Exercise intensity during competition time trials in professional road cycling

Guidelines to Classify Subject Groups in Sport-Science Research

Purpose:

The aim of this systematic literature review was to outline the various preexperimental maximal cycle-test protocols, terminology, and performance indicators currently used to classify subject groups in sportscience research and to construct a classification system for cycling-related research.

Methods:

A database of 130 subject-group descriptions contains information on preexperimental maximal cycle-protocol designs, terminology of the subject groups, biometrical and physiological data, cycling experience, and parameters. Kolmogorov-Smirnov test, 1-way ANOVA, post hoc Bonferroni (P < .05), and trend lines were calculated on height, body mass, relative and absolute maximal oxygen consumption (VO2max), and peak power output (PPO).

Results:

During preexperimental testing, an initial workload of 100 W and a workload increase of 25 W are most frequently used. Three-minute stages provide the most reliable and valid measures of endurance performance. After obtaining data on a subject group, researchers apply various terms to define the group. To solve this complexity, the authors introduced the neutral term performance levels 1 to 5, representing untrained, recreationally trained, trained, well-trained, and professional subject groups, respectively. The most cited parameter in literature to define subject groups is relative VO2max, and therefore no overlap between different performance levels may occur for this principal parameter. Another significant cycling parameter is the absolute PPO. The description of additional physiological information and current and past cycling data is advised.

Conclusion:

This review clearly shows the need to standardize the procedure for classifying subject groups. Recommendations are formulated concerning preexperimental testing, terminology, and performance indicators.

Comparison of heart rate and session rating of perceived exertion methods of defining exercise load in cyclists

The aim of this study was to analyze the competition load using the session rating of perceived exertion (RPE) during different professional cycling races and to assess its validity using the competition load based on heart rate (HR). During 2 consecutive seasons, 12 professional cyclists (mean ± SEM: age 25 ± 1 years, height 175 ± 3 cm, body mass 65.9 ± 2.0 kg, and V(O2)max 78.5 ± 1.7 ml · kg(-1) · min(-1)) competed in 5-, 7-, and 21-day cycling races. The HR response and session RPE were measured during the races to calculate the competition load based on the training impulse of the HR (TRIMP(HR)) and RPE data (TRIMP(RPE)). The highest (p < 0.05) TRIMP(RPE) was observed in 21-day races. However, the higher (p < 0.05) TRIMP(HR) was found in 5- and 7-day races. When TRIMP(HR) and TRIMP(RPE) were normalized by competing distance, neither TRIMP(HR) · km(-1) nor TRIMP(RPE) · km(-1) was significantly different between the analyzed cycling races. We found significant (p < 0.001) correlations between TRIMP(HR) and TRIMP(RPE) (r = 0.75) and between TRIMP(HR) · km(-1) and TRIMP(RPE) · km(-1) (r = 0.90). In conclusion, this study showed that the session RPE can be used to quantify the competition load during professional cycling races. This method can be a useful and noninvasive tool for coaches to monitor and control the training load in cyclists.

The Tour de France: An Updated Physiological Review

From its initial inception in 1903 as a race premised on a publicity stunt to sell newspapers, the Tour de France had grown and evolved over time to become one of the most difficult and heralded sporting events in the world. Though sporting science and the Tour paralleled each other, it was not until the midlate 1980s, and especially the midlate 1990s (with the use of heart-rate monitors) that the 2 began to unify and grow together. The purpose of this brief review is to summarize what is currently known of the physiological demands of the Tour de France, as well as of the main physiological profile of Tour de France competitors.

Salivary cortisol, heart rate, and blood lactate responses during elite downhill mountain bike racing

PURPOSE

This study aimed to quantify the intensity profile of elite downhill mountain bike races during competitions.

METHODS

Seventeen male downhill racers (22 ± 5 y; 185.1 ± 5.3 cm; 68.0 ± 3.9 kg; VO2peak: 59.4 ± 4.1 mL·min·kg-1) participated in the International German Downhill Championships in 2010. The racers' peak oxygen uptake and heart rate (HR) at 2 and 4 mmol·L-1 blood lactate (HR2 and HR4), were assessed during an incremental laboratory step test (100 W, increase 40 W every 5 min). During the races, the HR was recorded and pre- and postrace blood lactate concentrations as well as salivary cortisol levels were obtained.

RESULTS

During the race, the absolute time spent in the "easy" intensity zone was 23.3 ± 6.8 s, 24.2 ± 12.8 s (HR2-HR4) in the "moderate" zone, and 151.6 ± 18.3 s (>HR4) in the "hard" zone. Eighty percent of the entire race was accomplished at intensities >90% HRpeak. Blood lactate concentrations postrace were higher than those obtained after the qualification heat (8.0 ± 2.5 mmol·L-1 vs 6.7 ± 1.8 mmol·L-1, P < .01). Salivary levels of cortisol before the competition and the qualification heat were twice as high as at resting state (P < .01).

CONCLUSIONS

This study shows that mountain bike downhill races are conducted at high heart rates and levels of blood lactate as well as increased concentration of salivary cortisol as marker for psycho-physiological stress.

Ski mountaineering competition: fit for it?

OBJECTIVE

To examine the physiological characteristics of experienced ski mountaineers and to determine the physical demands of ski mountaineering competition.

DESIGN

Descriptive field study.

SETTING

An international ski mountaineering competition characterized by 20 400 m distance and 1869 m altitude difference that took place in March 2009 in the South Tyrolean Alps (Italy).

PARTICIPANTS

Nine healthy and experienced male ski mountaineers.

INTERVENTIONS

Bioimpedance measurements for body composition definition; maximal exercise testing (Bruce protocol) to determine maximal heart rate (HRmax), maximal oxygen uptake (.VO2max), and ventilatory thresholds (VT1 and VT2) and to define individual exercise intensity zones; HR registration during competition.

MAIN OUTCOME MEASURES

Exercise intensity distribution, occurrence of respiratory symptoms.

RESULTS

Ventilatory thresholds were found on average at 70.5% ± 5.0% (VT1) and 90.9% ± 2.6% (VT2) of .VO2max (68.18 ± 6.11 mL·kg⁻¹·minute⁻¹). The overall exercise intensity, defined by the ratio between mean HR during competition and maximal HR in the laboratory (0.87 ± 0.02), was high. Partial times (% of race time) spent competing in 4 defined performance zones were on average 20.4% ± 17.0% (maximal intensity), 59.8% ± 12.5% (high intensity), 12.8% ± 5.6% (moderate intensity), and 7.0% ± 5.9% (low intensity). Five participants reported respiratory discomfort during competition, with cough being the most frequent symptom. Statistical analysis revealed percent body fat mass to correlate with the partial time performed above VT2 (r = 0.782, P < 0.05); the latter was associated with a worse final placement (r = 0.734, P < 0.05).

CONCLUSIONS

Competitive ski mountaineering is characterized by an important cardiopulmonary strain and requires a high degree of physical fitness.

Aspectos fisiológicos do mountain biking competitivo

A prática do ciclismo off-road (mountain biking - MTB), cresceu muito nas últimas duas décadas, sendo incluído como esporte olímpico, nos Jogos de Atlanta em 1996, na modalidade Cross Country. Na última década, houve um aumento no número de publicações científicas que verificaram a demanda fisiológica durante competições, assim como o estudo de possíveis preditores da performance nesta modalidade. O objetivo deste estudo de revisão foi descrever alguns aspectos fisiológicos específicos do MTB Cross Country (MTB CC) competitivo (intensidade de provas, perfil fisiológico de atletas de elite, uso de suspensões e determinantes da performance em subidas). Observa-se na literatura analisada que as provas de MTB CC parecem impor uma sobrecarga fisiológica maior, quando analisada através da frequência cardíaca, do que provas de ciclismo de estrada com duração semelhante. Entretanto, quando analisada pela potência de pedalada, observa-se claramente a característica intermitente da modalidade, com variações de potência durante a prova entre zero e 500W, e potência média relativamente baixa em comparação aos valores de FC encontrados. Outro fator importante levantado neste estudo são as alterações fisiológicas decorrentes do uso de suspensões nas bicicletas de MTB CC. O uso deste equipamento reduz o estresse muscular provocado pelo terreno acidentado, embora pareça não afetar o gasto energético total, tanto em percurso plano como em subidas. Entretanto, é fato que o desempenho em circuitos acidentados é melhorado com o uso das suspensões. Com base nos estudos abordados nessa revisão, conclui-se que o MTB CC enquanto modalidade competitiva apresenta uma grande variação de intensidade (avaliada através da potência), sendo esta atribuída principalmente ao tipo de terreno (irregular e com muitas aclives e declives acentuados) em que as provas de MTB CC acontecem.

Mitochondrial gene expression in elite cyclists: effects of high-intensity interval exercise

Little is known about the effect of training on genetic markers for mitochondrial biogenesis in elite athletes. We tested the hypothesis that low-volume sprint interval exercise (SIE) would be as effective as high-volume interval exercise (IE). Ten male cyclists competing on national elite level (W (max) 403 ± 13 W, VO(2peak) 68 ± 1 mL kg(-1) min(-1)) performed two interval exercise protocols: 7 × 30-s "all-out" bouts (SIE) and 3 × 20-min bouts at ~87% of VO(2peak) (IE). During IE, the work was eightfold larger (1,095 ± 43 vs. 135 ± 5 kJ) and the exercise duration 17 times longer (60 vs. 3.5 min) than during SIE. Muscle samples were taken before and 3 h after exercise. The mRNA of upstream markers of mitochondrial biogenesis [peroxisome proliferator-activated receptor-γ coactivator-1 (PGC-1α), PGC-1α-related coactivator (PRC) and peroxisome proliferator-activated receptor δ (PPARδ)] increased to the same extent after SIE and IE (6-, 1.5- and 1.5-fold increase, respectively). Of the downstream targets of PGC-1α, mitochondrial transcription factor A (Tfam) increased only after SIE and was significantly different from that after IE (P < 0.05), whereas others increased to the same extent (pyruvate dehydrogenase kinase, PDK4) or was unchanged (nuclear respiratory factor 2, NRF2). We conclude that upstream genetic markers of mitochondrial biogenesis increase in a similar way in elite athletes after one exercise session of SIE and IE. However, since the volume and duration of work was considerably lower during SIE and since Tfam, the downstream target of PGC-1α, increased only after SIE, we conclude that SIE might be a time-efficient training strategy for highly trained individuals.

Measuring submaximal performance parameters to monitor fatigue and predict cycling performance: a case study of a world-class cyclo-cross cyclist

Recently a novel submaximal test, known as the Lamberts and Lambert submaximal cycle test (LSCT), has been developed with the purpose of monitoring and predicting changes in cycling performance. Although this test has been shown to be reliable and able to predict cycling performance, it is not known whether it can measure changes in training status. Therefore, the aim of this study was to determine whether the LSCT is able to track changes in performance parameters, and objective and subjective markers of well-being. A world class cyclo-cross athlete (31 years) volunteered to participate in a 10-week observational study. Before and after the study, a peak power output (PPO) test with respiratory gas analysis (VO(2max)) and a 40-km time trial (40-km TT) test were performed. Training data were recorded in a training logbook with a daily assessment of well-being, while a weekly LSCT was performed. After the training period all performance parameters had improved by a meaningful amount (PPO +5.2%; 40-km TT time -2.5%; VO(2max) +1.4%). Increased training loads during weeks 2 and 6 and the subsequent training-induced fatigue was reflected in the increased well-being scores. Changes during the LSCT were most clearly notable in (1) increased power during the first minute of third stage, (2) increased rating of perceived exertion during second and third stages, and (3) a faster heart rate recovery after the third stage. In conclusion, these data suggest that the LSCT is able to track changes in training status and detect the consequences of sharp increases in training loads which seem to be associated with accumulating fatigue.

Power output during a professional men's road-cycling tour

PURPOSE

To quantify the power-output demands of men's road-cycling stage racing using a direct measure of power output.

METHODS

Power-output data were collected from 207 races over 6 competition years on 31 Australian national male road cyclists. Subjects performed a maximal graded exercise test in the laboratory to determine maximum aerobic-power output, and bicycles were fitted with SRM power meters. Races were described as flat, hilly, or criterium, and linear mixed modeling was used to compare the races.

RESULTS

Criterium was the shortest race and displayed the highest mean power output (criterium 262 +/- 30 v hilly 203 +/- 32 v flat 188 +/- 30 W), percentage total race time above 7.5 W/kg (criterium 15.5% +/- 4.1% v hilly 3.8% +/- 1.7% v flat 3.5% +/- 1.4%) and SD in power output (criterium 250 v hilly 165 v flat 169 W). Approximately 67%, 80%, and 85% of total race time was spent below 5 W/kg for criterium, hilly and flat races, respectively. About 70, 40, and 20 sprints above maximum aerobic-power output occurred during criterium, hilly, and flat races, respectively, with most sprints being 6 to 10 s.

CONCLUSIONS

These data extend previous research documenting the demands of men's road cycling. Despite the relatively low mean power output, races were characterized by multiple high-intensity surges above maximum aerobic-power output. These data can be used to develop sport-specific interval-training programs that replicate the demands of competition.

Dose-response relationship of autonomic nervous system responses to individualized training impulse in marathon runners

In athletes, exercise training induces autonomic nervous system (ANS) adaptations that could be used to monitor training status. However, the relationship between training and ANS in athletes has been investigated without regard for individual training loads. We tested the hypothesis that in long-distance athletes, changes in ANS parameters are dose-response related to individual volume/intensity training load and could predict athletic performance. A spectral analysis of heart rate (HR), systolic arterial pressure variability, and baroreflex sensitivity by the sequences technique was investigated in eight recreational athletes during a 6-mo training period culminating with a marathon. Individualized training load responses were monitored by a modified training impulse (TRIMPi) method, which was determined in each athlete using the individual HR and lactate profiling determined during a treadmill test. Monthly TRIMPi steadily increased during the training period. All the ANS parameters were significantly and very highly correlated to the dose of exercise with a second-order regression model ( r2 ranged from 0.90 to 0.99; P < 0.001). Variance, high-frequency oscillations of HR variability (HRV), and baroreflex sensitivity resembled a bell-shaped curve with a minimum at the highest TRIMPi, whereas low-frequency oscillations of HR and systolic arterial pressure variability and the low frequency (LF)-to-high frequency ratio resembled an U-shaped curve with a maximum at the highest TRIMPi. The LF component of HRV assessed at the last recording session was significantly and inversely correlated to the time needed to complete the nearing marathon. These results suggest that in recreational athletes, ANS adaptations to exercise training are dose related on an individual basis, showing a progressive shift toward a sympathetic predominance, and that LF oscillations in HRV at peak training load could predict athletic achievement in this athlete population.

Arterial baroreflex control of cardiac vagal outflow in older individuals can be enhanced by aerobic exercise training

Maintained cardiac vagal function is critical to cardiovascular health in human aging. Aerobic exercise training has been considered an attractive intervention to increase cardiovagal baroreflex function; however, the data are equivocal. Moreover, if regular exercise does reverse the age-related decline in cardiovagal baroreflex function, it is unknown how this might be achieved. Therefore, we assessed the effects of a 6-month aerobic training program on baroreflex gain and its mechanical and neural components in older individuals (5 women and 7 men, aged 55 to 71 years). We assessed baroreflex function using pharmacological pressure changes (bolus nitroprusside followed by bolus phenylephrine) and estimated the integrated gain (Delta R-R interval/Delta systolic blood pressure) and mechanical (Delta diameter/Delta pressure) and neural (Delta R-R interval/Delta diameter) components via measurements of carotid artery diameter in previously sedentary older individuals before and after 6 months of aerobic training. There was a significant 26% increase in baroreflex gain that was directly related to the amount of exercise performed and that was derived mainly from an increase in the neural component of the arterial baroreflex (P<0.05). We did find changes in the mechanical component, but unlike integrated gain and the neural component, these were not related to the magnitude of the exercise stimulus. These results suggest that exercise training can have a powerful effect on cardiovagal baroreflex function, but a sufficient stimulus is necessary to produce the effect. Moreover, adaptations in the afferent-efferent baroreflex control of cardiac vagal outflow may be crucial for the improvement in arterial baroreflex function in older humans.

Workload demand in police officers during mountain bike patrols

To the authors' knowledge this is the first paper that has used the training impulse (TRIMP) 'methodology' to calculate workload demand. It is believed that this is a promising method to calculate workload in a range of professions in order to understand the relationship between work demands and aerobic fitness. The aim of this study was to assess workload demand in police officers from the Utrecht police department in the Netherlands, during patrol by mountain bike. Maximum oxygen intake, maximum heart rate (HRmax), ventilatory threshold (VT)1 and VT2 were determined with a maximal exercise test on a bicycle ergometer. Heart rates were registered throughout three shifts in 20 subjects using a heart rate monitor. Exercise intensity was divided into three phases: phase I (between 40% of HRmax and VT1); phase II (between VT and the respiratory compensation point (RCP)); and phase III (>RCP). The total TRIMP score was obtained by summating the results of the three phases. Average daily workload demands of 355 TRIMPs per day and 1777 TRIMPs per week were measured. Workload demand approached and in some cases exceeded the upper limit of 2000 TRIMPs per week threshold level for physiological stress demands in professional male cyclists.

Effect of a novel pedal design on maximal power output and mechanical efficiency in well-trained cyclists

In this study, we evaluated the effects of a novel pedal design, characterized by a downward and forward shift of the cleat fixing platform relative to the pedal axle, on maximal power output and mechanical efficiency in 22 well-trained cyclists. Maximal power output was measured during a series of short (5-s) intermittent sprints on an isokinetic cycle ergometer at cadences from 40 to 120 rev min(-1). Mechanical efficiency was evaluated during a submaximal incremental exercise test on a bicycle ergometer using continuous VO(2) and VCO(2) measurement. Similar tests with conventional pedals and the novel pedals, which were mounted on the individual racing bike of the participant, were randomized. Maximal power was greater with novel pedals than with conventional pedals (between 6.0%, s(x) = 1.5 at 40 rev min(-1) and 1.8%, s(x) = 0.7 at 120 rev min(-1); P = 0.01). Torque production between crank angles of 60 degrees and 150 degrees was higher with novel pedals than with conventional pedals (P = 0.004). The novel pedal design did not affect whole-body VO(2) or VCO(2). Mechanical efficiency was greater with novel pedals than with conventional pedals (27.2%, s(x) = 0.9 and 25.1%, s(x) = 0.9% respectively; P = 0.047; effect size = 0.9). In conclusion, the novel pedals can increase maximal power output and mechanical efficiency in well-trained cyclists.

Changes in heart rate recovery after high-intensity training in well-trained cyclists

Heart rate recovery (HRR) after submaximal exercise improves after training. However, it is unknown if this also occurs in already well-trained cyclists. Therefore, 14 well-trained cyclists (VO(2max) 60.3 +/- 7.2 ml kg(-1) min(-1); relative peak power output 5.2 +/- 0.6 W kg(-1)) participated in a high-intensity training programme (eight sessions in 4 weeks). Before and after high-intensity training, performance was assessed with a peak power output test including respiratory gas analysis (VO(2max)) and a 40-km time trial. HRR was measured after every high-intensity training session and 40-km time trial. After the training period peak power output, expressed as W kg(-1), improved by 4.7% (P = 0.000010) and 40-km time trial improved by 2.2% (P = 0.000007), whereas there was no change in VO(2max) (P = 0.066571). Both HRR after the high intensity training sessions (7 +/- 6 beats; P = 0.001302) and HRR after the 40-km time trials (6 +/- 3 beats; P = 0.023101) improved significantly after the training period. Good relationships were found between improvements in HRR(40-km) and improvements in peak power output (r = 0.73; P < 0.0001) and 40-km time trial time (r = 0.96; P < 0.0001). In conclusion, HRR is a sensitive marker which tracks changes in training status in already well-trained cyclists and has the potential to have an important role in monitoring and prescribing training.

Indoor 16.1-km time-trial performance in cyclists aged 25- 63 years

In this study, we assessed age-related changes in indoor 16.1-km cycling time-trial performance in 40 competitive male cyclists aged 25-63 years. Participants completed two tests: (1) a maximal ramped Kingcycle ergometer test, with maximal ramped minute power (RMPmax, W) recorded as the highest mean external power during any 60 s and maximal heart rate (HRmax, beats min(-1)) as the highest value during the test; and (2) an indoor Kingcycle 16.1-km time-trial with mean external power output (W), heart rate (beats min(-1)), and pedal cadence (rev min(-1)) recorded throughout the event. Results revealed age-related declines (P < 0.05) in absolute and relative time-trial external power output [(24 W (7.0%) per decade], heart rate [7 beats min(-1) (3.87%) per decade], and cadence [3 rev min(-1) (3.1%) per decade]. No relationships (P > 0.05) were observed for mean power output and heart rate recorded during the time-trial versus age when expressed relative to maximal ramped minute power and maximal heart rate respectively. Strong relationships (P < 0.05) were observed for maximal ramped minute power and time-trial power (r= 0.95) and for maximal heart rate and time-trial heart rate (r= 0.95). Our results show that indoor 16.1-km time-trial performance declines with age but relative exercise intensity (%RMPmax and %HRmax) does not change.

Comparison of different theoretical models estimating peak power output and maximal oxygen uptake in trained and elite triathletes and endurance cyclists in the velodrome

The aim of this study was to assess which of the equations that estimate peak power output and maximal oxygen uptake (VO2max) in the velodrome adapt best to the measurements made by reference systems. Thirty-four endurance cyclists and triathletes performed one incremental test in the laboratory and two tests in the velodrome. Maximal oxygen uptake and peak power output were measured with an indirect calorimetry system in the laboratory and with the SRM training system in the velodrome. The peak power output and VO2max of the field test were estimated by means of different equations. The agreement between the estimated and the reference values was assessed with the Bland-Altman method. The equation of Olds et al. (1995) showed the best agreement with respect to the peak power output reference values, and that of McCole et al. (1990) was the only equation to show good agreement with respect to the VO2max reference values. The VO2max values showed a higher coefficient of determination with respect to maximal aerobic speed when they were expressed in relative terms. In conclusion, the equations of Olds et al. (1995) and McCole et al. (1990) were best at estimating peak power output and VO2max in the velodrome, respectively.

Nonconsecutive- versus consecutive-day high-intensity interval training in cyclists

PURPOSE

We compared the effects of a high-intensity interval training (HIT) program completed on three consecutive or nonconsecutive days per week for 3 wk on VO2peak, peak aerobic power output (PPOa), and 5-km time trial (TT5k) performance in trained cyclists.

METHODS

Fifteen trained cyclists completed a TT5k and an incremental test to exhaustion for VO2peak and PPOa determination before and after training. Pretraining TT5k times were used to form groups, one of which (N=9) performed three HIT sessions per week on consecutive days (CD), while the other (N=6) did so on nonconsecutive days (NCD). Each interval session consisted of up to eight 2.5-min intervals at 100% of PPOa, separated by 4 min of active recovery. Pre- and posttraining TT5k performance, VO2peak, and PPOa were compared using 2x2 (groupxtime) ANOVA with repeated measures on time.

RESULTS

HIT significantly improved VO2peak, PPOa, and TT5k performance in both groups across time (P<0.05); there were no differences between groups. In both groups combined, VO2peak and PPOa increased by 0.2+/-0.2 L.min(-1) (5.7%) and 23+/-15 W (7.2%), respectively, and TT5k velocity and power output increased by 0.9+/-0.8 km.h(-1) (2.6%) and 17+/-19 W (6.9%), respectively. Despite comparable group changes, the individual response varied widely.

CONCLUSION

CD and NCD similarly improved TT5k performance, VO2peak, and PPOa, but the individual response varied widely in each group. Thus, athletes should experiment with both designs to discern which one optimizes their training.

Cycling power output produced during flat and mountain stages in the Giro d'Italia: A case study

Until recently, the physiological demands of cycling competitions were mostly reflected by the measurement of heart rate and the indirect estimation of exercise intensity. The purpose of this case study was to illustrate the varying power output of a professional cyclist during flat and mountain stages of a Grand Tour (Giro d'Italia). Nine stage recordings of a cyclist of the 2005 Giro d'Italia were monitored using a mobile power measurement device (SRM Trainingssystem, Julich, Germany), which recorded direct power output and heart rate. Stages were categorized into flat (n = 5) and mountain stages (n = 4). Data were processed electronically, and the overall mean power in flat and mountain stages and maximal mean power for various durations were calculated. Mean power output was 132 W +/- 26 (2.0 W x kg(-1) +/- 0.4) for the flat and 235 W +/- 10 (3.5 W x kg(-1) +/- 0.1) for the mountain stages. Mountain stages showed higher maximal mean power (367 W) for longer durations (1800 s) than flat stages (239 W). Flat stages are characterized by a large variability of power output with short bursts of high power and long periods with reduced intensity of exercise, whereas mountain stages mostly require submaximal, constant power output over longer periods.

The physiology of mountain biking

Mountain biking is a popular outdoor recreational activity and an Olympic sport. Cross-country circuit races have a winning time of approximately equal 120 minutes and are performed at an average heart rate close to 90% of the maximum, corresponding to 84% of maximum oxygen uptake (VO2max). More than 80% of race time is spent above the lactate threshold. This very high exercise intensity is related to the fast starting phase of the race; the several climbs, forcing off-road cyclists to expend most of their effort going against gravity; greater rolling resistance; and the isometric contractions of arm and leg muscles necessary for bike handling and stabilisation. Because of the high power output (up to 500W) required during steep climbing and at the start of the race, anaerobic energy metabolism is also likely to be a factor of off-road cycling and deserves further investigation. Mountain bikers' physiological characteristics indicate that aerobic power (VO2max >70 mL/kg/min) and the ability to sustain high work rates for prolonged periods of time are prerequisites for competing at a high level in off-road cycling events. The anthropometric characteristics of mountain bikers are similar to climbers and all-terrain road cyclists. Various parameters of aerobic fitness are correlated to cross-country performance, suggesting that these tests are valid for the physiological assessment of competitive mountain bikers, especially when normalised to body mass. Factors other than aerobic power and capacity might influence off-road cycling performance and require further investigation. These include off-road cycling economy, anaerobic power and capacity, technical ability and pre-exercise nutritional strategies.

A modified TRIMP to quantify the in-season training load of team sport players

The aims of the study were to modify the training impulse (TRIMP) method of quantifying training load for use with intermittent team sports, and to examine the relationship between this modified TRIMP (TRIMP(MOD)) and changes in the physiological profile of team sport players during a competitive season. Eight male field hockey players, participating in the English Premier Division, took part in the study (mean+/-s: age 26+/-4 years, body mass 80.8+/-5.2 kg, stature 1.82+/-0.04 m). Participants performed three treadmill exercise tests at the start of the competitive season and mid-season: a submaximal test to establish the treadmill speed at a blood lactate concentration of 4 mmol . l(-1); a maximal incremental test to determine maximal oxygen uptake ([V]O(2max)) and peak running speed; and an all-out constant-load test to determine time to exhaustion. Heart rate was recorded during all training sessions and match-play, from which TRIMP(MOD) was calculated. Mean weekly TRIMP(MOD) was correlated with the change in [V]O(2max) and treadmill speed at a blood lactate concentration of 4 mmol x l(-1) from the start of to mid-season (P<0.05). The results suggest that TRIMP(MOD) is a means of quantifying training load in team sports and can be used to prescribe training for the maintenance or improvement of aerobic fitness during the competitive season.

Incremental Exercise Test Design and Analysis

Physiological variables, such as maximum work rate or maximal oxygen uptake (VO2max), together with other submaximal metabolic inflection points (e.g. the lactate threshold [LT], the onset of blood lactate accumulation and the pulmonary ventilation threshold [VT]), are regularly quantified by sports scientists during an incremental exercise test to exhaustion. These variables have been shown to correlate with endurance performance, have been used to prescribe exercise training loads and are useful to monitor adaptation to training. However, an incremental exercise test can be modified in terms of starting and subsequent work rates, increments and duration of each stage. At the same time, the analysis of the blood lactate/ventilatory response to incremental exercise may vary due to the medium of blood analysed and the treatment (or mathematical modelling) of data following the test to model the metabolic inflection points. Modification of the stage duration during an incremental exercise test may influence the submaximal and maximal physiological variables. In particular, the peak power output is reduced in incremental exercise tests that have stages of longer duration. Furthermore, the VT or LT may also occur at higher absolute exercise work rate in incremental tests comprising shorter stages. These effects may influence the relationship of the variables to endurance performance or potentially influence the sensitivity of these results to endurance training. A difference in maximum work rate with modification of incremental exercise test design may change the validity of using these results for predicting performance, and prescribing or monitoring training. Sports scientists and coaches should consider these factors when conducting incremental exercise testing for the purposes of performance diagnostics.

Distribution of Power Output During Cycling

We aim to summarise the impact and mechanisms of work-rate pacing during individual cycling time trials (TTs). Unlike time-to-exhaustion tests, a TT provides an externally valid model for examining how an initial work rate is chosen and maintained by an athlete during self-selected exercise. The selection and distribution of work rate is one of many factors that influence cycling speed. Mathematical models are available to predict the impact of factors such as gradient and wind velocity on cycling speed, but only a few researchers have examined the inter-relationships between these factors and work-rate distribution within a TT. When environmental conditions are relatively stable (e.g. in a velodrome) and the TT is >10 minutes, then an even distribution of work rate is optimal. For a shorter TT (< or = 10 minutes), work rate should be increased during the starting effort because this proportion of total race time is significant. For a very short TT (< or = 2 minutes), the starting effort should be maximal, since the time saved during the starting phase is predicted to outweigh any time lost during the final metres because of fatigue. A similar 'time saving' rationale underpins the advice that work rate should vary in parallel with any changes in gradient or wind speed during a road TT. Increasing work rate in headwind and uphill sections, and vice versa, decreases the variability in speed and, therefore, the total race time. It seems that even experienced cyclists naturally select a supraoptimal work rate at the start of a longer TT. Whether such a start can be 'blunted' through coaching or the monitoring of psychophysiological variables is unknown. Similarly, the extent to which cyclists can vary and monitor work rate during a TT is unclear. There is evidence that sub-elite cyclists can vary work rate by +/-5% the average for a TT lasting 25-60 minutes, but such variability might be difficult with high-performance cyclists whose average work rate during a TT is already extremely high (>350 watts). During a TT, pacing strategy is regulated in a complex anticipatory system that monitors afferent feedback from various physiological systems, and then regulates the work rate so that potentially limiting changes do not occur before the endpoint of exercise is reached. It is critical that the endpoint of exercise is known by the cyclist so that adjustments to exercise work rate can be made within the context of an estimated finish time. Pacing strategies are thus the consequence of complex regulation and serve a dual role: they are both the result of homeostatic regulation by the brain, as well as being the means by which such regulation is achieved. The pacing strategy 'algorithm' is sited in the brain and would need afferent input from interoceptors, such as heart rate and respiratory rate, as well as exteroceptors providing information on local environmental conditions. Such inputs have been shown to induce activity in the thalamus, hypothalamus and the parietal somatosensory cortex. Knowledge of time, modulated by the cerebellum, basal ganglia and primary somatosensory cortex, would also input to the pacing algorithm as would information stored in memory about previous similar exercise bouts. How all this information is assimilated by the different regions of the brain is not known at present.

Power output of field-based downhill mountain biking

The purpose of this study was to assess the power output of field-based downhill mountain biking. Seventeen trained male downhill cyclists (age 27.1 +/- 5.1 years) competing nationally performed two timed runs of a measured downhill course. An SRM powermeter was used to simultaneously record power, cadence, and speed. Values were sampled at 1-s intervals. Heart rates were recorded at 5-s intervals using a Polar S710 heart rate monitor. Peak and mean power output were 834 +/- 129 W and 75 +/- 26 W respectively. Mean power accounted for only 9% of peak values. Paradoxically, mean heart rate was 168 +/- 9 beats x min(-1) (89% of age-predicted maximum heart rate). Mean cadence (27 +/- 5 rev x min(-1)) was significantly related to speed (r = 0.51; P < 0.01). Analysis revealed an average of 38 pedal actions per run, with average pedalling periods of 5 s. Power and cadence were not significantly related to run time or any other variable. Our results support the intermittent nature of downhill mountain biking. The poor relationships between power and run time and between cadence and run time suggest they are not essential pre-requisites to downhill mountain biking performance and indicate the importance of riding dynamics to overall performance.

Agreement between polar and SRM mobile ergometer systems during laboratory-based high-intensity, intermittent cycling activity

The purpose of this study was to assess the agreement between two mobile cycle ergometer systems for recording high-intensity, intermittent power output. Twelve trained male cyclists (age 31.4 +/- 9.8 years) performed a single 3 min intermittent cycle test consisting of 12 all-out efforts, separated by periods of passive recovery ranging from 5 to 15 s. Power output was recorded using a Polar S710 heart rate monitor and power sensor kit and an SRM Powercrank system for each test. The SRM used torque and angular velocity to calculate power, while the S710 used chain speed and vibration to calculate power. Significant differences (P < 0.05) in power were found at 8 of the 12 efforts. A significant difference (P = 0.001) was also found when power was averaged over all 12 intervals. Mean power was 556 +/- 102 W and 446 +/- 61 W for the SRM and S710 respectively. The S710 underestimated power by an average of 23% with random errors of */[division sign] 24% when compared with the SRM. Random errors ranged from 36% to 141% with a median of 51%. The results indicate there was little agreement between the two systems and that the Polar S710 did not provide a valid measure of power during intermittent cycling activity when compared with the SRM. Power recorded by the S710 system was influenced greatly by chain vibration and sampling rates.

Exercise intensity during repeated days of racing in professional triathletes

The purpose of this study was to estimate the exercise intensity from the competition heart rate (HR) of professional triathletes during a multi-triathlon race. Five internationally ranked professional triathletes completed incremental cycling and running tests to assess the first and second ventilatory thresholds (i.e., VT and RCT) and the HR at VT and RCT. HR was then monitored during a 5 d multi-triathlon race: a prologue time trial (PTT, 0.2 km swim -- 5 km cycle -- 1.2 km run) that opened the race; short-distance triathlons (SHD; 1.3 km swim -- 36 km cycle -- 8.4 km run) performed on the 2nd and 5th days; and sprint-distance triathlons (SPD; 0.75 km swim -- 20 km cycle -- 5 km run) performed on the 3rd and 4th days. All trials except the last (i.e., the second SHD) were performed above HR corresponding to RCT. PTT elicited significantly higher mean HR than the other trials (except for the first SPD trial). In contrast, the last SHD elicited significantly lower HR than the other trials. These responses were globally similar in the 3 segments (i.e., swim, cycle, and run). This study demonstrates that the triathletes performed at very high intensity during a drafting-permitted multi-triathlon race. However, as shown for multi-day cycling distances, the HR responses depended on (i) the distance covered and (ii) group behavior.

Dynamic Pacing Strategies during the Cycle Phase of an Ironman Triathlon

INTRODUCTION

A nonlinear dynamic systems model has previously been proposed to explain pacing strategies employed during exercise.

PURPOSE

This study was conducted to examine the pacing strategies used under varying conditions during the cycle phase of an Ironman triathlon.

METHODS

The bicycles of six well-trained male triathletes were equipped with SRM power meters set to record power output, cadence, speed, and heart rate. The flat, three-lap, out-and-back cycle course, coupled with relatively consistent wind conditions (17-30 km x h(-1)), enabled comparisons to be made between three consecutive 60-km laps and relative wind direction (headwind vs tailwind).

RESULTS

Participants finished the cycle phase (180 km) with consistently fast performance times (5 h, 11 +/- 2 min; top 10% of all finishers). Average power output (239 +/- 25 to 203 +/- 20 W), cadence (89 +/- 6 to 82 +/- 8 rpm), and speed (36.5 +/- 0.8 to 33.1 +/- 0.8 km x h(-1)) all significantly decreased with increasing number of laps (P < 0.05). These variables, however, were not significantly different between headwind and tailwind sections. The deviation (SD) in power output and cadence did not change with increasing number of laps; however, the deviations in torque (6.8 +/- 1.6 and 5.8 +/- 1.3 N x m) and speed (2.1 +/- 0.5 and 1.6 +/- 0.3 km x h(-1)) were significantly greater under headwind compared with tailwind conditions, respectively. The median power frequency tended to be lower in headwind (0.0480 +/- 0.0083) compared with tailwind (0.0531 +/- 0.0101) sections.

CONCLUSION

These data show evidence that a nonlinear dynamic pacing strategy is used by well-trained triathletes throughout various segments and conditions of the Ironman cycle phase. Moreover, an increased variation in torque and speed was found in the headwind versus the tailwind condition.

Models to explain fatigue during prolonged endurance cycling

Much of the previous research into understanding fatigue during prolonged cycling has found that cycling performance may be limited by numerous physiological, biomechanical, environmental, mechanical and psychological factors. From over 2000 manuscripts addressing the topic of fatigue, a number of diverse cause-and-effect models have been developed. These include the following models: (i) cardiovascular/anaerobic; (ii) energy supply/energy depletion; (iii) neuromuscular fatigue; (iv) muscle trauma; (v) biomechanical; (vi) thermoregulatory; (vii) psychological/motivational; and (viii) central governor. More recently, however, a complex systems model of fatigue has been proposed, whereby these aforementioned linear models provide afferent feedback that is integrated by a central governor into our unconscious perception of fatigue. This review outlines the more conventional linear models of fatigue and addresses specifically how these may influence the development of fatigue during cycling. The review concludes by showing how these linear models of fatigue might be integrated into a more recently proposed nonlinear complex systems model of exercise-induced fatigue.

Power output during stage racing in professional road cycling

PURPOSE

The aim of the study was to evaluate the power output during a multistage professional road race using direct power measurements and to compare these results with the performance measurements using competition heart rate recordings.

METHODS

Six professional road cyclists performed an incremental cycling test during which peak power output, power output, and heart rate at the lactate threshold (LT) and at a lactate increase of 1 mM above the LT (LT + 1) were assessed. During a six-stage road race competition, power output was measured directly (SRM crankset). To analyze the time spent at different intensities during competition, the amount of competition time spent below LT (zone 1), between the LT and LT + 1 (zone 2), and above LT + 1 (zone 3) determined during laboratory testing were calculated for power output and heart rate.

RESULTS

During the five mass start stages, a mean power output of 220 +/- 22 W (3.1 +/- 0.2 W x kg(-1)) with a mean heart rate of 142 +/- 5 bpm was measured. Average power output during an uphill time trial was 392 +/- 60 W (5.5 +/- 0.4 W x kg(-1)) with a mean heart rate of 169 +/- 3 bpm. For the mass start stages, the average distribution of exercise time spent in different intensities calculated for power output and heart rate was 58 versus 38% for zone 1, 14 versus 38% for zone 2, and 28 versus 24% for zone 3.

CONCLUSION

Most of the competition time during the mass start stages was spent at intensities near the LT. Compared with power output, heart rate measurement underestimated the time spent at intensity zones 1 and 3, and overestimated the time spent in zone 2.

Which laboratory variable is related with time trial performance time in the Tour de France?

OBJECTIVE

To investigate the relationship between several physiological variables that can be easily obtained during cycle ergometer gradual testing (for example, peak power output (W(peak)), Vo(2max), or ventilatory threshold (VT)) and actual (>50 km) time trials (TT) time performance during the Tour de France.

METHODS

We collected data in professional cyclists from the first TT of the 1998 Tour de France (TT1, 58 km distance; n = 6 cyclists) and the first (TT2, 56.5 km; n = 5) and second TT of the 1999 Tour de France (TT3, 57 km; n = 5).

RESULTS

A negative relationship was found between power output (W) at VT (VT(Watt)) and TT final time (s) in TT1 (r = -0.864; p = 0.026; standard error of estimate (SEE) of 73 s; and 95% confidence limits (95% CL) -0.98; -0.18), TT2 (r = -0.77; p = 0.27; SEE of 139 s; and 95% CL -0.98; 0.35), and TT3 (r = -0.923; p = 0.025; SEE of 94 s; and 95% CL -1.00; -0.22).

CONCLUSIONS

Actual performance in long TT during the Tour de France (>50 km distance, performed after at least 1-2 weeks of continuous competition), in which some cumulative fatigue inevitably occurs, is related, at least in part, to the power output that elicits the VT. No other routine physiological variable (for example, Vo(2max) or W(peak)) is related to performance in this type of event.

The Isocapnic Buffering Phase and Mechanical Efficiency: Relationship to Cycle Time Trial Performance of Short and Long Duration

The purpose of this study was to determine the relationship between the isocapnic buffer (βisocapnic) and hypocapnic hyperventilation (HHV) phases as well as performance in a short (20-min) and long (90-min) time trial (TT) in trained athletes. In addition, gross (GE, %) and delta (ΔE, %) efficiency were calculated and the relationship between these variables and the average power output (W) in each TT was determined. Thirteen male endurance athletes (Mean ± SD age 31 ± 6 yrs; body mass 75.6 ± 6.3 kg; height 185 ± 6 cm) completed a continuous incremental test to exhaustion for determination of the βisocapnic and HHV phases. A second submaximal test was used to determine GE and ΔE. The average power output (W) was measured in a 20-min and 90-min cycling TT. The βisocapnic phase (W) was significantly correlated to the average power output (W) in the 20-min TT (r = 0.58; p <  0.05), but not in the 90-min TT (r = 0.28). The HHV phase (W) was not significantly correlated to the average power output in the 20-min or 90-min TT. No significant correlation was found for GE or for ΔE and performance in the TT. The data from this study shows that βisocapnic together with HHV is not likely to be a useful indicator of cycle TT performance of 20- to 90-min duration. Furthermore, GE and ΔE determined from a submaximal incremental stepwise test are not related to cycling TT performance of different duration. Key words: incremental, correlation, metabolism, athletes, fatigue

Effect of ultramarathon cycling on the heart rate in elite cyclists

OBJECTIVES

To analyse the heart rate (HR) response and estimate the ultraendurance threshold-the optimum maintainable exercise intensity of ultraendurance cycling-in ultraendurance elite cyclists competing in the Race across the Alps.

METHODS

HR monitoring was performed in 10 male elite cyclists during the first Race across the Alps in 2001 (distance: 525 km; cumulative altitude difference: 12 600 m) to investigate the exercise intensity of a cycle ultramarathon and the cardiopulmonary strains involved. Four different exercise intensities were defined as percentages of maximal HR (HR(max)) as follows: recovery HR (HR(re)), <70% of HR(max); moderate aerobic HR (HR(ma)), 70-80%; intense aerobic HR (HR(ia)), 80-90%; and high intensity HR (HR(hi)), >90%.

RESULTS

All athletes investigated finished the competition. The mean racing time was 27 hours and 25 minutes, and the average speed was 18.6 km/h. The mean HR(max) was 186 beats/min, and the average value of measured HRs (HR(average)) was 126 beats/min resulting in a mean HR(average)/HR(max) ratio of 0.68, which probably corresponds to the ultraendurance threshold. The athletes spent 53% (14 hours 32 minutes) of total race time within HR(re), 25% (6 hours 51 minutes) within HR(ma), 19% (5 hours 13 minutes) within HR(ia), and only 3% (49 minutes) within HR(hi), which shows the exercise intensity to be predominantly moderate (HR(re) + HR(ma) = 78% or 21 hours 23 minutes). The HR response was influenced by the course profile as well as the duration. In all subjects, exercise intensity declined significantly during the race, as indicated by a decrease in HR(average)/HR(max) of 23% from 0.86 at the start to 0.66 at the end.

CONCLUSIONS

A substantial decrease (10% every 10 hours) in the HR response is a general cardiovascular feature of ultramarathon cycling, suggesting that the ultraendurance threshold lies at about 70% of HR(max) in elite ultramarathon cyclists.

Science and cycling: current knowledge and future directions for research

In this holistic review of cycling science, the objectives are: (1) to identify the various human and environmental factors that influence cycling power output and velocity; (2) to discuss, with the aid of a schematic model, the often complex interrelationships between these factors; and (3) to suggest future directions for research to help clarify how cycling performance can be optimized, given different race disciplines, environments and riders. Most successful cyclists, irrespective of the race discipline, have a high maximal aerobic power output measured from an incremental test, and an ability to work at relatively high power outputs for long periods. The relationship between these characteristics and inherent physiological factors such as muscle capilliarization and muscle fibre type is complicated by inter-individual differences in selecting cadence for different race conditions. More research is needed on high-class professional riders, since they probably represent the pinnacle of natural selection for, and physiological adaptation to, endurance exercise. Recent advances in mathematical modelling and bicycle-mounted strain gauges, which can measure power directly in races, are starting to help unravel the interrelationships between the various resistive forces on the bicycle (e.g. air and rolling resistance, gravity). Interventions on rider position to optimize aerodynamics should also consider the impact on power output of the rider. All-terrain bicycle (ATB) racing is a neglected discipline in terms of the characterization of power outputs in race conditions and the modelling of the effects of the different design of bicycle frame and components on the magnitude of resistive forces. A direct application of mathematical models of cycling velocity has been in identifying optimal pacing strategies for different race conditions. Such data should, nevertheless, be considered alongside physiological optimization of power output in a race. An even distribution of power output is both physiologically and biophysically optimal for longer ( > 4 km) time-trials held in conditions of unvarying wind and gradient. For shorter races (e.g. a 1 km time-trial), an 'all out' effort from the start is advised to 'save' time during the initial phase that contributes most to total race time and to optimize the contribution of kinetic energy to race velocity. From a biophysical standpoint, the optimum pacing strategy for road time-trials may involve increasing power in headwinds and uphill sections and decreasing power in tailwinds and when travelling downhill. More research, using models and direct power measurement, is needed to elucidate fully how much such a pacing strategy might save time in a real race and how much a variable power output can be tolerated by a rider. The cyclist's diet is a multifactorial issue in itself and many researchers have tried to examine aspects of cycling nutrition (e.g. timing, amount, composition) in isolation. Only recently have researchers attempted to analyse interrelationships between dietary factors (e.g. the link between pre-race and in-race dietary effects on performance). The thermal environment is a mediating factor in choice of diet, since there may be competing interests of replacing lost fluid and depleted glycogen during and after a race. Given the prevalence of stage racing in professional cycling, more research into the influence of nutrition on repeated bouts of exercise performance and training is required.

Effect of measuring blood lactate concentrations using different automated lactate analysers on blood lactate transition thresholds

This study investigated the effect of using three automated blood lactate analysers (Accusport, Lactate Pro, YSI 1500 Sport) on blood lactate transition thresholds (BLTT). Blood lactate concentrations were measured using the three analysers in rowers (n = 17) and kayakers (n = 6) during incremental exercise. The BLTT determined were: 1) ADAPT lactate threshold (data point preceding lactate increase of > or = 0.4 mmol x l(-1)), 2) log-log lactate threshold (point of lactate increase when log lactate plotted against log of relevant exercise parameter), 3) DMAX anaerobic threshold, 4) ADAPT anaerobic threshold (modified DMAX method), 5) Onset of blood lactate accumulation (OBLA, fixed blood lactate concentration of 4 mmol x l(-1)). Measurements of blood lactate concentration differed between analysers (p < 0.0001), resulting in BLTT differing between analysers when expressed as a blood lactate concentration (p < 0.0001), or when the BLTT was defined as a fixed blood lactate concentration (e.g. OBLA) (p < 0.0001). When expressed as a power output or heart rate using BLTT based on relative changes in lactate concentration (log-log, ADAPT and DMAX thresholds) the values were similar between analysers (p > 0.05), except the Accusport provided higher values for the log-log lactate threshold (p < 0.0001). We concluded that, despite providing significantly different lactate concentrations, unless the Accusport was used to determine the log-log lactate threshold, or values were expressed as a blood lactate concentration, the use of different analysers had little effect on the BLTT.

Comparison of Wpeak, VO2peak and the ventilation threshold from two different incremental exercise tests: Relationship to endurance performance

This report presents data comparing the peak rate of oxygen consumption (VO2(peak)), peak power output (W(peak)) and the ventilation threshold (VT) obtained from two different incremental cycle exercise tests performed by nine well trained triathletes (Mean +/- SD age 32 +/- 3 yrs; body mass 77.4 +/- 4.9 kg and height 185 +/- 3 cm). Furthermore, the relationship between these variables and the average sustained power output (W) during a 90 min cycle time trial (TT) was also determined. The two incremental exercise tests involved a 'short' test, which commenced at 150 W with 30 W increments every 60 s until exhaustion. The second ('long') incremental test commenced at a power output representing 50% of the W(peak) obtained in the short test. The subjects were then required to increase the power output by 5% every 3 min until exhaustion. The results showed the W(peak) (W) in the short test was significantly (p < 0.01) higher than in the long test. However, there was no significant difference in the VO2(peak) (1 x min(-1)) between the two tests. There was a weak but significant correlation between W(peak) (W) and VO2(peak) (l x min(-1)) (r = 0.72: p < 0.05) in the short (60 s stage) test but not the long (3 min stage) test (r = 0.52). There were no significant differences and good agreement between for the heart rate (HR) (b x min(-1)) and oxygen consumption (VO2) corresponding to the VT. In contrast, the power output (W) corresponding to the VT was significantly different and not comparable between the long and short incremental tests. The cycle TT performance was most correlated to the W(peak) (W) (r = 0.94; p < 0.01) and the VT (W) (r = 0.75; p < 0.05) from the long test as well as the VO2(peak) (l x min(-1)) obtained from the short incremental test (r = 0.75; p < 0.01). These data suggest that the length of stages during incremental cycle exercise may influence the W(peak) and in turn the relationship of this variable to VO2(peak). Furthermore, the W(peak) obtained from a test incorporating 3 min stage increments represents the best indicator of 90 min cycle performance in well-trained triathletes.

The Tour de France: a physiological review

On 5 July 2003, the Tour de France (TDF) has celebrated 100th running. Instead of a chimney sweep competing during his free time (as in 1903), the recent winner is a highly trained, professional cyclist whose entire life-style has been dedicated to reach his pinnacle during this event. The TDF has been held successfully for 100 years, but the application of the physiologic sciences to the sport is a relatively recent phenomenon. Although some historical reports help to understand the unique physiological characteristics of this race, scientific studies were not available in Sports Science/Applied Physiology journals until the 1990s. The aim of this article is to review the history of the TDF. Special emphasis is placed on the last decade where classic physiology has been integrated into applied scientific cycling data.

Prediction of drafted-triathlon race time from submaximal laboratory testing in elite triathletes

PURPOSE AND METHODS

To determine which physiological variables accurately predict the race time of an Olympic-distance International Triathlon undertaken in drafted conditions, 8 elite triathletes underwent both maximal and submaximal laboratory and field physiological testing: a 400-m maximal swim test; an incremental treadmill test; an incremental cycling test; 30 min of cycling followed by 20 min of running (C-R); and 20 min of control running (R) at the exact same speed variations as in running in C-R. Blood samples were drawn to measure venous lactate concentration after the 400-m swim and the cycle and run segments of C-R. During the maximal cycling and running exercises, data were collected using an automated breath-by-breath system.

RESULTS

The only parameters correlated with the overall drafted-triathlon time were lactate concentration noted at the end of the cycle segment (r = 0.83, p < 0. 05) and the distance covered during the running part of the submaximal C-R test (r = 0.92, p < 0. 01). Stepwise multiple regression analysis revealed a highly significant (r = 0.96, p < 0.02) relationship between predicted race time (from laboratory measures) and actual race time, using the following calculation: Predicted Triathlon Time (s) = 1.128 (distance covered during R of C-R [m]) + 38.8 ([lactate] at the end of C in C-R) + 13,338. The high R2 value of 0.93 indicated that, taken together, these two laboratory measures could account for 93% of the variance in race times during a drafted triathlon.

CONCLUSION

Complementing previous studies, this study demonstrates that different parameters seem to be reliable for predicting performance in drafted vs. nondrafted Olympic-triathlon races. It also demonstrates that, for elite triathletes competing in a drafted Olympic-distance triathlon, performance is accurately predicted from the results of submaximal laboratory measures.

Intensity of exercise according to topography in professional cyclists

PURPOSE

The aim of the study was to analyze the intensity of effort made by professional cyclists in the different mountain passes climbed during the 1999 and 2000 Vuelta a España.

METHODS

During the ascent of high mountain passes of different categories (special category (HMS), and 1st (HM1), 2nd (HM2), and 3rd category (HM3)), the response of the HR was analyzed according to three intensity zones: zone 1(Z1, above the ventilatory threshold (VT)), zone 2 (Z2, between VT and the respiratory compensation threshold (RCT)), and zone 3 (Z3, above the RCT).

RESULTS

The values are presented as mean +/- SEM. Values of HR were significantly higher (P < 0.05) in HM1 (160 +/- 1 beats x min-1) compared with the other types of ascents. When we compared the different passes, the intensity decreased in the following order: HM1, HMS, HM2, and HM3. The average time that cyclists spent in Z3 was significantly higher in HM1 (10.7 +/- 1.4 min) with respect to the other categories. The time in Z2 was significantly higher in HMS and HM1 (43.1 +/- 1.5 and 44.3 +/- 3.1 min) than in HM2 and HM3 (21.6 +/- 1.1 and 11.9 +/- 1.1 min). The percentage of total time spent in Z3 was significantly higher in HM1 and HM3 (21.2 +/- 2.9 and 17.3 +/- 1.9%) than in HME and HM2.

CONCLUSION

The ascent of mountain passes is an activity involving intense effort which is reflected in the time cyclists spend in Z3 and Z2, and is related to the category of the mountain passes involved.