Physiological correlates of simulated sprint-distance triathlon

The purpose of this study was to examine the relationship between simulated triathlon performance and physiological variables measured during conventional laboratory tests. Seven non-elite, competitive male triathletes completed incremental cycling and running tests in a random order, in addition to a simulated sprint-distance triathlon trial (750 m swim, 500 kJ bike, 5 km run) using a 25 m pool, an electromagnetically braked cycle ergometer and motorised treadmill. There were no significant correlations between overall performance time and either running or cycling incremental tests, however significant correlations were found between triathlon run time and both running and cycling incremental tests (Vpeak, r = -.900, p<0.05; V4mmol, r = -.822, p<0.05; Wpeak, r = -.844, p<0.05). Total simulated triathlon time was highly correlated to cycle time (r = .930, p<0.05) and mean cycling power output (r = -.956, p<0.05), whilst there was no significant correlation between either swim time or run time and overall performance time. For non-elite, competitive male triathletes, a performance assessment which better reflects the demands of the cycle phase of triathlon (i.e. a time-trial protocol) may provide a better indication of simulated sprint-distance triathlon performance in comparison to commonly used incremental laboratory tests. Furthermore, cycling performance appears more important to overall performance in simulated sprint-distance triathlon than swimming or running

Reliability of simulated sprint-distance triathlon

To assess reliability of simulated sprint-distance triathlon seven non-elite, male triathletes completed three trials (750 m swim, 20 km bike, 5 km run), using a 25 m pool, an electromagnetically braked cycle ergometer and motorised treadmill. Total times (h, min and s) were 1:17:37 ± 0:06:41, 1:18:22 ± 0:08:59 and 1:18:47 ± 0:09:56. Coefficient of variation (CV) for total performance time was 2.7% between trials 1&2 (CI = 1.7-6.0) and 2.3% between trials 2&3 (CI = 1.5-5.1). Performance CV’s for swim, cycle and run phases were also <5% between trials 2&3. These results show that for non-elite, competitive male triathletes, performance time in simulated sprint-distance triathlon is highly reproducible, with a CV comparable to endurance performances of similar duration (<5%)

Effects of residual fatigue on pace regulation during sprint-distance triathlon running

Introduction: It has been suggested that unique relationships exist between perceived exertion, pacing and physiological responses during triathlon. However, research to date has not clearly established how the interaction of these factors is affected by residual physiological fatigue, particularly during running performance over distances relevant to sprint-distance triathlon. This study therefore investigated the effects of the preceding swim and cycle on pacing strategy, perceived exertion, and physiological status during sprint-distance triathlon running. Methods: Eight amateur male triathletes (mean ± SD: age 36.0 ± 5.7 yrs, mass 75.7 ± 5.3 kg) completed two field-based performance trials. The first was a sprint-distance triathlon (0.75 km swim, 20 km cycle, 5 km run) and the second an isolated 5 km run time-trial, each separated by 7-18 days and utilising the same flat out-and-back road course. Wrist-mounted GPS devices (Garmin 310XT, UK) recorded performance time, running speed (km•h-1) and heart rate during each trial. Participants recorded ratings of perceived exertion (Borg 6-20 scale) every kilometre using a wrist-mounted recording sheet and pen. Core temperature (CorTemp, HQInc, USA), blood lactate concentration (Lactate Pro, Kodak, Japan) and body mass (to 0.1 kg; Seca 875) were also measured immediately prior to, and after, each run. Results: Performance time for isolated running (19:28 ± 00:32) was ~7% quicker than triathlon running (20:48 ± 00:43) (p<0.01), with a similar positive pacing strategy displayed throughout both trials (figure 1). Initial core temperature, blood lactate concentration and heart rate values were all significantly higher for the triathlon run compared to the isolated run (p<0.01), with no differences in final values for these measures. No significant differences were observed for initial RPE, rate of RPE increase, or final RPE between runs. Discussion/Conclusion: Prior swimming and cycling impair performance but do not affect pacing strategy during sprint-distance triathlon running. Reduced performance may be attributed to the residual physiological strain observed at the start of the triathlon run. However, the maintenance of scalar-linear increases in RPE appears to be the primary regulator of pacing strategy during triathlon running, with physiological responses only indirectly related to this process

Reliability of performance and associated physiological responses during simulated sprint-distance triathlon

Many different methods of simulating triathlon performance in controlled conditions have been developed without establishing the reliability of these assessments. The aim of this study was to determine the reliability of performance and physiological measures during simulated triathlon. Seven trained male triathletes completed initial familiarization, followed by three separate simulated sprint-distance triathlon trials (750 m swim, 500 kJ bike, 5 km run), using a 25 m pool, an electromagnetically braked cycle ergometer and motorized treadmill. Performance (time and mean cycling power) and physiological variables (oxygen uptake, ventilation, heart rate and blood lactate concentration) were measured throughout. Reliability between trials was assessed using one-way analysis of variance (ANOVA), coefficient of variation (CV), intraclass correlation coefficient (ICC) and ratio limits of agreement (LoA). No significant differences were found in performance or physiological variables measured across simulated triathlon trials. High levels of reliability (CV 0.8) were observed for all performance measures (except transitions) and a majority of physiological variables. Measurement of blood lactate concentration displayed the poorest reliability throughout, with CV’s up to 17.3% and ICC’s as low as 0.4. Ratio LoA for total performance time were similar between trials 1-2 (1.008 */÷ 1.077) and trials 2-3 (1.004 */÷ 1.064). Based on these results simulated sprint-distance triathlon allows for reliable measurement of performance parameters and associated physiological responses in a controlled environment. This reliability data should be considered by simulated triathlon studies when determining statistical power and sample sizes, to allow for more rigorous detection of genuine changes between trials

Physiological requirements in triathlon

This article aims to present the current knowledge on physiological requirements in Olympic distance and Ironman triathlon. Showing the data available from a “traditional point of view” (aerobic power, anaerobic threshold, heart rate, running economy) and from a “contemporary” point of view (V̇ O2 kinetics), it emphasises where we are currently and the areas that remain unknown

Gender effect on the relationship between talent identification tests and later world triathlon series performance

Background: We examined the explanatory power of the Spanish triathlon talent identification (TID) tests for later World Triathlon Series (WTS)-level racing performance as a function of gender. Methods: Youth TID (100 m and 1000 m swimming and 400 m and 1000 m running) test performance times for when they were 14–19 years old, and WTS performance data up to the end of 2017, were obtained for 29 female and 24 male “successful” Spanish triathletes. The relationships between the athletes’ test performances and their later best WTS ranking positions and performance times were modeled using multiple linear regression. Results: The swimming and running TID test data had greater explanatory power for best WTS ranking in the females and for best WTS position in the males (R2a = 0.34 and 0.37, respectively, p ≤ 0.009). The swimming TID times were better related to later race performance than were the running TID times. The predictive power of the TID tests for WTS performance was, however, low, irrespective of exercise mode and athlete gender. Conclusions: These results confirm that triathlon TID tests should not be based solely on swimming and running performance. Moreover, the predictive value of the individual tests within the Spanish TID battery is gender specific.Fundação para a Ciência e Tecnologia | Ref. UIDB / 00447/202

Longitudinal Changes in Response to a Cycle-Run Field Test of Young Male National "Talent identification" and Senior Elite Triathlon Squads.

This study investigated the changes in cardiorespiratory response and running performance of 9 male ?Talent Identification? (TID) and 6 male Senior Elite (SE) Spanish National Squad triathletes during a specific cycle-run test. The TID and SE triathletes (initial age 15.2±0.7 vs. 23.8±5.6 years, p=0.03; tests through the competitive period and the preparatory period, respectively, of two consecutive seasons: Test 1 was an incremental cycle test to determine the ventilatory threshold (Thvent); Test 2 (C-R) was 30 min constant load cycling at the Thvent power output followed by a 3-km time trial run; and Test 3 (R) was an isolated 3-km time trial control run, in randomized counterbalanced order. In both seasons the time required to complete the C-R 3-km run was greater than for R in TID (11:09±00:24 vs. 10:45±00:16 min:ss, pmenor que 0.01; and 10:24±00:22 vs. 10:04±00:14, p=0.006, for season 2005/06 and 2006/07, respectively) and SE (10:15±00:19 vs. 09:45±00:30, pmenor que 0.001 and 09:51±00:26 vs. 09:46±00:06, p= 0.02 for season 2005/06 and 2006/07, respectively). Compared to the first season, completion of the time trial run was faster in the second season (6.6%, pmenor que 0.01 and 6.4%, pmenor que 0.01, for C-R and R test, respectively) only in TID. Changes in post-cycling run performance were accompanied by changes in pacing strategy but only slight or non-significant changes in the cardiorespiratory response. Thus, the negative effect of cycling on performance may persist, independently of the period, over two consecutive seasons in TID and SE triathletes; however A improvements over time suggests that monitoring running pacing strategy after cycling may be a useful tool to control performance and training adaptations in TID. O2max 77.0±5.6 vs. 77.8±3.6 mL·kg-1·min-1, NS) underwent three TE D EP C

Discovering the sluggishness of triathlon running - using the attractor method to quantify the impact of the bike-run transition

Running in a triathlon, a so-called brick run, is uniquely influenced by accumulated load from its preceding disciplines. Crucially, however, and irrespective of race type, the demands of a triathlon always exceed the sum of its parts. Triathletes of all levels commonly report subjectively perceived incoordination within the initial stages of the cycle run transition (T2). Although minimizing it, and its influence on running kinematics, can positively impact running and overall triathlon performance, the mechanisms behind the T2 effect remain unclear. In the present study, we assessed the influence of the pre-load exercise mode focusing on the biomechanical perspective. To analyze inertial sensor-based raw data from both legs, the so-called Attractor Method was applied. The latter represents a sensitive approach, allowing to quantify subtle changes of cyclic motions to uncover the transient effect, a potentially detrimental transient phase at the beginning of a run. The purpose was to analyze the impact of a pre-load on the biomechanics of a brick run during a simulated Olympic Distance triathlon (without the swimming section). Therefore, we assessed the influence of pre-load exercise mode on running pattern (δM) and precision (δD), and on the length of the transient effect (tT) within a 10 km field-based run in 22 well-trained triathletes. We found that δD, but not δM, differed significantly between an isolated run (IRun) and when it was preceded by a 40 km cycle (TRun) or an energetically matched run (RRun). The average distance ran until overcoming the transient phase (tT) was 679 m for TRun, 450 m for RRun, and 29 4 m for IRun. The results demonstrated that especially the first kilometer of a triathlon run is prone to an uncoordinated running sensation, which is also commonly reported by athletes. That is, i) the T2 effect appeared more linked to variability in running style than to running style per se ii) run tT distance was influenced by preceding exercise load mode, being greater for a TRun than for the RRun condition, and iii) the Attractor Method seemed to be a potentially promising method of sensitively monitoring T2 adaptation under ecologically valid conditions

Mood profiles of amateur triathletes: Implications for mental health and performance

Moods have been shown to be predictive of athletic performance and a reflection of mental health status. The aims of our study were (a) to compare pre-race mood scores of triathletes with population norms; (b) to compare pre-race mood scores of triathletes grouped by gender and age bands; (c) to explore whether six distinct mood profile clusters reported in the literature were evident among triathletes and their respective prevalence; (d) to determine if pre-race mood scores predicted triathlon performance; and (e) to interpret our findings in terms of the risk of mental health issues for triathletes. Participants were 592 age-group triathletes (also referred to as recreational or amateur triathletes) who completed the Brunel Mood Scale pre-race and recorded their time goal for the race. Mean mood scores deviated significantly from population norms, with Tension and Vigor scores at the 55th and 54th percentile, respectively, and Depression, Anger, Fatigue, and Confusion scores between the 42nd and 46th percentile. Females reported higher Tension scores than males (p < 0.001), and those in the 18–25 years and 26–35 years age bands reported higher Tension scores than those in the 46–55 years age band (p < 0.008). Using k-means cluster analysis, six distinct mood profiles were identified, the distribution of which approximated the general population, except for a low prevalence of very negative profiles. Mean scores for Depression and Anger were exceptionally low and only 1.5% of triathletes, compared to the normal prevalence of ~5%, reported an 'inverse Everest' profile, which is associated with elevated risk of psychopathology. Mood scores did not predict triathlon performance, assessed by finish time as a percentage of time goal. Results showed an association between triathlon participation and psychological well-being. Findings will inform future investigations of mood responses among triathletes and provide a relevant point of reference for applied practitioners who work with triathletes