1084 Training & Testing
Anthropometric Characteristics Account for Time to Exhaustion in Cycling
Affiliations
Key words
▶ time limit ● ▶ lean body mass ● ▶ muscle phenotypes ● ▶ biomechanics ● ▶ cycling ●
F. A. Basset1, F. Billaut2, D. R. Joanisse3 1
Memorial University, School of Human Kinetics and Recreation, St. John’s, Canada Institut National du Sport de Quebec, Physiology, Montreal, Canada 3 Universite Laval, Kinesiology, Quebec, Canada 2
Abstract
▼
This study examined the relationship between the phenotypic and anthropometric characteristics and the cycling time to exhaustion (Tlim) at the maximal aerobic power output (Pmax). 12 (7 men, 5 women) physically-active participants performed a square-wave test at Pmax to determine the maximal time limit. Muscle histochemistry, enzymatic activities and buffer capacity were determined from a vastus lateralis muscle biopsy, lean body mass (LBM) by hydrostatic weighing, and total (TV) and lean (LV) volumes of the thigh by anthropometric measurements. The mean ( ± SD) Tlim was 235 ± 84 s (score range: 108–425 s). No relationship was found between
Introduction
▼ accepted after revision April 8, 2014 Bibliography DOI http://dx.doi.org/ 10.1055/s-0034-1375694 Published online: June 30, 2014 Int J Sports Med 2014; 35: 1084–1089 © Georg Thieme Verlag KG Stuttgart · New York ISSN 0172-4622 Correspondence Dr. Fabien Andre Basset Memorial University School of Human Kinetics and Recreation 230 Elizabeth Avenue St. John’s Canada A1C 5S7 Tel.: + 1/709/864 6132 Fax: + 1/709/864 3979 [email protected]
The maximal endurance time to exhaustion (Tlim) at the power output (Pmax) corresponding to the maximal oxygen uptake (V̇ Omax) has been used extensively to assess the ability to produce maximal power output [1], study the effect of training on endurance performance [2, 5, 20, 29], evaluate the metabolic acclimation to environmental stress [3] or simply explore the mechanisms of locomotor muscle fatigue during heavy exercise [24, 25]. However, there is also some skepticism about the utility of Tlim as a measure of performance [17]. Indeed, several confounding factors contribute to the large test-retest variability in reliability studies and to the inter-subject variability in homogeneous groups of athletes [4, 16, 21]. For instance, Tlim is positively correlated with both oxidative and glycolytic metabolisms [2, 13, 32], raising the question about which system (i. e., cardiovascular, neuromuscular) contributes most to this athletic performance. To maintain the pedaling rate at the targeted power output near the end of a severe squarewave test, the subject must apply a very high
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
Tlim and any muscle phenotypes. However, we observed a strong, linear relationship between Tlim and LBM (r = 0.84, P < 0.05). Thigh TV and LV displayed weaker correlation coefficients with Tlim (r = 0.66 and r = 0.73, respectively; P < 0.05). We further estimated the femur length and found this measure to correlate with Tlim (r = 0.81, P < 0.05). This study suggests that muscle phenotypes may not be representative of Tlim. Rather, anthropometric characteristics account for such performance by conferring a biomechanical advantage in cycling. We conclude that, in addition to metabolic factors, anthropometric characteristics with reasonable accuracy predict Tlim in cycling, and may account for the large intersubject variability observed in previous studies.
torque on the pedals until exhaustion. Therefore it is not surprising that the glycolytic capacity is related to performance during exercise of this nature. For example, it has been demonstrated that the runners displaying the greatest 30-m sprint velocity exhibited the longest running time to fatigue [2]. A significant, positive correlation between Tlim and the maximal accumulated O2 deficit, selected as an indicator of glycolytic energy production [28], has also been observed in different exercise conditions [10, 13, 32]. Thus, individuals with a greater glycolytic potential are ceteris paribus able to exercise for a longer period than individuals with a low glycolytic potential. If so, skeletal muscle phenotypes, in particular the factors associated with the glycolytic energy production, would play an important role in determining Tlim. It is also well established that muscle mass, specifically muscle cross-sectional area, is a primary intrinsic determinant of force [22, 23, 33]. Accordingly, a significant relationship has been established between lean body mass (LBM) and maximal torque or power development on several occasions [30, 31, 36], and anthropometric
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Authors
Training & Testing 1085
Methods
▼
Anthropometry and body composition Prior to hydrostatic weighing, height and body mass were measured using a wall stadiometer (Model HM200PW, Charder, Taichung, Taiwan – precision: 0.1 cm), and a strain gauge (Intertechnology, Don Mills, ON – accuracy ± 0.1 kg) sampled at 100 Hz (data acquisition system, IOtech Daqbook/2000®), respectively. Lung residual volume was determined using the oxygendilution principle (Model K520, KL Engineering, Sunnydale, CA). Thereafter, the participants, immersed in water, were instructed to exhale completely to the point of residual lung volume, at which point a load cell interfaced with a computer was used to obtain the underwater measurement of body mass. 10 measurements were obtained, and the 3 highest values were averaged. Total and lean volumes (TV and LV, respectively) of the left thigh were determined by the anthropometric method of Jones and Pearson [19]. Briefly, the method partitions the thigh into 2 different segments separated at a distance of two-thirds the length between the lateral femoral condyle and the gluteal crease proximal to the lateral femoral condyle. The circumferences and heights above the floor level were measured with a flexible metric tape. The volume of every segment was calculated as follows:
Participants Physically active men (n = 7) and women (n = 5) volunteered to participate in the study. All participants were healthy and with no known neurological or cardiovascular diseases. Participants’ ▶ Table 1. The anthropometric characteristics are reported in ● study was conducted in accordance with the ethical standards outlined in the declaration of Helsinki and according the requirements of, and following approval by, the institutional ethics committee [15]. All participants were informed of the nature of the investigation and provided written, informed consent.
V=
πh 2 (R + r 2 + Rr) 3
where R and r are the superior and inferior radii for the segment, and h represents the length of the segment. Skinfold thickness was measured with a caliper (Harpenden Ltd.) at the anterior (mid-point of the anterior surface of the thigh, midway between patella and inguinal fold) and posterior (half the distance between the ischial tuberosity and popliteal crease) thigh [19]. The LV was calculated from the above formula by correcting every radius for subcutaneous fat.
Training status The subjects were athletes of international and national caliber training at the Pierre Harvey Cross-Country Skiing National Centre (5 men and 3 women) and at the Gaétan Boucher Long-Track Speed Skating National Centre (2 men and 2 women) with an average of 10.8 ( ± 2.4) years of training experience. The study took place during the general preparatory phase in which training sessions mainly focused on aerobic workouts performed by running and cycling. Mean overall volumes – total training hours per week – were 11 h 52 min ( ± 3 h 24 min). In addition, total volumes of intensity (h week − 1) were calculated, including all workouts above 75 % of maximal aerobic running speed or maximal aerobic cycling workload. Values of total volume of intensity were 1 h 38 min ( ± 0 h 39 min), representing 12 % ( ± 6 %) of mean overall training volume, the latter being better indicators of the training density imposed on the athletes. 2–4 45-min weight training sessions were added per week, with emphasis on muscle hypertrophy.
Table 1 Anthropometric characteristics of participants.
age (y) body mass (kg) height (cm) body fat ( %) lean body mass (kg) thigh TV (L) thigh LV (L)
Men (n = 7)
Women (n = 5)
20 ± 1 77.9 ± 7.1 178 ± 8 8±3 69.4 ± 6.3 9.5 ± 1.6 8.2 ± 1.8
21 ± 2 59.8 ± 4.0* 168 ± 6* 17 ± 5* 50 ± 6* 7.9 ± 0.9* 6.9 ± 0.8*
Data are mean ± SD. TV: total volume, LV: lean volume
Ergometer tests Maximal oxygen uptake (V̇ O2max ) and time-to-exhaustion (Tlim) tests were conducted on a Schwinn cycle ergometer (IC Pro, Schwinn Cycling & Fitness Inc., Louisville, KY) equipped with a 1 500 Watt Electronic Load generator (Racer Mate Inc., Seattle, WA). This device allowed accurate monitoring of power output (random error: ± 2.5 %) and cadence. The handlebars and racing seat were adjusted vertically and horizontally according to athletes’ preferences. During both tests, athletes were required to maintain a familiar and comfortable pedaling rate greater than 60 rpm throughout the test. A Wingate anaerobic test was performed on a modified Monark cycle ergometer. A photoelectric cell and a potentiometer allowed the collection of flywheel revolution and produced tension, respectively. An electrical timing device controlled the input to the microprocessor, and the total work performed for each second was recorded. During all ergometer tests the participants wore their own cycling shoes equipped with pedal-clips.
Experimental design To ensure a complete recovery between tests, a 48-h interval was mandatory between VO2max determination, Tlim and Wingate tests. All experimental sessions were conducted at the same time of the day (between 8:00 and 12:00 am). All tests were conducted following a 15-min warm-up at 100 W for men and 50 W for women. Participants were instructed to maintain the same position on the cycle ergometer while receiving strong verbal encouragements throughout all tests.
*Significantly different from men (P < 0.05)
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
studies have found sprint cyclists to be heavier and stronger than their endurance peers [9]. Additionally, muscle volume has largely been demonstrated to contribute to the crank torque and power output maintenance during a given exercise [12, 26]. Whether Tlim is related to skeletal muscle morphological characteristics (fiber cross-sectional area and fiber type distribution, capillary density) or to metabolic potential (e. g. activities of glycolytic enzymes and muscle buffer capacity) remains unclear. In addition, the potential relationship of anthropometric characteristics to Tlim in cycling has not yet been established. The aim of this study was therefore to examine the relationship between cycling Tlim at a work rate corresponding to V̇ Omax and phenotypic and anthropometric characteristics. Our working hypotheses were as follows: i) skeletal muscle phenotypes, especially the determinants of glycolytic energy production, would account in part for Tlim performance, and ii) anthropometric measures would also correlate to Tlim in cycling.
1086 Training & Testing
Physiological measurements For triangular and rectangular tests, oxygen uptake, carbon dioxide output, and minute ventilation were continuously recorded with an automated breath-by-breath system (K4b2, Cosmed, Rome, Italy) using a Nafion filter tube and a turbine flow meter (opto-electric) and respiratory exchange ratio (RER) and ventilation equivalent of oxygen (V̇ E/V̇ O2) were calculated. Prior to testing, gas analyzers and volume were calibrated using medically certified calibration gases (15 % O2 and 5 % CO2) and a 3-liter calibration syringe, respectively. The criterion used for determination of V̇ O2max was a plateau in V̇ O2, corresponding to less than a 50 ml min − 1 rise despite increasing power output. If a plateau did not occur then V̇ O2peak was taken as the maximal oxygen values. In order to determine maximal O2 values, timeaveraged 15 s intervals were used.
Muscle biopsies 24 h prior to testing, one muscle sample was obtained from every subject in the morning following an overnight (12 h) fast from the middle portion of the right vastus lateralis muscle (i. e., about 15 cm above the patella and about 2 cm away from the epimysium) by the percutaneous needle biopsy technique. Muscle samples were divided into 2 parts: one was immediately frozen in liquid nitrogen for subsequent determination of muscle enzyme activities; the other part was trimmed, mounted on corkboard and frozen in isopentane cooled on liquid nitrogen for subsequent histochemical analyses. All samples were then stored at − 80 °C until used. One subject did not undergo a biopsy because of technical problems.
Skeletal muscle enzyme activities Small pieces of muscle (~ 10 mg) were homogenized in a glassglass homogenizer with 39 volumes of ice-cold extracting medium (0.1 M Na-K-phosphate, 2 mM EDTA, pH 7.2), and enzyme activities were measured as previously described [34]. The enzymes measured were creatine kinase (CK; EC 2.7.3.2), citrate synthase (CS; EC 4.1.3.7), cytochrome-c-oxidase (COX; EC 1.9.3.1), phosphofructokinase (PFK; EC 2.7.1.11), β-hydroxyacyl CoA dehydrogenase (HADH; EC 1.1.1.35), hexokinase (HK; EC 2.7.1.1) and glycogen phosphorylase (GPHOS; EC 2.4.1.1). The enzyme activities are expressed in units of μmoles of substrate converted per minute per gram of wet tissue (U g − 1). The intraindividual reproducibility of this measurement has previously been reported [34].
Muscle buffer capacity The muscle buffer capacity (βm) measurement used in the current study was based upon the method of Gore et al. [14]. The muscle sample was dissected to remove connective tissue, fat and blood prior to homogenization on ice with a manual glass homogenizer. The muscle samples were homogenized (1:40 dilution) in 145 mmol L − 1 KCl, 10 mmol L − 1 NaCl and 5 mmol L − 1 NaIAA, pH 7.0. The pH of the homogenate was measured at 37 °C using a microelectrode (Accumet Engineering Corporation, Hudson, MA), and was adjusted to pH 7.2 by addition of NaOH (10 mmol L − 1). Homogenates were briefly vortexed, and titrated from pH 7.2 to 6.1 with successive additions of 2 μL aliquots of 10 mmol L − 1 HCl. Results are expressed as μmol H + g muscle pH − 1.
Skeletal muscle histochemistry Cross sections (10 μm) of isopentane-frozen muscle were cut with a microtome at –20 °C and stained for myosin ATPase and capillaries [34]. The single-step staining procedure facilitated the identification of 3 fiber types (I, IIA, IIX) from the same section. To measure the cross-sectional area of the different fiber types, sections were examined under a light microscope (Leitz Dialux 20), which was connected to a charge-couple device (CCD) camera (Sony C-350), with an analog-to-digital conversion system. Image analysis was performed with a Power Macintosh computer using the public domain NIH Image program (developed at the U.S. National Institutes of Health and available on the Internet at http://rsb.info.nih.gov/nih-image/). The mean cross-sectional area was determined by averaging the measurement of 30 (when available) randomly selected fibers of each type that had been obtained from the mATPase-stained sections.
Statistical analysis First, in addition to running tests for equality of variances, statistical analyses were performed to ensure the appropriateness of the regression lines. Second, one-way analysis of variance was performed to test the effect of sex on anthropometrics characteristics, and mechanical and metabolic parameters. Finally, relationships between Tlim and variables of interest were obtained from linear regression analyses (Statistica, Statsoft Inc., Tulsa, OK). Differences were considered significant at P < 0.05, and data are expressed as mean and standard deviation ( ± SD).
Results
▼
▶ Table 2 reports anthropometric characteristics of the partici●
pants and performance indicators from the 3 tests, respectively. Statistical analysis revealed significant sex differences in most of anthropometrics and metabolic parameters, except for RER, and both relative PPO (W kg − 1 and W L − 1). However, no difference in V̇ O2max, RER and heart rate was observed between the squarewave test and incremental test for both sexes, indicating that the Tlim test was performed at maximal aerobic power. Skeletal muscle histochemistry variables, enzymatic activities and muscle buffer capacity obtained at rest from the vastus lat▶ Table 3. No significant correlaeralis muscle are presented in ● tion was found between Tlim and any of the muscle phenotypes (all P > 0.05). ▶ Fig. 1 displays the correlations of anthropometric characteris● tics to Tlim. Panel a shows the strong linear relationship between Tlim and LBM (r = 0.84, P < 0.05). Further analyses also reveal correlations between the thigh TV (r = 0.66, P < 0.05) and LV (r = 0.73,
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
The V̇ O2max determination test was initiated at a power output of 200 W for men and 140 W for women. Increments of 20 W were made every minute until reaching 300 W for men and 200 W for women. Thereafter, the workload was increased by 10 W every minute until exhaustion. This allowed a precise assessment of the power output (Pmax) associated with V̇ O2max for subsequent Tlim tests. For Tlim tests, Pmax was reached within 10 s and maintained until exhaustion. Tlim was recorded as the duration from when Pmax was reached until the point when participants were unable to maintain a cadence above 60 rpm [4, 21]. For Wingate anaerobic tests, participants were instructed to pedal as fast as possible for 30 s against a constant workload, determined according to body mass (90 g kg − 1). The resistance was adjusted within 3 s of the start of the test. Peak power output (PPO, W) was then determined. Fatigue indices were computed by regression equations from raw data.
Training & Testing 1087
incremental test
Tlim test
Wingate test
V̇ O2max (L min − 1) respiratory exchange ratio heart rate (beats min − 1) mean power output (W) V̇ O2 (L min − 1) respiratory exchange ratio heart rate (beats min − 1) mean power output (W) peak power output (W) (W kg − 1 BW) (W L − 1 TTV)
Men (n = 7)
Women (n = 5)
4.8 ± 0.5 1.09 ± 0.4 193 ± 7 334 ± 11 4.7 ± 0.3 1.08 ± 0.5 195 ± 9 325 ± 9 1 104 ± 187 14.1 ± 1.5 117 ± 16
3.3 ± 0.6* 1.10 ± 0.6 180 ± 5* 248 ± 24* 3.1 ± 0.5* 1.11 ± 0.9 176 ± 17* 240 ± 20* 782 ± 70* 13.1 ± 1.5 100 ± 14
Table 2 Performance indicators in the incremental, time-toexhaustion, and Wingate tests.
Data are mean ± SD. BW: body weight, TTV: thigh total volume
Table 3 Enzymatic activities, buffer capacity, and morphological variables of vastus lateralis muscle. R2 indicates the square correlation coefficient between Tlim and each variable (n = 11). There were no significant correlations between any of these parameters and the time-to-exhaustion (P < 0.05). R2 enzyme activities (U g − 1)
buffer capacity (μmol H + g − 1 pH − 1) fibre proportion ( %)
fibre cross-sectional area (μm2)
capillary contacts per fibre per surface (μm2)
PFK CK CS HADH COX HK GPHOS PFK/CS βm type I type IIA type IIX type I type IIA type IIX type I
65.5 ± 10.7 511.3 ± 112.1 8.0 ± 2.7 10.7 ± 2.3 6.4 ± 1.5 2.0 ± 0.4 34.0 ± 6.3 8.8 ± 3.3 43.4 ± 3.7 52.1 ± 14.0 26.6 ± 10.9 15.2 ± 10.3 6 580 ± 1 415 7 766 ± 2 089 6 209 ± 2 307 1 149 ± 328
0.01 0.00 0.07 0.00 0.00 0.00 0.33 0.00 0.15 0.06 0.01 0.22 0.06 0.00 0.21 0.06
type IIA type IIX
1 377 ± 368 1 560 ± 502
0.05 0.15
Data are mean ± SD
P < 0.05) and Tlim performance. However, the strength of the relationship between Tlim and the 2 former parameters needs cautious interpretation due to 2 extreme values (individual values beyond 3 standard deviations). In addition to these anthropometrics indices, we have estimated, as an index of biomechanical efficiency, the femur length from the gluteal furrow to the maximum circumference around the knee joint space. As dis▶ Fig. 1) this parameter correlated well with played on panel b (● Tlim (r = 0.81, P < 0.05). Furthermore, there were significant, positive correlations between Tlim and both PPO from the Wingate ▶ Fig. 1, panel c) and anaerobic capacity test (r = 0.76, P < 0.05, ● ▶ VO2max (r = 0.64, P < 0.05, ● Fig. 1, panel d).
Discussion
▼
This study provides additional information related to the factors influencing Tlim in cycling at high intensity. The main outcomes are that while metabolic parameters are still of importance to the maximal endurance time in cycling, anthropometric characteristics correlate well with this performance, and may account for the large inter-subject variability observed in previous stud-
ies. The most striking finding was that the femur length better relates to cycling Tlim than skeletal muscle phenotypes. Indeed, the longer the femur, the longer the maximal endurance time, which may reflect a biomechanical advantage. We hypothesized that skeletal muscle phenotypes related to glycolytic energy production (such as glycolytic potential, fiber type, buffer capacity) could predict Tlim at V̇ O2max. Yet, Tlim did not correlate with any of the measured phenotypes, which confirms that the assessment of muscle phenotypes is not particularly useful for the detection of high glycolytic potential [30]. With regard to metabolic parameters, V̇ O2max was found to posi▶ Fig. 1, panel d) corroborating previtively correlate with Tlim (● ous results in cyclists [21] and indicating a capacity to sustain high levels of O2 fluxes associated with an efficient metabolite exchange and/or removal system that contributes to maintain cellular enantiostasis. Although the aim of this study was not to examine the effect of sex on Tlim, it is worth noting that women and men differ in their relative contribution of energy systems to Tlim. In fact, despite the small sample size, simple linear regressions reveal that in women (n = 5) Tlim correlates well to V̇ O 2max (R2 = 0.72), while in men (n = 7) the former correlates better to PPO (R2 = 0.73), a good indicator of the phosphagen system and glycolysis. These findings are in good agreement with previous studies on the effect of sex on this performance [6]. Sex differences exist in substrate metabolism during exercise characterized by women having a higher fat, and lower carbohydrate and amino acid oxidation as compared to men [18, 35]. Well-controlled studies (e. g. training status, diet and other factors known to influence substrate metabolism) have reported a higher contribution of oxidative metabolism to total energy release in women than in men [6]. In the current study, Tlim also correlated positively with PPO on the ▶ Fig. 1, panel c). This relationship indicates that Wingate test (● peak power output developed by the lower limb muscles correlates with the maximal endurance time. Although this test has been considered to be largely dependent upon anaerobic metabolism [28], the sex differences, increasing the inter-subject variability, may in part explain the absence of correlation between Tlim and both skeletal muscle phenotypes and glycolytic metabolism. The second major purpose of this investigation was to identify whether anthropometric characteristics would correlate to Tlim. In fact, our results indicate that LBM predicts 71 % of Tlim vari▶ Fig. 1, panel a). This relationship sugance regardless of sex (● gests that heavier participants can maintain power output for longer period of time in a square-wave test. Comparison of
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
*Significantly different from men (P < 0.05)
1088 Training & Testing
a
b
400 Time-to-Exhaustion (s)
300
200
100
300
200
100
Y =26.637x –589.65
Y = 6.014x –133.08 r = 0.84, p < 0.05
r =0.81, p < 0.05 0
0 40
50
60 Lean Body Mass (kg)
70
80
28
34
36
d
c
400
400 Time-to-Exhaustion (s)
Time-to-Exhaustion (s)
30 32 Femur Length (cm)
300
200
100
300
200
100
Y = 0.290x –46.84 r = 0.76, p< 0.05 0
700
800
900
1 000
1 100
1 200
Y =0.069x –44.59 r =0.64, p < 0.05 0
1 300
2.5
Peak Power Output (W) Men
Women
3.0 3.5 4.0 4.5 Maximal Oxygen Uptake (L min–1)
5.0
95 % CI
Fig. 1 a Relationship of lean body mass (kg), b estimated femur length (cm), c peak power output (W) developed during a Wingate anaerobic test, and d maximal oxygen uptake (L min-1) to the time-to–exhaustion (s) on a cycle ergometer (men: n = 7; women: n = 5).
sprint track and endurance road cyclists has shown that sprint cyclists are heavier and stronger, and have larger chest, arm, thigh and calf girths than their endurance peers [27]. For instance, McLean and Ellis [26] reported significant relationships (r = 0.85, P < 0.05) between total and lean thigh volumes, and both peak power output and total mechanical work done in a 15-s cycle ergometer test in competitive junior cyclists. These findings were confirmed in elite track cyclists [12]. Maximal cycling power output obtained from a torque-velocity test was strongly correlated with the optimal torque applied on the pedals, the latter being itself correlated to the lower limb lean volume (r = 0.69, P < 0.05). This shows that absolute size and strength parameters are related to the ability to perform work on cycle ergometers [9, 11]. One may be tempted to explain the linear correlation of anthropometric characteristics to Tlim by the direct effect of muscle mass on power output [9, 11, 27]. In particular, positive relationships between crank torque and thigh TV on short-term cycle ergometer tests have been observed on many occasions [12, 24]. While we did also observe significant correlations of thigh TV and LV to Tlim (r = 0.66 and r = 0.73, respectively), these results must be interpreted with caution since 2 observations may have stretched the regression line. In further investigating the anthropometrics characteristics, we highlighted the impact of the femur length (as a biomechanical
index) on Tlim by showing a strong relationship between the 2 ▶ Fig. 1, panel b). This finding suggests that higher variables (● Tlim on a cycle ergometer is likely to correspond to longer thigh segments, i. e., taller individuals. In accordance with this reasoning, the effect of lever arm on torque and power output generation is well established [7, 37]. For instance, a long lever arm develops higher power output for a given thrust and a given pedaling cadence [7, 38]. Toward the end of the test, fatigue contributes to slowing down the pedaling rate, thereby sustaining a higher force production to maintain the workload. The longer the femur, the greater the mechanical lever, which results in a significantly higher torque on the pedals, conferring taller individuals a biomechanical advantage in maintaining the limit cadence. The average Tlim score (235 ± 84 s) and its correlative wide range (from 108 to 425 s) in the present study was similar to that reported for trained cyclists (222 to 241 s) [13, 21] and may be explained by the “open-loop design” of a square-wave test that could have made participants rely almost exclusively on afferent feedback [8]. However, the current study also showed that anthropometric characteristics – lean body mass and femur length – share part of the variability observed during a cycling time-to-exhaustion test, highlighting the impact of these determinants on Tlim scores.
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Time-to-Exhaustion (s)
400
Practical Applications and Conclusion
▼
Selecting the best cyclists through the systematic identification of genetic potential in talent programs has been practiced in many countries for a considerable time. Our data indicate that large body mass and long lower limb segments are necessary for successfully competing in endurance cycling, while reinforcing the usefulness of anthropometric parameters in talent identification regardless of sex. Altogether this suggests that in future investigations anthropometric characteristics must be regarded as one of the factors affecting cycling performance and be considered when determining the relationship between power output and endurance capacity. Such characteristics should be included with other methodological issues (Pmax and maximal O2 uptake determination [8], ‘open-loop’ model, familiarization [4, 21], metabolic efficiency glycolytic/oxidative ratio, lactate tolerance, movement economy [13, 32] and athletic profile (untrained/trained participants, sport specificity) [2]. When assessing performance potential it is important to note that while the results of the present study are applicable to Tlim in cycling, they must be used with caution in regard to other activities.
Acknowledgements
▼
We gratefully acknowledge Dr. Philippe Corbeil, Dr. Jean Doré, Dr. Richard Chouinard, Dr. Marcel R. Boulay, Gilles Bouchard, Guy Fournier, Frédéric Boivin, Josée St-Onge and Marcel Kaszap for their technical support, and the subjects for their participation and devotion to this work. Funding This project was funded by the Institut National du Sport du Québec and by Sports Internationaux de Québec.
Conflicts of interest: The authors have no conflict of interest to declare. References 1 Barnett C, Jenkins D, MacKinnon L, Green S. A new method for the calculation of constant supra-VO2peak power outputs. Med Sci Sports Exerc 1996; 28: 1505–1509 2 Basset FA, Chouinard R, Boulay MR. Training profile counts for timeto-exhaustion performance. Can J Appl Physiol 2003; 28: 654–666 3 Basset FA, Joanisse DR, Boivin F, St-Onge J, Billaut F, Dore J, Chouinard R, Falgairette G, Richard D, Boulay MR. Effects of short-term normobaric hypoxia on haematology, muscle phenotypes and physical performance in highly trained athletes. Exp Physiol 2006; 91: 391–402 4 Billat LV, Koralsztein JP. Significance of the velocity at VO2max and time to exhaustion at this velocity. Sports Med 1996; 22: 90–108 5 Billat VL, Blondel N, Berthoin S. Determination of the velocity associated with the longest time to exhaustion at maximal oxygen uptake. Eur J Appl Physiol 1999; 80: 159–161 6 Carter SL, Rennie C, Tarnopolsky MA. Substrate utilization during endurance exercise in men and women after endurance training. Am J Physiol 2001; 280: E898–907 7 Cavanagh PR, Sanderson DJ. The biomechanics of cycling: studies of the pedaling mechanics of elite pursuit riders. In: Burke ER (ed.). Science of cycling. Champaign, IL: Human Kinetics, 1986; 91–122 8 Coquart JB, Eston RG, Noakes TD, Tourny-Chollet C, L’Hermette M, Lemaitre F, Garcin M. Estimated time limit: a brief review of a perceptually based scale. Sports Med 2012; 42: 845–855 9 Craig NP, Norton KI. Characteristics of track cycling. Sports Med 2001; 31: 457–468 10 Craig NP, Norton KI, Bourdon PC, Woolford SM, Stanef T, Squires B, Olds TS, Conyers RA, Walsh CB. Aerobic and anaerobic indices contributing to track endurance cycling performance. Eur J Appl Physiol 1993; 67: 150–158 11 Davies CT, Sandstrom ER. Maximal mechanical power output and capacity of cyclists and young adults. Eur J Appl Physiol 1989; 58: 838–844
12 Dorel S, Hautier CA, Rambaud O, Rouffet D, Van Praagh E, Lacour JR, Bourdin M. Torque and power-velocity relationships in cycling: relevance to track sprint performance in world-class cyclists. Int J Sports Med 2005; 26: 739–746 13 Faina M, Billat VL, Squadrone R, De Angelis M, Koralsztein JP, Dal Monte A. Anaerobic contribution to the time to exhaustion at the minimal exercise intensity at which maximal oxygen uptake occurs in elite cyclists, kayakists and swimmers. Eur J Appl Physiol 1997; 76: 13–20 14 Gore CJ, Hahn AG, Aughey RJ, Martin DT, Ashenden MJ, Clark SA, Garnham AP, Roberts AD, Slater GJ, McKenna MJ. Live high:train low increases muscle buffer capacity and submaximal cycling efficiency. Acta Physiol Scand 2001; 173: 275–286 15 Harriss DJ, Atkinson G. Ethical standards in sports and exercise science research: 2014 update. Int J Sports Med 2013; 34: 1025–1028 16 Hopkins WG. Measures of reliability in sports medicine and science. Sports Med 2000; 30: 1–15 17 Hopkins WG, Schabort EJ, Hawley JA. Reliability of power in physical performance tests. Sports Med 2001; 31: 211–234 18 Horton TJ, Pagliassotti MJ, Hobbs K, Hill JO. Fuel metabolism in men and women during and after long-duration exercise. J Appl Physiol 1998; 85: 1823–1832 19 Jones PR, Pearson J. Anthropometric determination of leg fat and muscle plus bone volumes in young male and female adults. J Physiol 1969; 204: 63–66 20 Laursen PB, Rhodes EC, Langill RH, McKenzie DC, Taunton JE. Relationship of exercise test variables to cycling performance in an Ironman triathlon. Eur J Appl Physiol 2002; 87: 433–440 21 Laursen PB, Shing CM, Jenkins DG. Reproducibility of the cycling time to exhaustion at VO2peak in highly trained cyclists. Can J Appl Physiol 2003; 28: 605–615 22 Maughan RJ. The limits of human athletic performance. Ann Transplant 2005; 10: 52–54 23 Maughan RJ, Watson JS, Weir J. Strength and cross-sectional area of human skeletal muscle. J Physiol 1983; 338: 37–49 24 McCartney N, Heigenhauser GJ, Jones NL. Power output and fatigue of human muscle in maximal cycling exercise. J Appl Physiol 1983; 55: 218–224 25 McIntyre JP, Mawston GA, Cairns SP. Changes of whole-body power, muscle function, and jump performance with prolonged cycling to exhaustion. Int J Sports Physiol Perform 2012; 7: 332–339 26 McLean BD, Ellis L. Body mass, thigh volume and vertical jumping ability as predictors of short-term cycle ergometer performance in junior cyclists. Excel 1992; 8: 148–153 27 McLean BD, Parker AW. An anthropometric analysis of elite Australian track cyclists. J Sports Sci 1989; 7: 247–255 28 Medbo JI, Tabata I. Anaerobic energy release in working muscle during 30 s to 3 min of exhausting bicycling. J Appl Physiol 1993; 75: 1654–1660 29 Morton RH, Billat VL. Maximal endurance time at VO2max. Med Sci Sports Exerc 2000; 32: 1496–1504 30 Patton JF, Kraemer WJ, Knuttgen HG, Harman EA. Factors in maximal power production and in exercise endurance relative to maximal power. Eur J Appl Physiol 1990; 60: 222–227 31 Potteiger JA, Smith DL, Maier ML, Foster TS. Relationship between body composition, leg strength, anaerobic power, and on-ice skating performance in division I men’s hockey athletes. J Strength Cond Res 2010; 24: 1755–1762 32 Renoux JC, Petit B, Billat V, Koralsztein JP. Oxygen deficit is related to the exercise time to exhaustion at maximal aerobic speed in middle distance runners. Arch Physiol Biochem 1999; 107: 280–285 33 Seynnes OR, de Boer M, Narici MV. Early skeletal muscle hypertrophy and architectural changes in response to high-intensity resistance training. J Appl Physiol 2007; 102: 368–373 34 Simoneau JA, Lortie G, Boulay MR, Thibault MC, Bouchard C. Repeatability of fibre type and enzyme activity measurements in human skeletal muscle. Clin Physiol 1986; 6: 347–356 35 Tarnopolsky LJ, MacDougall JD, Atkinson SA, Tarnopolsky MA, Sutton JR. Gender differences in substrate for endurance exercise. J Appl Physiol 1990; 68: 302–308 36 Vardar SA, Tezel S, Ozturk L, Kaya O. The relationship between body composition and anaerobic performance of elite young wrestlers. J Sports Sci Med 2007; 6: 34–38 37 Yoshihuku Y, Herzog W. Maximal muscle power output in cycling: a modelling approach. J Sports Sci 1996; 14: 139–157 38 Zamparo P, Minetti A, di Prampero P. Mechanical efficiency of cycling with a new developed pedal-crank. J Biomech 2002; 35: 1387–1398
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Training & Testing 1089
Copyright of International Journal of Sports Medicine is the property of Georg Thieme Verlag Stuttgart and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
Anthropometric Characteristics Account for Time to Exhaustion in Cycling
Affiliations
Key words
▶ time limit ● ▶ lean body mass ● ▶ muscle phenotypes ● ▶ biomechanics ● ▶ cycling ●
F. A. Basset1, F. Billaut2, D. R. Joanisse3 1
Memorial University, School of Human Kinetics and Recreation, St. John’s, Canada Institut National du Sport de Quebec, Physiology, Montreal, Canada 3 Universite Laval, Kinesiology, Quebec, Canada 2
Abstract
▼
This study examined the relationship between the phenotypic and anthropometric characteristics and the cycling time to exhaustion (Tlim) at the maximal aerobic power output (Pmax). 12 (7 men, 5 women) physically-active participants performed a square-wave test at Pmax to determine the maximal time limit. Muscle histochemistry, enzymatic activities and buffer capacity were determined from a vastus lateralis muscle biopsy, lean body mass (LBM) by hydrostatic weighing, and total (TV) and lean (LV) volumes of the thigh by anthropometric measurements. The mean ( ± SD) Tlim was 235 ± 84 s (score range: 108–425 s). No relationship was found between
Introduction
▼ accepted after revision April 8, 2014 Bibliography DOI http://dx.doi.org/ 10.1055/s-0034-1375694 Published online: June 30, 2014 Int J Sports Med 2014; 35: 1084–1089 © Georg Thieme Verlag KG Stuttgart · New York ISSN 0172-4622 Correspondence Dr. Fabien Andre Basset Memorial University School of Human Kinetics and Recreation 230 Elizabeth Avenue St. John’s Canada A1C 5S7 Tel.: + 1/709/864 6132 Fax: + 1/709/864 3979 [email protected]
The maximal endurance time to exhaustion (Tlim) at the power output (Pmax) corresponding to the maximal oxygen uptake (V̇ Omax) has been used extensively to assess the ability to produce maximal power output [1], study the effect of training on endurance performance [2, 5, 20, 29], evaluate the metabolic acclimation to environmental stress [3] or simply explore the mechanisms of locomotor muscle fatigue during heavy exercise [24, 25]. However, there is also some skepticism about the utility of Tlim as a measure of performance [17]. Indeed, several confounding factors contribute to the large test-retest variability in reliability studies and to the inter-subject variability in homogeneous groups of athletes [4, 16, 21]. For instance, Tlim is positively correlated with both oxidative and glycolytic metabolisms [2, 13, 32], raising the question about which system (i. e., cardiovascular, neuromuscular) contributes most to this athletic performance. To maintain the pedaling rate at the targeted power output near the end of a severe squarewave test, the subject must apply a very high
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
Tlim and any muscle phenotypes. However, we observed a strong, linear relationship between Tlim and LBM (r = 0.84, P < 0.05). Thigh TV and LV displayed weaker correlation coefficients with Tlim (r = 0.66 and r = 0.73, respectively; P < 0.05). We further estimated the femur length and found this measure to correlate with Tlim (r = 0.81, P < 0.05). This study suggests that muscle phenotypes may not be representative of Tlim. Rather, anthropometric characteristics account for such performance by conferring a biomechanical advantage in cycling. We conclude that, in addition to metabolic factors, anthropometric characteristics with reasonable accuracy predict Tlim in cycling, and may account for the large intersubject variability observed in previous studies.
torque on the pedals until exhaustion. Therefore it is not surprising that the glycolytic capacity is related to performance during exercise of this nature. For example, it has been demonstrated that the runners displaying the greatest 30-m sprint velocity exhibited the longest running time to fatigue [2]. A significant, positive correlation between Tlim and the maximal accumulated O2 deficit, selected as an indicator of glycolytic energy production [28], has also been observed in different exercise conditions [10, 13, 32]. Thus, individuals with a greater glycolytic potential are ceteris paribus able to exercise for a longer period than individuals with a low glycolytic potential. If so, skeletal muscle phenotypes, in particular the factors associated with the glycolytic energy production, would play an important role in determining Tlim. It is also well established that muscle mass, specifically muscle cross-sectional area, is a primary intrinsic determinant of force [22, 23, 33]. Accordingly, a significant relationship has been established between lean body mass (LBM) and maximal torque or power development on several occasions [30, 31, 36], and anthropometric
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Authors
Training & Testing 1085
Methods
▼
Anthropometry and body composition Prior to hydrostatic weighing, height and body mass were measured using a wall stadiometer (Model HM200PW, Charder, Taichung, Taiwan – precision: 0.1 cm), and a strain gauge (Intertechnology, Don Mills, ON – accuracy ± 0.1 kg) sampled at 100 Hz (data acquisition system, IOtech Daqbook/2000®), respectively. Lung residual volume was determined using the oxygendilution principle (Model K520, KL Engineering, Sunnydale, CA). Thereafter, the participants, immersed in water, were instructed to exhale completely to the point of residual lung volume, at which point a load cell interfaced with a computer was used to obtain the underwater measurement of body mass. 10 measurements were obtained, and the 3 highest values were averaged. Total and lean volumes (TV and LV, respectively) of the left thigh were determined by the anthropometric method of Jones and Pearson [19]. Briefly, the method partitions the thigh into 2 different segments separated at a distance of two-thirds the length between the lateral femoral condyle and the gluteal crease proximal to the lateral femoral condyle. The circumferences and heights above the floor level were measured with a flexible metric tape. The volume of every segment was calculated as follows:
Participants Physically active men (n = 7) and women (n = 5) volunteered to participate in the study. All participants were healthy and with no known neurological or cardiovascular diseases. Participants’ ▶ Table 1. The anthropometric characteristics are reported in ● study was conducted in accordance with the ethical standards outlined in the declaration of Helsinki and according the requirements of, and following approval by, the institutional ethics committee [15]. All participants were informed of the nature of the investigation and provided written, informed consent.
V=
πh 2 (R + r 2 + Rr) 3
where R and r are the superior and inferior radii for the segment, and h represents the length of the segment. Skinfold thickness was measured with a caliper (Harpenden Ltd.) at the anterior (mid-point of the anterior surface of the thigh, midway between patella and inguinal fold) and posterior (half the distance between the ischial tuberosity and popliteal crease) thigh [19]. The LV was calculated from the above formula by correcting every radius for subcutaneous fat.
Training status The subjects were athletes of international and national caliber training at the Pierre Harvey Cross-Country Skiing National Centre (5 men and 3 women) and at the Gaétan Boucher Long-Track Speed Skating National Centre (2 men and 2 women) with an average of 10.8 ( ± 2.4) years of training experience. The study took place during the general preparatory phase in which training sessions mainly focused on aerobic workouts performed by running and cycling. Mean overall volumes – total training hours per week – were 11 h 52 min ( ± 3 h 24 min). In addition, total volumes of intensity (h week − 1) were calculated, including all workouts above 75 % of maximal aerobic running speed or maximal aerobic cycling workload. Values of total volume of intensity were 1 h 38 min ( ± 0 h 39 min), representing 12 % ( ± 6 %) of mean overall training volume, the latter being better indicators of the training density imposed on the athletes. 2–4 45-min weight training sessions were added per week, with emphasis on muscle hypertrophy.
Table 1 Anthropometric characteristics of participants.
age (y) body mass (kg) height (cm) body fat ( %) lean body mass (kg) thigh TV (L) thigh LV (L)
Men (n = 7)
Women (n = 5)
20 ± 1 77.9 ± 7.1 178 ± 8 8±3 69.4 ± 6.3 9.5 ± 1.6 8.2 ± 1.8
21 ± 2 59.8 ± 4.0* 168 ± 6* 17 ± 5* 50 ± 6* 7.9 ± 0.9* 6.9 ± 0.8*
Data are mean ± SD. TV: total volume, LV: lean volume
Ergometer tests Maximal oxygen uptake (V̇ O2max ) and time-to-exhaustion (Tlim) tests were conducted on a Schwinn cycle ergometer (IC Pro, Schwinn Cycling & Fitness Inc., Louisville, KY) equipped with a 1 500 Watt Electronic Load generator (Racer Mate Inc., Seattle, WA). This device allowed accurate monitoring of power output (random error: ± 2.5 %) and cadence. The handlebars and racing seat were adjusted vertically and horizontally according to athletes’ preferences. During both tests, athletes were required to maintain a familiar and comfortable pedaling rate greater than 60 rpm throughout the test. A Wingate anaerobic test was performed on a modified Monark cycle ergometer. A photoelectric cell and a potentiometer allowed the collection of flywheel revolution and produced tension, respectively. An electrical timing device controlled the input to the microprocessor, and the total work performed for each second was recorded. During all ergometer tests the participants wore their own cycling shoes equipped with pedal-clips.
Experimental design To ensure a complete recovery between tests, a 48-h interval was mandatory between VO2max determination, Tlim and Wingate tests. All experimental sessions were conducted at the same time of the day (between 8:00 and 12:00 am). All tests were conducted following a 15-min warm-up at 100 W for men and 50 W for women. Participants were instructed to maintain the same position on the cycle ergometer while receiving strong verbal encouragements throughout all tests.
*Significantly different from men (P < 0.05)
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
studies have found sprint cyclists to be heavier and stronger than their endurance peers [9]. Additionally, muscle volume has largely been demonstrated to contribute to the crank torque and power output maintenance during a given exercise [12, 26]. Whether Tlim is related to skeletal muscle morphological characteristics (fiber cross-sectional area and fiber type distribution, capillary density) or to metabolic potential (e. g. activities of glycolytic enzymes and muscle buffer capacity) remains unclear. In addition, the potential relationship of anthropometric characteristics to Tlim in cycling has not yet been established. The aim of this study was therefore to examine the relationship between cycling Tlim at a work rate corresponding to V̇ Omax and phenotypic and anthropometric characteristics. Our working hypotheses were as follows: i) skeletal muscle phenotypes, especially the determinants of glycolytic energy production, would account in part for Tlim performance, and ii) anthropometric measures would also correlate to Tlim in cycling.
1086 Training & Testing
Physiological measurements For triangular and rectangular tests, oxygen uptake, carbon dioxide output, and minute ventilation were continuously recorded with an automated breath-by-breath system (K4b2, Cosmed, Rome, Italy) using a Nafion filter tube and a turbine flow meter (opto-electric) and respiratory exchange ratio (RER) and ventilation equivalent of oxygen (V̇ E/V̇ O2) were calculated. Prior to testing, gas analyzers and volume were calibrated using medically certified calibration gases (15 % O2 and 5 % CO2) and a 3-liter calibration syringe, respectively. The criterion used for determination of V̇ O2max was a plateau in V̇ O2, corresponding to less than a 50 ml min − 1 rise despite increasing power output. If a plateau did not occur then V̇ O2peak was taken as the maximal oxygen values. In order to determine maximal O2 values, timeaveraged 15 s intervals were used.
Muscle biopsies 24 h prior to testing, one muscle sample was obtained from every subject in the morning following an overnight (12 h) fast from the middle portion of the right vastus lateralis muscle (i. e., about 15 cm above the patella and about 2 cm away from the epimysium) by the percutaneous needle biopsy technique. Muscle samples were divided into 2 parts: one was immediately frozen in liquid nitrogen for subsequent determination of muscle enzyme activities; the other part was trimmed, mounted on corkboard and frozen in isopentane cooled on liquid nitrogen for subsequent histochemical analyses. All samples were then stored at − 80 °C until used. One subject did not undergo a biopsy because of technical problems.
Skeletal muscle enzyme activities Small pieces of muscle (~ 10 mg) were homogenized in a glassglass homogenizer with 39 volumes of ice-cold extracting medium (0.1 M Na-K-phosphate, 2 mM EDTA, pH 7.2), and enzyme activities were measured as previously described [34]. The enzymes measured were creatine kinase (CK; EC 2.7.3.2), citrate synthase (CS; EC 4.1.3.7), cytochrome-c-oxidase (COX; EC 1.9.3.1), phosphofructokinase (PFK; EC 2.7.1.11), β-hydroxyacyl CoA dehydrogenase (HADH; EC 1.1.1.35), hexokinase (HK; EC 2.7.1.1) and glycogen phosphorylase (GPHOS; EC 2.4.1.1). The enzyme activities are expressed in units of μmoles of substrate converted per minute per gram of wet tissue (U g − 1). The intraindividual reproducibility of this measurement has previously been reported [34].
Muscle buffer capacity The muscle buffer capacity (βm) measurement used in the current study was based upon the method of Gore et al. [14]. The muscle sample was dissected to remove connective tissue, fat and blood prior to homogenization on ice with a manual glass homogenizer. The muscle samples were homogenized (1:40 dilution) in 145 mmol L − 1 KCl, 10 mmol L − 1 NaCl and 5 mmol L − 1 NaIAA, pH 7.0. The pH of the homogenate was measured at 37 °C using a microelectrode (Accumet Engineering Corporation, Hudson, MA), and was adjusted to pH 7.2 by addition of NaOH (10 mmol L − 1). Homogenates were briefly vortexed, and titrated from pH 7.2 to 6.1 with successive additions of 2 μL aliquots of 10 mmol L − 1 HCl. Results are expressed as μmol H + g muscle pH − 1.
Skeletal muscle histochemistry Cross sections (10 μm) of isopentane-frozen muscle were cut with a microtome at –20 °C and stained for myosin ATPase and capillaries [34]. The single-step staining procedure facilitated the identification of 3 fiber types (I, IIA, IIX) from the same section. To measure the cross-sectional area of the different fiber types, sections were examined under a light microscope (Leitz Dialux 20), which was connected to a charge-couple device (CCD) camera (Sony C-350), with an analog-to-digital conversion system. Image analysis was performed with a Power Macintosh computer using the public domain NIH Image program (developed at the U.S. National Institutes of Health and available on the Internet at http://rsb.info.nih.gov/nih-image/). The mean cross-sectional area was determined by averaging the measurement of 30 (when available) randomly selected fibers of each type that had been obtained from the mATPase-stained sections.
Statistical analysis First, in addition to running tests for equality of variances, statistical analyses were performed to ensure the appropriateness of the regression lines. Second, one-way analysis of variance was performed to test the effect of sex on anthropometrics characteristics, and mechanical and metabolic parameters. Finally, relationships between Tlim and variables of interest were obtained from linear regression analyses (Statistica, Statsoft Inc., Tulsa, OK). Differences were considered significant at P < 0.05, and data are expressed as mean and standard deviation ( ± SD).
Results
▼
▶ Table 2 reports anthropometric characteristics of the partici●
pants and performance indicators from the 3 tests, respectively. Statistical analysis revealed significant sex differences in most of anthropometrics and metabolic parameters, except for RER, and both relative PPO (W kg − 1 and W L − 1). However, no difference in V̇ O2max, RER and heart rate was observed between the squarewave test and incremental test for both sexes, indicating that the Tlim test was performed at maximal aerobic power. Skeletal muscle histochemistry variables, enzymatic activities and muscle buffer capacity obtained at rest from the vastus lat▶ Table 3. No significant correlaeralis muscle are presented in ● tion was found between Tlim and any of the muscle phenotypes (all P > 0.05). ▶ Fig. 1 displays the correlations of anthropometric characteris● tics to Tlim. Panel a shows the strong linear relationship between Tlim and LBM (r = 0.84, P < 0.05). Further analyses also reveal correlations between the thigh TV (r = 0.66, P < 0.05) and LV (r = 0.73,
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
The V̇ O2max determination test was initiated at a power output of 200 W for men and 140 W for women. Increments of 20 W were made every minute until reaching 300 W for men and 200 W for women. Thereafter, the workload was increased by 10 W every minute until exhaustion. This allowed a precise assessment of the power output (Pmax) associated with V̇ O2max for subsequent Tlim tests. For Tlim tests, Pmax was reached within 10 s and maintained until exhaustion. Tlim was recorded as the duration from when Pmax was reached until the point when participants were unable to maintain a cadence above 60 rpm [4, 21]. For Wingate anaerobic tests, participants were instructed to pedal as fast as possible for 30 s against a constant workload, determined according to body mass (90 g kg − 1). The resistance was adjusted within 3 s of the start of the test. Peak power output (PPO, W) was then determined. Fatigue indices were computed by regression equations from raw data.
Training & Testing 1087
incremental test
Tlim test
Wingate test
V̇ O2max (L min − 1) respiratory exchange ratio heart rate (beats min − 1) mean power output (W) V̇ O2 (L min − 1) respiratory exchange ratio heart rate (beats min − 1) mean power output (W) peak power output (W) (W kg − 1 BW) (W L − 1 TTV)
Men (n = 7)
Women (n = 5)
4.8 ± 0.5 1.09 ± 0.4 193 ± 7 334 ± 11 4.7 ± 0.3 1.08 ± 0.5 195 ± 9 325 ± 9 1 104 ± 187 14.1 ± 1.5 117 ± 16
3.3 ± 0.6* 1.10 ± 0.6 180 ± 5* 248 ± 24* 3.1 ± 0.5* 1.11 ± 0.9 176 ± 17* 240 ± 20* 782 ± 70* 13.1 ± 1.5 100 ± 14
Table 2 Performance indicators in the incremental, time-toexhaustion, and Wingate tests.
Data are mean ± SD. BW: body weight, TTV: thigh total volume
Table 3 Enzymatic activities, buffer capacity, and morphological variables of vastus lateralis muscle. R2 indicates the square correlation coefficient between Tlim and each variable (n = 11). There were no significant correlations between any of these parameters and the time-to-exhaustion (P < 0.05). R2 enzyme activities (U g − 1)
buffer capacity (μmol H + g − 1 pH − 1) fibre proportion ( %)
fibre cross-sectional area (μm2)
capillary contacts per fibre per surface (μm2)
PFK CK CS HADH COX HK GPHOS PFK/CS βm type I type IIA type IIX type I type IIA type IIX type I
65.5 ± 10.7 511.3 ± 112.1 8.0 ± 2.7 10.7 ± 2.3 6.4 ± 1.5 2.0 ± 0.4 34.0 ± 6.3 8.8 ± 3.3 43.4 ± 3.7 52.1 ± 14.0 26.6 ± 10.9 15.2 ± 10.3 6 580 ± 1 415 7 766 ± 2 089 6 209 ± 2 307 1 149 ± 328
0.01 0.00 0.07 0.00 0.00 0.00 0.33 0.00 0.15 0.06 0.01 0.22 0.06 0.00 0.21 0.06
type IIA type IIX
1 377 ± 368 1 560 ± 502
0.05 0.15
Data are mean ± SD
P < 0.05) and Tlim performance. However, the strength of the relationship between Tlim and the 2 former parameters needs cautious interpretation due to 2 extreme values (individual values beyond 3 standard deviations). In addition to these anthropometrics indices, we have estimated, as an index of biomechanical efficiency, the femur length from the gluteal furrow to the maximum circumference around the knee joint space. As dis▶ Fig. 1) this parameter correlated well with played on panel b (● Tlim (r = 0.81, P < 0.05). Furthermore, there were significant, positive correlations between Tlim and both PPO from the Wingate ▶ Fig. 1, panel c) and anaerobic capacity test (r = 0.76, P < 0.05, ● ▶ VO2max (r = 0.64, P < 0.05, ● Fig. 1, panel d).
Discussion
▼
This study provides additional information related to the factors influencing Tlim in cycling at high intensity. The main outcomes are that while metabolic parameters are still of importance to the maximal endurance time in cycling, anthropometric characteristics correlate well with this performance, and may account for the large inter-subject variability observed in previous stud-
ies. The most striking finding was that the femur length better relates to cycling Tlim than skeletal muscle phenotypes. Indeed, the longer the femur, the longer the maximal endurance time, which may reflect a biomechanical advantage. We hypothesized that skeletal muscle phenotypes related to glycolytic energy production (such as glycolytic potential, fiber type, buffer capacity) could predict Tlim at V̇ O2max. Yet, Tlim did not correlate with any of the measured phenotypes, which confirms that the assessment of muscle phenotypes is not particularly useful for the detection of high glycolytic potential [30]. With regard to metabolic parameters, V̇ O2max was found to posi▶ Fig. 1, panel d) corroborating previtively correlate with Tlim (● ous results in cyclists [21] and indicating a capacity to sustain high levels of O2 fluxes associated with an efficient metabolite exchange and/or removal system that contributes to maintain cellular enantiostasis. Although the aim of this study was not to examine the effect of sex on Tlim, it is worth noting that women and men differ in their relative contribution of energy systems to Tlim. In fact, despite the small sample size, simple linear regressions reveal that in women (n = 5) Tlim correlates well to V̇ O 2max (R2 = 0.72), while in men (n = 7) the former correlates better to PPO (R2 = 0.73), a good indicator of the phosphagen system and glycolysis. These findings are in good agreement with previous studies on the effect of sex on this performance [6]. Sex differences exist in substrate metabolism during exercise characterized by women having a higher fat, and lower carbohydrate and amino acid oxidation as compared to men [18, 35]. Well-controlled studies (e. g. training status, diet and other factors known to influence substrate metabolism) have reported a higher contribution of oxidative metabolism to total energy release in women than in men [6]. In the current study, Tlim also correlated positively with PPO on the ▶ Fig. 1, panel c). This relationship indicates that Wingate test (● peak power output developed by the lower limb muscles correlates with the maximal endurance time. Although this test has been considered to be largely dependent upon anaerobic metabolism [28], the sex differences, increasing the inter-subject variability, may in part explain the absence of correlation between Tlim and both skeletal muscle phenotypes and glycolytic metabolism. The second major purpose of this investigation was to identify whether anthropometric characteristics would correlate to Tlim. In fact, our results indicate that LBM predicts 71 % of Tlim vari▶ Fig. 1, panel a). This relationship sugance regardless of sex (● gests that heavier participants can maintain power output for longer period of time in a square-wave test. Comparison of
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
*Significantly different from men (P < 0.05)
1088 Training & Testing
a
b
400 Time-to-Exhaustion (s)
300
200
100
300
200
100
Y =26.637x –589.65
Y = 6.014x –133.08 r = 0.84, p < 0.05
r =0.81, p < 0.05 0
0 40
50
60 Lean Body Mass (kg)
70
80
28
34
36
d
c
400
400 Time-to-Exhaustion (s)
Time-to-Exhaustion (s)
30 32 Femur Length (cm)
300
200
100
300
200
100
Y = 0.290x –46.84 r = 0.76, p< 0.05 0
700
800
900
1 000
1 100
1 200
Y =0.069x –44.59 r =0.64, p < 0.05 0
1 300
2.5
Peak Power Output (W) Men
Women
3.0 3.5 4.0 4.5 Maximal Oxygen Uptake (L min–1)
5.0
95 % CI
Fig. 1 a Relationship of lean body mass (kg), b estimated femur length (cm), c peak power output (W) developed during a Wingate anaerobic test, and d maximal oxygen uptake (L min-1) to the time-to–exhaustion (s) on a cycle ergometer (men: n = 7; women: n = 5).
sprint track and endurance road cyclists has shown that sprint cyclists are heavier and stronger, and have larger chest, arm, thigh and calf girths than their endurance peers [27]. For instance, McLean and Ellis [26] reported significant relationships (r = 0.85, P < 0.05) between total and lean thigh volumes, and both peak power output and total mechanical work done in a 15-s cycle ergometer test in competitive junior cyclists. These findings were confirmed in elite track cyclists [12]. Maximal cycling power output obtained from a torque-velocity test was strongly correlated with the optimal torque applied on the pedals, the latter being itself correlated to the lower limb lean volume (r = 0.69, P < 0.05). This shows that absolute size and strength parameters are related to the ability to perform work on cycle ergometers [9, 11]. One may be tempted to explain the linear correlation of anthropometric characteristics to Tlim by the direct effect of muscle mass on power output [9, 11, 27]. In particular, positive relationships between crank torque and thigh TV on short-term cycle ergometer tests have been observed on many occasions [12, 24]. While we did also observe significant correlations of thigh TV and LV to Tlim (r = 0.66 and r = 0.73, respectively), these results must be interpreted with caution since 2 observations may have stretched the regression line. In further investigating the anthropometrics characteristics, we highlighted the impact of the femur length (as a biomechanical
index) on Tlim by showing a strong relationship between the 2 ▶ Fig. 1, panel b). This finding suggests that higher variables (● Tlim on a cycle ergometer is likely to correspond to longer thigh segments, i. e., taller individuals. In accordance with this reasoning, the effect of lever arm on torque and power output generation is well established [7, 37]. For instance, a long lever arm develops higher power output for a given thrust and a given pedaling cadence [7, 38]. Toward the end of the test, fatigue contributes to slowing down the pedaling rate, thereby sustaining a higher force production to maintain the workload. The longer the femur, the greater the mechanical lever, which results in a significantly higher torque on the pedals, conferring taller individuals a biomechanical advantage in maintaining the limit cadence. The average Tlim score (235 ± 84 s) and its correlative wide range (from 108 to 425 s) in the present study was similar to that reported for trained cyclists (222 to 241 s) [13, 21] and may be explained by the “open-loop design” of a square-wave test that could have made participants rely almost exclusively on afferent feedback [8]. However, the current study also showed that anthropometric characteristics – lean body mass and femur length – share part of the variability observed during a cycling time-to-exhaustion test, highlighting the impact of these determinants on Tlim scores.
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Time-to-Exhaustion (s)
400
Practical Applications and Conclusion
▼
Selecting the best cyclists through the systematic identification of genetic potential in talent programs has been practiced in many countries for a considerable time. Our data indicate that large body mass and long lower limb segments are necessary for successfully competing in endurance cycling, while reinforcing the usefulness of anthropometric parameters in talent identification regardless of sex. Altogether this suggests that in future investigations anthropometric characteristics must be regarded as one of the factors affecting cycling performance and be considered when determining the relationship between power output and endurance capacity. Such characteristics should be included with other methodological issues (Pmax and maximal O2 uptake determination [8], ‘open-loop’ model, familiarization [4, 21], metabolic efficiency glycolytic/oxidative ratio, lactate tolerance, movement economy [13, 32] and athletic profile (untrained/trained participants, sport specificity) [2]. When assessing performance potential it is important to note that while the results of the present study are applicable to Tlim in cycling, they must be used with caution in regard to other activities.
Acknowledgements
▼
We gratefully acknowledge Dr. Philippe Corbeil, Dr. Jean Doré, Dr. Richard Chouinard, Dr. Marcel R. Boulay, Gilles Bouchard, Guy Fournier, Frédéric Boivin, Josée St-Onge and Marcel Kaszap for their technical support, and the subjects for their participation and devotion to this work. Funding This project was funded by the Institut National du Sport du Québec and by Sports Internationaux de Québec.
Conflicts of interest: The authors have no conflict of interest to declare. References 1 Barnett C, Jenkins D, MacKinnon L, Green S. A new method for the calculation of constant supra-VO2peak power outputs. Med Sci Sports Exerc 1996; 28: 1505–1509 2 Basset FA, Chouinard R, Boulay MR. Training profile counts for timeto-exhaustion performance. Can J Appl Physiol 2003; 28: 654–666 3 Basset FA, Joanisse DR, Boivin F, St-Onge J, Billaut F, Dore J, Chouinard R, Falgairette G, Richard D, Boulay MR. Effects of short-term normobaric hypoxia on haematology, muscle phenotypes and physical performance in highly trained athletes. Exp Physiol 2006; 91: 391–402 4 Billat LV, Koralsztein JP. Significance of the velocity at VO2max and time to exhaustion at this velocity. Sports Med 1996; 22: 90–108 5 Billat VL, Blondel N, Berthoin S. Determination of the velocity associated with the longest time to exhaustion at maximal oxygen uptake. Eur J Appl Physiol 1999; 80: 159–161 6 Carter SL, Rennie C, Tarnopolsky MA. Substrate utilization during endurance exercise in men and women after endurance training. Am J Physiol 2001; 280: E898–907 7 Cavanagh PR, Sanderson DJ. The biomechanics of cycling: studies of the pedaling mechanics of elite pursuit riders. In: Burke ER (ed.). Science of cycling. Champaign, IL: Human Kinetics, 1986; 91–122 8 Coquart JB, Eston RG, Noakes TD, Tourny-Chollet C, L’Hermette M, Lemaitre F, Garcin M. Estimated time limit: a brief review of a perceptually based scale. Sports Med 2012; 42: 845–855 9 Craig NP, Norton KI. Characteristics of track cycling. Sports Med 2001; 31: 457–468 10 Craig NP, Norton KI, Bourdon PC, Woolford SM, Stanef T, Squires B, Olds TS, Conyers RA, Walsh CB. Aerobic and anaerobic indices contributing to track endurance cycling performance. Eur J Appl Physiol 1993; 67: 150–158 11 Davies CT, Sandstrom ER. Maximal mechanical power output and capacity of cyclists and young adults. Eur J Appl Physiol 1989; 58: 838–844
12 Dorel S, Hautier CA, Rambaud O, Rouffet D, Van Praagh E, Lacour JR, Bourdin M. Torque and power-velocity relationships in cycling: relevance to track sprint performance in world-class cyclists. Int J Sports Med 2005; 26: 739–746 13 Faina M, Billat VL, Squadrone R, De Angelis M, Koralsztein JP, Dal Monte A. Anaerobic contribution to the time to exhaustion at the minimal exercise intensity at which maximal oxygen uptake occurs in elite cyclists, kayakists and swimmers. Eur J Appl Physiol 1997; 76: 13–20 14 Gore CJ, Hahn AG, Aughey RJ, Martin DT, Ashenden MJ, Clark SA, Garnham AP, Roberts AD, Slater GJ, McKenna MJ. Live high:train low increases muscle buffer capacity and submaximal cycling efficiency. Acta Physiol Scand 2001; 173: 275–286 15 Harriss DJ, Atkinson G. Ethical standards in sports and exercise science research: 2014 update. Int J Sports Med 2013; 34: 1025–1028 16 Hopkins WG. Measures of reliability in sports medicine and science. Sports Med 2000; 30: 1–15 17 Hopkins WG, Schabort EJ, Hawley JA. Reliability of power in physical performance tests. Sports Med 2001; 31: 211–234 18 Horton TJ, Pagliassotti MJ, Hobbs K, Hill JO. Fuel metabolism in men and women during and after long-duration exercise. J Appl Physiol 1998; 85: 1823–1832 19 Jones PR, Pearson J. Anthropometric determination of leg fat and muscle plus bone volumes in young male and female adults. J Physiol 1969; 204: 63–66 20 Laursen PB, Rhodes EC, Langill RH, McKenzie DC, Taunton JE. Relationship of exercise test variables to cycling performance in an Ironman triathlon. Eur J Appl Physiol 2002; 87: 433–440 21 Laursen PB, Shing CM, Jenkins DG. Reproducibility of the cycling time to exhaustion at VO2peak in highly trained cyclists. Can J Appl Physiol 2003; 28: 605–615 22 Maughan RJ. The limits of human athletic performance. Ann Transplant 2005; 10: 52–54 23 Maughan RJ, Watson JS, Weir J. Strength and cross-sectional area of human skeletal muscle. J Physiol 1983; 338: 37–49 24 McCartney N, Heigenhauser GJ, Jones NL. Power output and fatigue of human muscle in maximal cycling exercise. J Appl Physiol 1983; 55: 218–224 25 McIntyre JP, Mawston GA, Cairns SP. Changes of whole-body power, muscle function, and jump performance with prolonged cycling to exhaustion. Int J Sports Physiol Perform 2012; 7: 332–339 26 McLean BD, Ellis L. Body mass, thigh volume and vertical jumping ability as predictors of short-term cycle ergometer performance in junior cyclists. Excel 1992; 8: 148–153 27 McLean BD, Parker AW. An anthropometric analysis of elite Australian track cyclists. J Sports Sci 1989; 7: 247–255 28 Medbo JI, Tabata I. Anaerobic energy release in working muscle during 30 s to 3 min of exhausting bicycling. J Appl Physiol 1993; 75: 1654–1660 29 Morton RH, Billat VL. Maximal endurance time at VO2max. Med Sci Sports Exerc 2000; 32: 1496–1504 30 Patton JF, Kraemer WJ, Knuttgen HG, Harman EA. Factors in maximal power production and in exercise endurance relative to maximal power. Eur J Appl Physiol 1990; 60: 222–227 31 Potteiger JA, Smith DL, Maier ML, Foster TS. Relationship between body composition, leg strength, anaerobic power, and on-ice skating performance in division I men’s hockey athletes. J Strength Cond Res 2010; 24: 1755–1762 32 Renoux JC, Petit B, Billat V, Koralsztein JP. Oxygen deficit is related to the exercise time to exhaustion at maximal aerobic speed in middle distance runners. Arch Physiol Biochem 1999; 107: 280–285 33 Seynnes OR, de Boer M, Narici MV. Early skeletal muscle hypertrophy and architectural changes in response to high-intensity resistance training. J Appl Physiol 2007; 102: 368–373 34 Simoneau JA, Lortie G, Boulay MR, Thibault MC, Bouchard C. Repeatability of fibre type and enzyme activity measurements in human skeletal muscle. Clin Physiol 1986; 6: 347–356 35 Tarnopolsky LJ, MacDougall JD, Atkinson SA, Tarnopolsky MA, Sutton JR. Gender differences in substrate for endurance exercise. J Appl Physiol 1990; 68: 302–308 36 Vardar SA, Tezel S, Ozturk L, Kaya O. The relationship between body composition and anaerobic performance of elite young wrestlers. J Sports Sci Med 2007; 6: 34–38 37 Yoshihuku Y, Herzog W. Maximal muscle power output in cycling: a modelling approach. J Sports Sci 1996; 14: 139–157 38 Zamparo P, Minetti A, di Prampero P. Mechanical efficiency of cycling with a new developed pedal-crank. J Biomech 2002; 35: 1387–1398
Basset FA et al. Anthropometric Characteristics Account for … Int J Sports Med 2014; 35: 1084–1089
This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited.
Training & Testing 1089
Copyright of International Journal of Sports Medicine is the property of Georg Thieme Verlag Stuttgart and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
