Introduction

Biathlon and cross-country skiing (XC skiing) are endurance sports where competitors ski over various distances and terrain, with the skiing and shooting components significantly different. For instance, biathlon skiing during competition is intermittent, being stopped by 1-minute breaks on the shooting range, unlike XC skiing, which comprises non-stop skiing from start to finish1. Winter Olympics endurance sports include cross-country skiing and biathlon, where the latter combines cross-country skiing and accurate shooting. XC skiers and biathletes must have a good aerobic capacity because competitions typically last 10 to 120 min2,3. Physiological variables such as maximum oxygen uptake (VO2max) and exercise intensity equivalent to the lactate or anaerobic threshold (AT) are believed to have an impact on endurance cycling performance4,5,6. These physiological variables indicate maintaining the highest potential power production and oxygen intake (VO2) during the event7. According to Hawley et al.8, successful endurance athletes can hold high VO2max percentages for extended periods, develop high power outputs and maintain effective technique. Therefore, the sustained power output and, in turn, the relationship between performance on these tasks and the physiological outcomes of incremental exercise testing, such as VO2max and AT, may be impacted by the difference in exercise duration and the physiological demands of the event9. It is common knowledge that men and women perform differently in sports. These disparities can be explained by several physiological justifications10,11. Specifically, males typically have more extensive anthropometric measurements, higher testosterone levels, greater capacity for type II fibre hypertrophy and reactivity to exercise. Additionally, males have a higher relative stroke volume and cardiac output, higher red blood cell mass, higher glycolysis enzyme activity and higher glycogen storage capacity. However, there are no differences between males and females in the composition, activation or strength of the same diameter muscle fibres10.

On the other hand, females may have more vital coordination skills and more elastic connective tissue and tend to use fat more efficiently during aerobic exercise. It is well known that males have more prominent upper-body musculature and strength than females, whereas females have more body fat and lesser aerobic capacity. However, in world-class XC skiers, neither oxygen (O2) debt nor gross efficiency varies between the sexes12,13. However, no published data demonstrates gender disparities among elite XC skiers and biathletes. Therefore, comparing these athletes’ anthropometric, physiological, and training regimens is required to understand better the reported disparities in skiing speed between XC skiers and biathletes while considering gender. To prescribe an efficient endurance athlete’s training program and track their progress, the ventilatory threshold and respiratory compensation point have been frequently employed to establish three training intensities4. Ventilatory threshold (VT) can be calculated using non-invasive gas exchange measures during incremental exercise as an alternative to measurements of the blood lactate concentration14. Due to the bicarbonate buffering of hydrogen ions (H+) in response to the systemic increase in blood lactate above resting values, power or VO2 at VT correlates with the nonlinear increase in carbon dioxide (CO2) generation and ventilation15. During an incremental exercise test, the minute ventilation (VE), CO2 production (VCO2) and VO2 all increase linearly as the exercise intensity rises until lactic acidosis sets in15. VCO2 rises faster than VO2 at exercise intensities above AT because non-metabolic VCO2 from buffering lactic acid with bicarbonate is added to the metabolic VCO2. Bicarbonate causes a drop in blood pH and stimulates the carotid bodies to augment the ventilatory drive, which causes hyperventilation when H+ cannot be replaced by circulation15. As a result, VE initially rises proportionately to VCO2 rise, but as exercise intensity increases above AT, it grows faster than VCO2. The respiratory compensation point (RCP) is the term used to describe this increased ventilatory reaction. The isocapnic buffering phase (ICB) between AT and RCP compensates for exercise-induced metabolic acidosis16.

The hypocapnic hyperventilation phase (HHV) is the period from RCP through the end of the exercise17. The duration of the ICB during an incremental exercise test is likely influenced by several physiological and biochemical factors, including the ratio of fast and slow-twitch muscle fibers, the oxidative capacities of fast-twitch muscle fibers, the activity of anaerobic glycolysis enzymes, hypertrophy of muscle fibers, muscle capillarization, and the power of monocarboxylate transporters such as MCT1 and MCT417,18. Although buffering capacity may affect the ICB, its contribution to the variance of this indicator is minimal, potentially accounting for only 5–10%. The ICB phase is a useful index for evaluating athletes’ aerobic capabilities. While it does not directly enhance aerobic capacity, it provides insights into the buffering capacity and tolerance to high-intensity exercise, which are critical components of overall aerobic performance In addition, it was hypothesised that the ICB helps athletes’ aerobic capability19, whereas another research reported that ICB is unrelated to endurance performance20. Recently, it was demonstrated that athletes’ anaerobic and aerobic capacities might be predicted using the relative ICB18. The non-invasive assessment of the buffering capacity may benefit from knowledge gained through observing the ICB during incremental exercise testing, as this phase reflects critical physiological responses to increasing exercise intensity. The ICB, which spans from the VT to the RCP, indicates the body’s ability to buffer lactate produced during high-intensity exercise. This buffering capacity is essential for sustaining performance in endurance sports. Studies have shown that athletes with a higher ICB tend to have better aerobic and anaerobic capacities, suggesting that observing the ICB can provide valuable insights into an athlete’s overall metabolic adaptations and endurance capabilities17. Furthermore, non-invasive measurements during the ICB phase allow for continuous monitoring without the need for invasive blood sampling, making it a practical and effective method for assessing and optimizing training programs. A few studies compared the ICB of athletes who trained aerobically with those who trained anaerobically and discovered that anaerobic-trained athletes experienced higher lactate rises during the ICB than endurance-trained competitors18,21.

Numerous incremental exercise methods, including measuring AT and VO2max, have been used to assess exercise capacity. These procedures have varied, particularly regarding the length and strength of step increments. Nowadays, the most common method for determining AT and VO2max is a ramp exercise test on a cycle ergometer. However, in trained runners, cycle ergometry has significantly underestimated VO2max compared with moderately fit and active non-athletes22. There is limited research on the ICB of athletes with aerobic and anaerobic training. The athletes’ ICB measurements can be used to assess the physiological demands of their sport and understand the physiological changes induced by exercise, which may contribute to the explanation of gender differences in training adaptation. Therefore, this study compares the isocapnic buffering, hypocapnic hyperventilation, ventilatory threshold and VO2max in junior biathlon and cross-country ski male and female athletes during an incremental exercise test.

Methods

Participants

37 male and 33 female Turkish National Team athletes, including 17 female and 19 male cross-country skiers and 16 female and 18 male biathlon athletes, volunteered to participate in the study. Characteristics of athletes are presented in Table 1. The inclusion criteria for the study group were to have participated in competitions in national team classes in international tournaments and have not been injured in the past year. The study was approved by the Gazi University Faculty of Medicine Ethics Committee (E-77082166-604.01.02-538554) following the latest declarations of Helsinki. All testing procedures were thoroughly explained and written informed consent was obtained from each subject. This study was conducted at the Olympic Preparation Centre, the largest rehabilitation and performance measurement center in Turkey, located in Ankara and operated under the Ministry of Youth and Sports of the Republic of Turkey. The center offers state-of-the-art facilities designed to optimize athlete performance.

Table 1 Characteristics of the biathletes and XC skiers (mean ± standard deviation).
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Bioelectrical impedance analysis (BIA)

The athletes’ body fat percentage, lean mass and fat mass values were measured using the bioelectrical impedance analysis method (MC 980, 1000 kHz, Tanita Corporation, Tokyo, Japan) after 12 h of fasting. With the help of hand and foot electrodes in the device, the electric current passing through the body provides a comprehensive body analysis.

VO2max test

Oxygen consumption was measured with a portable cardiopulmonary exercise test K5 system (Cosmed, Rome, Italy), capable of automatic gas analysis from each expiratory air, with a ramp protocol23 performed on a treadmill. Before each test, the portable metabolic gas analyser was calibrated using a sample of recognised gases (5.0% CO2 and 16.0% O2). To eliminate the adverse effects of room conditions on performance and VO2 data during the tests carried out in the laboratory environment, the temperature was kept at 18–23 °C and the relative humidity below 70% with air conditioners24. Participants warmed up at 8 km·h− 1 for 4 min. Then, the running speed progressively increased by 1 km·h− 1·min− 1 until volitional exhaustion. The breath-by-breath VO2 was smoothed using a five-step average filter, then decreased to 5 s stationary averages for the incremental test to reduce noise in the data and improve the underlying features. The most excellent 15-second VO2 value obtained during the incremental test was considered as VO2max. The achievement of VO2max needed to be confirmed as the plateauing of VO2 (< 2.1 ml·kg− 1·min− 1 decrease) despite an increase in workload, a plateau in VO2 despite the increasing speed and a respiratory exchange ratio (VCO2/VO2) above 1.1025. The duration of the run from the beginning to the point of exhaustion, or “time to exhaustion”, was recorded (i.e., the time at which the subject could no longer maintain the treadmill’s pace). Regarding the data obtained from the VO2max test, absolute (Abs) VO2max is simply the amount of O2 breathed in litres per minute. Relative (Rel) VO2max measures O2 consumption in millilitres per minute per kilogram of body mass. In accordance with standard practices in physiological studies and to ensure that the regression analysis accurately reflects steady-state exercise conditions, the initial 5–6 min of data, corresponding to the warm-up phase, were excluded from the analysis. This exclusion is essential for maintaining the reliability and validity of VO2max measurements by minimizing the confounding effects of initial physiological fluctuations25.

Determination of the ventilatory threshold and respiratory compensation point

The V-slope approach by Beaver et al.14 was used to calculate VT and RCP. The VO2 value that falls within the intersection of two linear regression lines that were independently constructed from the data points below and above the breakpoint in the VCO2 versus VO2 and the VE versus the VCO2 relationships, respectively, was identified as VT and RCP (Fig. 1). Additionally, the following visual identification method was utilised to improve the precision of the identification of VT and RCP. RCP corresponded to an increase in the VE/VCO2 and a drop in the end-tidal CO2 pressure. In contrast, VT was established using the criteria of an increase in the VE/VO2 with no rise in the VE/VCO2 and an increase in the end-tidal O2 pressure with no decrease in the end-tidal CO2 pressure. Two researchers analysed the data to diminish the variability of VT and RCP identification. In a disagreement, a third investigator’s opinion was sought. Running speed (km·h− 1), VO2 (ml·kg− 1·min− 1) and VO2 as a percentage of VO2max (%VO2max) were all measured at VT and RCP. Figure 1 presents the phases of VT, ICP, and HHV26.

Fig. 1
figure 1

Determination of VT and RCP phases in one subject.

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Determination of the isocapnic buffering and hypocapnic hyperventilation phases

The ICB phase was calculated as the difference in VO2 between the RCP and VT and was expressed in either absolute or relative values (expressed as a percentage of the RCP previously described by Röcker et al.)27. The HHV phase was calculated as the difference in VO2 between the end of exercise and the RCP and was expressed in either absolute or relative values (expressed as a percentage of VO2max)23. The calculation methods for the ICB and HHV phases are presented below:

ICB;

Abs VO2 : RCP-VT.

Rel VO2 : (RCP-VT) ÷ RCP × 100.

HHV;

Abs VO2 : VO2max - RCP.

Rel VO2 : (VO2max -RCP) ÷ VO2max × 100.

Statistical analysis

Data are reported as the means ± standard deviation. Statistical analyses were performed using the SPSS software (IBM SPSS Statistics, Version 21.0, Chicago, USA; https://www.ibm.com/support/pages/spss-statistics-210-available-download). The normality of the data was examined by performing the Shapiro-Wilk test on all measured variables. The two groups made comparisons using independent t-tests or the Mann-Whitney U test according to the distribution. Simple linear regression analysis was used to determine the success of the prediction. Effect sizes were also calculated using Cohen’s d to allow a better interpretation of the results. Effect sizes were interpreted as negligible (d ≤ 0.2), small (0.2 < d ≤ 0.5), medium (0.5 < d ≤ 0.8) or large (0.8 > d). Linear regression analyses were performed using the Sigma Plot program (SigmaPlot, Version 12.0, Systat Software, Chicago, USA; https://grafiti.com). Statistical significance was accepted at p < 0.05. The mixed 2 × 2 (category) analysis of variance (ANOVA) with repeated measures was used to compare variables related to different genders and categories. Partial eta squared values (ηp2) were calculated for the effect size in the ANOVA, and effect sizes were classified as small (ηp2 ≤ 0.01), medium (ηp2 ≤ 0.06) and large (ηp2 ≤ 0.14).

Results

Regarding body composition, no significant differences were recorded between male and female athletes (Table 1, p > 0.05).

Ventilatory threshold point

For VO2, the gender effect (F(1;38) = 55.247, p = 0.000, ƞ²=0.456) and gender×category interaction (F(1;38) = 11.077, p = 0.001, ƞ²=0.144) were significant, whereas category effect was not significant (Table 2, p > 0.05).

By %VO2max, the gender (F(1;38) = 7.385, p = 0.008, ƞ²=0.101) and category effects (F(1;38) = 8.589, p = 0.005, ƞ²=0.115) and gender×category interaction (F(1;38) = 55.247, p = 0.011, ƞ²=0.094) were significant.

Based on speed, the gender effect (F(1;38) = 57.998, p = 0.000, ƞ²=0.468) was significant, whereas category effect and gender×category interaction were not significant (p > 0.05).

According to heart rate (bpm), the gender effect (F(1;38) = 6.677, p = 0.012, ƞ²=0.093) and gender×category interaction (F(1;38) = 9.297, p = 0.003, ƞ²=0.125) were significant, whereas category effect was not significant (p > 0.05).

Table 2 Physiological variables corresponding to the ventilator threshold, respiratory compensation point, maximal values, isocapnic buffering and hypocapnic hyperventilation phases of the men and women biathletes and XC skiers.
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Respiratory compensation point

For VO2, the gender effect (F(1;38) = 98.694, p = 0.000, ƞ²=0.599) and gender×category interaction (F(1;38) = 7.362, p = 0.008, ƞ²=0.100) were significant, whereas category effect was not significant (p > 0.05).

By %VO2max, gender×category interaction (F(1;38) = 10.391, p = 0.002, ƞ²=0.136) was significant, whereas category and gender effects were no significant (p > 0.05).

Based on speed, the gender effect (F(1;38) = 96.381, p = 0.000, ƞ²=0.594) was significant, whereas category effect and gender×category interaction were not significant (p > 0.05).

According to heart rate, gender×category interaction (F(1;38) = 13.065, p = 0.001, ƞ²=0.165) was significant, whereas gender and category effects were not significant (p > 0.05).

Maximum oxygen uptake phase

For VO2max, the gender effect (F(1;38) = 91.584, p = 0.000, ƞ²=0.581) was significant, whereas category effect and gender×category interaction were not significant (p > 0.05).

Based on the time of exhaustion, the gender (F(1;38) = 58.744, p = 0.000, ƞ²=0.471) and category effects (F(1;38) = 7.566, p = 0.008, ƞ²=0.103) were significant, whereas gender×category interaction was not significant (p > 0.05).

Based on RQ, the gender and category effects and gender×category interaction were not significant (p > 0.05).

Based on max speed, the gender effect (F(1;38) = 149.065, p = 0.000, ƞ²=0.693) was significant, whereas category effect and gender×category interaction were no significant (p > 0.05).

According to max heart rate, gender×category (F(1;38) = 12.824, p = 0.001, ƞ²=0.163) interaction was significant, whereas gender and category effects were no significant (p > 0.05).

Isocapnic buffering phase

Based on Abs VO2, the gender (F(1;38) = 31.479, p = 0.000, ƞ²=0.323) and category effects (F(1;38) = 19.668, p = 0.000, ƞ²=0.230) were significant, whereas gender×category interaction was not significant (p > 0.05).

Based on Rel VO2, the gender (F(1;38) = 7.111, p = 0.010, ƞ²=0.097) and category effectd (F(1;38) = 15.862, p = 0.000, ƞ²=0.194) and gender×category interaction (F(1;38) = 4.332, p = 0.042, ƞ²=0.061) were significant.

Hypocapnic hyperventilation phase

Based on Abs VO2, gender×category interaction (F(1;38) = 8.498, p = 0.005, ƞ²=0.114) was significant, whereas gender and category effects were no significant (p > 0.05).

Based on Rel VO2, gender×category interaction (F(1;38) = 10.806, p = 0.002, ƞ²=0.141) was significant, whereas gender and category effects were no significant (p > 0.05).

Discussion

This study examined the aerobic capacity indices, such as the ICB, HHV phase, VT, RCP, and VO2max, among junior biathlon and cross-country ski athletes during an incremental exercise test. The results of this study indicated that males and females in both groups had similar body composition analyses. In VT, RCP and VO2max phases, male athletes had higher VO2 and speed values than female athletes, whereas they had similar values by category. In addition, XC skiers and males had higher Abs VO2 and Rel VO2 values than biathletes and females in exhaustion times and ICBs, whereas they had similar Abs VO2 and Rel VO2 values in HHV.

VO2max and VT are the essential physiological variables to evaluate athletes’ aerobic endurance28. Therefore, cross-country skiers are expected to have high VT and VO2max. Different physiological adaptations develop in the body depending on the intensity and duration of the training29. Cross-country skiers typically practice most of their training sessions at intensities below the VT30. According to some theories, lower-intensity exercise at levels just below AT primarily causes central adaptations, which raise AT and enhance physiological functions such as pulmonary diffusion, haemoglobin affinity and cardiac output29. The genetic makeup of this group could be another reason for the increased VT values of XC skiers compared with biathletes. The proportion of slow-twitch muscle fibres and the muscle fibres’ ability to breathe may be critical factors in determining the relative VT31. According to Ivy et al.31, there is a direct link between the percentage of slow-twitch muscle fibres, the muscle’s respiratory capacity and LT values31. Interestingly, VO2max values did not differ between XC skiers and biathletes. It was unexpected because a previous study found that XC skiers’ VO2max values were significantly greater than biathletes32. The fact that biathletes had the same volume33 but a higher ratio of high-intensity training in the total endurance training volume may help explain this part. However, XC skiers had better cardiovascular capacity (i.e., cardiac output index and threshold oxygen pulses), likely due to increased low-intensity training and moderate-intensity training volumes.

Previous studies have compared ICB between aerobic- and anaerobic-trained athletes. These studies showed a higher relative ICB in anaerobic-trained athletes than endurance-trained athletes1,12,18. Unlike previous studies, the present study compared male and female athletes with high aerobic endurance values in two branches. Chicharro et al.17 reported that rigorous anaerobic-based training sessions increase buffering capacity, which causes RCP to shift towards higher intensities and lengthen ICB. Conversely, aerobic-based training sessions may cause a similar change in both VT and RCP17. According to these findings, RCP appears more affected by high-intensity training sessions than AT. As a result of training athletes in both groups, there were no appreciable variations in relative RCP values between the biathletes and XC skiers in our study. For their lower relative VT, team sport athletes may have a more significant ICB than other athletes1. Increased buffer capacity in anaerobic-trained athletes may improve their ability to operate in anaerobic conditions34. Previous studies have indicated that training intensity can differ between genders, even when the overall training volume is similar. For instance, Laaksonen et al. (2018) found that biathletes and XC skiers may prioritize different training intensities based on their specific physiological demands35. Additionally, the tendency for females to engage in lower intensity training could be due to different physiological and metabolic adaptations that influence their endurance and strength training processes. More research is needed to explore these differences in greater detail and their implications on performance.

Some researchers suggested that ICB helps athletes’ aerobic capability19. Previous research showed that athletes’ VO2max and ICBs correlate19,36. On the other hand, another study suggested that ICB is unrelated to endurance athletes’ performance20. Even though the endurance athletes’ VO2max was higher in this study, ICB was higher in team sport participants. Oshima et al.19 demonstrated that ICB had a stronger correlation with VO2max than AT in athletes. Differences in the physiology and movement abilities of females would be partially impacted. As a result of specific metabolic adaptations developed with anaerobic training, buffer capacity may develop and exercise can be continued for a relatively more extended period after the respiratory threshold thanks to this improvement. The more extended ICB in anaerobically trained athletes may be essential in increasing tolerance to high-intensity exercise18.

Conclusions

The present study found that %VO2max values were significantly higher in cross-country skiers (XC skiers) compared to biathletes, whereas relative respiratory compensation point (RCP) values were similar between the two groups. Among female athletes, both XC skiers and biathletes exhibited similar values. These findings suggest that gender variations in athletic performance are predominantly influenced by genetic factors. The elevated ICB values observed in male XC skiers may indicate an enhanced buffering capacity, which could be attributed to their rigorous anaerobic training regimens. This training likely improves their ability to manage H+ ions, thereby allowing them to sustain higher intensities for longer durations. Although our study did not directly measure the impact of anaerobic training on buffering capacity, previous research has shown that such training can lead to significant physiological adaptations that enhance performance in high-intensity sports17. Additionally, the data suggests that male athletes and XC skiers generally exhibit higher VO2 and speed values across various physiological phases, highlighting the impact of gender and sport-specific training on these physiological variables.