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��ࡱ�>��	������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������	���ObjbjQFQF4T3,3,t�+���������������������86T���D0F��������=C?C?C?C?C?C?C$BE��G@cCi������cC������Cm5m5m5������=Cm5�=Cm5m5:�9,g:�����0W:�	U��c1.:
)C�C0D:R$H�4�$Hg:g:V$H��?l��m5�����cCcCm5���D������������������������������������������������������������������������$H�����������:	Comparison of body composition, heart rate variability, aerobic and anaerobic performance between competitive cyclists and triathletes
Er_an ARSLAN1, Dicle ARAS2
Abstract
	The aim of this study was to compare of body composition, heart rate variability, aerobic and anaerobic performance between competitive cyclists and triathletes. Six cyclists (mean age 32.33�3.01 yrs; height 175.50�5.50 cm; body mass 75.43�5.14 kg) and 8 triathletes (mean age 36.25�5.60 yrs; height 181.63�4.07 cm; body mass 74.30�3.76 kg) with experience in competitions voluntarily participated in this study. The tests were performed on two different days, with an interval of 48 h between sessions. On the first day, the athletes were submitted to anthropometric assessment (body mass, height, and skinfold thickness), 7 min ECG recording for heart rate variability analysis and incremental treadmill test to determine maximal oxygen consumption and maximum heart rate. The Wingate test was conducted on the second day to determine peak power, average power, minimum power and fatigue index. There were significant difference (p < 0.05), with small effect size (0.35 - 0.80), in minimum power (377.55 � 29.03 and 471.71 � 90.87 W), relative minimum power (5.09 � 0.42 and 6.26 � 1.17 W.kg-1) between triathletes and cyclists, respectively. The other variables did not differ between triathletes and cyclists. Descriptive, anthropometric characteristics and heart rate variability responses are similar in triathletes and cyclists. However, triathletes demonstrate higher maximal oxygen consumption and lower resting heart rate.
Key words: Triathletes, Cyclists, Anaerobic Power, Heart Rate Variability, Maximal Oxygen Consumption
1Siirt University, School of Physical Education and Sports (Siirt, Turkey)
2Ankara University, Faculty of Sport Sciences, (Ankara, Turkey)


Introduction
	Challenging and individual sport triathlon involves three disciplines cycling, swimming and running and these disciplines are combined in a continuous manner through two transitions (1). The ability to sustain high metabolic power for long periods of these disciplines is very essential for triathletes in triathlon competitions. Several field-based studies showed that the physiological (e.g. muscle strength, oxygen carrying capacity) and morphological (e.g. percentage of body fat, muscle mass) functional characteristics change with age negatively (2,3,4,5). 
	It is important that triathletes have suitable anthropometric and physiological characteristics to advance performance according to sport branches. Some studies have found that anthropometric characteristics (e.g. percentage  of  body  fat, body segment length and lean body mass) are associated with higher performance especially swimming and running performance during triathlon competitions (1,6,7,8,9). The triathletes� anthropometry was found to account for 47% of the variance in triathlon performance (10). It is also well known that endurance runners have low levels of body mass which relates to improved running performance (11,12). It may not be only anthropometric characteristics determining success, but a combination of other characteristics such as physiological variables. 
	As a physiological characteristics, high maximal oxygen uptake (VO2max) play an important role in order to achieve best performance for triathletes in competitions. VO2max values in elite triathletes have been reported in the range of 70-90 ml.kg-1.min-1 (13,14,15). However, VO2max has not been taken as a good predictor of triathlon performance in elite triathletes (16). In addition, VO2max plateau duration has more correlation to triathlon performance than VO2max value (17). Other important physiological characteristics anaerobic power and capacity, which are required during to perform sprints, overtake, break away or follow with the group, are very important for the performance of triathletes particularly at the end of the triathlon competitions (18). Heart rate (HR) recordings provide information about training load and psychophysiological status in endurance sports such as triathlon and cycling and heart rate variability (HRV) are analyzed from the HR recordings (19,20). Reduction in the high frequency component (HF) and an increase in the low frequency component (LF) of the power spectrum of the HRV have been shown to relate with fatigue and training load (21) showed that continued exposure to prolonged periods of intense cycling exercise (about 3-week) caused a severe reduction in HRV indices in cyclist.
	In this context, anthropometric characteristics may not be only determining performance, but also a combination of other physiological characteristics such as maximal oxygen uptake and anaerobic power and capacity. Therefore, the aim of the present study was to compare of body composition, heart rate variability, aerobic and anaerobic performance between competitive cyclists and triathletes.
Methods
Participants
	Six cyclists and eight male triathletes had participated for more than three years in regional and national competitions. All athletes were notified of the research procedures, requirements, benefits, and risks before giving informed consent. Written informed consent was obtained from all the subjects. The study was approved by the research ethics committee of local university and was conducted in a manner consistent with the institutional ethical requirements for human experimentation in accordance with the Declaration of Helsinki
Procedures
	The tests were conducted on 2 days at an interval of 48 h between sessions. On the first day, the athletes were submitted to anthropometric assessment (body mass, height, and skinfold thickness), 7 min ECG recording for HRV analysis and incremental treadmill test to determine maximal oxygen consumption and maximum heart rate. On the second measurement day, the Wingate test was performed to evaluate anaerobic fitness. The Wingate test was completed on an electromagnetically braked cycle ergometer (Monark 894E Peak Bike, Varberg, SWEDEN). The cycle ergometer was adjusted individually to reproduce the configuration of the cyclist�s bicycle in terms of horizontal position and saddle and handlebar height. The subjects were asked not to exercise exhaustively on the day prior to assessment and to have eaten and be hydrated on the day of the test. The temperature (20-22�C) and relative air humidity (<60%) of the room throughout all steps of the study. 
Anthropometry
	Body mass and height were measured with an electronic scale (Seca, Hamburg, Germany) to the nearest 100 g and with a wall stadiometer (Seca, Hamburg, Germany) to the nearest 1 mm, respectively. To estimate percent body fat composition, a seven site skinfold thickness technique was used with a scientific skinfold caliper (Holtain, UK) to the nearest 0.1 mm. The anatomical sites used were: chest, abdominal, thigh, triceps, suprailium, subscapular and iliac crest. Body density was estimated using the equation developed by Jackson and Pollock in 1978, which was validated for male aged 18 to 61 years: body density = 1.112 - (0.00043499 x sum of skinfolds) + (0.00000055 x square of the sum of skinfold sites) - (0.00028826 x age), where �7SF is the sum of chest, abdominal, thigh, triceps, suprailium, subscapular and iliac crest skinfolds (22). Body density was used to estimate body fat percentage using the Siri equation: [%Body fat = (495 / body density) � 450]. Fat mass was calculated by the transformation of percent body fat values [fat mass = (body mass x %body fat)/100]. Lean body mass was determined by the fractionation of body mass into two components: lean body mass = body mass � fat mass).
Incremental Treadmill Test
	All the players completed an incremental treadmill test on a motorized treadmill (Cosmed, Italy) at an incline of 1% to determine maximal oxygen uptake (VO2max) and maximum heart rate (HRmax). The test began at 9 km.h-1 and the speed was increased by 1 km.h-1 every minute until exhaustion. Achievement of VO2max was considered as the attainment of at least 2 of the following criteria: (a) a plateau in VO2max despite increasing speed, (b) a respiratory exchange ratio above 1.10, and (c) HR � 10 b.min-1 of age-predicted maximal HR (220-age) (23). The subjects were verbally encouraged to give maximal effort during the test. During the test, expired gases were analyzed using a breath-by-breath automated gas-analysis system (Oxycon Mobile; Viasys Healthcare, Hoechberg, Germany). The flow, volume, and gas analyzer were calibrated before each test according to the manufacturer�s instructions. The data from the gas analyzer were smoothed (mean of 15 s). In the last minute of each 3-min stage of the test, a mean value was calculated to determine VO2max corresponding to each stage and the highest value obtained was defined as VO2max. Heart rate was monitored continuously throughout the test with a Polar S610 HR monitor (Polar, Finland). The heart rate data were transferred to the computer and smoothed (average of 5 s) by Polar Precision Performance Software TM (PPP4, Finland). In the last minute of each 3-min stage of the incremental treadmill test, a mean value was calculated to determine the HR corresponding to each stage and the highest value was defined as the maximum heart rate (HRmax).
30-Second Wingate test (WAnT)
	The subjects were familiarized with the Wingate test by performing a 10-s trial after the incremental treadmill test on the first day of data collection. The Wingate Anaerobic Test (WAnT) was conducted using a mechanically braked cycle ergometer (834 E, Monark, Vansbro, Sweden). At the beginning of the test, the athletes performed a warm-up for 5 min by cycling at a load of 50 W, with a sprint of 3 to 5 s at the end of each minute, after which they rested for 5 minutes. After the warm-up period, the subjects were asked to remain seated and to perform maximal effort over the 30 seconds of the test. The load (resistance) used in the WAnT test was 7.5% of the subject�s body mass. When the pedalling rate reached approximately 160�170 rpm, the resistance was applied and subjects continued pedalling as fast as possible for 30 seconds. During the test, the athletes were verbally encouraged to give the maximum effort possible. At the end of the test, peak power and mean power was calculated automatically by the WAnT test computer program. A fatigue index (FI) was calculated by using the following equation (24). 
FI = [(Peak Power Output-Minimum Power Output) / Peak Power Output] x 100
Measurement of Heart Rate Variability (HRV)
	Heart rate variability (HRV) was measured using the OmegaWave sport technology system (OmegaWave Technologies,LLC, Portland, OR, USA) as described in the manufacturer�s reference manual and standardized guidelines for the measurement of HRV. The following time domain indices (in milliseconds) were analyzed and are assumed to represent ANS activity: the standard deviation of all normal RR (SDNN) and square root of the mean of the sum of the squares of differences between adjacent RR (rMSSD). Frequency domain parameters include total power (TP-ms2), low-frequency power (LF-ms2), high-frequency power (HF-ms2), and low-to-high frequency ratio (LF:HF). Whereas the HF component is generally defined as a marker of vagal modulation, the LF component depends on both the sympathetic and parasympathetic nervous systems. The LF:HF ratio reflects the global sympathovagal balance and can be used as a measure of ANS balance. After a 15-min rest, the measurements (recording the beat to beat) took time almost 6-7 minutes and took place in the morning after emptying their bladders athletes lay down in the supine position in the light dimmed and silence (25). HRV is measured in early morning, after an overnight fast and before any strenuous activity, the measurements are highly reproducible (intra-class correlation coefficient >0.97 for all HR and HRV indices) (26). No heavy training session took place before the HRV tests. The temperature (20-22�C) and relative air humidity (<60%) of the room throughout all steps of the study. 
Statistical analyses
	The Shapiro-Wilk test was used to determine whether the data showed a normal distribution. Differences in the anthropometric and physiological variables between cyclists and triathletes were tested by nonparametric Wilcoxon signed rank tests for independent samples. A level of significance of p<0.05 was adopted. Effect size was used to evaluate the magnitude of the differences between cyclists and triathletes and was classified as non significant (<0.35), small (0.35�0.80), medium (0.80�1.5), and large (>1.5) (27). The results were analyzed using the SPSS 20.0 for Windows (SPSS, Inc., USA) software.
Results
Table 1. Descriptive and anthropometric characteristics of the cyclists and triathletes 
Descriptive characteristicsTriathletes (n=8)Cyclists (n=6)pESAge (years)36.25 � 5.6032.33 � 3.01.104.399Training age (years)10.56 � 2.959.67 � 4.76.556.111Height (cm)181.63 � 4.07175.50 � 5.50.031.535Weight (kg)74.30 � 3.7675.43 � 5.14.606.124Skinfold thicknessChest (mm)10.06 � 4.2810.35 � 3.64.846.036Abdominal (mm)17.96 � 2.7019.23 � 3.17.400.210Thigh (mm)12.69 � 3.6514.87 � 2.27.196.337Triceps (mm)9.90 � 1.9512.62 � 3.66.197.420Supraspinal (mm)11.83 � 3.9212.78 � 4.45.245.112Subscapular (mm)12.80 � 4.8112.93 � 4.35.606.010Iliac crest (mm)7.98 � 1.889.75 � 2.59.699.364Sum 7SF (mm)83.21 � 23.1992.53 � 24.13.197.193Body fat (%)17.72 � 3.2119.26 � 3.25.439.231Fat mass (kg)13.22 � 2.8014.59 � 3.16.439.223Lean body mass (kg)61.07 � 2.6860.83 � 3.66.897.037Values are mean�SD and and effect size.

The results demonstrated that there were similar values in descriptive and anthropometric characteristics between cyclists and triathletes
Table 2. Aerobic and anaerobic performance of cyclists and triathletes
Incremental Treadmill TestTriathletes (n=8)Cyclists (n=6)pESVO2max (ml.kg-1.min-1)58.46 � 5.6857.66 � 5.83.846.069HRmax (b.min-1)187.13 � 8.15193.50 � 6.66.091.393HRresting (b.min-1)59.63 � 7.3560.67 � 9.48.918.061Maximum power (W)527,50 � 64.77516.60 � 62.06.783.086Maximum power (W.kg-1)7.10 � 0.906.85 � 0.82.211.143WaNTPeak power (W)796.37 � 74.65933.32 � 189.52.245.429Peak power (W.kg-1)10.75 � 1.2812.37 � 2.29.197.400Average power (W)586.96 � 45.80702.51 � 139.35.093.486Average power (W.kg-1)7.92 � 0.799.31 � 1.71.121.502Minimum power (W)377.55 � 29.03471.71 � 90.87.020*.572Minimum power (W.kg-1)5.09 � 0.426.26 � 1.17.020*.554Fatigue index (%)52.36 � 4.0749.34 � 2.20.053.419VO2max = maximum oxygen consumption; HRmax = maximum heart rate; HRresting = resting heart rate; Values are mean�SD and and effect size. *p < 0.05
	The results demonstrated that there were similar values in VO2max, HRmax and HRresting between cyclists and triathletes. Wingate test results demonstrated that there were no significant differences in peak, average power (absolute and relative values) and the fatigue index between cyclists and triathletes. In contrast, minimum power (absolute and relative values) was significant lower in triathletes. 

Table 3. Heart rate variability responses of cyclists and triathletes.
HRVTriathletes (n=8)Cyclists (n=6)pESSDNN (ms)50.25 � 16.8357.17 � 20.87.401.179RMSSD (ms)35.75 � 18.8242.17 � 24.23.698.146TP (ms2)1066.00 � 860.66804.67 � 756.36.606.159LF (ms2)643.38 � 545.52537.00 � 411.07.699.109HF (ms2)279.13 � 314.78456.17 � 420.61.366.231LF/HF4.34 � 3.692.44 � 3.02.156.271LFnu72.12 � 15.1058.72 � 19.10.156.362HFnu27.87 � 15.1041.20 � 19.07.156.361VLF (ms2)161.86 � 202.25131.50 � 70.11.606.099SDNN=standard deviation of RR interval; RMSSD=root mean square of successive differences in RR intervals; TP= total power; LF = low frequency; HF = high frequency components; nu = normalized units; VLF=very low frequency components. Values are mean�SD and and effect size. 
	There were no significant differences in heart rate variability between cyclists and triathletes.
Conflicts of interest

	All contributing authors declare no conflicts of interest.

Acknowledgments

	The authors would like to thank all the participants for their time and effort during study.
Discussion

	The aim of this study was to compare of body composition, heart rate variability, aerobic and anaerobic performance between competitive cyclists and triathletes. The present results showed that there was no significant differences in seven sites skinfold thicknesses, body fat percentage, fat mass, and lean body mass between cyclists and triathletes. Similarly, Moro et al.. (25) also found no differences in triceps, biceps, subscapular, iliac crest, supraspinal, abdominal and medial calf skinfold thicknesses, sum of four sites skinfold thicknesses, body fat percentage, fat mass, and lean body mass in cyclists and triathletes except for medial calf skinfold thickness. In addition, Laursen et al., (26) observed no significant differences in body mass or sum of five skinfolds (biceps, triceps, subscapular, supraspinal, and abdominal) between cyclists and triathletes. Furthermore, Rust et al.. (9) also found no differences in body mass, height, fat percentage or pectoral, axillary, triceps, subscapular, abdominal, iliac crest and calf skinfold thicknesses between triathletes and cyclists. Millet et al., (27) found significant differences in height, body mass between competitive cyclists and triathletes. Brunkhorst and Kielstein, (12) found that male cyclists had a higher BMI, larger thighs and were taller as compared to the male triathletes. Contrary to them, Landers et al., (10) reported strong and positive correlation existed between height and mass (r= 0.794, p<0.0001) in elite male triathletes. These findings in literature are similar with the present study and indicate that anthropometric characteristics are similar in competitive and elite cyclists and triathletes. 
	Previous triathlon researches have shown that anthropometric characteristics of athletes may play a role in triathlon performance (10). Endurance runners have low levels of body mass and reduced skinfold thickness which relates to improved running performance (11,29). In addition, low levels of adiposity positively influenced swimming and running performance during triathlon (7,9,28). Knechtle et al., (30) suggested that the anthropometry of triathletes is associated with training volume. This finding can be explained by the specificity of triathlon training, with the run training and training volume causing a reduction in skinfold thicknesses of the lower limbs. Highlighting that, successive performance may not explain only physiological characteristics, but also its effected by a combination of anthropometric and  physiological characteristics. 
	Male national elite triathletes VO2max values have ranged from 49.7�78.5 ml.kg-1.min-1 reported during running (31). In addition to this, triathletes divide their training time into three disciplines (swimming, cycling and running) and their training volume and spent time for training are higher than cyclists. Swimming and running training performed by the triathletes may have positive influenced the relative VO2max values in elite triathletes. The present study also showed that triathletes had higher relative VO2max values compared to cyclists. We suggested that this might be because triathletes and cyclists have similar physiological and anthropometric characteristics in this study. Triathletes generally possess high VO2max values in studies, when comparing the VO2max values of cyclists and triathletes. In similar study, Peveler et al., (32) showed that triathletes and cyclists had higher VO2max values compared to our results. As triathletes compete in swimming, cycling and running VO2max has often been reported in both relative and absolute values (13). Costill et al., (33) reported a relationship between both absolute and relative VO2max and running performance, a stronger relationship was found for relative compared to absolute VO2max (r= 0.83 and 0.59 respectively). Generally, VO2max values are reported as relative because of the fact that extra body mass effect running performance negatively.
	The specificity of the discipline can influence aerobic performance, with cyclists presenting a higher performance than triathletes in cycling tests, whereas the opposite is observed in running tests (13,34). Numerous studies support that VO2max and Wpeak value measured by treadmill are higher for triathletes compared to cycle ergometer (35,36,37,38). The present study also showed that triathletes had higher maximum power measured with treadmill compared to cyclists maximum power measured by cycle ergometer. In similar study, Mujika and Padilla (39) showed that Wpeak value of 440�3.3 W was reported for 14 elite cyclist, while Wpeak of 439 W for 24 professional cyclists. We suggested that this differences might be because of sport specific features, requirement and different measurement tools.
	There were no significant differences in absolute and relative peak and average power and fatigue index obtained in the WaNT between cyclists and triathletes. In contrast, minimum power was significantly lower in triathletes than in cyclists. Higher peak and average power have been reported for cyclists although lower fatique index result obtained in the literature (16). In similar study, Peveler et al., (32) showed that triathletes and cyclists had lower peak power and mean power compared to our results. Furthermore, Higher values of peak power and average power have been reported for cyclists although similar statistical result obtained in the literature with present study (25). According to sport-specific requirements, anaerobic power and capacity for cyclists are more important than triathletes. A cycling race is characterized by maintained for prolonged periods of time and high peak power for short periods of time for sprints (40). In contrast, triathletes perform fewer sprints during the cycling race than cyclists, since higher demand of the anaerobic energy system during cycling may accelerate the process of muscle fatigue, reducing the performance of the triathletes during running. However, it is believed that anaerobic fitness is important for the performance of triathletes, since the intervals in short-distance triathlon races permit the athletes to eventually perform sprints when they overtake, break away or follow with the group and when they pick up speed again (1). 

	One limitation of the present study is the fact that body circumferences and prolonged recordings (24-hour) for HRV were not measured. We have monitored HRV (7 min.) that is known to reflect autonomic imbalance, which is widely utilized among sportsmen and a good candidate to reflect training load and psychophysiological information in this study. We did not find any significant differences in heart rate variability responses in cyclists and triathletes. We thought that this outcome not surprising because of the training age of the sportsmen. In addition to this, athletes have similar anthropometric and physiological characteristics. In elites and athletes with extensive training histories, makes it difficult to practically use HRV to maximize training in these sportsmen because of the negative and positive adaptation of the endurance training regimens (41,42).

	In conclusion, it can be concluded that anthropometric characteristics aerobic and anaerobic profile and heart rate variability are similar in triathletes and cyclists. Triathletes demonstrate higher VO2max and power outputs and fatigue indexes, suggesting that the specificity of training causes different anthropometric, psychophysiological and physiological adaptations in triathlon and cycling. These parameters could provide further information about the anthropometric and psychophysiological profile of cyclists and triathletes.
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