High-intensity cycle interval training improves cycling and running performance in triathletes

The Characteristics of Endurance Events with a Variable Pacing Profile-Time to Embrace the Concept of "Intermittent Endurance Events"?

A variable pacing profile is common in different endurance events. In these races, several factors, such as changes in elevation or race dynamics, lead participants to perform numerous surges in intensity. These surges are so frequent that certain events, such as cross-country (XC) skiing, mountain biking (MTB), triathlon, and road cycling, have been termed "intermittent endurance events". The characteristics of these surges vary depending on the sport: MTB and triathlon require athletes to perform numerous short (<10 s) bouts; XC skiing require periods of short- and moderate-(30 s to 2 min) duration efforts, while road cycling is comprised of a mix of short-, moderate-, and long-duration (>2 min) bouts. These bouts occur at intensities above the maximal metabolic steady state (MMSS), with many efforts performed at intensities above the athletes' maximal aerobic power or speed (MAP/MAS) (i.e., supramaximal intensities). Given the factors that influence the requirement to perform surges in these events, athletes must be prepared to always engage in a race with a highly stochastic pace. The aim of this review is to characterize the variable pacing profile seen in endurance events and to discuss how the performance of multiple maximal and supramaximal surges in intensity can affect how athletes fatigue during a race and influence training strategies that can lead to success in these races.

The Effects of Sprint Interval Training on Physical Performance: A Systematic Review and Meta-Analysis

ABSTRACT

Hall, AJ, Aspe, RR, Craig, TP, Kavaliauskas, M, Babraj, J, and Swinton, PA. The effects of sprint interval training on physical performance: a systematic review and meta-analysis. J Strength Cond Res 37(2): 457-481, 2023-The present study aimed to synthesize findings from published research and through meta-analysis quantify the effect of sprint interval training (SIT) and potential moderators on physical performance outcomes (categorized as aerobic, anaerobic, mixed aerobic-anaerobic, or muscular force) with healthy adults, in addition to assessing the methodological quality of included studies and the existence of small study effects. Fifty-five studies were included (50% moderate methodological quality, 42% low methodological quality), with 58% comprising an intervention duration of ≤4 weeks and an array of different training protocols. Bayesian's meta-analysis of standardized mean differences (SMD) identified a medium effect of improved physical performance with SIT (ES 0.5 = 0.52; 95% credible intervals [CrI]: 0.42-0.62). Moderator analyses identified overlap between outcome types with the largest effects estimated for anaerobic outcomes (ES 0.5 = 0.61; 95% CrI: 0.48-0.75). Moderator effects were identified for intervention duration, sprint length, and number of sprints performed per session, with larger effects obtained for greater values of each moderator. A substantive number of very large effect sizes (41 SMDs > 2) were identified with additional evidence of extensive small study effects. This meta-analysis demonstrates that short-term SIT interventions are effective for developing moderate improvements in physical performance outcomes. However, extensive small study effects, likely influenced by researchers analyzing many outcomes, suggest potential overestimation of reported effects. Future research should analyze fewer a priori selected outcomes and investigate models to progress SIT interventions for longer-term performance improvements.

Effects of Training on Cardiorespiratory Fitness in Triathletes: A Systematic Review and Meta-Analysis

Triathlon is an aerobic sport, which is commonly measured by maximal aerobic consumption (VO₂max). Objective: to analyze the changes produced in cardiorespiratory and physiological measurements during practice, which determine triathletes’ performance level. A systematic review and a meta-analysis based on PRISMA protocol and registered in PROSPERO (CRD42020189076) was conducted. The research was performed using PubMed, SPORTDiscus, Embase, Dialnet, Web of Science (WOS) and MEDLINE databases during February and March 2020. Studies that measured cardiorespiratory variables in triathletes published in the last 10 years were included. Results: 713 articles were identified, with 25 studies selected for the systematic review and five articles for the meta-analysis. These articles concluded that the main cardiorespiratory variables that determine triathletes’ performance were modified depending on the triathlon segment performed and the athletes’ sex and age. The meta-analysis showed no conclusive results related to the effects of changes in VO₂max in triathletes’ performance [SMD = −0.21; 95%CI: (−0.84 to 0.43)]. Conclusions: cardiorespiratory fitness, in terms of VO₂max and ventilatory thresholds, is the strongest predictor of performance in triathlon. This response may be affected depending on the triathlon segment performed and the athlete’s age or sex, leading to both physiological and biomechanical alterations that affect competition performance.

Comparison of training responses and performance adaptations in endurance-trained men and women performing high-intensity interval training

The efficacy of high-intensity interval training (HIIT) to elicit physiological and performance adaptations in endurance athletes has been established in men and to a lesser extent in women. This study compared lactate threshold (LT₂) and performance adaptations to HIIT between men and women. Nine male and eight female cyclists and triathletes completed trials to determine their LT₂ and 40 km cycling performance before, and after 10 HIIT sessions. Each HIIT session consisted of 10 × 90 s at peak power output, separated by 60 s active recovery. Main effects showed that HIIT improved peak power output (p = 0.05; ES: 0.2); relative peak power output (W.kg^-1; p = 0.04; ES: 0.3 and W.kg^-0.32; p = 0.04; ES: 0.3); incremental time to fatigue (p = 0.01; ES: 0.4), time trial time (p < 0.001; ES: 0.7) and time trial power output (p < 0.001; ES: 0.7) equally in both sexes. Although LT₂ power output explained 77% of the performance improvement in women, no variable explained the performance improvement in men, suggesting another mechanism(s) was involved. Although HIIT improved cycling performance in men and women, it might not be appropriate to evaluate the effectiveness of HIIT using the same variables for both sexes.

Running economy and effort after cycling: Effect of methodological choices

Prior exercise can negatively affect movement economy of a subsequent task. However, the impact of cycling exercise on the energy cost of subsequent running is difficult to ascertain, possibly because of the use of different methods of calculating economy. We examined the influence of a simulated cycling bout on running physiological cost (running economy, heart rate and ventilation rates) and perceptual responses (ratings of perceived exertion and effort) by comparing two running bouts, performed before and after cycling using different running economy calculation methods. Seventeen competitive male triathletes ran at race pace before and after a simulated Olympic-distance cycling bout. Running economy was calculated as V̇O₂ (mL∙kg^-1∙min^-1), oxygen cost (EO₂, mL∙kg^-1∙m^-1) and aerobic energy cost (E_aer, J∙kg^-1∙m^-1). All measures of running economy and perceptual responses indicated significant alterations imposed by prior cycling. Despite a good level of agreement with minimal bias between calculation methods, differences (p < 0.05) were observed between E_aer and both V̇O₂ and EO₂. The results confirmed that prior cycling increased physiological cost and perceptual responses in a subsequent running bout. It is recommended that E_aer be calculated as a more valid measure of running economy alongside perceptual responses to assist in the identification of individual responses in running economy following cycling.

Running Stride Length And Rate Are Changed And Mechanical Efficiency Is Preserved After Cycling In Middle-Level Triathletes

Although cycling impairs the subsequent metabolic cost and performance of running in some triathletes, the consequences on mechanical efficiency (Eff) and kinetic and potential energy fluctuations of the body center of mass are still unknown. The aim of this study was to investigate the effects of previous cycling on the cost-of-transport, Eff, mechanical energy fluctuations (W_tot), spring stiffness (K_leg and K_vert) and spatiotemporal parameters. Fourteen middle-level triathletes (mean ± SD: maximal oxygen uptake, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\dot{{\rm{V}}}$$\end{document}V˙O_2max = 65.3 ± 2.7 ml.kg⁻¹.min⁻¹, age = 30 ± 5 years, practice time = 6.8 ± 3.0 years) performed four tests. Two maximal oxygen uptake tests on a cycle ergometer and treadmill, and two submaximal 20-minute running tests (14 km.h⁻¹) with (prior-cycling) and without (control) a previous submaximal 30-minute cycling test. No differences were observed between the control and post-cycling groups in Eff or W_tot. The Eff remains unchanged between conditions. On the other hand, the K_vert (20.2 vs 24.4 kN.m⁻¹) and K_leg (7.1 vs 8.2 kN.m⁻¹, p < 0.05) were lower and the cost-of-transport was higher (p = 0.018, 3.71 vs 3.31 J.kg⁻¹.m⁻¹) when running was preceded by cycling. Significantly higher stride frequency (p < 0.05, 1.46 vs 1.43 Hz) and lower stride length (p < 0.05, 2.60 vs 2.65 m) were observed in the running after cycling condition in comparison with control condition. Mechanical adjustments were needed to maintain the Eff, even resulting in an impaired metabolic cost after cycling performed at moderate intensity. These findings are compatible with the concept that specific adjustments in spatiotemporal parameters preserve the Eff when running is preceded by cycling in middle-level triathletes, though the cost-of-transport increased.

Neuromuscular Adaptations to Short-Term High-Intensity Interval Training in Female Ice-Hockey Players

Kinnunen, J-V, Piitulainen, H, and Piirainen, JM. Neuromuscular adaptations to short-term high-intensity interval training in female ice-hockey players. J Strength Cond Res 33(2): 479-485, 2019-High-intensity interval training (HIIT)-related neuromuscular adaptations, changes in force production, and on-ice performance were investigated in female ice-hockey players during preseason. Fourteen Finnish championship level ice-hockey players (average age 22 ± 3 years) participated in 2½-week HIIT. Both spinal (H-reflex) and supraspinal (V-wave) neuromuscular responses of the soleus muscle were recorded before and after the training period. Static jump (SJ) and countermovement jump heights, plantarflexor maximum voluntary contraction (MVC), and rate of force development (RFD) were measured. In addition, soleus and tibialis anterior muscle activations (electromyography) were measured during MVC and RFD tests. During on-ice training, skating speed and acceleration tests were performed. Subjects significantly improved their plantarflexion MVC force (11.6 ± 11.2%, p < 0.001), RFD (15.2 ± 15.9%, p < 0.01), and SJ (4.8 ± 7.6%, p ≤ 0.05). Voluntary motor drive to the soleus muscle (V-wave amplitude) increased by 16.0 ± 15.4% (p < 0.01), and coactivation of the tibialis anterior muscle during the plantarflexion RFD test was reduced by -18.9 ± 22.2% (p ≤ 0.05). No change was observed in spinal α-motoneuron excitability (H-reflex) during MVC or in on-ice performance. These results indicate that HIIT can be used to improve athletes' capability to produce maximal and explosive forces, likely through enhanced voluntary activation of their muscles and reduced antagonist coactivation. Therefore, HIIT can be recommended in preseason training to improve neuromuscular performance. However, a longer than 2½-week HIIT period is needed to improve on-ice performance in female ice-hockey players.

Sprinting After Having Sprinted: Prior High-Intensity Stochastic Cycling Impairs the Winning Strike for Gold

Bunch riding in closed circuit cycling courses and some track cycling events are often typified by highly variable power output and a maximal sprint to the finish. How criterium style race demands affect final sprint performance however, is unclear. We studied the effects of 1 h variable power cycling on a subsequent maximal 30 s sprint in the laboratory. Nine well-trained male cyclists/triathletes (O_2peak 4.9 ± 0.4 L⋅min^-1; mean ± SD) performed two 1 h cycling trials in a randomized order with either a constant (CON) or variable (VAR) power output matched for mean power output. The VAR protocol comprised intervals of varying intensities (40–135% of maximal aerobic power) and durations (10 to 90 s). A 30 s maximal sprint was performed before and immediately after each 1 h cycling trial. When compared with CON, there was a greater reduction in peak (-5.1 ± 6.1%; mean ± 90% confidence limits) and mean (-5.9 ± 5.2%) power output during the 30 s sprint after the 1 h VAR cycle. Variable power cycling, commonly encountered during criterium and triathlon races can impair an optimal final sprint, potentially compromising race performance. Athletes, coaches, and staff should evaluate training (to improve repeat sprint-ability) and race-day strategies (minimize power variability) to optimize the final sprint.

Changes in exercise capacity and serum BDNF following long-term sprint interval training in well-trained cyclists

The study determined the effects of sprint interval training on the acute and chronic changes of serum brain-derived neurotrophic factor (BDNF) and aerobic capacity. Twenty-six cyclists were divided into experimental (E) and control groups. Both groups executed a 6-month exercise intervention involving high-intensity interval training (HIIT) and continuous endurance training (CET) with group E replacing HIIT and CET sessions with sprint interval training (SIT) that was executed twice a week. Two exercise tests were administered prior to the intervention and at 2 and 6 months after study outset. Incremental exercise test assessed aerobic capacity by measuring maximal oxygen uptake and work output; the sprint interval exercise test (SIXT) comprises 3 sets of four 30-s all-out repetitions interspersed with 90 s of rest with sets separated by 25-40 min of active recovery. Oxygen uptake, work output, BDNF, and vascular endothelial growth factor A (VEGF-A) concentrations (baseline, 10 min after first set, and 10 and 60 min after third SIXT set) were taken during the SIXT. Significant decreases in BDNF relative to baseline values were observed 10 min after the first set and 60 min after the third set in group E at the 2- and 6-month assessments. Increases in baseline VEGF-A after 2 and 6 months of training and increases in maximal oxygen uptake after 2 months of training were also observed only in group E. The inclusion of SIT with HIIT and CET shows positive long-term effects, including increased maximal oxygen uptake and baseline VEGF-A and a reduction in BDNF below baseline levels during and after SIXT.

Training Intensity Distribution and Changes in Performance and Physiology of a 2nd Place Finisher Team of the Race across America Over a 6 Month Preparation Period

Aim: To monitor the training intensity distribution (TID) and the development of physiological and performance parameters.

Methods: During their preparation period for the RAAM, 4 athletes (plus 1 additional backup racer) performed 3 testing sessions; one before, one after 3, and one after 6 months of training. VO_2max, maximal rate of lactate accumulation (dLa/dt_max), critical power, power output at lactate minimum (MLSS_P), peak and mean power output during a sprint test, heart rate recovery, isometric strength, jumping height, and body composition were determined. All training sessions were recorded with a power meter. The endurance TID was analyzed based on the time in zone approach, according to a classical 3-zone model, including all power data of training sessions, and a power specific 3-zone model, where time with power output below 50% of MLSS_P was not considered.

Results: The TID using the classical 3-zone model reflected a pyramidal TID (zone 1: 63 ± 16, zone 2: 28 ± 13 and zone 3: 9 ± 4%). The power specific 3-zone model resulted in a threshold-based TID (zone 1: 48 ± 13, zone 2: 39 ± 10, zone 3: 13 ± 4%). VO_2max increased by 7.1 ± 5.3% (P = 0.06). dLa/dt_max decreased by 16.3 ± 8.1% (P = 0.03). Power output at lactate minimum and critical power increased by 10.3 ± 4.1 and 16.8 ± 6.2% (P = 0.01), respectively. No changes were found for strength parameters and jumps.

Conclusion: The present study underlines that a threshold oriented TID results in only moderate increases in physiological parameters. The amount of training below 50% of MLSSp (~28% of total training time) is remarkably high. Researchers, trainers, and athletes should pay attention to the different ways of interpreting training power data, to gain realistic insights into the TID and the corresponding improvements in performance and physiological parameters.

High-Intensity Cycling Training: The Effect of Work-to-Rest Intervals on Running Performance Measures

The work-to-rest ratio during cycling-based high-intensity interval training (HIT) could be important in regulating physiological and performance adaptations. We sought to determine the effectiveness of cycling-based HIT with different work-to-rest ratios for long-distance running. Thirty-two long-distance runners (age: 39 ± 8 years; sex: 14 men, 18 women; average weekly running training volume: 25 miles) underwent baseline testing (3-km time-trial, V[Combining Dot Above]O2peak and time to exhaustion, and Wingate test) before a 2-week matched-work cycling HIT of 6 × 10-second sprints with different rest periods (30 seconds [R30], 80 seconds [R80], 120 seconds [R120], or control). Three-kilometer time trial was significantly improved in the R30 group only (3.1 ± 4.0%, p = 0.04), whereas time to exhaustion was significantly increased in the 2 groups with a lower work-to-rest ratio (R30 group 6.4 ± 6.3%, p = 0.003 vs. R80 group 4.4 ± 2.7%, p = 0.03 vs. R120 group 1.9 ± 5.0%, p = 0.2). However, improvements in average power production were significantly greater with a higher work-to-rest ratio (R30 group 0.3 ± 4.1%, p = 0.8 vs. R80 group 4.6 ± 4.2%, p = 0.03 vs. R120 group 5.3 ± 5.9%, p = 0.02), whereas peak power significantly increased only in the R80 group (8.5 ± 8.2%, p = 0.04) but not in the R30 group (4.3 ± 6.1%, p = 0.3) or in the R120 group (7.1 ± 7.9%, p = 0.09). Therefore, cycling-based HIT is an effective way to improve running performance, and the type and magnitude of adaptation is dependent on the work-to-rest ratio.

Effect of 3-week high-intensity interval training on VO2max, total haemoglobin mass, plasma and blood volume in well-trained athletes

PURPOSE

This study examined the haematological adaptations to high-intensity interval training (HIT), i.e. total haemoglobin mass (tHb-mass), blood volume (BV), and plasma volume (PV), and its effects on VO2max in well-trained athletes.

METHODS

Twenty-seven male and eight female well-trained (VO2max 63.7 ± 7.7 ml/min/kg) athletes were randomly assigned to the HIT (HITG, N = 19) or the control group (CG, N = 16). Over a 3-week period, the HITG performed 11 HIT sessions, consisting of four 4-min interval bouts at an exercise intensity of 90-95 % of the individual maximal heart rate (HRmax), separated by 4-min active recovery periods. Before and 5 ± 2 days after the intervention, tHb-mass, BV and PV were determined by the CO-rebreathing method. VO2max was assessed in a laboratory treadmill test.

RESULTS

tHb-mass (from 753 ± 124 to 760 ± 121 g), BV (from 5.6 ± 0.8 to 5.6 ± 0.9 l) and PV (from 3.2 ± 0.5 to 3.2 ± 0.5 l) remained unchanged after HIT and did not show an interaction (group × time). Within the HITG, VO2max improved from baseline by +3.5 % (p = 0.011), but remained unchanged in the CG. No interaction (group × time) was seen for VO2max. The HITG showed a significant reduction in HRmax compared to the baseline measurement (-2.3 %, p ≤ 0.001), but HRmax remained unchanged in the CG. There was a significant interaction (group × time) for HRmax (p = 0.006). Also, oxygen pulse significantly increased only in HITG from 22.9 ± 4.4 to 23.9 ± 4.2 ml/beat, with no interaction (p = 0.150).

CONCLUSIONS

Eleven HIT sessions added to usual training did neither improve VO2max nor haematological parameters compared to the CG.

What predicts performance in ultra-triathlon races? - a comparison between Ironman distance triathlon and ultra-triathlon

Objective

This narrative review summarizes recent intentions to find potential predictor variables for ultra-triathlon race performance (ie, triathlon races longer than the Ironman distance covering 3.8 km swimming, 180 km cycling, and 42.195 km running). Results from studies on ultra-triathletes were compared to results on studies on Ironman triathletes.

Methods

A literature search was performed in PubMed using the terms “ultra”, “triathlon”, and “performance” for the aspects of “ultra-triathlon”, and “Ironman”, “triathlon”, and “performance” for the aspects of “Ironman triathlon”. All resulting papers were searched for related citations. Results for ultra-triathlons were compared to results for Ironman-distance triathlons to find potential differences.

Results

Athletes competing in Ironman and ultra-triathlon differed in anthropometric and training characteristics, where both Ironmen and ultra-triathletes profited from low body fat, but ultra-triathletes relied more on training volume, whereas speed during training was related to Ironman race time. The most important predictive variables for a fast race time in an ultra-triathlon from Double Iron (ie, 7.6 km swimming, 360 km cycling, and 84.4 km running) and longer were male sex, low body fat, age of 35–40 years, extensive previous experience, a fast time in cycling and running but not in swimming, and origins in Central Europe.

Conclusion

Any athlete intending to compete in an ultra-triathlon should be aware that low body fat and high training volumes are highly predictive for overall race time. Little is known about the physiological characteristics of these athletes and about female ultra-triathletes. Future studies need to investigate anthropometric and training characteristics of female ultra-triathletes and what motivates women to compete in these races. Future studies need to correlate physiological characteristics such as maximum oxygen uptake (VO_2max) with ultra-triathlon race performance in order to investigate whether these characteristics are also predictive for ultra-triathlon race performance.