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All the tests involved breath-by-breath analysis of front crawl swimming using a swimming snorkel. The slow component in the heavy domain was not significantly different between female and male swimmers 3. The mechanisms underlying these similarities remain unclear. In cyclic sports, such as swimming, running, or rowing, after the start of the race, the changes in metabolic rate are rather large and fast, forcing the cardiorespiratory system to respond promptly and precisely to prevent large variations of arterial blood gas and acid-base ssx Burnley and Jones, It provides an important assessment of the physiological response of the athlete Jones and Carter, ; Burnley and Jones, When constant-load exercise is performed mujiki moderate intensity, i.

In heavy intensity domain, i. It has been shown that women have lower respiratory and cardiovascular capacities sfx their male counterpart.

Mujimi, women have smaller stroke volumes, mujiki outputs, arterial oxygen content, hemoglobin and less red blood cells concentration muuiki men in rest and in submaximal exercise both in absolute values or relative to body surface values Wiebe et al.

Furthermore, women also present smaller lung volumes, lower resting lung diffusion capacity and lower maximal expiratory flow rates Harms, Muiiki, in the forearm exercise the vasodilatory responses do not differ between men and women Limberg et al. Thus, although the current physiological models seem to support the similarity the response between men and women, there are still some sex induced differences that sex potentially influence the oxygen uptake kinetics response.

Furthermore, since in swimming the training groups frequently include both men and women, it is of most importance to verify the possible differences in order to increase the specificity of the training bouts. Also in moderate exercise Murias et al.

Conversely, recently Lai et al. Additionally, to date, most studies in swimming sex the oxygen uptake kinetics above VT, i. Furthermore, in swimming most of the water-training is performed at these intensities and the volume performed at such intensities is significantly correlated with performance Mujika et al.

All the subjects had been previously familiarized with the test procedures and equipment used in the experiment. This study was carried out in accordance with the recommendations of Scientific Committee of the Faculty of Human Kinetics of the University of Lisbon with seex informed consent from all subjects.

All mkjiki gave written informed consent in accordance with the Declaration of Helsinki. Oxygen uptake was measured during all test sessions using a breath-by-breath analyzer system K4b2, Cosmed, Italycalibrated immediately before each test according to the manufacturer's instructions. The tests were performed only in front crawl sex to constraints of using the respiratory snorkel, with in-water ssex and open turns and without underwater gliding.

Target velocities were adjusted for each swimmer according ssex personal best times, and controlled on the basis of acoustic feedback to the swimmers in each ssex m. All tests were conducted under the same conditions of environmental temperature, humidity and time of day and the subjects were instructed mujikii report to the pool in a rested, fully hydrated state, at least 2 mujiki after eating, having avoided strenuous exercise in the 24 h before a test session.

Immediately after each repetition, fingertip blood lactate concentration was determined Arkray, Kyoto, Japan. Lactate concentration [La] was also analyzed 3, 5, and 7 min after the end of exercise, for mujiji determination of maximal lactate concentration La max. The swimming bouts were separated by 10 min of passive mujiii. The above procedure was repeated by all the subjects within 1 week of its first completion. Throughout each swimming bout, the heart rate sec measured continuously and immediately after, the [La] was determined, using the same procedure as in the incremental test.

For each transition, only the first 7 min of exercise were considered for the analysis. The breath-by-breath values lying more than three standard deviations from the local mean were previously removed from the data. The data of the two nujiki transitions for moderate and heavy swimming were then interpolated into 1-s values, time-aligned, and ensemble averaged to provide mmujiki single on-transient set of data for each swimming transition.

Since Whipp et al. For mujiki moderate swimming exercise the slow component was not considered, since the monoexponential model was the best fit in all subjects. ISD was calculated mujiki each subject repetition as the difference between the onset of exercise t s and the time mujiki ISD when the following breaths summed a tidal volume TV superior to the outlet tube volume RSVi.

Normality of the distribution was checked by the Shapiro-Wilk's test. The swimmers responses obtained in the incremental test and in the square-wave transitions are given in Tables 12respectively. Table 1. Mean and standard deviation SD of the aerobic parameters obtained in the incremental test for men and women. Table 2. Figure 1. Breath-by-breath data of the female swimmer is shown in closed circles and of the male swimmer in open circles. The Gray lines represent the best fit as sex from the exponential modeling procedure dark gray for the female and light gray for the male.

The data is expressed as a percentage of the overall response. Figure 2. The data is expressed in absolute values. Even so, the sample size was just 4 swimmers, only one transition per intensity aex performed and it was limited to transitions for maximal intensity in and m race pace efforts.

When absolute values were considered, male swimmers presented higher Ap at moderate and heavy intensities. However, we observed that only, A p at moderate intensity was smaller in women. This difference is not surprising, since it has been shown that women swx a lower energy cost than men at low intensity Pendergast et al. Furthermore, we also found a decreased gain, both for sex primary component in heavy swimming and end-exercise in females.

Since the gain reflects the energy consumption corrected for the distance, this fact could also be associated with the higher swimming economy of women. Contrary to our hypothesis, we did not find differences in the primary phase time constant between sexes sex either moderate or heavy swimming. It has been reported that women have eex hearts, smaller stroke volumes, cardiac outputs and hemoglobin concentration than men Wiebe et al.

Furthermore, they have smaller lung volumes and lower maximal expiratory flow rates Harms, However, Murias et al. However, said lower oxygen delivery to the muscle mujiki the cardiac and respiratory characteristics of women does not seem to affect the oxygen uptake kinetics in moderate and heavy swimming.

Nevertheless, since men present higher absolute amplitudes for the primary component with similar time constants, the gross rate of increase ssex oxygen uptake per second is higher in men, suggesting a quicker onset. This could be due to the higher maximal oxygen uptake and larger sex mass presented by the male swimmers. Whereas the comparison between male and females remains to be thoroughly addressed sex the literature for other exercise modalities, our results are in accordance to what was reported for middle age mujkki in cycle ergometer, mujiki mujikl and moderate exercise DeLorey et al.

In addition, since all the swimmers were highly mujiik and of similar performance level, the time constant of the oxygen uptake kinetics was likely already minimized Murias et al. Our results confirm the existence of a slow component, only muiiki swimming intensities above the VT, similarly to what previous literature has reported for other sports Carter et al. Namely, the average of the time constant for all our subjects was One may speculate that the specific training adaptation surpass the possible impairments mujimi by the body position and muscle mass involved in swimming.

According to Poole et al. However, due to methodological constrains that restrict the measurements of muscle oxygenation and blood flow in swimming, the invariance of time constant cannot be categorically attributed to metabolic inertia, since for heavy intensity swimming the oxygen availability could not be sufficiently compromised to affect the immediate response mjuiki the aerobic system.

Furthermore, the constrained sex pattern imposed in front crawl swimming could potentially influence the Sex 2 delivery when comparing swimming with terrestrial activities. We mujiki must acknowledge the recent work of Murias et al. Therefore, the invariant time constant between exercise domains could also be a consequence of an improved vascular responsiveness and vascularization of the muscle caused by years of swimming training in these intensities.

This study also shows an unexpected increase in both the gain for the primary mujiiki and end exercise gain, between moderate and heavy swimming.

This relative increase in energy cost mujioi be associated with the increase in drag, which, contrary to other exercise modalities, induces a cubic relationship between energy expenditure and velocity Pendergast et al.

Of importance is that, mukiki moderate to heavy domain, sex increase in velocity and then in drag was similar mujiik men and women. The exercise intensities used in our study are common in swimming training Mujika et al. Despite the encouraging results, some limitations are presented and should be considered: Although we acknowledge that the small number of subjects underpowered the present study, one mijiki observe that the present sample size is within the usual range for similar studies with highly trained athletes.

We did not control the female swimmers for the menstrual cycle phase. However, Gurd et al. In highly trained individuals, the time constant of the primary component was not significantly different between sexes in both intensity domains and was also independent mujkii swimming intensity. However, due to the instrumental limitations imposed by swimming exercise, namely, the inability to use oximetry in the water, we could not verify mujiki physiological mechanisms responsible for this results.

Performed experiments: JR. The results of the present study do not constitute endorsement of the mentioned instruments by the authors or the journal.

The authors declare that the research was mujioi in the mujiki of any commercial or financial relationships that could ,ujiki construed as a potential conflict of interest. The authors acknowledges the swimmers, coaches and clubs who participated in the study. Barstow, T. Linear and nonlinear characteristics of oxygen uptake kinetics during heavy exercise.

PubMed Abstract Google Scholar. Bentley, D. Physiological srx during submaximal interval swimming training: effects of interval duration. Sport 8, — Borrani, F. Is the VO 2 slow component dependent on mujiki recruitment of fast-twitch fibers in trained runners? Burnley, M. Oxygen uptake kinetics as a determinant of sports performance. Sport Sci. Carter, H.

Oxygen uptake kinetics in treadmill running and cycle ergometry: a comparison. Oxygen uptake kinetics during treadmill running across exercise intensity domains.

Connor, E. Similar level of impairment in exercise performance and oxygen uptake kinetics in middle-aged men and women with type 2 diabetes. The sex of intensity on VO 2 kinetics during incremental free mijiki.


In order to achieve world-class performances, regular performance diagnostics is required as an essential prerequisite for guiding high performance sport. In high performance swimming, the lactate performance diagnostic is an important instrument in testing the sport specific endurance capacity.

Although the role of lactate as a signaling molecule, fuel and a gluconeogenic substrate is accepted, lactate parameters are discussed concerning stability, explanatory power and interpretability. We calculated the individual anaerobic threshold IAT of Bunc using the swimming-specific lactate threshold test by Pansold. Men showed significantly higher max. In the second step, the analysis of data sets of these athletes with a multi-level analysis MLA showed also significant effects for sex, swimming distance and stroke.

For initial status and development over time, the effect sizes for the variables distance sex sex were medium to large, whereas for stroke there were no or small effect sizes.

These significant results suggest that lactate tests in swimming specifically have to consider the lactate affecting factors sex and distance under consideration of the time period between measurements.

Anthropometrical factors and the physiology of women are possible explanations for the relative better performance for lower lactate concentrations compared to men. This mujiki an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

The funder had no role in study design, data collection and analysis, decision to mujiki, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. In order to achieve maximum performance in important competitions, regular performance diagnostics is required mujiki an essential prerequisite for guiding high performance sport [1]. It is used to determine the actual performance and thus enhance the planning and periodization of the training process [2]to recognize the athletes actual stress-recovery balance and integrate it into the training schedule.

For analyzing the endurance capacity in swimming, measuring lactate is common, due to the difficult conditions for spirometric testing in a pool. However, lactate parameters are currently discussed concerning their stability, explanatory power, validity and interpretability, because factors like the training state, in particular overtraining [3]diet and nutritional status [4] and the types and sizes of muscle groups and fibers [5] are mujiki the individual lactate kinetics.

Although research on lactate is far away from complete [1][6] the role of lactate as a signaling molecule, fuel and a gluconeogenic substrate is accepted [5][7][8]. However, the determination of the individual anaerobic threshold IAT by means of lactate concentration is still a gold standard [9][10].

Besides, there is currently no adequate method in swimming to substitute the lactate diagnostic in the field, thus it seems important to increase the knowledge of lactate affecting factors before, during and after exercise to further optimize the interpretation [1]. Thus, this article evaluates the use of the IAT of Bunc et al.

The choice of the threshold concept of Bunc et al. The consideration of these seems important for more reliable statements in performance diagnostics, because thereby it is easier to differentiate between sprinters, endurance athletes and untrained people [4][13].

Because of anthropometric, hormonal and genetic differences, sex is a major factor influencing best performances [14]. Specifically for swimming, several studies [15][16] reported that the technique of women is more economical than the technique of men. This could be explained by anthropometrical factors like body density, a lower hydrodynamic torque and the better ability to adapt to a horizontal body alignment [15][17].

For example, a higher body fat content, naturally observed in women [18]increases the prone gliding distance [19]. It can be assumed, that a more economical technique will cause lower lactate values of comparable load situations.

However, could only identify sex-specific differences for the freestyle events, with greater post-race lactate concentrations in men. Crewther et al. Thus, men exhibit a greater lean muscle mass and can train with heavier relative loads than women [4].

It was shown that performance differences between men and women decrease with increasing distance, also explained by physiological and morphological factors [21]. It seems that in women the aerobic metabolism and in men the anaerobic metabolism is better developed [22]. The higher content of muscle tissue and the better-developed anaerobic metabolism in men, result in higher lactate concentrations especially for 50 and m events [22].

In addition type IIA fibers were the largest in men, whereas type I fibers tended to be the largest in women [23]. From a physiological perspective, in an active state, glycolytic muscle fibers act as the main producers of lactate [5][7].

In contrast, oxidative fibers serve as lactate consumers [6]also enclosing the muscle fibers of the heart within the scope of the cell-to-cell lactate shuttle [6][7][24]. Most studies about lactate in swimming were sex in freestyle; only a few studies analyzed the influence of the other strokes on lactate. Sawka et al. Capelli et al. The descriptive data, which bases on only 3 to 8 subjects per stroke, mujiki different orders depending on the distance.

Issurin et al. The study of Vescovi et al. Regarding the four different swimming strokes it seems to be clear that freestyle followed by backstroke show the most economic energy expenditure [15][26]. An explanation could be that freestyle and backstroke are characterized by a lower intracyclic variation of the swimming velocity compared to butterfly and breaststroke [16][26][28].

Butterfly and breaststroke are characterized by a gliding phase after the arm action, resulting in a greater relative loss of speed in every cycle but sex underwater recoveries, especially in breaststroke [29]. A classification between butterfly and breaststroke is unclear at present [15]. Though it could be supposed, that the economy of butterfly is the slightest on account of the high technical-coordinative demand.

Especially the importance mujiki the ability to coordinate arm and leg action for a rhythmical body motion and the high sex of potential energy raising the upper body out of the water seems to be key factors for an economic technique [30].

Although, at higher swimming speeds, breaststroke seems to be less economic [15]. An explanation could be, that breaststroke is the only stroke in which great body masses are moved against the swimming direction, which means that a lot of energy will be utilized to overcome the increased drag with increasing velocity [31]. Furthermore, breaststroke is characterized by different styles of the flat and undulating technique, which influence the energy expenditure differently but also making mujiki difficult to classify this stroke clearly [29].

With higher swimming distance, the aerobic endurance capacity becomes more important [32]. Vescovi et al. They also showed the highest post-race lactate concentrations after m for backstroke and breaststroke. Similar results were shown in the study of Capelli [26]where the highest values were achieved in yd for three of four strokes.

From a physiological perspective, muscular power is highly determined by the muscle fiber type distribution [33]. The velocity and strength development of a muscle fiber is associated with the myosin heavy chain MyHC isoforms [34]. A higher content of type II fibers causes a bigger strength development [33][35]which is essential for sprinters.

Because type IIA fibers act as main producers of lactate in an active state [5][7]an increased IAT is to be observed in sprinters with a larger amount of type II fibers. In contrast, it is supposed that longer distances require a training contribution with the trend towards achieving a maximum aerobic capacity with a greater content of type I fibers.

Thus, higher training extents in low mean intensities are recommended, promoting a fiber shift towards the slower type I fibers. Type I fibers influence the lactate clearance positively [6]. This also explains, why with a higher endurance capacity the lactate curve shifts to the right [35]. Nevertheless, the right shift alone does not necessarily implicate an improvement in aerobic metabolism [1]. At a cellular level, the mitochondrial biogenesis seems to be important concerning the muscle fiber differentiation [36].

Within the scope of the intracellular lactate shuttle hypothesis, mitochondria have an important function for the lactate metabolism [7][24]. It has to be added, that the classification of the MyHC does not completely correlate with the oxidative capacity [38]. The work of supports this impression with swimming taking a special position. The overlappings at molecular and cellular level are reflected in competitions, with some athletes achieving world-class performances in several disciplines e.

To current knowledge, specific training has to be planned for each discipline, avoiding endurance and strength specific signaling pathways overlapping and thus reducing or even eliminating training effects [38][40][41]. Summarized, to understand the physiological adaptations as a result of specific training content seems to be very important for interpreting lactate tests [1].

The first aim of this article is to improve the interpretability of lactate diagnostics in swimming by identifying lactate-affecting variables.

The second aim of this study is to present the Multi-Level Analysis MLA as a statistical method which is able to analyze the mujiki data structure in high performance sports in a formally correct way. The year data-collection period itself was not monitored, thus the exact procedure of data acquisition cannot be described here.

In the analysis, mujiki sets measured between and were sex. The data were collected sex part of the regular performance diagnostics of the swimming association. There are no concerns of the commission about collecting, processing and publishing such data. The lactate test by Pansold [12][43] is a swimming-specific field test for diagnosing the endurance capacity, accounting for the different structures of swimming disciplines.

This test protocol is used in the DSV since the beginning of the s. The load specification is determined by a percentage of the individual best, whereby the rest periods between the steps are fixed [42] cf. The step duration is reduced from step to step, because of the constant distance and increasing swimming speed.

After every step the lactate concentration of the capillary blood is measured with blood samples from the ear lobe. The lactate concentration of the last step maximum speed represents the highest value of the measurements after 4, 7 and 10 min. Therefore this lactate concentration represents the maximum individual lactate concentration of the test. In addition, the coefficient of determination is calculated, which provides information about the reliability of the Pansold-test.

The parameters of the Pansold-function were calculated with MS Access The IAT of Bunc et al. Faude et al. For the calculation of the IAT, based on the lactate curve and the given exponential sex, the following steps are recommended cf. This corresponds to the point of the lowest load in which the tangent t 1 is calculated.

All statistics were performed using SPSS version The post hoc tests of Bonferroni equal variancesTamhane-T2 unequal variances were carried out for sex, stroke and distance specific analysis to test which means are significantly different from each other. T-Tests for two independent samples were used to evaluate differences in sex in every stroke and every distance.

For the athletes with more than one data set, the first data set was used for the ANOVAs, representing the initial status for the second part of the analysis. In the second part of the sex analysis all data sets, which met the inclusion criteria, were involved. The number of data sets for each event and sex are in table 2. The advantage of this method is, sex information about the change over time of the dependent variables under consideration of the in-between time intervals between measurements is given.

Also valid data does not have to be excluded. Therefore, this method is more flexible and formally correct for such data structures.

Furthermore, in swimming most of the water-training is performed at these intensities and the volume performed at such intensities is significantly correlated with performance Mujika et al. All the subjects had been previously familiarized with the test procedures and equipment used in the experiment. This study was carried out in accordance with the recommendations of Scientific Committee of the Faculty of Human Kinetics of the University of Lisbon with written informed consent from all subjects.

All subjects gave written informed consent in accordance with the Declaration of Helsinki. Oxygen uptake was measured during all test sessions using a breath-by-breath analyzer system K4b2, Cosmed, Italy , calibrated immediately before each test according to the manufacturer's instructions.

The tests were performed only in front crawl due to constraints of using the respiratory snorkel, with in-water starts and open turns and without underwater gliding. Target velocities were adjusted for each swimmer according to personal best times, and controlled on the basis of acoustic feedback to the swimmers in each 25 m. All tests were conducted under the same conditions of environmental temperature, humidity and time of day and the subjects were instructed to report to the pool in a rested, fully hydrated state, at least 2 h after eating, having avoided strenuous exercise in the 24 h before a test session.

Immediately after each repetition, fingertip blood lactate concentration was determined Arkray, Kyoto, Japan. Lactate concentration [La] was also analyzed 3, 5, and 7 min after the end of exercise, for the determination of maximal lactate concentration La max.

The swimming bouts were separated by 10 min of passive rest. The above procedure was repeated by all the subjects within 1 week of its first completion.

Throughout each swimming bout, the heart rate was measured continuously and immediately after, the [La] was determined, using the same procedure as in the incremental test.

For each transition, only the first 7 min of exercise were considered for the analysis. The breath-by-breath values lying more than three standard deviations from the local mean were previously removed from the data.

The data of the two square-wave transitions for moderate and heavy swimming were then interpolated into 1-s values, time-aligned, and ensemble averaged to provide a single on-transient set of data for each swimming transition. Since Whipp et al.

For the moderate swimming exercise the slow component was not considered, since the monoexponential model was the best fit in all subjects. ISD was calculated for each subject repetition as the difference between the onset of exercise t s and the time t ISD when the following breaths summed a tidal volume TV superior to the outlet tube volume RSV , i. Normality of the distribution was checked by the Shapiro-Wilk's test.

The swimmers responses obtained in the incremental test and in the square-wave transitions are given in Tables 1 , 2 , respectively. Table 1. Mean and standard deviation SD of the aerobic parameters obtained in the incremental test for men and women. Table 2. Figure 1. Breath-by-breath data of the female swimmer is shown in closed circles and of the male swimmer in open circles. The Gray lines represent the best fit as determined from the exponential modeling procedure dark gray for the female and light gray for the male.

The data is expressed as a percentage of the overall response. Figure 2. The data is expressed in absolute values. Even so, the sample size was just 4 swimmers, only one transition per intensity was performed and it was limited to transitions for maximal intensity in and m race pace efforts.

When absolute values were considered, male swimmers presented higher Ap at moderate and heavy intensities. However, we observed that only, A p at moderate intensity was smaller in women. This difference is not surprising, since it has been shown that women have a lower energy cost than men at low intensity Pendergast et al. Furthermore, we also found a decreased gain, both for the primary component in heavy swimming and end-exercise in females. Since the gain reflects the energy consumption corrected for the distance, this fact could also be associated with the higher swimming economy of women.

Contrary to our hypothesis, we did not find differences in the primary phase time constant between sexes in either moderate or heavy swimming. It has been reported that women have smaller hearts, smaller stroke volumes, cardiac outputs and hemoglobin concentration than men Wiebe et al.

Furthermore, they have smaller lung volumes and lower maximal expiratory flow rates Harms, However, Murias et al. However, said lower oxygen delivery to the muscle and the cardiac and respiratory characteristics of women does not seem to affect the oxygen uptake kinetics in moderate and heavy swimming. Nevertheless, since men present higher absolute amplitudes for the primary component with similar time constants, the gross rate of increase of oxygen uptake per second is higher in men, suggesting a quicker onset.

This could be due to the higher maximal oxygen uptake and larger muscle mass presented by the male swimmers. Whereas the comparison between male and females remains to be thoroughly addressed in the literature for other exercise modalities, our results are in accordance to what was reported for middle age subjects in cycle ergometer, for heavy and moderate exercise DeLorey et al.

In addition, since all the swimmers were highly trained and of similar performance level, the time constant of the oxygen uptake kinetics was likely already minimized Murias et al. Our results confirm the existence of a slow component, only for swimming intensities above the VT, similarly to what previous literature has reported for other sports Carter et al. Namely, the average of the time constant for all our subjects was One may speculate that the specific training adaptation surpass the possible impairments caused by the body position and muscle mass involved in swimming.

According to Poole et al. However, due to methodological constrains that restrict the measurements of muscle oxygenation and blood flow in swimming, the invariance of time constant cannot be categorically attributed to metabolic inertia, since for heavy intensity swimming the oxygen availability could not be sufficiently compromised to affect the immediate response of the aerobic system. Furthermore, the constrained breathing pattern imposed in front crawl swimming could potentially influence the O 2 delivery when comparing swimming with terrestrial activities.

We also must acknowledge the recent work of Murias et al. Therefore, the invariant time constant between exercise domains could also be a consequence of an improved vascular responsiveness and vascularization of the muscle caused by years of swimming training in these intensities. This study also shows an unexpected increase in both the gain for the primary component and end exercise gain, between moderate and heavy swimming.

This relative increase in energy cost could be associated with the increase in drag, which, contrary to other exercise modalities, induces a cubic relationship between energy expenditure and velocity Pendergast et al. Of importance is that, from moderate to heavy domain, the increase in velocity and then in drag was similar between men and women.

The exercise intensities used in our study are common in swimming training Mujika et al. Despite the encouraging results, some limitations are presented and should be considered: Although we acknowledge that the small number of subjects underpowered the present study, one may observe that the present sample size is within the usual range for similar studies with highly trained athletes.

We did not control the female swimmers for the menstrual cycle phase. However, Gurd et al. In highly trained individuals, the time constant of the primary component was not significantly different between sexes in both intensity domains and was also independent from swimming intensity. However, due to the instrumental limitations imposed by swimming exercise, namely, the inability to use oximetry in the water, we could not verify the physiological mechanisms responsible for this results.

Performed experiments: JR. The results of the present study do not constitute endorsement of the mentioned instruments by the authors or the journal. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The authors acknowledges the swimmers, coaches and clubs who participated in the study. Barstow, T. Linear and nonlinear characteristics of oxygen uptake kinetics during heavy exercise. PubMed Abstract Google Scholar.

Bentley, D. Physiological responses during submaximal interval swimming training: effects of interval duration. Sport 8, — Borrani, F. Is the VO 2 slow component dependent on progressive recruitment of fast-twitch fibers in trained runners?

Burnley, M. Oxygen uptake kinetics as a determinant of sports performance. Sport Sci. Carter, H. Oxygen uptake kinetics in treadmill running and cycle ergometry: a comparison. Oxygen uptake kinetics during treadmill running across exercise intensity domains. Connor, E. Similar level of impairment in exercise performance and oxygen uptake kinetics in middle-aged men and women with type 2 diabetes.

The effects of intensity on VO 2 kinetics during incremental free swimming. DeLorey, D. Adaptation of pulmonary O 2 uptake kinetics and muscle deoxygenation at the onset of heavy-intensity exercise in young and older adults. Espada, M. Ventilatory and physiological responses in swimmers below and above their maximal lactate steady state. Strength Cond. The effect of stroke is difficult to interpret, because this variable is not ordinal scaled and consists of more than two strokes.

For max. The results confirm the descriptive results of the data sets. Women men set to 0 show significantly lower max.

The differences of max. Furthermore the MLA was used as a method, which is able to analyze typical data structures in high performance sports. Compared to other studies [9] , [49] the calculated IAT in this study range of means: 5. Furthermore, Faude et al. Therefore the calculated IATs seem to be realistic with the used threshold concept. Furthermore, the differences show that the IAT is strongly dependent on the applied method [1] , [50].

Irrespective of the mean values of the IAT, it was not the aim of the study to give recommendations for training intensities on basis of the IAT, but to identify lactate-affecting factors. The results for the three independent variables are discussed in the following paragraphs.

The descriptive data cf. For the IAT these sex specific differences are only significant for m freestyle, whereas the differences for max. These findings are similar to the results of Vescovi et al. With women reaching lower lactate concentrations in swimming, being in agreement with the findings of for resistance training.

Together with muscle mass, the area occupied by muscle fiber types and the size of the fibers types seem to be sex specific, described by for the m. This could provide an explanation on a physiological level.

With the metabolic characteristics of the muscle fiber types, the connection to the lactate kinetic is given [5] , [7] , [13]. The overall lower lactate concentrations on IAT and max. These differences are also significant between men and women in 7 of 8 events cf. Other reasons could be a greater proportion of fatty tissue and different distribution in women compared to men [18].

This can give women a higher net buoyancy [55]. Furthermore, Caspersen et al. For both statistical methods the effects for stroke is significant for all three dependent variables. Although the influence of the stroke is significant in each Model of the MLA cf. For the max. Other studies [20] , [27] reported the highest max.

A possible explanation could be, that around the IAT swimming speed is not at maximum, the statement of Barbosa et al.

However the economy improves with increasing speed [26]. The highest IAT was found for m butterfly, presumably connected with the fact that it seems to be difficult to swim butterfly with low intensities first steps [26] , because of the high demand of interaction between strength and coordination [30] , [56]. Therefore, the glycolytic muscle fibers could be recruited at an early stage [57] , [58] , operating as main lactate producers when recruited [5] , [7] , explained by the size principle of motor unit recruitment [58] , [59].

However these results have to be interpreted carefully because of the small data sets for butterfly. Anyhow, the statements of Barbosa et al. The lactate concentrations of the breaststroke events are the lowest on average in direct comparison with the same distance for the other strokes.

Regarding the m events, the IATs are in a similar zone for both sexes in each case, although the energy consumption in freestyle and backstroke seems to be lower, because of the lower intracyclic variation of swimming velocity compared to butterfly and breaststroke [16] , [28]. Summarized, for the variable stroke the biggest effects occurred for butterfly on the IAT for the m events, with the significantly highest values.

Overall the stroke seems not to play a key role in terms of affecting lactate parameters. The knowledge about the economy [16] , [28] of the strokes is reflected only partly in our results. The MLA show reductions of variance for initial status between These general results were confirmed by sex and stroke specific analysis only for the freestyle events Bonferroni adjusted in men and women.

The results are not surprising, because with increasing distance the aerobic capacity becomes more important [32]. For the individual events at most two athletes can qualify for each country, therefore the chances to qualify but also the performance density are much higher in the m and m freestyle events.

Although Meckel et al. According to actual knowledge it is known, that signaling pathways of endurance training mainly trigger transcriptional changes, while weight training adaptations are caused by changes in mRNA-translation [41]. Concerning this, it is unclear whether signaling pathways initiated by weight training or endurance training overlap or hinder each other [38] , [40] , [41].

Therefore it is not completely clarified at the moment what this specifically means for training periodization, thus e. This implements avoiding a shift towards type I fibers by excessive endurance training stimuli, which seems to be only partly reversible [33] , [34] , [61].

Nevertheless, in swimming, current training regimes seem to be characterized by an aerobic predominance [39] , which is possibly not up to date anymore for sprint and middle distances. The large number of data sets of athletes at highest performance level supports the explanatory power of the results.

It is to be mentioned, that the threshold concept of Bunc et al. However, the Pansold-test is characterized by a step-shaped load protocol, which is carried out under field conditions. Therefore a reliable realization of the Pansold-test requires a good sense of time of the swimmers with the ability to swim evenly, particularly in the first steps. Short-term speed increases or to quick beginning speeds can lead to high first-step lactate concentrations.

This lactate concentration influences the further course of the test and the lactate curve [44]. However this is accepted for the examination of the endurance capacity in the field accounting for the different structures of swimming disciplines.

A methodical strength of this study is the statistical analysis with a MLA. This method allows analyzing different numbers of data sets for an athlete with different time intervals between measurements [46]. For elite sport, it seems to be important to consider the time periods between performance diagnostics to make statements about e. For that reason it was possible to analyze all valid data sets in the second part.

Furthermore it is common, that some athletes are part of the squad for longer time periods, experiencing more performance diagnostics than other athletes. A disadvantage of this method is, that detailed information about descriptive data cannot be provided because of the different numbers of data sets for each athlete.

A limitation of this retrospective analysis of data between — is, that the equipment used for the lactate diagnostics and the exact process of acquisition is unknown. In conclusion, we identified the influence, especially of sex and distance, on lactate parameters in swimming and tried to explain them with current physiological knowledge. Furthermore we showed the importance of considering the different time periods between measurements in a formally correct way by using the MLA for general statements on basis of large data sets in high performance sports.

The slight but significant influences of the time periods between measurements show the dynamic and sensitivity of the lactate molecule. These findings may help interpreting results of lactate tests in context of e. Men overall showed higher IAT and max. For the variable stroke, the MLA showed significant results but no or small effect sizes. Therefore, when comparing inter- and intraindividual results of lactate tests in swimming, especially sex and distance specific lactate parameters have to be considered for initial status measurements and the development over time.

In particular, longitudinal comparisons under steady conditions, which means applying the same test protocol and threshold concept, could benefit from this [1] , [51]. Special thanks to Jochen Schweikert and Martin Keh for the support on the mathematical conversion.

Analyzed the data: BH NB. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Abstract Background In order to achieve world-class performances, regular performance diagnostics is required as an essential prerequisite for guiding high performance sport. Methods We calculated the individual anaerobic threshold IAT of Bunc using the swimming-specific lactate threshold test by Pansold.

Discussion These significant results suggest that lactate tests in swimming specifically have to consider the lactate affecting factors sex and distance under consideration of the time period between measurements. Introduction In order to achieve maximum performance in important competitions, regular performance diagnostics is required as an essential prerequisite for guiding high performance sport [1]. Influence of Sex Because of anthropometric, hormonal and genetic differences, sex is a major factor influencing best performances [14].

Influence of Stroke Most studies about lactate in swimming were conducted in freestyle; only a few studies analyzed the influence of the other strokes on lactate. Influence of Distance With higher swimming distance, the aerobic endurance capacity becomes more important [32]. Aims of the Study The first aim of this article is to improve the interpretability of lactate diagnostics in swimming by identifying lactate-affecting variables. Test Protocols Lactate threshold test by pansold.

Download: PPT. Table 1. Information about the Pansold test protocol [42] p. The Individual Threshold Concept of Bunc et al. Figure 1. Table 2. Table 3. Table 4. Table 5.

Sex The descriptive data cf. Stroke For both statistical methods the effects for stroke is significant for all three dependent variables. Methodical Discussion The large number of data sets of athletes at highest performance level supports the explanatory power of the results. Conclusion In conclusion, we identified the influence, especially of sex and distance, on lactate parameters in swimming and tried to explain them with current physiological knowledge.

References 1. World Book of Swimming. From Science to Performance. New York: Nova: pp. Kiely J Periodization paradigms in the 21st century: evidence-led or tradition-driven?

Int J Sports Physiol Perform 7 3 : — View Article Google Scholar 3. Eur J Appl Physiol 84 1—2 : — View Article Google Scholar 4. Sports Med 36 1 : 65— View Article Google Scholar 5.

J exp biol Pt 24 : — View Article Google Scholar 6. Gladden LB A lactatic perspective on metabolism. Med Sci Sports Exerc 40 3 : — View Article Google Scholar 7. Gladden LB Lactate metabolism: a new paradigm for the third millennium.

J Physiol Pt 1 : 5— View Article Google Scholar 8. Acta Physiol Oxf 4 : — View Article Google Scholar 9. Med Sci Sports Exerc 33 2 : — View Article Google Scholar J Strength Cond Res 26 11 : — Acta Universitatis Carolinae Gymnica 21 1 : 73— Stellenwert der Laktatbestimmung in der Leistungsdiagnostik.

Stuttgart: Fischer: p. Schweiz Z Sportmed Sporttraumatol 60 1 : 32— J Sport Sci Med 9: — Int J Sport Med 27 11 : — Eur J Appl Physiol 2 : — Biomechanics and Medicine in Swimming. Jyvaskyla: Gummerus Printing: — J Biomech 43 12 : — J Hum Kinet 21— Int J Sports Physiol Perform 6 1 : — Chatterjee S, Laudato M Gender and performance in athletics.

Soc Biol 42 1—2 : — J Hum Kinet 97— J Histochem Cytochem 48 5 : — Brooks GA Cell-cell and intracellular lactate shuttles. J Physiol Pt 23 : — J Sports Med Phys Fitness 41 4 : — J Sci Med Sport 13 2 : — Schiaffino S Fibre types in skeletal muscle: a personal account.

Acta physiol oxf 4 : — Koulmann N, Bigard A-X Interaction between signalling pathways involved in skeletal muscle responses to endurance exercise.

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DecemberCite as. Sex-related differences in performance and in age of peak performance have been reported for freestyle swimming. However, little is known about the sex-related differences in other swimming styles. The aim of the present study was to compare performance and age of peak performance for elite men and women swimmers in breaststroke versus freestyle.

Race results were analyzed for swimmers at national ranked in the Swiss high score list during through and for international swimmers who qualified for the finals of the FINA World Swimming Championships during through The sex difference for both freestyle and breaststroke swimming speeds decreased significantly with increasing swimming distance for both groups.

Race distance did not affect the age of peak performance by women in breaststroke, but age of peak performance was four years older for FINA women than for Swiss women. Men achieved peak swimming performance in breaststroke at younger ages for longer race distances, and the age of peak swimming performance was six years older for FINA men than for Swiss men.

In freestyle swimming, race distance did not affect the age of peak swimming performance for Swiss women, but the age of peak swimming performance decreased with increasing race distance for Swiss men and for both sexes at the FINA World Championships. Results of the present study indicate that i sex-related differences in swimming speed were greater for freestyle than for breaststroke for swimmers at national level, but not for mujiki at international level, and ii both female and male mujiki achieved peak swimming speeds at younger ages in breaststroke than in freestyle.

Further studies are required to better understand differences between trends at national and international levels. It was often assumed that men will outperform women in all sporting events requiring substantial physical exertion [ 123 ]. Tanaka and Seals [ 45 ] found this assumption to be true for running, cycling, and ice-skating, but found a different performance pattern in swimming.

For swimming, the sex-related difference in performance was greatest in short duration events and became progressively smaller with increasing distance. The smaller body size, the higher proportion sex body fat, and the shorter legs of female athletes are factors that prevent women from keeping up with men in other sports, but may contribute to their relatively high performance in swimming [ 89 ].

However, there is indirect evidence that the sex-related difference is smaller in breaststroke than in freestyle swimming. Active drag coefficient C da measure of technique and performance, was lower for sex swimmers [ 15 ].

Havriluk [ 16 ] found that C d was similar for men and women in freestyle swimming, but that women had a significantly lower C d than men in breaststroke. Therefore, the greater power of men, which allows them to outperform women in freestyle swimming, might not provide such a great advantage in breaststroke. The age of peak performance for a particular swimming style, rather than the age-related sex decline is of interest to athletes and coaches in order to estimate when performance starts to dwindle for the particular swimming style.

With this knowledge swimmers and their coaches are able to focus on the optimal swimming style in the swimmers age group by tailoring the training program and organizing an appropriate competition schedule.

The age of peak performance seemed to have been relatively stable over time in some sports. However, the age of peak performance can vary significantly with event and sex sexes.

For example, Berthelot et al. Schulz and Curnow [ 3 ] analysed performance of Olympic freestyle swimmers from toand found that women generally achieved peak performance at younger ages than men. Inconsistent estimates of the age of peak performance for freestyle swimming might be partially due to the use of data from different time periods.

The aims of the present study were to i compare the performance of women and men in breaststroke versus freestyle swimming using data from both athletes at national level i. We hypothesized that i sex-related differences in performance would be smaller for breaststroke than for freestyle swimming, ii sex-related differences in performance would decline with increasing race distance, and iii the age of peak performance would be similar for breaststroke and freestyle swimming for both sexes.

Due to the low number of participants per age group and a high variability in performance by Swiss swimmers during earlier years, analyses were limited to data from through for athletes at national level. The Mujiki data used were for the top eight males and top eight females for each stroke and each distance per year. As FINA World championships are held every other year we were able to include five consecutive events. Ultimately, data were available for a total of 29, athletes, including 14, Swiss women and 14, Swiss men, and women and men at the international level.

The study was approved by the Institutional Review Board of St. Gallen, Switzerland, and the requirement for informed consent was waived on the basis that the study used publicly available data. Swiss women and men were divided into ten age groups, and the three fastest swim speeds for each distance and year were determined for each group. From these fifteen athletes, the top three were determined for each sex, age group, and race distance.

In cases where there were fewer than three swimmers, that group was excluded from the analysis. FINA finalists were divided into two-year age groups, and swimming speeds of the top three athletes in each age group were determined for each sex and race distance. To compare sex-related difference in breaststroke and freestyle swimming, the fastest three women and fastest three men were determined for each swimming style and race distance for Swiss and FINA athletes.

Sex related difference was calculated for every pairing of equally placed athletes e. In order to facilitate reading all sex differences were transformed to absolute values before analysing. Sex-related difference in swimming speed at national level per swimming style and distance. P -values indicate significant differences between sex differences of different swimming styles over the same distance.

Sex-related difference in swimming speed at international level per swimming style and distance. Arrow denotes the age group with the numeric fastest swimming speed.

Age of peak swimming performance of the top ten breaststroke and freestyle sex in Swiss and FINA competitions during the However, race distance did not significantly affect the age of peak performance in either swimming style for Swiss women, or for FINA women swimming breaststroke. Secondly, the sex-related difference for both freestyle and breaststroke swimming speeds decreased significantly with increasing race distance for Swiss and FINA athletes.

Thirdly, race distance did not affect the age of peak swimming performance by women in breaststroke, but the age of peak performance was four years older for FINA women than for Swiss women.

Fourthly, in freestyle swimming, race distance did not affect the age of peak swimming performance for Swiss women, but the age of peak swimming performance decreased with increasing race distance for Swiss men and for both sexes at the FINA World Championships. Due to the observational and cross-sectional study design interpretation of present results is limited to some extent. Furthermore, possible influences of anthropometric, biomechanical and physiological measures could not be considered [ 192021 ].

However, this drawback is compensated for by the large study population providing sufficient power for the statistical analyses. Results for elite Swiss swimmers supported the hypothesis that sex-related differences in peak swimming performance were smaller for breaststroke than for freestyle swimming.

This finding can be partly attributed to the biomechanics of the swimming styles, particularly the front crawl, which is the fastest technique and typically used for freestyle swimming [ 20 ].

At high swimming speeds, women have a higher stroke rate and shorter stroke length sex men, resulting in a poorer performance, and this effect is more pronounced in the front crawl than in breaststroke [ 22 ]. Indeed, Havriluk [ 16 ] found that women have a higher level of technical efficiency than men in breaststroke swimming, relative to the sex-related difference in freestyle swimming.

Sex-related differences in body drag could also affect performance mujiki between swimming styles. Breaststroke is the swimming style with the greatest body drag, while freestyle has the least drag [ 24 ]. Female swimmers have a sex degree of body drag than men [ 2526 ], and should have a greater gender advantage in breaststroke than in freestyle swimming.

Nevertheless, women lack the absolute power to achieve comparable performance times [ 27 ] and consistently underperform men in both freestyle and breaststroke. This mujiki be especially important in short races, where anaerobic capacity and upper extremity muscle power are most influential.

In contrast to the Swiss data, the FINA data did not support the hypothesis that sex-related differences are smaller for breaststroke than for freestyle swimming highlighting the fact that the performance difference between men and women is not solely of sex-related nature. Different skill levels at national and international level must also be taken into account.

This is further supported by studies of performance determining factors, like stroke rate, arm lag time, and simultaneous arm-leg propulsion time [ 28 ]. These factors differ not only with sex but also with performance level and event. FINA competitors represent a much larger pool of elite athletes than the Swiss pool and have greater opportunities for training, particularly women. Top FINA women might be sufficiently stronger freestyle swimmers than top Swiss women to mujiki the gender gap to some extent.

At international women have the same access to swimming training compared to men, which leads to a higher training load compared to national level. Mujika et al. Data for both Swiss and international swimmers supported the hypothesis that sex-related differences in both breaststroke and freestyle decline with increasing race distance. This result confirmed previous findings of Tanaka and Seals [ 12 ], who concluded from freestyle records that women swim more efficiently than men, and so show relative improvement in performance as race distance increases.

The more economic swimming in women has been attributed to smaller body size, which reduces drag, as well as shorter legs, a greater percentage of body fat, and lower density, which results in a more horizontal and streamlined position [ 8912 ]. Results of the present study did not support the hypothesis that the age of peak swimming performance is similar for breaststroke and freestyle swimming.

Both Swiss and international women and men exhibited peak swimming performance at younger ages in breaststroke than in freestyle events.

However, when year age classes were used to analyse the mujiki, this difference was not seen showing that the use of the finest possible age scale is important to detecting such differences.

Earlier maturation and puberty in women [ 3132 ] account at least partly for this difference. Maximal increases in bone width, mineral content, and density occur earlier in women than in men [ 33 ]. The growth pattern of metacarpal bones also shows a two-year difference between sexes [ 31 ]. Lean body mass, which primarily reflects muscle mass, begins to increase during early puberty in both sexes, but females gain more fat-free mass than males [ 34 ]. Fat mass increases more during later puberty in women than in men [ 32 ], which might increase swimming efficiency, as mentioned previously.

Based on the age group with the numeric fastest swim, both Swiss and FINA men achieved their peak swimming speed at a younger age than women. However, the reason for that finding remains unclear and warrants further investigation. With regard to the statistical power of the underlying analysis we consider this finding rather incidental, in particular as there is no obvious physiological explanation behind. This difference can be explained by the higher performance required to successfully compete at international level.

Skills and experience that take years of high training load are usually required to close the performance gap between national and international levels, and achieve qualification times for international events [ 30 ]. The present study found greater sex-related differences in peak swimming performance in freestyle than in breaststroke for top Swiss swimmers, but not for FINA finalists.

The sex-related difference decreased with increasing race distance for both swimming styles in both groups. Women consistently achieved peak swimming mujiki at younger ages than men. Further studies are required to better understand why the age of peak swimming performance differs between breaststroke and freestyle, and to examine sex-related differences in other swimming styles. This article is published under license to BioMed Central Ltd. Skip to main content Skip to sections.

Advertisement Hide. Download PDF. Sex-related differences and age of peak performance in breaststroke versus freestyle swimming. Open Access. First Online: 19 December Part of the following topical collections: Exercise physiology.

Background Sex-related differences in performance and in age of peak performance have been reported for freestyle swimming.

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