triathlon is a challenging individual sport that involves the disciplines of cycling , 
 swimming , and running ; these disciplines are combined in a continuous manner through two 
 transitions1 . the ability to sustain 
 high metabolic power for long periods is very important for athletes competing in 
 triathlons . several field - based studies have shown that physiological and morphological 
 functional characteristics change negatively with age2 , 3 . it is very important that 
 triathletes have suitable anthropometric and physiological characteristics to advance 
 performance in the three disciplines involved . some studies have found that anthropometric 
 characteristics are associated with better performance , especially during the swimming and 
 running components of triathlon competitions4 . the triathletes anthropometry was found to account for 47% of the 
 variance in triathlon performance landers5 . it is also well known that endurance runners have low levels of body 
 mass and that it is related to improved running performance6 , 7 . thus , success in a 
 competitive sport is determined not by anthropometric characteristics alone , but by a 
 combination of other characteristics such as physiological variables . a high maximal oxygen uptake ( vo2max ) is a physiological characteristic that 
 plays an important role in the performance of triathletes in competitions . however , 
 vo2max has not been shown to be a good predictor of triathlon performance in 
 elite triathletes8 . in fact , the 
 vo2max plateau duration has more correlation to triathlon performance than the 
 vo2max value9 . other 
 important physiological characteristics , such as 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 
 competitions10 . heart rate recordings 
 have been used to assess maximal heart rate , minimum heart rate , and training intensity 
 among sportsmen , particularly in endurance sports11 . heart rate variability ( hrv ) , which is analyzed from the heart 
 rate recordings , provides information about the training load and psychophysiological status 
 in endurance sports such as triathlons and cycling . a reduction in the high frequency 
 component and an increase in the low frequency component of the power spectrum of hrv have 
 been shown to relate with fatigue and training load12 , and it has been demonstrated that continued exposure to prolonged 
 periods of intense cycling exercise ( about 3-week ) can cause a marked reduction in hrv 
 indices in cyclists . thus , anthropometric characteristics may not be the only determinants of competitive 
 athletic performance ; a combination of other physiological characteristics such as maximal 
 oxygen uptake and anaerobic power and capacity may also play significant roles . the 
 objective of the study was to compare of body composition , heart rate variability , aerobic 
 and anaerobic performance between competitive cyclists and triathletes . after a 2-weeks pre - season training period for the participants in the aerobic and 
 anaerobic performance tests , the anthropometric , body composition , and heart rate 
 variability measurements were performed at a temperature - controlled performance laboratory 
 in a public university . six cyclists ( age 32.33.0 yrs ; height 175.55.5  cm ; body mass 
 75.47.4  kg ; training experience 9.74.8 yrs ) and eight triathletes ( age 36.25.6 yrs ; 
 height 181.64.1  cm ; body mass 74.33.8  kg ; training experience 10.62.9 yrs ) ( 14 males 
 athletes in total ) who had participated for more than three years in regional and national 
 competitions were recruited for the study . all the athletes were notified of the research 
 procedures , requirements , benefits , and risks before obtaining informed consent . the study was approved by the 
 research ethics committee of the local university and was conducted in a manner consistent 
 with the institutional ethical requirements for human experimentation in accordance with the 
 declaration of helsinki . standardized testing procedures were followed as defined in the 
 american college of sports medicine guidelines ( acsm)13 . all measurements were performed by the same researchers after 
 overnight fasting , at a similar time of the day - in order to have similar chronobiological 
 characteristics14 . the temperature 
 ( 2022  c ) and relative air humidity ( < 60% ) of the room were consistent throughout all 
 the steps of the study . the subjects were asked not to exercise exhaustively on the day 
 prior to assessment . the height and weight were measured for each volunteer while they were wearing light 
 clothing and no shoes and socks . weight was measured to the nearest 0.1  kg using calibrated 
 scales ( seca , germany ) , while the height was measured to the nearest 0.1  cm using a 
 calibrated stadiometer ( holtain ltd , england ) . a gulick anthropometric tape ( holtain ) with 
 an accuracy of 1  mm was used to measure the circumferences of the waist , hip , abdominal , 
 thighs , and calves . to estimate the body fat percentage , 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 : the chest , abdominal , thigh , triceps , suprailium , 
 subscapular , and iliac crest . body density was estimated using the equation that has been 
 validated for males aged 18 to 61 years15 . the body density estimate was in turn used to estimate the body fat 
 percentage using the siri equation : [ % body fat = ( 495 / body density )  450 ] . fat mass was 
 calculated by the transformation of the percent body fat values [ fat mass = ( body mass  
 % body fat)/100 ] . lean body mass was determined by the fractionation of body mass into two 
 components : lean body mass = body mass  fat mass ) . body mass and body fat percentage were 
 measured using bioelectrical impedance analysis ( tbf 401 a , tanita , tokyo , japan ) . two 
 measurements were taken for each of these variables , and then the average values were used 
 to perform the statistical analysis . all of the athletes completed an incremental treadmill 
 test on a motorized treadmill ( cosmed , italy ) according to the procedures suggested by 
 rossato et al.11 . during the test , the 
 expired gases were analyzed using a breath - by - breath automated gas - analysis system ( oxycon 
 mobile ; viasys healthcare , hoechberg , germany ) and heart rate was monitored continuously 
 throughout the test with a polar s610 heart rate monitor ( polar , finland ) . mean hr and vo2 values measured during the test were used as maximum values 
 ( hrmax and vo2max ) . 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 . hrv was tested , the athletes voided their bladders and lay in a supine 
 position for 15 minutes in silence with the lights dimmed ; the actual hrv recording took 
 67  min . before any strenuous activity16 . after hrv test , the wingate anaerobic test ( want ) was conducted using a mechanically braked 
 cycle ergometer ( 834 e , monark , vansbro , sweden ) according to the procedures suggested by 
 inbar et al.17 . during the test , the 
 athletes were verbally encouraged to give the maximum effort possible . at the end of the 
 test , the peak power and mean power were calculated automatically by the want test computer 
 program . a fatigue index ( fi ) was calculated using the following equation17 : fi = [ ( peak power output - minimum power 
 output ) / peak power output ]  100 . the data are reported as means and standard deviations . 
 before using the parametric tests , the assumption of normality differences in the all tests performance variables between the cyclists 
 and the triathletes were tested by the nonparametric wilcoxon signed rank tests for 
 independent samples . effect sizes (  ) values of < 0.20 , 0.200.60 , 0.601.2 , 
 1.22.0 , 2.04.0 were considered to represent small , moderate , large , very large and 
 extremely large differences , respectively18 . all statistical analyses were performed with the spss version 
 16.0 , and the level of statistical significance was set at p<0.05 . table 1table 1.anthropometric characteristics and body composition of the cyclists and 
 triathletesskinfold thicknesstriathletes ( n=8)cyclists ( n=6)chest ( mm)10.14.310.33.6abdominal ( mm)17.92.719.23.2thigh ( mm)12.73.614.92.3triceps ( mm)9.91.912.63.7supraspinal ( mm)11.83.912 . 84.4subscapular ( mm)12.84.812.94.3iliac crest ( mm)7.91.99.72.6sum 7sf ( mm)83.223.292.524.1body fat ( % ) 17.73.219.33.2fat mass ( kg)13.22.814.63.2lean body mass ( kg)61.12.760.83.7 shows the anthropometric characteristics and body composition of the cyclists 
 and triathletes . there were no significant differences between the anthropometric 
 characteristics and body composition of the cyclists and triathletes . however , cyclists had 
 a higher body fat percentage ( 17.719.3% , p=0.44 , =0.23 moderate effect ) and 
 fat mass ( 13.214.6  kg , p=0.44 , =0.22 moderate effect ) compared to the 
 triathletes . in addition , lean body mass was higher in the triathletes ; however , no 
 significant difference was found ( 61.160.8  kg , p=0.89 ,  = 0.03 small 
 effect ) . table 2table 2.aerobic performance of cyclists and triathletesincremental treadmill testtriathletes ( n=8)cyclists ( n=6)vo2max ( ml.kg.min)58.55.757.75.8hrmax ( b.min)187.18.1193.56.7hrresting ( b.min)59.67.360.79.5maximum power ( w)527.564.8516.662.1maximum power ( w.kg)7.10.96.80.8 shows the aerobic performance of the cyclists and triathletes studied . there 
 were no significant differences in the aerobic performances responses of the cyclists and 
 triathletes . however , triathletes demonstrated higher vo2max 
 ( 58.557.7  ml.kg.min , p=0.85 , =0.07 small effect ) 
 and maximum power ( 7.16.8 w.kg , p=0.21 , =0.14 small effect ) 
 compared to the cyclists . in addition , hrmax was higher in the cyclists , but no 
 significant difference was found ( 187.1193.5 b.min , p=0.09 , =0.39 
 moderate effect ) . table 3table 3.anaerobic performance of cyclists and triathleteswanttriathletes ( n=8)cyclists ( n=6)peak power ( w)796.474.6933.3189.5peak power ( w.kg)10.71.312.42.3average power ( w)586.945.8702.5139.3average power ( w.kg)7.90.89.31.7minimum power ( w)377.529.0471.790.9*minimum power ( w.kg)5.10.46.31.2*fatigue index ( % ) 52.44.149.32.2 * p the cyclists 
 group showed statistically significant differences in minimum power ( 377.5471.7  w , p=0.02 , 
 =0.57 moderate effect ) and relative minimum power ( 5.16.3 w.kg , 
 p=0.02 , =0.55 moderate effect ) compared to the triathletes . table 4table 4.heart rate variability responses of cyclists and triathleteshrvtriathletes ( n=8)cyclists ( n=6)sdnn ( ms)50.216.857.220.9rmssd ( ms)35.718.842.224.2tp ( ms)1066.0860.7804.7756.4lf ( ms)643.4545.5537.0411.1hf ( ms)279.1314.8456.2420.6lf / hf4.33.72.43.0lfnu72.115.158.719.1hfnu27.915.141.219.1vlf ( ms)161.9202.2131.570.1sdnn : 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 shows the heart rate variability responses of the cyclists and triathletes 
 studied . there were no significant differences in any heart rate variability responses 
 between cyclists and triathletes . sdnn : 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 the aim of this study was to compare the body composition , heart rate variability , aerobic 
 and anaerobic performances between competitive cyclists and triathletes . the study revealed 
 no significant differences in the seven sites skinfold thicknesses , body fat percentage , fat 
 mass , and lean body mass between cyclists and triathletes . moro et al.19 also found no differences in seven sites skinfold 
 thicknesses in cyclists and triathletes , except for medial calf skinfold thickness . in 
 addition , laursen et al.20 observed no 
 significant differences in body mass or the sum of five skinfolds between cyclists and 
 triathletes . furthermore , rst et al.4 
 found no differences in anthropometric characteristics and body composition between 
 triathletes and cyclists . in contrast , millet et al.21 , found significant differences in height and body mass between 
 competitive cyclists and triathletes . brunkhorst and kielstein7 , found that cyclists who were males had a higher bmi and larger 
 thighs and were taller when compared to the male triathletes . in addition , landers et 
 al.5 reported a strong and positive 
 correlation between height and mass in elite triathletes who were males . these reported 
 findings are similar to the results of the present study and indicate that anthropometric 
 characteristics are similar in competitive cyclists and triathletes . previous researches 
 have shown that the physical characteristics of athletes may play a role in determining 
 performance . the participant s anthropometry was found to account for 47% of the variance in 
 triathlon performances5 , and low levels of 
 adiposity positively influenced swimming and running performance during triathlons4 , 22 . other performance and anthropometric characteristics studies have revealed that endurance 
 runners have low levels of body mass and reduced skinfold thickness , which are related to 
 improved running performance6 . given these 
 findings , successful performance may not be determined only by physiological 
 characteristics , but it may also be affected by a combination of anthropometric and 
 physiological characteristics . knechtle et al.22 suggested that the anthropometry of triathletes is associated with 
 training volume . the seven sites skinfold thickness , body fat percentage , and fat mass were 
 lower in triathletes than in cyclists ( table 1 ) . 
 these finding can be explained by the nature of triathlon training , because running training 
 and overall training volume cause a reduction in the skinfold thickness of the lower 
 limbs . the present study also showed that triathletes had higher relative vo2max values 
 compared to cyclists . similarly , triathletes generally possess high vo2max values 
 in studies , compared with cyclists in studies19 . we believe this might be because triathletes divide their training 
 time into three disciplines ( swimming , cycling , and running ) and their training volume and 
 overall training time are higher than that of cyclists . generally , vo2max values 
 are reported as relative because of extra body mass affects running performance negatively . for example , costill et al.23 reported a 
 relationship between both absolute and relative vo2max and running performance , 
 and a stronger relationship was found for relative compared to absolute vo2max 
 ( r=0.83 and 0.59 respectively ) . the specificity of each discipline can influence the aerobic 
 performance ; cyclists achieve a higher performance than triathletes in cycling tests , 
 whereas the opposite is observed in running tests24 . numerous studies have demonstrated that vo2max and 
 wpeak value measured by treadmill are higher for triathletes compared to cycle 
 ergometer25 . the present study also 
 showed that triathletes had higher maximum power measured with treadmill compared to the 
 cyclists maximum power measured by cycle ergometer . in similar with our result , mujika and 
 padilla26 showed that wpeak value of 
 4403.3  w was reported for 14 elite cyclists , compared to a wpeak of 439  w for 24 
 professional cyclists . we believe that this difference might be because of the specific 
 features of the individual sports , their requirements , and the different measurement 
 tools . the wingate anaerobic test ( want ) is the gold standard for evaluating anaerobic 
 capacity17 . there were no significant 
 differences in absolute and relative peak and average power and fatigue index obtained on 
 the want between the cyclists and triathletes , except for minimum power . in a similar study 
 showed that triathletes and cyclists had lower peak power and mean power than we found in 
 our results . furthermore , higher values of peak power and average power have been reported 
 for cyclists , although similar statistical results to the present study have been obtained 
 in the literature19 . according to the 
 sport - specific requirements , anaerobic power and capacity are more important for cyclists 
 than triathletes . a cycling race is characterized by power maintained for prolonged periods 
 of time and high peak power for short periods of time for sprints8 . in contrast , triathletes perform fewer sprints during the 
 cycling race than cyclists , since a higher demand on the anaerobic energy system during 
 cycling may accelerate the process of muscle fatigue , and reduce 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 perform sprints when they overtake , break away , or follow with the group and 
 when they pick up speed again1 . in 
 addition , a previous study demonstrated a relationship between running speed and heart rate 
 from low to submaximal speeds27 . one limitation of the present study is the fact that we monitored hrv for 7  min . prolonged 
 recordings ( 24-hour ) for hrv is a better assessment to reflect training load and to collect 
 psychophysiological information for this study . in conclusion , the anthropometric 
 characteristics , aerobic and anaerobic profile , and heart rate variability were similar in 
 triathletes and cyclists . triathletes demonstrated higher vo2max , power outputs 
 and fatigue indexes , suggesting that the specificity of their training caused 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 .