG] and control group [CG]), 13 triathletes were assessed. Athletes from the CG were asked to maintain their training routines, whereas triathletes from the EG modified their running plans, but maintained their swimming and cycling routines. Testing was completed at week zero (pre) and week 5 (post) to monitor changes over the course of a 5-week training program. This would allow coaches and other professionals to have further knowledge about the effect of a low-volume and high-intensity running plan and the effects that this program had on athletic performance and muscular performance parameters.
Sixteen male triathletes (age = 33 ± 5 years, age range = 24 to 42 years, body mass = 74 ± 5 kg, height = 176 ± 9 cm) volunteered for the study, which was performed according to the ethical standards established by the Helsinki Declaration (2013) and was approved by the local ethical committee of the University of Jaen (Spain). Inclusion criteria were (a) older than 18 years, (b) actively competing in races, (c) a clean bill of health for the past 6 months, and (d) not engaged in a high-intensity training program. Three of the triathletes did not complete the study because of illness during the intervention period, and their data were excluded. Each signed a written informed consent before participation, completed a detailed questionnaire, and recorded race distances and times, training type, total distance, and training duration, which were confirmed by their respective coaches. The group competed in a sprint-distance triathlon race to validate the current performance status. Further information about participants—demographic and training background—is shown in Table 1.
The study was conducted between March and April 2015. At the time of these observations, the triathletes had completed between 3 and 4 months of training. A parallel 2-group, longitudinal (pre and post) design was used. Thus, physical tests were performed before (pretest) and after (posttest) the 5-week intervention period. The triathletes were assigned and matched to 2 groups, EG and CG, based on their performance in a sprint-distance triathlon competition (overall race time). To investigate the effect of a HIIT-based running program, triathletes from the CG were asked to maintain their training routines, whereas triathletes from the EG modified their running plans, but maintained their swimming and cycling routines. Therefore, during the HIIT period, the CG performed continuous moderate-intensity training sessions (for swimming, cycling, and running), whereas the EG implemented their continuous moderate-intensity sessions for swimming and cycling and HIIT for running.
All HIIT sessions performed within this training program have been investigated in previous studies on endurance athletes (1,8,31) and training volume and intensity were prescribed according to these works. Instructions for athletes regarding exercise intensity were given according to running pace, in terms of kilometers per hour (kmh). For this purpose, the variable used was the velocity associated with V̇o2max (VVO2max) which was indirectly estimated through the velocity of a 3000-m race (11,18), information reported from the coaches.
The HIIT program included 3–4 sessions per week for 5 weeks. This running program led to a reduction of average weekly running distance in the EG (−69.8%, from 33.6 km per week before training program to 10.14 km per week during training program). A description of the 5-week HIIT-based program is reported in Table 2.
Materials and Testing
The triathletes were instructed to refrain from intense exercise two days preceding testing and to perform the last HIIT session 3 days before the posttest. They were not allowed to eat during the hour preceding the test or to consume coffee or other products containing caffeine during the preceding 3 hours. Pretesting and posttesting were conducted at the same time of day to avoid the influence of the circadian rhythm and under similar environmental conditions (20–24° C).
Either at pretest or posttest, participation involved the execution of a sprint-distance triathlon race (750-m swimming, 20-km cycling, and 5-km running), which was completely performed in simulated conditions, in the same sports facilities (closer than 100 m to each other). The triathlon involved swimming in an eight-lane, 25-m pool; and cycling on their own road racing bicycles, connected to the same electromagnetically braked roller (T2170; Tacx Vortex, Wassenaar, the Netherlands), which was calibrated to quantify and adjust wheel-ergometer rolling resistance to 1.1–1.6 kg, as prescribed by the manufacturer; and running on an outdoor 400-m synthetic track.
In both occasions (pretest and posttest), just before starting the race and after a standardized warm-up, the participants performed jumping tests (countermovement [CMJ] and squat jumps [SJ]) as baseline values. These measurements were repeated 3 more times, after swimming (Post-Sw), after cycling (Post-Cy), and after running (Post-Ru) to monitor the neuromuscular response during the competition. The participants were experienced athletes who performed jumping tests in their daily training sessions. Moreover, to make sure the execution was correct, a familiarization session was conducted during the last training session before testing. The CMJ and SJ were recorded using the OptoGait system (Microgate, Bolzano, Italy), which has been previously used in similar studies (21). Subjects performed two trials with a 15-second recovery period between them, and the best trial was used for the statistical analysis.
The elapsed time (seconds) for the swimming, cycling, and running stages, and overall triathlon (transition times excluded) were registered for the subsequent analysis. Participants were experienced triathletes who had competed in these events; thus, the only instructions were to finish the race as fast as they could (transitions included). No other guidelines were provided as to exercise intensity, apart from the participants being informed that they were to exercise at an intensity of their own choice.
Additionally, to control the exhaustion level after the race and possible adaptations to the training program, some parameters were registered at both pretest and posttest: cardiovascular response—in terms of heart rate, in beats per minute—was monitored (Garmin Forerunner 405, Garmin International Inc., Olathe, KS, USA) throughout the race, and the average heart rate (HRmean) during every stage of the race was used for the analysis; the rate of perceived exertion (RPE) was recorded on the 6–20 Borg scale (5) immediately after the race; and blood lactate accumulation (BLa), at 1-minute after the race, was measured via fingertip blood samples, which were analyzed with a portable lactate analyzer (Scout Lactate; SensLab GmbH, Leipzig, Germany).
Descriptive statistics are represented as mean (SD). Tests of normal distribution and homogeneity (Shapiro-Wilk and Levene's, respectively) were conducted on all data before analysis. Paired t-test was used to compare demographic data, body composition, and training background of participants. A 2 × 2 analysis of variance (ANOVA) with repeated measures (group × measurement) was conducted for the dependent variables (time for swimming, cycling, running, and overall triathlon; and vertical jumping ability). The alpha was adjusted by Bonferroni correction. Nonparametric statistics were used with ordinal data—RPE—(Wilcoxon test, for within-group differences; Mann-Whitney U-test, for between-group comparison). Additionally, the magnitude of the differences between values was also interpreted using the Cohen's d effect size (ES) (30). Effect sizes of less than 0.4 represented a small magnitude of change, whereas 0.41–0.7 and greater than 0.7 represented moderate and large magnitudes of change, respectively (30). A Pearson correlation analysis was performed between the post-pre increase in elapsed time (ΔSw_time, ΔCy_time, ΔRu_time, and ΔOverall_time, respectively), with the post-pre increase in baseline CMJ and SJ values (ΔCMJ and ΔSJ). Based on the findings from the correlation analysis, a simple linear regression analysis was used to predict ΔRu_time and ΔOverall_time from the ΔCMJ during the intervention. The level of significance was p ≤ 0.05. The data analysis was performed using SPSS (version 21; SPSS Inc., Chicago, IL, USA).
In a comparison between the CG and EG before the training program (pretest), no significant differences (p ≥ 0.05) were found in demographic data or in body composition parameters. As for the characteristics of training routines and athletic level, the results obtained in both the CG and EG were similar with no significant differences (p ≥ 0.05) (Table 1).
The results obtained regarding the effect of the training program on athletic performance are presented in Figure 1 and Table 3 (individual responses). Both the CG and EG showed similar athletic levels with no significant differences in swimming (p = 0.511), cycling (p = 0.995), or running (p = 0.355) before the intervention period (at pretest). However, according to 2 × 2 ANOVA, EG and CG swimming and running times were different (p ≤ 0.05) after training program. Significant group-by-training interaction was found in the athletic performance after 5 weeks of training: the EG improved swimming time (2.90%, p = 0.013, ES = 0.438) and 5-km running performance (3.93%, p = 0.001, ES = 0.667), whereas the CG remained unchanged (p ≥ 0.05, ES < 0.4).
Cardiovascular response during every stage and RPE and BLa after the race are shown in Table 4. No significant differences (p ≥ 0.05) between groups were found at pretest or posttest. After the HIIT intervention, neither the CG nor the EG experienced significant alterations in any variable analyzed (p ≥ 0.05, ES < 0.4).
The neuromuscular response to a sprint-distance triathlon race, measured by means of vertical jump ability (CMJ and SJ), and the effect of the five-week intervention period on this response are shown in Figure 2. Both the CG and EG showed similar performance before the HIIT intervention (CMJ: 30.5 and 30.98 cm; SJ: 29.77 and 29.43 cm, for the EG and CG, respectively; p ≥ 0.05), but the performance was different after the training program (p ≤ 0.05). Significant group-by-training interaction was found in vertical jumping ability: the EG improved CMJ (+9.21%, p = 0.015, ES = 1.498) and SJ performance (+5.9%, p = 0.026, ES = 1.065), whereas the CG experienced nonsignificant impairments in CMJ (−3.0%, p = 0.373, ES = 0.505) and SJ (−1.8%, p = 0.228, ES = 0.413). Concerning the dynamic of CMJ and SJ during the race, the repeated-measures analysis showed no significant changes (p ≥ 0.05) at pretest or posttest for both the CG and EG.
The Pearson correlation analysis showed significant correlations between ΔCMJ and ΔSJ with ΔRu_time (p < 0.001) and between ΔCMJ and ΔOverall_time (p = 0.040). A linear regression analysis showed that ΔCMJ predicted both the ΔRu_time (R = 0.748; R2 = 0.559; p = 0.008) and the ΔOverall_time (R = 0.625; R2 = 0.391; p = 0.048).
The major finding of the present study was that the inclusion of a HIIT-based running plan with a reduction in training volume not only resulted in improved muscular performance (∼6–9% in vertical jump ability) but also increased athletic performance during a sprint-distance triathlon (improvements of 2.90% in swimming time, 0.47% in cycling time, and 3.93% in running time). Conversely, the triathletes from the CG, who continued their usual high-volume and low-/moderate-intensity training program, did not experience significant changes in muscular performance parameters or racing times. Additionally, the improvements reported by the EG in athletic performance were not accompanied by significant changes in the physiological response during the simulated race or in exhaustion level reached, which indicates that the triathletes experienced some adaptations that allow them to race faster with the same physiological impact.
To justify this study, some facts must be considered. First, a growing body of literature points to mean training intensity over a season as the key factor for performance improvement (8,20). It is also known that the risk of injury increases with increased weekly running distances in triathletes (9,28). With regard to this, the current running program led to a substantial reduction in average weekly running distance in the EG (−69.8%, from 33.6 km·wk−1 before the training program to 10.14 km·wk−1 during the plan), and an increase in average running pace (participants did not include HIIT sessions in their training routines before this training program).
Second, independent of the differences in distance and duration, all triathlons are considered continuous endurance events (29). Despite the physiological basis of aerobic endurance being not clearly understood (6), it is well known that some of the major physiological determinants of endurance performance are work economy, lactate threshold, and maximal oxygen consumption (6). It has been shown that the presence of HIIT in endurance athletes' training programs facilitates the aforementioned adaptations (1,12,17,19). Likewise, the importance of high volumes performed at low/moderate intensity for maximizing athletic performance in endurance sports has also been demonstrated (22). For both reasons, a combination of high training volume at low exercise intensities and lower training volumes of HIIT seems to be necessary to obtain optimal development of endurance performance (7,8,20,27). In the current training program, all of these suggestions have been taken into consideration by ensuring the presence of low/moderate intensity over long periods of time (through swimming and cycling sessions) and by reducing weekly running volumes and increasing the average intensity of running sessions by means of HIIT.
Regarding the results obtained, this study is in agreement with previous works that have shown the effectiveness of HIIT programs for improving endurance performance and associated physiological variables (1,10,12,17,19). Focusing on athletic performance of trained individuals, the finding of a ∼3–4% improvement in swimming and running performance after HIIT intervention is similar to the findings of Laursen et al. (19), who reported a 4.4% improvement in a 40-km cycling time trial after HIIT. Likewise, previous works (1,12) have reported an improvement in 3-km and 10-km running performance (3–7%) in endurance runners after different HIIT programs. To our knowledge, just 1 study (16) showed neither improvements nor decrements in athletic performance after a HIIT intervention in swimmers. As the authors explained, those results might be due to the extensive experience of the participants in HIIT exercises—criterion not met in the rest of studies. Previous studies performing HIIT interventions have been conducted in single sports, such as swimming (16), running (1,12,17), or cycling (19), but no previous work has proposed any strategy to insert and apply the HIIT methodology to a triathlon. In this regard, this study shows that the presence of HIIT in the triathletes' running plan not only improves running performance but also swimming performance during a sprint-distance competition, which might be associated with the “cross-training” principle (a phenomenon that refers to the cross-transfer of training effects from one sport to another) (24).
The precise mechanisms by which HIIT can improve endurance performance remain undetermined. Potential adaptations that may contribute to the improvement in endurance performance after HIIT include the increased ability of skeletal muscle to buffer hydrogen ions (32) and increased Na+/K+ pump capacity (1), anaerobic capacity (19), and motor unit activation (10,17). Although the acute neuromuscular, physiological, and metabolic responses were not directly controlled in the present study, the data reported on the dynamic of HR, BLa, and muscular performance parameters during a sprint-distance triathlon before and after a 5-week HIIT plan let us gain some insight into the effectiveness of this training program. The results showed that a 5-week HIIT-based running plan improved vertical jumping capacity in triathletes, whereas triathletes who continued training at low-moderate intensities with high volumes (CG) did not experience changes in muscular performance variables. Additionally, the regression model performed in this study confirms the relationship between the gains in explosive muscular power and athletic performance improvements during a sprint triathlon. This finding supports the conclusion reported by Nummela et al. (25), who noted the importance of neuromuscular characteristics in determining running economy and, thereby, running performance. Likewise and regarding cycling performance, Faria et al. (14) indicated that peripheral adaptations in working muscles play a more important role for enhanced submaximal cycling capacity than central adaptations. And finally, with regard to the swimming performance improvement (although not statistically significant), the gains reported in explosive muscular power seem to maximize the positive effect of leg kick on the swimming speed—obvious direct generation of propulsive forces from the legs (15).
Hence, the improvements reported in this study highlight the effectiveness of a HIIT-based training program for improving explosive muscular power and accentuate the importance of neuromuscular performance in endurance performance. Nevertheless, the exact mechanism by which muscular performance improves after a period of HIIT in trained athletes is still unknown. What is clear is that a faster running pace during the HIIT sessions will demand higher levels of neural drive, will lead to higher levels of activation of the anaerobic glycolysis, and will recruit additional fast-twitch motor units for relatively short durations (26), which may be the physiological basis of improvements reported in this study.
Another important finding was the lack of changes in the physiological response during the simulated race at posttest, according to pretest data. The CG did not experience alterations in athletic performance and, thus, a similar cardiovascular response and BLa might be expected at pretest and posttest. However, the EG improved athletic performance at posttest, which was not accompanied by significant changes in the physiological response during the simulated race nor in exhaustion level reached, which indicates that the triathletes experienced some adaptations that allowed them to race faster with the same physiological impact. A right shift in the lactate threshold, so that higher running speeds are achieved at equivalent BLa levels, is a well-known consequence of endurance training and a determinant of endurance performance (23). Therefore, as well as muscle power improvements, physiological adaptations to the HIIT period might be determinants of athletic performance improvements reported in the current study.
The current study shows that a low-volume HIIT-based running plan combined with the already high training volumes of these triathletes in swimming and cycling is effective for improving athletic performance during a simulated sprint-distance triathlon competition. This improvement is suggested to be due to improved neuromuscular characteristics that were transferred into improved muscle power and work economy.
From a practical point of view, the current study offers insight into a training method prescription for triathletes by determining the effectiveness of a HIIT-based running program, which not only causes improvements in muscular performance parameters and allows athletes to enhance their athletic performance in a competition but also facilitates the reduction of a major risk factor for injury in triathletes such as weekly running distances.
1. Bangsbo J, Gunnarsson TP, Wendell J, Nybo L, Thomassen M. Reduced volume and increased training intensity elevate muscle Na+-K+ pump alpha2-subunit expression as well as short- and long-term work capacity in humans. J Appl Physiol 107: 1771–1780, 2009.
2. Billat LV. Interval training
for performance: A scientific and empirical practice. Special recommendations for middle- and long-distance running. Part I: Aerobic interval training
. Sport Med 31: 13–31, 2001.
3. Billat LV. Interval training
for performance: A scientific and empirical practice. Special recommendations for middle- and long-distance running. Part II: Anaerobic interval training
. Sports Med 31: 75–90, 2001.
4. Billat V, Lepretre P-M, Heugas A-M, Laurence M-H, Salim D, Koralsztein JP. Training and bioenergetic characteristics in elite male and female Kenyan runners. Med Sci Sports Exerc 35: 297–304, 2003. discussion 305–6. Available at: http://www.ncbi.nlm.nih.gov/pubmed/12569219
5. Borg G. Psychophysical bases of perceived exertion. Med Sci Sports Exerc 14: 377–381, 1982.
6. Bosquet L, Léger L, Legros P. Methods to determine aerobic endurance. Sport Med 32: 675–700, 2002.
7. Buchheit M, Laursen PB. High-intensity interval training
, solutions to the programming puzzle: Part I: Cardiopulmonary emphasis. Sport Med 43: 313–338, 2013.
8. Buchheit M, Laursen PB. High-intensity interval training
, solutions to the programming puzzle. Part II: Anaerobic energy, neuromuscular load and practical applications. Sport Med 43: 927–954, 2013.
9. Burns J, Keenan AM, Redmond AC. Factors associated with triathlon-related overuse injuries. J Orthop Sports Phys Ther 33: 177–184, 2003.
10. Creer AR, Ricard MD, Conlee RK, Hoyt GL, Parcell AC. Neural, metabolic, and performance adaptations to four weeks of high intensity sprint-interval training
in trained cyclists. Int J Sports Med 25: 92–98, 2004. Available at: http://www.ncbi.nlm.nih.gov/pubmed/14986190
11. Demarie S, Koralsztein JP, Billat V. Time limit and time at VO2max' during a continuous and an intermittent run. J Sports Med Phys Fitness 40: 96–102, 2000.
12. Esfarjani F, Laursen PB. Manipulating high-intensity interval training
: Effects on VO2max, the lactate threshold and 3000m running performance in moderately trained males. J Sci Med Sport 10: 27–35, 2007.
13. Esteve-Lanao J, San Juan AF, Earnest CP, Foster C, Lucia A. How do endurance runners actually train? Relationship with competition performance. Med Sci Sports Exerc 37: 496–504, 2005.
14. Faria EW, Parker DL, Faria IE. The Science of cycling: physiology and training. Part I. Sport Med 35: 285–312, 2005.
15. Gourgoulis V, Boli A, Aggeloussis N, Toubekis A, Antoniou P, Kasimatis P, Vezos N, Michalopoulou M, Kambas A, Mavromatis G. The effect of leg kick on sprint front crawl swimming. J Sports Sci, 2014.
16. Kilen A, Larsson TH, Jørgensen M, Johansen L, Jørgensen S, Nordsborg NB. Effects of 12 weeks high-intensity & reduced-volume training in elite athletes. PLoS One 9: e95025, 2014.
17. Kohn TA, Essén-Gustavsson B, Myburgh KH. Specific muscle adaptations in type II fibers after high-intensity interval training
of well-trained runners. Scand J Med Sci Sports 21: 765–772, 2011.
18. Lacour JR, Padilla-Magunacelaya S, Barthélémy JC, Dormois D. The energetics of middle-distance running. Eur J Appl Physiol Occup Physiol 60: 38–43, 1990. Available at: http://www.ncbi.nlm.nih.gov/pubmed/2311592
19. Laursen PB, Shing CM, Peake JM, Coombes JS, Jenkins DG. Influence of high-intensity interval training
on adaptations in well-trained cyclists. J Strength Cond Res 19: 527–533, 2005.
20. Laursen PB. Training for intense exercise performance: High-intensity or high-volume training? Scand J Med Sci Sports 20(Suppl 2): 1–10, 2010.
21. Lehance C, Binet J, Bury T, Croisier JL. Muscular strength, functional performances and injury risk in professional and junior elite soccer players. Scand J Med Sci Sports 19: 243–251, 2009.
22. Lucía A, Hoyos J, Pérez M, Santalla A, Chicharro JL. Inverse relationship between VO2max and economy/efficiency in world-class cyclists. Med Sci Sports Exerc 34: 2079–2084, 2002.
23. Messonnier L, Freund H, Denis C, Dormois D, Dufour A-B, Lacour J-R. Time to exhaustion at VO(2)max is related to the lactate exchange and removal abilities. Int J Sports Med 23: 433–438, 2002. Available at: http://www.ncbi.nlm.nih.gov/pubmed/12215963
24. Millet GP, Candau RB, Barbier B, Busso T, Rouillon JD, Chatard JC. Modelling the transfers of training effects on performance in elite triathletes. Int J Sports Med 23: 55–63, 2002.
25. Nummela A, Paavolainen L, Sharwood K, Lambert M, Noakes T, Rusko H. Neuromuscular factors determining 5 km running performance and running economy in well-trained athletes. Eur J Appl Physiol 97: 1–8, 2006.
26. Ross A, Leveritt M, Riek S. Neural influences on sprint running: training adaptations and acute responses. Sport Med 31: 409–425, 2001.
27. Seiler S. What is best practice for training intensity and duration distribution in endurance athletes
? Int J Sports Physiol Perform 5: 276–291, 2010.
28. Shaw T, Howat P, Trainor M, Maycock B. Training patterns and sports injuries in triathletes. J Sci Med Sport 7: 446–450, 2004.
29. Suriano R, Bishop D. Physiological attributes of triathletes. J Sci Med Sport 13: 340–347, 2010.
30. Thomas RJ, Silverman S, Nelson J. Research Methods in Physical Activity (7th ed.). Champaign, IL: Human Kinetics, 2015.
31. Vuorimaa T, Vasankari T, Rusko H. Comparison of physiological Strain and muscular performance of athletes during two intermittent running exercises at the velocity associated with VO2max. Int J Sports Med 21: 96–101, 2000.
32. Weston AR, Myburgh KH, Lindsay FH, Dennis SC, Noakes TD, Hawley JA. Skeletal muscle buffering capacity and endurance performance after high-intensity interval training
by well-trained cyclists. Eur J Appl Physiol Occup Physiol 75: 7–13, 1996.