Printer Friendly

Physiological demands of simulated off-road cycling competition.

Introduction

The history of off-road cycling or mountain biking (MB) began in the mid 1970s. Popularity of MB rapidly developed from a minority group activity to a worldwide sport. The implementation of the first World Championship in Durango (USA) in 1990 and the first MB competition (COMP) at the Olympic Games in Atlanta in 1996 further contributed to shift MB toward a professional sport.

Current COMPs are typically performed on rocky dirt trails, sometimes complicated by tree roots, and commonly consist of alternating technical descents, flat sections and hill climbs. Previous findings indicate that data derived from road cycling can only be partially transferred to off-road events (Impellizzeri et al., 2005b; Impellizzeri and Marcora, 2007; Lee et al., 2002).

To date, only limited empirical evidence is available to assess and compare the physiology of off-road cyclists to provide a scientific basis to monitor training progress.

Earlier studies used primarily heart rate (HR) to determine workload profiles (Faiss et al., 2007; Gregory et al., 2007; Hurst and Atkins, 2006; Impellizzeri et al., 2002; 2005b; MacRae et al., 1999; Nishii et al., 2004; Prins et al., 2007; Seifert et al., 1997; Stapelfeldt et al., 2004). Other investigations used blood lactate (BLa) measures (Gregory et al., 2007; MacRae et al., 1999; Nishii et al., 2004) to ascertain information regarding the metabolic demand during competitive off-road cycling and some studies (Gregory et al., 2007; MacRae et al., 1999; Nishii et al., 2004; Stapelfeldt et al., 2004) have evaluated power output (PO) during COMP.

However, the pattern of workload observed in COMP limits the utility of BLa measures to determine metabolic demand. Since BLa accumulation in COMP occurs quickly, depending on the course (Bond et al. 1991), it may reflect only periods of high intensity work rather than overall load profile of COMP. Also HR response is problematic to assess load profile of MB as it may be influenced by psychological stress performing COMPs (Baron et al., 1992). Furthermore, HR is known to be behind instantaneous changes in power output (Jagoda et al., 2014) and HR even at given PO increases in the time course of exercise (Soares-Caldeira et al., 2012).

Power measures derived from MB pedals represent exertion of force expended by lower limbs and not overall physical activity pattern since off-road cycling on rough terrain requires recruitment of additional muscle mass to handle the bike, stabilize the body against gravity, and respond to heavy vibration (Fraiss et al., 2007; Rittweger et al., 2002).

Considering these above mentioned limitations of single parameters utilized in previous investigations, the main aim of our study was to describe the load profile of COMPs in subjects with different sport-specific performance via the combination of BLa measures and real-time measures of PO, HR and respiratory gas parameters. These normative data may be useful to coaches, athletes and sport scientists working with competitive athletes. We also sought to identify whether laboratory tests (LabT) can serve as predictors for sport specific MB performance.

Methods

Subjects

Twenty-four healthy male competitive off-road cyclists (mean [+ or -] SD: age 29 [+ or -] 7.2 years, height: 1.79 [+ or -] 0.05 m, body mass: 70.0 [+ or -] 4.9 kg, V[O.sub.2peak]: 64.9 [+ or -] 7.5 ml x [kg.sup.-1] x [min.sup.-1]) participated in this study. Athletes participating in this study ranged from competitive amateur racers (5 subjects) to competitive athletes with national ranking (18 subjects). Additionally, one "high performance athlete" (HPA) (age: 26 years, height: 1.84 m, body mass: 75.0 kg, V[O.sub.2peak]: 79.9 ml x [kg.sup.-1] x [min.sup.-1]) that had been in the top 10 of the 2012 Olympic Games volunteered for this study. Subjects were asked to refrain from intense training within 48 h before all tests. Furthermore, the athletes had to record nutritional intake and fluid consumption during a period of 48 h prior to both tests and were asked to utilize the same procedure prior to both trials (LabT, COMP).

The University of Vienna Ethics Committee approved the study and all subjects agreed and signed an informed consent prior to participation.

Laboratory Tests (LabT)

One-minute incremental cycle ergometer tests to maximal voluntary exhaustion were conducted on an electronically braked cycle ergometer (Lode Excalibur Sport, Groningen, Netherlands) according to performance level of the subjects. Based on previous exercise tests LabT were designed to last between 15 to 20 min (starting load 20W; increment size 20 W x [min.sup.-1], 25 W x [min.sup.-1] or 30 W x [min.sup.-1]). During each trial, participants pedaled at their preferred cadence between 70 to 100 rev x [min.sup.-1]. V[O.sub.2peak] was determined as the highest mean 30 s value calculated from breath-by-breath measures during LabT. Tests were administered one week prior to the simulated COMP. Respiratory gas measures were conducted using a wireless portable ergo-spirometry system (Oxycon Mobile Pro, Jager, Wurzburg, Germany) in breath-by-breath mode. Volume and gas calibration of the portable system was conducted before each test according to the manufacturer's guidelines. In both test series' (LabT and COMP) BLa was determined utilizing a fully enzymaticamperometric method (Eppendorf ESAT 6666, Hamburg, Germany). HR was determined by means of a chest-belt telemetry monitor (Polar Mod. T61, Kempele, Finland) transmitted to the portable system.

LabT was utilized to determine PO, V[O.sub.2], HR, VE, RER and BLa at maximal workload and respiratory thresholds (VT1 and VT2) (Table 1). Duration was recorded at the final stage of LabT and utilized for linear extrapolation of PO at maximum load. The VT1 introduced by Wasserman (Wasserman and Mcllroy, 1964) was defined using the following criteria: first upward shift in VE, an increase in VE/V[O.sub.2] without an increase of VE/C[O.sub.2] and an increase in oxygen end-tidal volume (PET[O.sub.2]). The VT2, as reported by Beaver et al. (1986) and originally termed respiratory compensation point, was identified by a second upward shift in VE, an increase in VE/C[O.sub.2] and a decrease in carbon dioxide end-tidal volume (PETC[O.sub.2]). Determining VT1 and VT2 from LabT, three phases of aerobic-anaerobic transition (Skinner and McLellan, 1980) were established: 1) Phase 1 constitutes predominant aerobic energy supply (end of VT1); Phase 2 is the compensation phase (between VT1 and VT2); and Phase 3 is the decompensation phase (beginning of VT2). LabT data were deemed useful to provide relevant information to other measures made during COMP trials.

Mountain Bike Competition/"Cross Country" (COMP)

The COMP was conducted in a wooded area, on a hilly, rocky, single trail with many roots and curves. The entire COMP was divided into four identical laps. The distance for one lap was 6,087 [+ or -] 69 m (Figure 1), the overall distance of the COMP, consisting of 4 laps, was 24,348 [+ or -] 195 m. Distance was recorded using a bicycle computer in each case and given as mean of all athletes. The course was chosen as a typical cross country course (single competition with repeated identical laps) according to UCI Cycling Regulation E0414 (Version on 4.04.14). The characteristics of the course made it possible to divide the rounds into three sections (Figure 1): 1) Start with section 1 (GPS: longitude: 48.247310, latitude: 16.267591; starting at an elevation of 308 m; ending at an elevation of 456 m); uphill section, distance: 2,095 [+ or -] 19 m, average grade: 7.1%, highest grade (distance of 100 m): 15.0%; ground condition: alternation of stony ground with roots, sometimes covered with leaves 2) Section 2: (GPS: longitude: 48.51893; latitude: 16.248302, ending at an elevation of 462 m); rather flat terrain; maximal altitude deviation of 15 m; length 1,553 m [+ or -] 23 m; ground condition: hard ground often covered with gravel and granite-grit; 3) Section 3 (GPS: longitude: 48.54545; latitude: 16.265741; finishing at the Section 1/Start); downhill section with narrow curves; length 2,439 [+ or -] 27 m, average grade: 6.3%; highest grade (distance of 100 m): 10.5%; ground condition: hard ground with stones, sometimes covered with leaves. Values for altitude and elevation were determined from a special map utilized in orienteering competitions.

All COMP's were performed using an identical cycle (Mountain-Bike: Specialized Epic Comp 2005, Morgan Hill, California, USA; frame: Epic-FSR-M4 Aluminum; suspension strut: Specialized AFR inertia, Brain Fade; suspension fork: Fox F100 RL, Specialized). All subjects were equipped with a powermeter and the identical portable spirometry system during LabT.

During the COMP, data collection was conducted utilizing the same spirometry system as during the LabT. A powermeter (SRM/MTB, Julich, Germany) allowed for on-line measures of power output and cadence during COMP. Both systems were synchronized and data were sampled in time intervals of 5 s. During COMP field variables were measured (RT, POCOMP, HRCOMP, V[O.sub.2]COMP, VECOMP, RERCOMP, BLaCOMP and cadence (see Table 2). Raw data from SRM and spirometry were synchronized to 5 s intervals. This was the shortest constant interval to be depicted from both the spirometry system and the SRM system utilizing the manufacturers software. Blood samples for determination of BLa were taken immediately after completion of each lap of COMP resulting in interruptions of approximately 30 s for blood collection after each lap. Method of blood sampling and BLa measures was identical with that utilized in laboratory.

Statistical analyses

Statistical analyses were conducted using Statistica Software (Version 6.0, StatSoft, Inc. Tulsa, OK, USA). The results were expressed as mean [+ or -] SD. Measure of the linear correlation between two variables was calculated using Pearson Product Moment Correlation. The level of significance was set at p < 0.05. Normal distribution of the sample was evaluated utilizing Shapiro-Wilk-Test in all cases. Evaluation of differences between means of field variables recorded during the four laps as well as recorded during uphill, nearly flat and downhill cycling was conducted by one-way analysis of variance (ANOVA) with repeated measures. Post-hoc comparison was made by employing the Least Significance Test. A k-means cluster analysis for three clusters based on RTMBC was used to separate data into three groups of subjects with different sport-specific performance capacity. The analysis of variance (ANOVA) and Tukey HSD tests were employed to detect significant differences between clusters (for field as well as for laboratory variables).

Results

Table 1 depicts results of LabT for study variables determined for power output at VT1, VT2 and maximum load for all subjects, including the criterion HPA. Table 2 shows results of the simulated COMP. All values in Table 2 were calculated for the entire COMP and for each lap. Values of field-testing (COMP) are also reported for the HP A (Table 2). When considering the racing time of single laps of COMP, the first lap was completed significantly faster than the subsequent three laps. That was associated with significantly higher values for P[O.sub.COMP], V[O.sub.2COMP], and BLaCOMP in lap 1 (Table 2). The higher V[O.sub.2] was found in lap 1 that was also accompanied by a higher ventilatory effort ([V.sub.ECOMP]) (Table 2). In contrast, no differences between the single laps were found for HR.

In approximately 12% of entire RT, we found no or low PO (less than 30 Watt) determined from the SRM powermeter. When manually eliminating phases of no or low PO from 5 s measures (phases of rolling, downhill riding, and racing through sharp turns) the average P[O.sub.COMP] of athletes increased from 2.64 [+ or -] 0.43 W x [kg.sup.-1] to 3.13 [+ or -] 0.49 W x [kg.sup.-1] and from 3.52 W x [kg.sup.-1] to 4.11 W x [kg.sup.-1] for the HPA, respectively.

The entire data set of 24 subjects with a broad range of performance capacities was additionally divided into three groups based on [RT.sub.COMP] (k-means cluster analysis for three clusters based on RT). The ANOVA and Tukey HSD-test revealed significant differences in [RT.sub.COMP] between the three groups (p < 0.001 in all cases; see Table 3). Tables 3 and 4 depict data of the three clusters calculated for COMP and LabT. These variables represent the physical activity pattern and endurance performance of cyclists with different sport specific MB levels.

We were additionally interested in the question of whether a faster [RT.sub.COMP] resulted in higher metabolic responses. When calculating a correlation between [RT.sub.COMP] vs. variables of energy demand of COMP (P[O.sub.COMP], V[O.sub.2COMP], [VE.sub.COMP], [HR.sub.COMP], [BLa.sub.COMP]) we found a significant negative correlation between [RT.sub.COMP] vs. P[O.sub.COMP] (p < 0.001; r = -0.78), [RT.sub.COMP] vs. V[O.sub.2COMP] (p < 0.001; r = -0.83) and [RT.sub.COMP] vs. [V.sub.ECOMP] (p < 0.05; r = 0.60). There was no evidence that ]BLa.sub.COMP] and/or cadence had an influence on [RT.sub.COMP]. When examining ventilatory data, we found significant positive correlations between P[O.sub.COMP] vs. V[O.sub.2COMP] (p < 0.001; r = 0.71) and P[O.sub.COMP] vs. [V.sub.ECOMP] (p < 0.01; r = 0.53).

We further analyzed P[O.sub.COMP], V[O.sub.2COMP], and [R.sub.COMP] when expressed as percentages of corresponding variables during LabTs. Mean P[O.sub.COMP] was 61.9% of P[O.sub.VT2] and 47.2% of P[O.sub.max], whereas V[O.sub.2COMP] was 112% of V[O.sub.2VT2] and 88% of V[O.sub.2peak] and [HR.sub.COMP] was 102% of [HR.sub.VT2]s and 90% of [HR.sub.max]. Calculating differences by one-way ANOVA with repeated measures (post-hoc Least Significance Test), we found the percentages for PO were significantly lower than that detected for V[O.sub.2] and HR (p < 0.001 in all cases). The following values were found for the HPA: P[O.sub.COMP] 67.8% of P[O.sub.VT2]; 54.2% of P[O.sub.max]; V[O.sub.2COMP] 112% of V[O.sub.2VT2]; 89% of V[O.sub.2peak] and [HR.sub.COMP] 102% of [HR.sub.VT2]; and 91% of [HR.sub.max]. The comparison of COMP and LabT data for all subjects are also presented in Figures 2A, 2B and 2C.

Our COMP trail was divided into three sections with different gradients, uphill, flat and downhill terrain (Figure 1). The COMP values calculated for the three sections are presented in Table 5. In addition, we provide information regarding the intensity pattern determined during COMP. The COMP variables of P[O.sub.COMP], V[O.sub.2COMP], and [HR.sub.COMP] were compared with maximal values measured during LabT (Figure 3), whereby the total time spent at various percentage bands (10% bands) are expressed as percentage of peak values determined in LabT_(Figures 3 A, 3B and 3C). The variables of cardiopulmonary demands (V[O.sub.2COMP], [HR.sub.COMP]) appeared at considerably higher percentage ranges (Figures 3B and 3C) when compared to P[O.sub.MTB] (Figure 3A). For V[O.sub.2COMP] (Figure 3B) the most frequent intensity range was 100110% of V[O.sub.2peak] (29.2% for the entire [RT.sub.COMP]) and the most frequent intensity range for [HR.sub.COMP] (Figure 3C) was 90-100% of [HR.sub.max] (60.6% for the entire [RT.sub.COMP]). In contrast, for P[O.sub.COMP] the highest value found in a percentage band was found between 50-60% of P[O.sub.max] of LabT (18.4% for the entire RT; Figure 3A). This result again demonstrates the essential differences of [P.sub.COMP] compared to variables of cardiopulmonary demands and V[O.sub.2] during COMP.

Finally, we assessed performance measurements of COMP ([RT.sub.COMP] and P[O.sub.COMP]) to endurance measures of LabT to determine the relationship and association of these variables. We calculated the correlation between [RT.sub.COMP] and [P.sub.COMP] and endurance variables of LabT (PO and V[O.sub.2]) determined at maximal workload and at VT1 and VsT2 (Table 6). No correlation was found for BLa during LabT ([BLa.sub.COMP] vs. [BLa.sub.max], [BLa.sub.VT2] and B[La.sub.VT1]).

The association between sport specific performance of COMP ([RT.sub.COMP]) and results of LabT are also supported by our clusters showing that in the cluster with the shortest [RT.sub.COMP] (good performance; Table 3) all endurance variables of subjects (Table 3) were significantly higher than those observed in the other two clusters with significantly lower [RT.sub.COMP] (p < 0.001 between Cluster "Good Performance" vs. "Low Performance" in all cases and p < 0.01 between Cluster "Good Performance" vs. "Medium Performance" in all cases).

Discussion

The main aim of this study was to assess load profile of COMP ("Cross Country"). To our knowledge, this is the first study evaluating oxygen costs of an entire COMP using open circuit spirometry. Combining V[O.sub.2] with measures of PO, HR and blood lactate may provide additional information about the external workload and metabolic response of athletes performing COMP. Our group of competitive MB cyclists and a single high level professional MB cyclist were used for that purpose.

Regarding the mean V[O.sub.2peak] determined from our LabT (Table 1), there are MB studies reporting higher V[O.sub.2max]/V[O.sub.2peak] values (Baron, 2001; Impellizzeri et al., 2002; 2005a; 2005b; 2008; Lee et al., 2002; Nishii et al., 2004; Wilber et al., 1997), others with comparable values (Gregory et al., 2007; Prins et al., 2007; Stapelfeldt et al., 2004) and others with lower values (Faiss et al., 2007; MacRae et al., 1999) (Table 7). Our subjects exhibited a broad range of aerobic capacities (Table 1) and sport specific performance (Table 2). We divided the group into three clusters based on RTCOMP. The resulting clusters of good, medium and low performance document aerobic power of three groups of MB cyclists with significantly different sport specific abilities (Table 3).

The mean maximal power (P[O.sub.max]) determined from LabT for all subjects in our investigation (Table 1) was lower than that of Impellizzeri et al. (2005a), Impellizzeri et al. (2005b), Nishii et al. (2004), Lee et al. (2002) and Wilber et al. (1997), comparable with results of Baron (2001) and Impellizzeri et al. (2002) and higher than those reported by Gregory et al. (2007), MacRae et al. (1999), Prins et al. (2007) and Stapelfeldt et al. (2004) (Table 7). The P[O.sub.max] found for the three clusters of good, medium, and low performance participants were significantly different (p < 0.001; Table 3).

The data determined for the HPA (Table 1) during LabT were lower than the highest values (V[O.sub.2max] of 86.1 ml x [kg.sup.-1] x [min.sup.-1] and P[O.sub.max] of 7.4 W x [kg.sup.-1]) reported by Impellizzeri et al. (2005a) for a single elite cyclist. Comparing data of HPA (Table 1) with mean values of Earnest et al. (2009) who examined 26 professional road cyclists that repeatedly participated in Grand Tours (Tour de France and Vuelta), we found higher V[O.sub.2peak] (75.8 [+ or -] 5.5 9 ml x [kg.sup.-1] x [min.sup.-1]) and lower P[O.sub.max] (7.06 [+ or -] 0.51 W x [kg.sup.-1]) for the HPA.

We additionally determined V[O.sub.2] and PO at VT1 and at VT2 (Table 1) for athletes and found only a single study that utilized a comparable threshold concept (Impellizzeri et al. 2005a). The authors presented higher mean values (56.8 [+ or -] 4.8 ml x [kg.sup.-1] x [min.sup.-1] for V[O.sub.2VT1], 67.3 [+ or -] 4.8 ml x [kg.sup.-1] x [min.sup.-1] for V[O.sub.2VT2], 4.1 [+ or -] 0.6 W x [kg.sup.-1] for POVT1 and 5.4 [+ or -] 0.4 W x [kg.sup.-1] for P[O.sub.VT2]) for their MB athletes_compared to our sample. The HPA (Table1) again exhibited lower values at VT1 and VT2 compared to the highest values measured for a single athlete by Impellizzeri (2005a) (V[O.sub.2VT1]: 67.5 ml x [kg.sup.-1] x [min.sup.-1], V[O.sub.2VT2d]: 75.0 ml x [kg.sup.-1] x [min.sup.-1], P[O.sub.VT1]: 5.2 W x [kg.sup.-1] and P[O.sub.VT2]: 6.1 W x [kg.sup.-1]). The mean BLa observed at VTs was relatively low (Table 1). For example, Smekal et al. (2012) determined [BLa.sub.VT2] of 4.5 [+ or -] 1.1 mmol x [l.sup.-1] in a group of 62 subjects (42 men and 20 women) with a broad range of V[O.sub.2peak] (34.1 to 74.8 ml x [kg.sup.-1] x [min.sup.-1]).

Characteristics of the COMP trail and racing time

The COMP trail was a rocky, hilly single trail with many roots and stones in a wooded area. The entire distance consisted of four identical laps (Figure 1) comprising ~24,348 m (average for entire four laps of [RT.sub.COMP] was 1:05:24 [+ or -] 6:03 (h:mm:ss; Table 2, Table 3). As expected, the fastest [RT.sub.COMP] was completed by the HPA (0:51:49; see Table 2). As mentioned above, the course was chosen as a cross country course (single competition with repeated identical laps) according to UCI Cycling Regulation E0414 (Version on 4.04.14). The average [RT.sub.COMP] was somewhat shorter than specified for a Cross-Country Olympic XCO (UCI sanctioned race between 1:15:00 and 1:30:00) and longer than a Cross-Country Short Circuit XCC, Short Track (UCI sanctioned for races with a duration of 00:30:00 to 01:00:00 hh:mm:ss). Our athletes started the COMP with high ambition--a fact that was demonstrated by a significantly faster first lap than the following three laps (Table 2). This pacing strategy may be surprising in the light of previous data suggesting that uniform racing pace may be advantageous for cycling time trials (Atkinson et al., 2000; 2003; Impellizzeri and Marcora, 2007; Mattern et al., 2001) but there are also findings suggesting that the pacing strategy observed in our investigation is not unusual in cross-country cycling (Impellizzeri et al., 2002; Stapelfeldt et al., 2004). The faster racing time of lap 1 also resulted in significantly higher values for P[O.sub.COMP], V[O.sub.2COMP], [V.sub.ECOMP] and [BLa.sub.COMP] (Table 2). In contrast, [HR.sub.COMP] was similar and not significantly different between all four laps, demonstrating that HR measures are not sensitive to ascertain load profiles of off-road events (Smekal et al. 2003).

Physiological profile of COMP/V[O.sub.2], HR

The average V[O.sub.2COMP] calculated for all subjects was 57.0 ml x [kg.sup.-1] x [min.sup.-1] or 12.0% lower than the V[O.sub.2peak] determined in LabT, and 13.1% higher than the V[O.sub.2VT2] (Figure 2B, Tables 1 and 2). No significant differences were found between the clusters in this context. Despite significantly different sport specific performance capacity observed between the clusters, COMP was completed within comparable intensity. For the HPA, the V[O.sub.2COMP], corresponded to 88.9% of V[O.sub.2peak] or 110.4% of V[O.sub.2VT2].

However, these data refer to the fact that riders during cross-country MB exhibit a considerable high intensity. This observation is in line with findings reported by Impellizzeri et al. (2002) and Impellizzeri and Marcora (2007). Impellizzeri et al. (2002) monitored nine MB athletes (six under 23 years old and three elite/UCI categories) calculating a somewhat lower mean percentage of 84 [+ or -] 3% of V[O.sub.2peak] from HR data measured during different MB competitions. But in this study, the mean duration of races was longer 147 [+ or -] 15 min than in our investigation. Comparing our recent data with those determined from another off-road event in running (orienteering), athletes of the Austrian National Team showed an average V[O.sub.2] during simulated competitions (mean duration 57:44 min) of 83.0 [+ or -] 3.8% of athlete's V[O.sub.2max] obtained in a TT. However, the high percentage of V[O.sub.2COMP] with respect to V[O.sub.2max] of LabT illustrates the aerobic abilities that are required to meet the physiological demand of off-road cycling.

The findings of high oxygen costs of MB are supported by the V[O.sub.2] time duration. Expressing the total time spent at various percentage bands (10% bands) as percentages of peak values determined from LabTs, the highest intensity band for V[O.sub.2COMP] (Figure 3B) was found between 100-109.9% of V[O.sub.2peak] (29.2% for the entire [RT.sub.COMP]). These V[O.sub.2COMP] values are likely attributable to high muscular effort and greater engaging muscle mass of the athletes not only for maintaining the workload and cadence but also for bike handling, bike and body stabilization working against gravity, rolling resistance and heavy bike vibration (Fraiss et al., 2007; Rittweger at al., 2002). This notion is supported by the finding that during downhill sections V[O.sub.2] values decreased, corresponding to no less than 70% of V[O.sub.2peak] (Table 5).

Regarding the respiratory gas exchange measures, only a few papers are comparable to our study. To our knowledge, only a single investigation is currently available that measured V[O.sub.2] during a short phase of MB cycling (Fraiss et al. 2007). But these data are not really comparable to ours, since cyclists were instructed to cycle at a HR corresponding to the HR determined at their anaerobic threshold (LA concentration of ~4.0 mmol x [l.sup.-1]).

The [HR.sub.COMP] (Table 2, Figure 2C) was 169 [+ or -] 13 bpm corresponding to 89.8% of [HR.sub.max] and 102.2% of [HR.sub.VT2] (Figure 2C). These values are similar to those reported in the literature. Impellizzeri et al. (2002) found an average [HR.sub.COMP] of 171 [+ or -] 6 bpm (mean of 4 COMP) for well trained, competitive MB cyclists with a mean V[O.sub.2peak] of 75.0 [+ or -] 6 ml x [kg.sup.-1] x [min.sup.-1] corresponding to 90.0 [+ or -] 3% of [HR.sub.max]. However, in this study, the racing distance was longer, ranging between 33 and 44 km. In a different investigation of simulated COMP with a mean RTCOMP of 1:36:33 hour, Impellizzeri et al. (2005b) measured a HRmax of 90.0 [+ or -] 4%. Stapelfeldt et al. (2004) examined 11 national team cyclists (9 male, 2 female) during 15 races (RTcomp between 1:58 and 2:27 hours) and calculated an average [HR.sub.COMP] of 177 [+ or -] 6 bpm for male cyclists with a HRmax of 91.7%. In a study published by Gregory et al. (2007) investigating nine A-class MB cyclists with a mean V[O.sub.2peak] of 67.1 [+ or -] 3.6 ml x [kg.sup.-1] x [min.sup.-1] reported a mean [HR.sub.COMP] of 91.2% of [HR.sub.max] during a simulated COMP (mean [RT.sub.COMP] of 61:33 min).

When assessing HR times (Figure 3C) and dividing the entire [RT.sub.COMP] into percent ranges of 10%, the most frequent percent range was between 90-99.9% of [HR.sub.max] (60.6% for the entire [RT.sub.COMP]). In practice, HR values during off-road cycling events support the findings of high demand of whole body cardiopulmonary requirements. Assessing the average HR of the four laps of our COMP, we observed the average HR of all laps to be very similar (Figure 2C, Table 2). In contrast, PO and V[O.sub.2] were significantly higher in lap 1 resulting in a significantly faster RT in lap 1 (Table 2).

Physiological measures of COMP/PO, BLa, cadence

The component of POCOMp was substantially different compared to variables of cardiopulmonary demands and V[O.sub.2] of COMP (V[O.sub.2COMP] and [HR.sub.COMP]). The relative P[O.sub.COMP] calculated for all subjects (2.66 [+ or -] 0.43 W x [kg.sup.-1]; see also Tables 1 and 2) accounted for 47.2% of P[O.sub.max] and 61.9% of P[O.sub.VT2]. As demonstrated in Figure 2A, Tables 1 and 2, the mean P[O.sub.COMP] calculated for all subjects was similar to P[O.sub.VT1] determined during the LabT (P[O.sub.VT1]: 2.67 W x [kg.sup.-1]). The mean P[O.sub.COMP] value for our total group of cyclists was higher compared with the PO measured in a group of German National Team cyclists (Stapelfeldt et al. 2004) during 15 races (3.5 W x [kg.sup.-1]). Nevertheless, in the investigation of Stapelfeldt, RT was longer (mean RT: 2:08 h). In another study by Nishii et al. (2004), they reported a higher mean PO (3.76 and 3.78 W x [kg.sup.-1]) when comparing two different suspension systems during offroad cycling (RT of 30 min). The HPA (Table 2) revealed a higher P[O.sub.COMP] in comparison to the group of German National Team MB cyclists tested by Stapelfeldt et al. (2004) and Nishii et al. (2004).

However, the relatively low values of P[O.sub.COMP] in our group of cyclists were also influenced by the periods of cycling where there was no or very low force production applied to the pedals, particularly during the downhill portion (Table 5, Figure 4). By manually eliminating low power output phases and removing time with no or very low power output (less than 30 Watts) from the data set the average P[O.sub.COMP] increased from 2.64 [+ or -] 0.43 W x [kg.sup.-1] to 3.13 [+ or -] 0.49 W x [kg.sup.-1]. After removal of these low PO phases, the P[O.sub.COMP] corresponded to only 59.0% of P[O.sub.max], 77.4% of P[O.sub.VT2] and 124.7% of P[O.sub.VT1]. Compared to our HPA, the mean P[O.sub.COMP] increased from 3.52 W x [kg.sup.-1] to 4.11 W x [kg.sup.-1] during active phases.

As previously mentioned, the increase in V[O.sub.2COMP] and [HR.sub.COMP] may be attributed to the larger muscle mass simultaneously working to fulfill the demand of MB. It cannot be ruled out that blood flow to lower limbs may have been reduced (Volianitis et al., 2003) in these conditions. This assumption is supported by findings showing that depending on exercise intensity, blood flow to exercising leg muscles is reduced due to the recruitment of additional muscle mass (e.g. arm exercise) (Bangsbo et al., 1997; Richardson et al., 1997; Richter et al., 1992; Savard et al., 1989), thus negatively influencing leg muscle oxygenation. As a result, leg muscle performance and force production might be considered to be impaired. The low [P.sub.COMP] measured in the present study may also have been influenced by the topography of our trail, which was difficult to maneuver, consisting of a variety of roots, curves, sometimes loam and cluttered with large stones. This was especially true during the uphill stages. This terrain characteristic may have forced athletes to react with much caution when pedaling and required strategic and technical knowledge of each cyclist. That has been subsequently confirmed by the athletes.

The blood lactate concentration ([BLa.sub.COMP]) (mean of four laps) was 5.98 [+ or -] 1.38 mmol x [l.sup.-1] (Table 2), while no differences were observed between the clusters (Table 3). This [BLa.sub.COMP] was nearly identical with that reported by Nishii et al. (2004) and lower than that found by Gregory et al. (2007) and MacRea et al. (1999), who determined mean BLa values between 8.0 and 9.0 mmol x [l.sup.-1]. However, in the investigation of Nishii et al. (2004) that was similar to ours, blood samples were collected after a longer period of downhill riding, while in the study of Gregory et al. (2007) the downhill passage prior to blood sampling was very short (600 m). In the study of MacRea et al. (1999) the BLa was measured following an uphill section. The BLa measured in sports with intermittent workload are substantially influenced by the high intensity work, the amount and duration of phases and the time of blood sampling following these sections. Consequently, BLa measures during off-road cycling similar to off-road running (Smekal et al., 2003) may not be appropriate to evaluate varying load profiles and may lead to inaccurate estimates of a physical activity pattern of MB.

Concerning cadence during COMP, there were no significant differences with respect to laps (Table 2) as well as between the three clusters with different COMP performances (Table 4). A higher cadence was found for the HPA compared to all subjects (Table 2 and Table 4). However, our approach using mean values may be problematic to describe the variable cadence accurately under these conditions.

Relationship between RT vs. other study variables of field testing

It is not surprising that faster [RT.sub.COMP] resulted in higher load profiles, a finding that has been documented by significant correlations found between [RT.sub.COMP] vs. P[O.sub.COMP], V[O.sub.2COMP], [V.sub.ECOMP] and [HR.sub.COMP]. There was no evidence of an influence of [BLa.sub.COMP] and cadence associated with [RT.sub.COMP] . Despite the above described differences between P[O.sub.COMP] and V[O.sub.2COMP], these two variables were significantly and positively correlated. In addition, [V.sub.ECOMP] was correlated with P[O.sub.COMP], indicating higher ventilatory effort with higher workload.

Association between LabT and COMP variables

We further found that endurance variables were credible predictors for sport specific performance of [RT.sub.COMP] and P[O.sub.COMP]. This statement is supported by significant correlations between [RT.sub.COMP] and [P.sub.COMP] and variables of aerobic power (LabT; Table 6). This result underlines the necessity for sport specific abilities of successful MB performance. Our study is in agreement with others who also reported significant correlations between [RT.sub.COMP] and endurance variables determined from LabT (Gregory et al., 2007; Impellizzeri et al., 2005a; 2005b). In spite of these reported results, only 65% of the variance could be explained by a single endurance variable (Table 6). Comparisons between LabT and COMP (Tables 1, 2 and 5) demonstrate the different practical relevance of variables. Data determined from LabT may be utilized to supplement specific abilities of MB athletes on a cycle ergometer, while findings originating from COMP could be especially considered when designing mountain bike specific training.

Finally we want to refer to some limitations. As mentioned before, the average RTcomP due to loading capacity of the batteries (time for warming up and calibration procedure of the spirometry system, for slowly cycling to the starting point and for performing COMP) was somewhat shorter than specified for a Cross-Country Olympic Competition. Furthermore, within the UCI guidelines, there is a considerable variation concerning the characteristics of a course. Our course (chosen by two semi professional MB trainers) was very rocky with many roots and curves. Participants (including the HP A) described the trail as competitive and technically selective. However, the question is whether data derived from only a single course really reflects the broad spectrum possible for cross-country cycling competitions. We also have to concede that all athletes used the same MB cycle for COMP. This approach seemed practicable, since an accurate service and preparation of equipment (SRM system and cycle) could be completed on evenings prior to tests. Only a short warm-up phase of approximately 10 min remained for participants to become acquainted with the MB cycle (however, during the entire phase of COMP measures there was no critique about the cycle).

Conclusion

The present study resulted in the following main findings: 1) HR and BLa measures were not sufficiently sensitive to ascertain the load profiles of COMP. Therefore, respiratory gas and power output measures are helpful to provide new insights to the physiological profile of cross-country cycling. 2) During COMP, very high oxygen costs exist, probably influenced by the high muscle mass simultaneously working to fulfill the demands of the COMP. On the other hand, based on data determined from LabT (maximum, VT1 and VT2) P[O.sub.COMP] turned out to be lower when compared to V[O.sub.2COMP], likely caused by phases of no or very low force production applied to the pedals (particularly during the downhill phases), by the rocky trail with many roots and stones forcing athletes to react with caution and maybe also by a lower blood flow and leg muscle oxygenation due to the recruitment of a high number of muscle groups. 3) An excellent endurance cycling ability appears to be a prerequisite for COMP, but good sport-specific abilities are also needed for successful off-road cycling. 4) Data determined from LabT might be utilized to describe semi-specific abilities of MB athletes on a cycle ergometer, while data originating from COMP might be useful when designing MB-specific training. 5) Our data only measured a single MB trail, hardly reflective of the broad spectrum of possible cross-country courses. Therefore, generalization of these results is limited.

Key points

* Cross-country cycling is characterized by high oxygen costs due to the high muscle mass simultaneously working to fulfill the demands of this kind of sports.

* Heart rate and blood lactate concentration measures are not sensitive enough to assess the energy requirements of COMP. Therefore, respiratory gas and power output measures are helpful to provide new information to physiological profile of cross-country cycling.

* An excellent cycling-specific capacity is a prerequisite for successful off-road cycling.

* Data determined from LabT might be utilized to describe semi-specific abilities of MB--athletes on a cycle ergometer, while data originating from COMP might be useful when designing a mountain bike specific training.

Received: 11 March 2015 / Accepted: 28 September 2015 / Published (online): 24 November 2015

Acknowledgements

Authors declare no conflict of interest.

References

Atkinson, G. and Brunskill, A. (2000) Pacing strategies during a cycling time trial with simulated headwinds and tailwinds. Ergonomics 43(10), 1449-1460.

Atkinson, G., Davison, R., Jeukendrup, A., and Passfield, L (2003). Science and cycling: current knowledge and future directions for research. Journal of Sports Science 21(9), 767-787.

Bangsbo, J., Juel, C., Hellsten, Y., and Saltin, B (1997). Dissociation between lactate and proton exchange in muscle during intense exercise in man. Journal of Physiology (15)504, 489-499.

Baron, R., Petschnig, R., Bachl, N., Raberger, G., Smekal, G., and Kastner, P. (1992) Catecholamine excretion and heart rate as factors of psychophysical stress in table tennis. International Journal of Sports Medicine 13(7), 501-505.

Baron, R. (2001) Aerobic and anaerobic power characteristics of off-road cyclists. Medicine Science in Sports and Exercise 33(8), 1387-1393.

Beaver, W.L., Wasserman, K., and Whipp, B.J. (1986) A new method for detecting anaerobic threshold by gas exchange. Journal of Applied Physiology 60(6), 2020-2027.

Bond, V, Adams, R.G., Tearney, R.J., Gresham, K., and Ruff, W. (1991) Effects of active and passive recovery on lactate removal and subsequent isokinetic muscle function. Journal of Sports Medicine and Physical Fitness 31(3), 357-361.

Earnest, C.P., Foster, C., Hoyos, J., Muniesa, C.A., Santalla, A., and Lucia, A. (2009) Time trial exertion traits of cycling's Grand Tours. International Journal of Sports Medicine 30(4), 240244.

Fraiss, R., Praz, M., Meichtry, A., Gobelet, C., and Deriaz, O. (2007) The effect of mountain bike suspension on vibrations and off-road uphill performance. Journal of Sports Medicine and Physical Fitness 47(2), 151-158.

Gregory, J., Johns, D.P. and Walls, J.T. (2007) Relative vs. absolute physiological measures as predictors of mountain bike cross-country race performance. Journal of Strength and Conditioning Research 21(1), 17-22.

Hurst, H.T. and Atkins, S. (2006) Power output of field-based downhill mountain biking. Journal of Sports Science 24(10), 1047-1053. Impellizzeri, F.M., Sassi, A., Rodriguez-Alonso, M., Mognoni, P. and Marcora, S. (2002) Exercise intensity during off-road cycling competitions. Medicine Science in Sports and Exercise 3(11), 1808-1813.

Impellizzeri, F.M., Marcora, S.M., Rampinini, E., Mognoni, P. and Sassi A. (2005a) Correlations between physiological variables and performance in high level cross country off road cyclists. British Journal of Sports Medicine 39(10), 747-751.

Impellizzeri, F.M., Rampinini, E., Sassi, A., Mognoni, P. and Marcora, S. (2005b) Physiological correlates to off-road cycling performance. Journal of Sports Science 23(1), 41-47.

Impellizzeri, F.M. and Marcora, M.S. (2007) The physiology of mountain biking. Sports Medicine 37(1), 59-71.

Impellizzeri, F.M., Ebert, T., Sassi, A., Menaspa, P., Rampinini, E., and Martin D.T. (2008) Level gap and uphill cycling ability in elite female mountain bikers and road cyclists. European Journal of Applied Physiology 102(3), 335-341.

Jagoda, A., Jonathan, N., Kaminsky L.A. and Mitchell, H.W. (2014) Heart rate response at the onset of exercise in an apparently healthy cohort. European Journal of Applied Physiology 114, 1367-1375.

Lee, H., Martin, D.T., Anson, J.M., Grundy, D. and Hahn, A.G. (2002) Physiological characteristics of successful mountain bikers and professional road cyclists. Journal of Sports Science 20(12), 1001-1008.

MacRae, H.S., Hise, K.J. and Allen, P.J. (1999) Effects of front and dual suspension mountain bike systems on uphill cycling performance. Medicine Science in Sports and Exercise 32(7), 12761280.

Mattern, C.O., Kenefick, R.W., Kertzer, R. and Quinn T.J. (2001) Impact of starting strategy on cycling performance. International Journal of Sports Medicine 22(5), 350-355.

Nishii, T., Umemura, K. and Kitagawa, K. (2004) Full suspension mountain bike improves off-road cycling performance. Journal of Sports Medicine and Physical Fitness 44(4), 356-360.

Prins, L., Terblanche, E. and Myburgh, K.H. (2007) Field and laboratory correlates of performance in competitive cross-country mountain bikers. Journal of Sports Science 25(8), 927-935.

Richardson, R.S., Kennedy, B., Knight, D.R. and Wagner, P.D. (1997) High muscle blood flows are not attenuated by recruitment of additional muscle mass. American Journal of Physiology 269, H1545-1552.

Richter, E.A., Kiens, B., Hargreaves, M. and Kjaer, M. (1992) Effect of arm-cranking on leg blood flow and noradrenaline spillover during leg exercise in man. Acta Physiologica Scandinavia 144(1), 9-14

Rittweger, J., Ehrig, J., Just, K., Mutschelknauss, M., Kirsch, K.A. and Felsenberg, D. (2002) Oxygen uptake in whole-body vibration exercise: influence of vibration frequency, amplitude, and external load. International Journal of Sports Medicine 2(6), 428432.

Savard, G.K., Richter, E.A., Strange, S., Kiens, B., Christensen, N.J. and Saltin, B. (1989) Norepinephrine spillover from skeletal muscle during exercise in humans: role of muscle mass. American Journal of Physiology 257, H1812-1818.

Seifert, J.G., Luetkemeier, M.J., Spencer, M.K., Miller, D. and Burke, E.R. (1997) The effects of mountain bike suspension systems on energy expenditure, physical exertion, and time trial performance during mountain bicycling. International Journal of Sports Medicine 18(3), 197-200.

Skinner, J.S. and McLellan, T.H. (1980) The transition from aerobic to anaerobic metabolism. Res Q Exerc Sport 51(1), 234-248.

Smekal, G., von Duvillard, S.P., Pokan, R., Lang, K., Baron, R., Tschan, H., Hofmann, P. and Bachl, N. (2003) Respiratory gas exchange and lactate measures during competitive orienteering. Medicine Science in Sports and Exercise 35(4), 682-689.

Smekal, G., von Duvillard, S.P., Pokan, R., Hofmann, P., Braun, W.A., Arciero, P.J., Tschan, H., Wonisch, M., Baron, R. and Bachl, N. (2012) Blood lactate concentration at the maximal lactate steady state is not dependent on endurance capacity in healthy recreationally trained individuals. European Journal of Applied Physiology 112 (8), 3079-3086.

Soares-Caldeira, L.F., Okuno, N.M., Magalhaes-Sales, M., Campbell, C.S., Simoes, H.G. and Nakamura, F.Y. (2012) Similarity in physiological and perceived exertion responses to exercise at continuous and intermittent critical power. European Journal of Applied Physiology 112 (5), 1637-1644.

Stapelfeldt, B., Schwirtz, A., Schumacher, Y.O. and Hillebrecht, M. (2004) Workload demands in mountain bike racing. International Journal of Sports Medicine 25(4), 294-300.

Volianitis, S., Krustrup, P., Dawson, E. and Secher, N.H. (2003) Arm blood flow and oxygenation on the transition from arm to combined arm and leg exercise in humans. Journal of Physiology 547(2), 641-648.

Wasserman, K. and Mcllroy, M.B. (1964) Detecting the threshold of anaerobic metabolism in cardiac patients during exercise. American Journal of Cardiology 14(6), 844-852.

Wilber, R.L., Zawadzki, K.M., Kearney, J.T., Shannon, M.P. and Disalvo, D. (1997) Physiological profiles of elite off-road and road cyclists. Medicine Science in Sports and Exercise 29(8), 10901094.

Gerhard Smekal (1), Serge P. von Duvillard (2, [mail]), Maximilian Hormandinger (1), Roland Moll (1), Mario Heller (3), Rochus Pokan (1), David W. Bacharach (4), Linda M. LeMura (5) and Paul Arciero (6)

(1) Department of Sport Physiology, Institute of Sports Sciences, University of Vienna, Austria; 2 Department of Sport Science and Kinesiology, University of Salzburg, Salzburg, Austria; 3 Section of Biomechanics, Kinesiology and Applied Computer Science, Institute of Sports Sciences, University of Vienna, Austria; 4 Human Performance Laboratory, St. Cloud State University, St. Cloud, Minnesota, USA; 5 Department of Biology, Le Moyne College, Syracuse, New York, USA; 6 Department of Health and Exercise Sciences, Skidmore College, Saratoga Springs, New York, USA.

([mail]) Serge P. von Duvillard, Ph.D., FACSM, FECSS

Department of Sport Science and Kinesiology, University of Salzburg, Rifer Schlossallee 49, A-5400 Hallein/Rif, Austria

AUTHOR BIOGRAPHY

Gerhard SMEKAL

Employment

Prof., Institute of Sports Science, Depart. of Exercise Physiology, Univ. of Vienna

Degree

MD

Research interests

Exercise Physiology, Applied Physiology,

Exercise Science, Sports Analysis, Nutrition

E-mail: gerhard.smekal@univie.ac.at

Serge P. von DUVILLARD

Employment

Visiting Professor, Depart. of Sport Science and Kinesiology at the Univ. of Salzburg

Degree

Ph.D., FACSM, FECSS

Research interests

Applied/Exercise Physiology, Testing and Monitoring and Testing of Elite Athletes, Biomarkers of Performance, Exercise Biochemistry, Exercise Cardiology, Cardiac Rehabilitation

E-mail: spvonduvillard@aol.com

Max HORMANDINGER

Employment

Institute of Sports Science Depart. of Exercise Physiology, Univ. of Vienna Austria

Degree

MS

Research interests

Exercise Physiology, Applied Physiology, Exercise Science

E-mail: mexx.hoermandinger@gmx.at

Roland MOLL

Employment

Institute of Sports Science Depart. of Exercise Physiology Univ. of Vienna Austria

Degree

MS

Research interests

Exercise Physiology, Applied Physiology, Exercise Science

E-mail: info@/dynamo-fit.at

Mario HELLER

Employment

Institute of Sports Science Depart. of Biomechanics Kinesiology and Applied Computer Science Univ. of Vienna Austria

Degree

Ph.D.

Research interests

Sports and Exercise Biomechanics, Analysis of Technique, Surface Electromyography, Applications in Motor Control, Fatigue and Perception of Effort

E-mail: mario. heller@/univie.ac.at

Rochus POKAN

Employment

Institute of Sports Science Depart. of Exercise Physiology Univ. of Vienna Austria

Degree

MD, FACSM

Research interests

Exercise Physiology, Applied Physiology, Internal Medicine, Cardiology, Exercise Science

E-mail: rochus.pokan@univie.ac.at_

David W. BACHARACH

Employment

Professor, St. Cloud State University Director, Human Performance Laboratory St. Cloud, Minnesota, USA

Degree

PhD, FACSM

Research interests

Exercise Physiology, Alpine skiing, Elite Athlete Testing

E-mail: dwbacharach@/stcloudstate. edu

Linda M. LeMURA

Employment

President, LeMoyne College Syracuse,

New York, USA

Degree

Ph.D., FACSM

Research interests

Pediatric obesity, pediatric applied physiology, lipid metabolism, energy metabolism, athlete testing

E-mail: lemuralm@/lemoyne. edu

Paul J. ARCIERO

Employment

Prof., Depart. of Health and Exercise Sciences Director, Human Nutrition & Metabolism Lab, Skidmore College Saratoga, and Research Prof., Psychology Department, Union College, Schenectady, NY

Degree

Ph.D., FACSM

Research interests

Bioenergetics, Nutrition, Exercise, and Physical Activity Interventions, Effects on Energy Metabolism, Sport and Athletic Performance Nutrition, Nutrition & Supplementation, Prevention of Obesity, Diabetes, and Cardiovascular Disease, Optimal Nourishment for Health and Performance

E-mail: parciero @/skidmore. edu

Caption: Figure l.Schematic diagram of the mountain bike course (one of four identical laps). Each lap was divided in three sections: Section 1: uphill section (uphill; start at an elevation of 318m; length ~2095m; and ended at an elevation of 456m). Section 2: rather flat terrain (flat; length ~1553m, and ended at an elevation of 462m). Section 3: downhill section (downhill; start at an elevation of 462m; length ~ 2439m; and finished at the starting point).

Caption: Figure 2. PO (2A), V[O.sub.2] (2B), HR (2C) and BLa (2D) during COMP. Values represent the mean of the entire COMP (2A-2C: average of 5 s; 2D: average of 4 laps) and for every lap. Values are related to variables of LabT (VT1, VT2, and max). Values are means [+ or -] SD for all subjects (n = 24).

Caption: Figure 3. Mountain bike competition: Percentage of total time spent at various percentage bands (10% bands) expressed as percentage of peak values determined from LabTs. Values are shown for PO (3 A), V[O.sub.2] (3B) and HR (3C). Values are means [+ or -] SD for all subjects (n = 24). The term inactive (Figure 3A) depicts the inactive phases of COMP (no power output or power output of less than 30 W).

Caption: Figure 4. Power output and cadence during uphill and downhill phases of COMP. *** p < 0.001.
Table 1. Laboratory tests (LabT). Data are given for relative power
output (PO), oxygen uptake (V[O.sub.2]), heart rate (HR), pulmonary
ventilation ([V.sub.E]), respiratory exchange ratio (RER), and blood
lactate concentration (BLa). Data are shown at maximal load, at the
ventilatory threshold 1 (VT1) and at the ventilatory threshold 2
(VT2). Data are means ([+ or -]SD) for all subjects (n = 24) and for
a high performance athlete (HPA).

Data determined from Laboratory Testing (LabT): All Subjects (n = 24)

Variables                                             Maximum
                                                Load/V[O.sub.2peak]

Power output (W)                                     394 (51)
Power output (W x [kg.sup.-1])                      5.64 (.64)
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])        64.9 (7.5)
HR (bpm)                                             188 (10)
VE (l x [min.sup.-1])                                161 (21)
RER                                                 1.18 (.09)
BLa (mmol x [l.sup.-1])                             10.6 (2.9)

Data determined from Laboratory Testing (LabT): High Performance
Athlete (HPA)

Variables                                             Maximum
                                                Load/V[O.sub.2peak]

Power output (W)                                        500
Power output (W x [kg.sup.-1])                         6.67
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])           79.9
HR (bpm)                                                183
VE (l x [min.sup.-1])                                   188
RER                                                    1.28
BLa (mmol x [l.sup.-1])                                 8.3

Data determined from Laboratory Testing (LabT): All Subjects (n = 24)

Variables                                          VT1         VT2

Power output (W)                                 186 (48     299 (47)
Power output (W x [kg.sup.-1])                  2.67 (.65   4.30 (.62)
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])    34.6 (7.1   50.8 (6.6)
HR (bpm)                                        133 (10)     165 (14)
VE (l x [min.sup.-1])                            55 (16)     90 (17)
RER                                             .88 (.05)   1.00 (.04)
BLa (mmol x [l.sup.-1])                         1.2 (.8)     3.2 (.9)

Data determined from Laboratory Testing (LabT): High Performance
Athlete (HPA)

Variables                                          VT1         VT2

Power output (W)                                   300         405
Power output (W x [kg.sup.-1])                    4.00         5.40
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])      48.1         64.4
HR (bpm)                                           146         170
VE (l x [min.sup.-1])                              94          126
RER                                               0.98         0.93
BLa (mmol x [l.sup.-1])                            0.9         1.9

Table 2. Mountain bike competition (COMP): Data represent racing time
([RT.sub.COMP]), power output (P[O.SUB.COMP]), cadence, oxygen uptake
(V[O.SUB.2COMP]), heart rate ([HR.SUB.COMP]), pulmonary ventilation
([V.SUB.ECOMP]), respiratory exchange ratio ([RER.SUB.COMP]) and blood
lactate concentration ([BLa.sub.COMP]) and are depicted for the entire
COMP and for every lap. Values are (means [+ or -] SD) for all
subjects (n = 24) and for a high performance athlete (HPA).

Data determined form Mountain Bike Competition (COMP): All Subjects
(n=24)

Variables                                         Entire COMP

Racing time (hh:mm:ss)                         01:05:49 (:06:02)
Power output (W)                                   186 (33)
Power output (W x [kg.sup.-1])                    2.66 (.43)
Cadence (rev x [min.sup.-1])                        70 (7)
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])      57.0 (6.8)
Heart rate (bpm)                                   169 (13)
VE (l x [min.sup.-1])                             115 (19.5)
RER                                                .89 (.04)
BLa (mmol x [l.sup.-1])                            6.0 (1.4)

Data determined from Mountain Bike Competition (COMP): High
s

Variables                                         EntireCOMP

Racing time (hh:mm:ss)                             00:51:49
Power output (W)                                      264
Power output (W x [kg.sup.-1])                       3.52
Cadence (rev x [min.sup.-1])                          84
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])         71.1
Heart rate (bpm)                                      181
VE (l x [min.sup.-1])                                 172
RER                                                  0.92
BLa (mmol x [l.sup.-1])                               6.7

Data determined form Mountain Bike Competition (COMP): All Subjects
(n=24)

Variables                                              Lap 1

Racing time (hh:mm:ss)                         00:15:57 (:01:2) (abc)
Power output (W)                                   192 (34) (abc)
Power output (W x [kg.sup.-1])                    2.75 (.45) (abc)
Cadence (rev x [min.sup.-1])                           70 (7)
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])      59.1 (6.9) (abc)
Heart rate (bpm)                                      169 (12)
VE (l x [min.sup.-1])                              120 (21) (bc)
RER                                               .91 (.06) (abc)
BLa (mmol x [l.sup.-1])                           6.7 (1.9) (abc)

Data determined from Mountain Bike Competition (COMP): High
s

Variables                                              Lap 1

Racing time (hh:mm:ss)                                00:12:45
Power output (W)                                        274
Power output (W x [kg.sup.-1])                          3.65
Cadence (rev x [min.sup.-1])                             84
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])            73.0
Heart rate (bpm)                                        179
VE (l x [min.sup.-1])                                   172
RER                                                     0.92
BLa (mmol x [l.sup.-1])                                 6.2

Data determined form Mountain Bike Competition (COMP): All Subjects
(n=24)

Variables                                              Lap 2

Racing time (hh:mm:ss)                         00:16:25 (:01:36) (a)
Power output (W)                                    184 (31)(a)
Power output (W x [kg.sup.-1])                    2.65 (.43) (a)
Cadence (rev x [min.sup.-1])                          70 (7)
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])       56.8 (7) (a)
Heart rate (bpm)                                     169 (13)
VE (l x [min.sup.-1])                              116 (19) (d)
RER                                                .88 (.04) (a)
BLa (mmol x [l.sup.-1])                            5.9 (1.3)(a)

Data determined from Mountain Bike Competition (COMP): High
s

Variables                                              Lap 2

Racing time (hh:mm:ss)                               00:12:48
Power output (W)                                        256
Power output (W x [kg.sup.-1])                         3.41
Cadence (rev x [min.sup.-1])                            84
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])           70.9
Heart rate (bpm)                                        182
VE (l x [min.sup.-1])                                   170
RER                                                    0.93
BLa (mmol x [l.sup.-1])                                 6.8

Data determined form Mountain Bike Competition (COMP): All Subjects
(n=24)

Variables                                              Lap 3

Racing time (hh:mm:ss)                         00:16:36 (:01:09) (b)
Power output (W)                                   180 (33) (af)
Power output (W x [kg.sup.-1])                    2.59 (.43) (af)
Cadence (rev x [min.sup.-1])                          69 (7)
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])      55.7 (7.2) (b)
Heart rate (bpm)                                     170 (11)
VE (l x [min.sup.-1])                              111 (18) (bd)
RER                                                .88 (.04) (b)
BLa (mmol x [l.sup.-1])                            5.4 (1.4) (b)

Data determined from Mountain Bike Competition (COMP): High
s

Variables                                              Lap 3

Racing time (hh:mm:ss)                               00:13:12
Power output (W)                                        253
Power output (W x [kg.sup.-1])                         3.37
Cadence (rev x [min.sup.-1])                            82
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])           69.9
Heart rate (bpm)                                        181
VE (l x [min.sup.-1])                                   172
RER                                                    0.92
BLa (mmol x [l.sup.-1])                                 6.3

Data determined form Mountain Bike Competition (COMP): All Subjects
(n=24)

Variables                                              Lap 4

Racing time (hh:mm:ss)                         00:16:26 (:01:38) (c)
Power output (W)                                   186 (36) (cf)
Power output (W x [kg.sup.-1])                    2.67 (.47) (cf)
Cadence (rev x [min.sup.-1])                          70 (8)
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])      56.4 (6.8) (c)
Heart rate (bpm)                                      171(12)
VE (l x [min.sup.-1])                              113 (21) (c)
RER                                                .89 (.04) (c)
BLa (mmol x [l.sup.-1])                            5.9 (2.4) (c)

Data determined from Mountain Bike Competition (COMP): High

Variables                                              Lap 4

Racing time (hh:mm:ss)                               00:13:04
Power output (W)                                        274
Power output (W x [kg.sup.-1])                         3.65
Cadence (rev x [min.sup.-1])                            86
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])           70.5
Heart rate (bpm)                                        181
VE (l x [min.sup.-1])                                   174
RER                                                    0.92
BLa (mmol x [l.sup.-1])                                 7.3

(a) Lap1 vs. Lap2 significantly different; (b) Lap1 vs. Lap3
significantly different. (c) Lap1 vs. Lap4 significantly different.
(d) Lap2 vs. Lap3 significantly different. (e) Lap2 vs. Lap4
significantly different. (f) Lap3 vs. Lap4 significantly different

Table 3. LabT data for three clusters (Good, Medium and Low
Performance) consisting of subjects with significantly different
racing time (clusters calculated by k-means analysis). Data are shown
for variables measured and for performance variables of Laboratory
Tests (LabT). For descriptions of variables see Table 1 and Table 2.
Values are (means [+ or -] SD).

Data determined from Laboratory Testing (LabT)

Variables                                                 Cluster
                                                         1 (n = 5)
                                                      Good Performance

Age (years)                                              29.8 (7.8
Height (m)                                               1.83 (.02)
Weight (kg)                                            73.4 (1.3) (a)
Power output at VT1 (W)                                255 (29) (ab)
Power output at the VT1 (W x [kg.sup.-1])             3.48 (.28) (ab)
Power output at VT2 (W)                                368 (26) (ab)
Power output at VT2 (W x [kg.sup.-1])                 5.02 (.28) (ab)
Peak V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])     74.2 (4.7) (ab)
V[O.sub.2] at VT1 (ml x [kg.sup.-1] x [min.sup.-1])   43.1 (3.5) (ab)
V[O.sub.2] at VT2 (ml x [kg.sup.-1] x [min.sup.-1])   58.8 (5.2) (ab)

Variables                                                Cluster
                                                        2 (n = 12)
                                                          Medium
                                                        Performance

Age (years)                                             29.4 (7.6)
Height (m)                                              1.77 (.04)
Weight (kg)                                           68.5 (5.1) (a)
Power output at VT1 (W)                                173 (22) (a)
Power output at the VT1 (W x [kg.sup.-1])             2.54 (.40) (a)
Power output at VT2 (W)                                293 (14) (a)
Power output at VT2 (W x [kg.sup.-1])                 4.30 (.44) (a)
Peak V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])     65.5 (5.0) (ac)
V[O.sub.2] at VT1 (ml x [kg.sup.-1] x [min.sup.-1])   33.2 (4.5) (a)
V[O.sub.2] at VT2 (ml x [kg.sup.-1] x [min.sup.-1])   50.4 (4.3) (a)

Variables                                                Cluster
                                                         3 (n = 7)
                                                      Low Performance

Age (years)                                              27.7 (7.1
Height (m)                                              1.78 (.06)
Weight (kg)                                             69.4 (5.6)
Power output at VT1 (W)                                160 (47) (b)
Power output at the VT1 (W x [kg.sup.-1])             2.31 (.69) (b)
Power output at VT2 (W)                                262 (43) (b)
Power output at VT2 (W x [kg.sup.-1])                 3.77 (.56) (b)
Peak V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])     57.3 (3.7) (bc)
V[O.sub.2] at VT1 (ml x [kg.sup.-1] x [min.sup.-1])   31.1 (8.4) (b)
V[O.sub.2] at VT2 (ml x [kg.sup.-1] x [min.sup.-1])   45.6 (3.7) (b)

(a) Good Performance vs. Medium Performance significantly different.
(b) Good Performance vs. Low Performance significantly different.
(c) Medium Performance vs. Low Performance significantly different.

Table 4. Data of three clusters (Good, Medium and Low Performance)
consisting of subjects with significantly different racing time
(clusters calculated by k-means analysis). Data are shown for
variables measured during COMP. For description of variables see Table
2. Values are (means [+ or -] SD).

Data determined from Mountain Bike Competition (COMP)

Variables                                          Cluster 1 (n = 5)
                                                   Good Performance

Racing time (s)                                     3444 (201) (ab)
Power output (W)                                     231 (2) (ab)
Power output (W x [kg.sup.-1])                      3.18 (.29) (ab)
Cadence (rev x [min.sup.-1])                            72 (9)
V[O.sub.2COMP] (ml x [kg.sup.-1] x [min.sup.-1])    64.8 (5.0) (ab)
Heart rate (bpm)                                       165 (17)
VE (l x [min.sup.1])                                 129 (29) (b)
RER                                                    .90 (.09)
BLa (mmol x [l.sup.-1])                                5.9 (.9)

Variables                                          Cluster 2 (n = 12)
                                                   Medium Performance

Racing time (s)                                     3867 (118) (ac)
Power output (W)                                     184 (17) (ac)
Power output (W x [kg.sup.-1])                      2.69 (.27) (ac)
Cadence (rev x [min.sup.-1])                             70 (7)
V[O.sub.2COMP] (ml x [kg.sup.-1] x [min.sup.-1])    57.5 (4.2) (ac)
Heart rate (bpm)                                        168 (7)
VE (l x [min.sup.1])                                 118 (13) (ac)
RER                                                    .89 (.03)
BLa (mmol x [l.sup.-1])                                5.9 (1.5)

Variables                                          Cluster 3 (n = 7)
                                                    Low Performance

Racing time (s)                                     4362 (174) (bc)
Power output (W)                                     155 (19) (bc)
Power output (W x [kg.sup.-1])                      2.26 (.31) (bc)
Cadence (rev x [min.sup.-1])                            69 (5)
V[O.sub.2COMP] (ml x [kg.sup.-1] x [min.sup.-1])    50.7 (4.3) (bc)
Heart rate (bpm)                                        172(19)
VE (l x [min.sup.1])                                 101 (14) (b)
RER                                                    .91 (.03)
BLa (mmol x [l.sup.-1])                                6.2 (1.6)

(a) Good Performance vs. Medium Performance significantly different.
(b) Good Performance vs. Low Performance significantly different. (c)
Medium Performance vs. Low Performance significantly different.

Table 5. Mountain bike competition (COMP): Data (means [+ or -] SD)
are presented for sections Uphill, Flat and Downhill (see Figure 1)
for all subjects (n = 24) and for a high performance athlete (HPA).
For legend of variables see Table 3. Values are (means [+ or -] SD).

Data determined form Mountain Bike Competition (COMP): All Subjects
(n=24)

Variables                                      Section 1 (Uphill)

Power output (W)                               226.1 (41.7) (ab)
Power output (W x [kg.sup.-1])                  3.24 (.55) (ab)
Cadence (rev x [min.sup.-1])                      79 (9) (ab)
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])    62.5 (7.9) (ab)
HR (bpm)                                           172 (14)b
[V.sub.E] (l x [min.sup.-1])                     126 (21) (ab)
RER                                              .91 (.04) (ab)

Data determined from Mountain Bike Competition (COMP): High
Performance Athlete (HPA)

Variables                                      Section 1 (Uphill)

Power output (W)                                      328
Power output (W x [kg.sup.-1])                        4.37
Cadence (rev x [min.sup.-1])                           89
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])          76.6
HR (bpm)                                              184
[V.sub.E] (l x [min.sup.-1])                          185
RER                                                   0.95

Data determined form Mountain Bike Competition (COMP): All Subjects
(n=24)

Variables                                         Section 2
                                                (Nearly Flat)

Power output (W)                               175 (32.9) (ac)
Power output (W x [kg.sup.-1])                 2.52 (.43) (ac)
Cadence (rev x [min.sup.-1])                     74 (7) (ac)
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])   55.9 (7.3) (ac)
HR (bpm)                                          170 (13)c
[V.sub.E] (l x [min.sup.-1])                   115 (22.7) (ac)
RER                                            . 88 (.04) (ac)

Data determined from Mountain Bike Competition (COMP): High
Performance Athlete (HPA)

Variables                                         Section 2
                                                (Nearly Flat)

Power output (W)                                     259
Power output (W x [kg.sup.-1])                      3.45
Cadence (rev x [min.sup.-1])                         97
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])        69.7
HR (bpm)                                             185
[V.sub.E] (l x [min.sup.-1])                         185
RER                                                 0.93

Data determined form Mountain Bike Competition (COMP): All Subjects
(n=24)

Variables                                         Section 3
                                                 (Downhill)

Power output (W)                                101 (26) (bc)
Power output (W x [kg.sup.-1])                 1.44 (.35) (bc)
Cadence (rev x [min.sup.-1])                    54 (12) (bc)
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])   45.6 (6.0) (bc)
HR (bpm)                                        159 (14) (bc)
[V.sub.E] (l x [min.sup.-1])                    91 (17) (bc)
RER                                            .86 (.65) (bc)

Data determined from Mountain Bike Competition (COMP): High
Performance Athlete (HPA)

Variables                                         Section 3
                                                 (Downhill)

Power output (W)                                     149
Power output (W x [kg.sup.-1])                      1.99
Cadence (rev x [min.sup.-1])                         64
V[O.sub.2] (ml x [kg.sup.-1] x [min.sup.-1])        59.2
HR (bpm)                                             171
[V.sub.E] (l x [min.sup.-1])                         137
RER                                                 0.87

(a) Sectiont vs. Section2 significantly different. (b) Sectiont vs,
Section3 significantly different. (c) Section2 vs. Section3
significantly different.

Table 6. Results of correlation coefficients (r) between the variables
of racing time and P[O.sub.COMP] vs. endurance variables of LabTs (PO
and V[O.sub.2] measured at maximal workload, VT1 and VT2). Values are
presented for all subjects (n = 24).

Variables                                               Racing time

Maximal power output (W x [kg.sup.-1]) = P[O.sub.max]     -78 ***
Power output at VT1 (W x [kg.sup.-1]) = P[O.sub.VT1]      -.63 **
Power output at VT2 (W x [kg.sup.-1]) = P[O.sub.VT2]      -77 ***
Peak [??][0.sub.2] (ml x [kg.sup.-1] x                    -80 ***
  [min.su.-1]) = V[0.sub.2peak]
V[O.sub.2] at VT1 = V[0.sub.2VT1]                         -59 **
V[O.sub.2] at VT2 = V[O.sub.2VT2]                         -75 ***

Variables                                               POCOMP

Maximal power output (W x [kg.sup.-1]) = P[O.sub.max]   72 ***
Power output at VT1 (W x [kg.sup.-1]) = P[O.sub.VT1]    .65 **
Power output at VT2 (W x [kg.sup.-1]) = P[O.sub.VT2]    76 ***
Peak [??][0.sub.2] (ml x [kg.sup.-1] x                  77 ***
  [min.su.-1]) = V[0.sub.2peak]
V[O.sub.2] at VT1 = V[0.sub.2VT1]                       .66 **
V[O.sub.2] at VT2 = V[O.sub.2VT2]                       .68 ***

** p < 0.01; *** 0 < 0.001

Table 7. Results of previous MB studies reporting V[O.sub.2max]/
V[O.sub.2peak] (ml x [kg.sup.-1] x [min.sup.-1]) and P[O.sub.max]
(Watt and Watt x [kg.sup.-1]). Values are (means [+ or -] SD).

Author                         Level    (n)   [??][O.sub.2max/peak]

Baron (2001)                   Elite    25      68.4 [+ or -] 3.8
Gregory et al. (2007)          Elite    11      67.1 [+ or -] 3.6
Impellizzeri et al. (2002)     Elite     5      75.9 [+ or -] 5.0
Impellizzeri et al. (2005a)    Elite    12      76.9 [+ or -] 5.3
Impellizzerri (2005b)          Elite    13      72.1 [+ or -] 7.4
Lee et al. (2002)              Elite     7      78.3 [+ or -] 4.4
MacRae et al. (2000)          Amateur    6      58.4 [+ or -] 2.3
Nishii et al. (2004)           Elite     9      67.8 [+ or -] 5.8
Prins et al. (2007)           Amateur    8      63.6 [+ or -] 5.7
Stapefeldt et al. (2004)       Elite     9      66.5 [+ or -] 2.6
Wilber et al. (1997)           Elite    10      70.0 [+ or -] 3.7

Author                         P[O.sub.max]         P[O.sub.max]
                                  (Watt)        (Watt x [kg.sup.-1])

Baron (2001)                  384 [+ or -] 34     5.5 [+ or -] 0.4
Gregory et al. (2007)         367 [+ or -] 32     5.1 [+ or -] 4.4
Impellizzeri et al. (2002)    368 [+ or -] 31     5.7 [+ or -] 0.5
Impellizzeri et al. (2005a)   426 [+ or -] 40     6.4 [+ or -] 0.6
Impellizzerri (2005b)         392 [+ or -] 35     6.0 [+ or -] 0.4
Lee et al. (2002)             413 [+ or -] 36     6.3 [+ or -] 0.5
MacRae et al. (2000)          389 [+ or -] 41     5.1 [+ or -] 0.3
Nishii et al. (2004)          380 [+ or -] 35     6.0 [+ or -] 0.5
Prins et al. (2007)           272 [+ or -] 37     5.1 [+ or -] 0.4
Stapefeldt et al. (2004)      368 [+ or -] 25     5.3 [+ or -] 0.3
Wilber et al. (1997)          420 [+ or -] 42     5.9 [+ or -] 0.3

Elite = Competitive cyclist at international level. Amateur =
Competitive cyclist at national/amateur level.
COPYRIGHT 2015 Journal of Sports Science and Medicine
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2015 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Title Annotation:Research article
Author:Smekal, Gerhard; von Duvillard, Serge P.; Hormandinger, Maximilian; Moll, Roland; Heller, Mario; Pok
Publication:Journal of Sports Science and Medicine
Article Type:Report
Date:Dec 1, 2015
Words:11437
Previous Article:Jump rope training: balance and motor coordination in preadolescent soccer players.
Next Article:Symptoms of common mental disorders in professional football (soccer) across five European countries.
Topics:

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters