Effects of oxygen uptake kinetics on 100-m and 800-m front crawl performance in pubertal swimmers.

Effects of oxygen uptake kinetics on 100-m and 800-m front crawl performance in pubertal swimmers - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites. Search Log in Dashboard Publications Account settings Log out Search… Search NCBI Primary site navigation Search Logged in as: Dashboard Publications Account settings Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide PERMALINK Copy As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice BMC Sports Sci Med Rehabil . 2026 Mar 10;18:201. doi: 10.1186/s13102-026-01644-6 Search in PMC Search in PubMed View in NLM Catalog Add to search Effects of oxygen uptake kinetics on 100-m and 800-m front crawl performance in pubertal swimmers Marek Strzała Marek Strzała 1 Department of Water Sports, Institute of Sports Sciences, University of Physical Culture in Kraków, Kraków, Poland Find articles by Marek Strzała 1, ✉ , Raul Bartolomeu Raul Bartolomeu 2 Polytechnic of Guarda, Guarda, Portugal 3 Instituto Politécnico de Bragança, Bragança, Portugal Find articles by Raul Bartolomeu 2, 3 , Piotr Krężałek Piotr Krężałek 4 Department of Biomechanics, Laboratory of Biophysics and Movement Analysis, University of Physical Culture in Kraków, Kraków, Poland Find articles by Piotr Krężałek 4 , Kamil Sokołowski Kamil Sokołowski 1 Department of Water Sports, Institute of Sports Sciences, University of Physical Culture in Kraków, Kraków, Poland Find articles by Kamil Sokołowski 1 , Łukasz Wądrzyk Łukasz Wądrzyk 1 Department of Water Sports, Institute of Sports Sciences, University of Physical Culture in Kraków, Kraków, Poland Find articles by Łukasz Wądrzyk 1 , Łukasz Kryst Łukasz Kryst 5 Department of Anthropology, Faculty of Physical Education and Sport, University of Physical Culture in Kraków, Kraków, Poland Find articles by Łukasz Kryst 5 , Marcin Maciejczyk Marcin Maciejczyk 6 Department of Physiology and Biochemistry, Faculty of Physical Education and Sport, University of Physical Culture in Kraków, Kraków, Poland Find articles by Marcin Maciejczyk 6 Author information Article notes Copyright and License information 1 Department of Water Sports, Institute of Sports Sciences, University of Physical Culture in Kraków, Kraków, Poland 2 Polytechnic of Guarda, Guarda, Portugal 3 Instituto Politécnico de Bragança, Bragança, Portugal 4 Department of Biomechanics, Laboratory of Biophysics and Movement Analysis, University of Physical Culture in Kraków, Kraków, Poland 5 Department of Anthropology, Faculty of Physical Education and Sport, University of Physical Culture in Kraków, Kraków, Poland 6 Department of Physiology and Biochemistry, Faculty of Physical Education and Sport, University of Physical Culture in Kraków, Kraków, Poland ✉ Corresponding author. Received 2025 Nov 4; Accepted 2026 Feb 27; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13088418  PMID: 41808200 Abstract Purpose This study assessed the effect of oxygen uptake ( ) kinetics on swimming performance on 100-m ( V 100 ) and 800-m ( V 800 ) races. Method In male pubertal swimmers trained competitively for 4–5 years, pulling force ( F ave ) and kinetics were measured in tethered swimming, and amplitude ( and time constant (τ) were calculated. Biological age ( BA ) and such physical characteristics as body mass ( BM ), skeletal muscle mass of body segments, fat-free mass ( FFM ), and total body length ( TBL ) were considered in mutual interdependence and in the context of their influence on swimming performance. Results Depending on the significant differences in BA , swimmers were divided into early maturing and late maturing, and these groups presented differences in kinetics and in F ave in relation to and BM . Considering all swimmers, in the subsequent 10-s periods was positively related to F ave , muscle mass of particular body segments, TBL , and BA . The same was observed between subsequent F ave in 10-s periods and and body physical indicators: muscle mass, TBL , and BA . Longer τ was not positively related to V 100 or V 800 ; e.g., the indicator of kinetics ( 31–60 ) was strongly related to FFM (0.60; p < 0.001), F ave1-60 (0.72; p < 0.001), and, though to a lesser extent, to TBL (0.44; p < 0.001) . The collected physiological and anthropometric data mostly strongly influenced V 100 and mostly moderately influenced V 800 ; TBL was a weaker (did not reach the significance threshold) predictor of swimming performance. Conclusions kinetics constitutes an appropriate indicator of well-trained physiological predispositions, which translate into skillfully performed front crawl races ( V 100 , V 800 ). The results indicate that physiologically more mature pubertal swimmers—typically characterized by greater muscle mass and higher strength—tend to achieve better front crawl performance over 100 m and 800 m. Keywords: Oxygen uptake kinetics, Tethered force, Exercise physiology, Anthropometrics, Maturation Background The key factors influencing performance in endurance disciplines are maximal oxygen uptake, lactate threshold and economy of movement. These elements, by regulating the adaptation of the respiratory and circulatory systems, determine both the rate of energy transfer and the athlete's exercise capacity. It has been suggested that traditional parameters of performance interact with the oxygen kinetics and collectively they can be determinants of performance [ 1 ]. Training an athlete competing with high intensity effort, from 20s to several minutes, requires good preparation in terms of cardiorespiratory effectiveness and endurance with well-developed aerobic and anaerobic energy. The secure supply of energy from the very beginning of the effort from an anaerobic source is important, and its further use over seconds to minutes is associated with exhaustive training. Similarly in sports performance, the efficient development of aerobic metabolism, with fast kinetics of less anaerobic already in the first minute is essential owing to the economy combined with rational expenditure of energy [ 2 ]. Of course, studies on the kinetics of in athletes have been conducted many times together with the assessment on sports performance [ 1 ]. Fast oxygen kinetics is related with smaller oxygen deficit, less substrate-level phosphorylation, and high exercise tolerance, and slow oxygen kinetics results in a high oxygen deficit, disturbs homeostasis, and causes poor exercise tolerance [ 3 ]. That is why one trains in competitive swimming to raise the parameters of aerobic capacity, such , gas exchange threshold, and respiratory compensation point, to the desired level, considering their values mainly in terms of increasing (as for a marathon runner) [ 1 , 4 ]. However, properly trained, balanced energy production – which is efficient, aerobic up to 50% [ 5 ] over a 100-m distance and rapid, anaerobic, causing quickly increasing fatigue, but giving high speed – is a challenge. Comprehensive training for a swimmer should be related to changes in the muscle phosphate controllers of oxidative phosphorylation, muscle oxygen delivery and utilization, and/or muscle fiber type recruitment patterns [ 6 ]. Findings in adults suggest that aerobic training is associated with a faster phase II (primary phase) time constant (τ), a fundamental parameter of aerobic performance, i.e., the speed of kinetics (in short, it is the ability to rapidly increase oxygen consumption after starting exercise) and a smaller slow component in youth (represents an additional or excess energetic cost) [ 3 ], independent of age or maturity, indicative of enhanced oxidative metabolism [ 7 ]. McNarry et al. [ 8 ] found training to be associated with a significantly faster pulmonary phase II τ in both prepubertal and pubertal swimmers. Moreover, looking further for the fast kinetics of [ 9 ] and indices of phase II and its amplitude, τ was already considered as a useful indicator of aerobic conditioning in swimmers and preparation to 100-m [ 10 – 12 ] and of course longer races. The assessment of a talented young swimmer with a view to their future development should take into account somatic properties [ 13 ], including the ability to generate propulsive force [ 14 , 15 ], e.g. while swimming on a tether [ 16 ]. During tethered swimming, the specificity of the strokes, strength workout modalities, and limb differentiation may affect differently the dry-land to in situ transfer [ 17 ]. Additionally, in young swimmers, the pace or rate of maturation is a related aspect of talent development [ 18 ]. The processes of physical growth, biological maturation, and behavioral changes, which occur simultaneously and interact with each other, are highly individualized and also impact the demands of competitive swimming [ 19 ]. However, considerations about fast kinetics regarding changes caused by biological development in the context of appropriate training [ 20 ], shape of the technique, and kinematics of the performed swimming should remain in the background as physiological and biomechanical demands [ 21 , 22 ]. This is especially true since others have noticed a lack of reliable knowledge in the literature on the importance of anaerobic factors, and especially aerobic factors, in the physiological preparation of swimmers, which translates into the production of propulsive force, swimming technique and subsequently performance [ 23 ] However, specific training-related properties of swimming technique [ 13 ], such as stroke length or propelling efficiency, may be independent of maturation [ 24 ]. We hypothesized that indicators of the aerobic capacity and speed of kinetics would have a significant effect on the ability to achieve higher results in front crawl in short and long races. In addition, they would interact with other indicators that determine this swimming ability, such as muscle mass, body length, and swimming thrust. The aim of this study was to assess kinetics in 1-min tethered swimming, including amplitude and τ, in male pubertal swimmers and in relation to the pulling force of the tethered swimming. The procedure was carried out with the consideration of the influence of biological age ( BA ) and physical characteristics of young pubertal swimmers. Methods Study design The study was planned 2 months in advance with coaches and swimmers. Participants and their parents (or legal guardians) received appropriate information about the study procedures and provided written informed consent. On the weekend preceding the week of the tethered swimming, somatic parameter measurements, and other tests (Tuesday, Wednesday, Thursday), all swimmers took part in a 100-m freestyle competition, and on the following weekend, they took part in an 800-m freestyle competition. All individuals followed the normal procedure of preparing for the competition and tethered swimming (rest, nutrition). The swimmers and their coaches were familiarized with the testing procedure at least 2 weeks in advance. All study participants were recommended in a limited number of about 40 by the Małopolska District Swimming Association, after being selected by this institution as exhibiting appropriate talent enabling further sports development. The study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethics Committee at the Regional Medical Chamber (No. 94/KBL/OIL/2020; 5 June 2020). Participants The study involved 41 male swimmers; their age based on date of birth was 12.87 ± 0.65 years, body height ( BH ) 162.1 ± 10.11 cm, body mass ( BM ) 49.7 ± 10.34 kg, and fat-free mass ( FFM ) 49.71 ± 10.33 kg. The participants had been training competitively for 4–5 years, their sports level was level 5 in the classification by Ruiz-Navarro et al. [ 25 ]. They were licensed by the Polish Swimming Federation, and the calculated number of World Aquatics Points, based on the swimming results covered by this research, equaled 304.26 ± 75.34 for 100-m freestyle and 325.68 ± 72.08 on 800-m freestyle. The subjects routinely attended 8 training sessions in the water and 3 on dryland a week, trained in accordance with the recommendations of the Polish Swimming Federation, and regularly took part in regional and national competitions planned for their age group in the annual calendar of competitions. Somatic parameters and biological age BH was measured from the bottom of the feet to the vertex of the head while standing erect. Total body length ( TBL ) was determined when lying back, from the tips of the fingers (with arms stretched up above the head) down to the pointed toes (foot plantar flexion). BH measurements were completed with the use of an anthropometer, and TBL measurements with the use of an extended anthropometer (Sieber Hegner Maschinen AG, Zurich, Switzerland; accuracy of 1 mm). The intra-observer error was 0.071, while inter-observer error was 0.095. The errors have been calculated by the formula: TEM = summation D square divided by 2n over root, where D is the difference between the measurements taken on two occasions and n is the number of subjects measured in duplicate. Anthropometric measurements were obtained following International Society for the Advancement of Kinanthropometry (ISAK) recommendations [ 26 ]. Body composition was measured using a bioelectrical impedance analyzer (BC-418 MA, Tanita Corp., Tokyo, Japan), certified as a Class IIa medical device. The instrument operates at 50 kHz and 90 μA, using eight stainless-steel tactile electrodes (hand-to-foot pathway) to estimate segmental impedance (150–1200 Ω) and body composition parameters. BM was recorded by an integrated strain-gauge load cell (accuracy ± 0.2 kg; range 0–200 kg; resolution 0.1 kg). Measurements were performed in the standard mode, under controlled ambient conditions (temperature and relative humidity), within the manufacturer’s specified operating limits. The device was leveled before each session and used in standalone configuration with thermal printout. According to the Tanita Technical Note [ 27 ], the BC-418 MA demonstrates a coefficient of variation < 0.5% for key composition measures and used in this type of research in pediatric swimmers [ 28 , 29 ]. This examination included the measurement of BM (in kg), FFM (in kg), and predicted skeletal muscle mass for specific body segments: arms ( arM , in kg), legs ( lgM , in kg), and trunk ( trM , in kg). BA was assessed on the basis of the collected measurements of BH and BM ; these data, in relation to percentile charts, were entered into the formula presented below: where BHage is the age obtained from the percentile charts in accordance with the participant’s BH and BMage is the age obtained from the percentile charts in accordance with the participant’s BM . Growth charts by the Children’s Memorial Health Institute, standardized and validated for the Polish population, were used (the 50th percentile was applied to align BH and BM with age) [ 30 ]. Division into groups according to biological age In this study, in order to show significant differences in essential somatic and physiological properties determining swimming efficiency [ 9 ], participants were divided into the 2 most numerous groups based on biological age: younger (late mature, n = 19, chronological age ( CA ) 12.53 ± 0.56, range 11.96 to 13.74) and older (early mature, n = 22, CA ± 13.16, range 12.16 to 13.83). The objective criterion of dividing swimmers into equal BA groups (half and half) could not be fully met with an evenly divided line between 13.00 and 13.25 years, as five swimmers were 13.25 years of BA . Therefore, it was necessary to enlarge the early mature group. The range of BA in late mature individuals ranged from 9.75 to 13.0 years with an average 11.82 ± 0.94, while in early mature the range was between 13.25 to 18.0 years, 14.63 ± 1.47 average (Fig. 1 ). Fig. 1. Open in a new tab The biological age ( BA ) of the examined swimmers divided into younger (late mature, 19 swimmers) and older (early mature, 22 swimmers) ones. Bars indicate standard deviation and the box plot analysis involves means and 0.95 confidence intervals Force generated in a 1-min extreme intensity test and oxygen uptake kinetics In the tethered front crawl test, the swimmers breathed through a system of valves. Respiratory parameters were simultaneously recorded with an ergospirometer with sampling frequency 128 Hz (Start 2000 MES, Poland) and afterwards underwent a computer analysis (Ergo 2000 M software MES, Poland). Gas and volume calibration of the ergospirometer was performed before each series of tests in accordance with the recommendations contained in the manufacturer's instructions. The accuracy of the ergospirometer oxygen and carbon dioxide analyzer was 0.02% (of the range). A tether with a force gauge (ZPS5-BTU1kN, Staniak, Poland, with relative measurement linearity error of less than 0.10%, used in accordance with the manufacturer's instructions) with sampling frequency 200 Hz was used to analyze the recorded force curve for each participant with computer software (MAX6v0M software, Poland). The connection to the breathing system suspended on a specially designed crane and the swimmer’s attachment to the tether through a waist belt (Fig. 2 ) have been described in detail in the literature [ 9 ], and the measuring method has been assessed to be reliable [ 31 ]. The kinetics of was analyzed during a 1-min extreme intensity test. During the tethered swimming test, respiratory parameters were recorded using the breath-by-breath method using an ergospirometer, which enabled obtaining a dynamic picture of changes in oxygen uptake during intense exercise. Average values were calculated for each 5-s interval to reduce inter-breath noise, as recommended in swimming kinetics studies [ 10 ]. When mono-exponential fitting was unstable due to noise in short (1-min) trials, τ was obtained from the 63% amplitude crossing by linear interpolation between adjacent 5-s means. The individuals who did not reach the plateau phase of (3 cases) were excluded from further analysis; ultimately, the final sample involved 41 swimmers. Specifically, we determined τ as the time required for to reach approximately 63% of its total change from the baseline value to the peak value [ 12 , 32 ], using the following procedure: ◦ was measured breath-by-breath during the 1-min test. The average value was calculated for each 5-s interval and assigned to the midpoints of these intervals (e.g., 2.5 s, 7.5 s, 12.5 s). ◦ The initial value, i.e. , was defined as the average in the first 5-s interval ( ). ◦ The peak value ( ) was determined as the highest average value achieved during the test. ◦ The calculation of amplitude ( and was as follows: and the value was calculated as: Fig. 2. Open in a new tab One of the swimmers performing the 1-min tether test Linear interpolation was used to determine τ: ◦ The two consecutive time points (tᵢ and tᵢ₊₁), derived from adjacent 5-s averaged intervals, between which crossed the 63% amplitude threshold were identified. Assuming a linear change in between these intervals, the exact time ( ) at which reached was determined by using linear interpolation: ◦ τ was defined as . Before the test, the swimmers performed a warm-up in the water, routinely about 1000 m in the same way as before the competition. The tethered front crawl test was preceded by easy limb stroking and kicking with the tether rope taut; a loud whistle began a 1-min swim with extreme intensity and then a whistle signaled the end of the test (Fig. 1 ). The data collected in this test enabled the calculation of the average value of pulling force ( F ave ) and in each 10-s period and in the entire 1-min tethered test ( F ave1-60 [N] and 1–60 [l∙min –1 ]). Relative indicators were also determined, as F ave to (N∙l –1 ∙min) and F ave to and BM (N∙l –1 ∙min∙kg –1 ), both in the 10-s periods. 100-m and 800-m front crawl race in competition Before the short-course pool competition, a swimming warm-up was performed with changes in pace, turns, starting jumps, etc., adequate to the front crawl technique used in the races. The 100-m and 800-m front crawl velocity ( V 100 and V 800 [m·s –1 ]) was defined as the swimming distance divided by the official final time of the race. During the competition, an automatic timing device (Omega, Zürich, Switzerland; OCP5, StartTime V, Swiss Timing, Corgémont, Switzerland) was used. Statistical analysis The assumption of the normality of the variables was verified by a visual examination of the distributions and the Lilliefors test. The sphericity assumption was checked by means of the Mauchly test. The results of this analysis were empowering to carry out a 2-factor ANOVA (6 × 2) with 1 within-subject factor (6 measurements of or F ave ) and 1 between-subject factor (2 BA groups: older, n = 22; and younger, n = 19). The main effects of the measurements and the groups were calculated, as well as the interaction between them and simple effects. In these calculations, the Greenhouse–Geisser correction was applied owing to the failure to meet the sphericity assumption. In the case of a simple comparison between the groups of biologically older and younger swimmers for CA and BA , the independent sample Student t-test was applied. The Pearson correlation coefficient was also computed between all variables collected during the 1-min tethered test and swimming kinematics or swimming speed for all swimmers ( n = 41). Confidence intervals for Pearson r (95%) were calculated, using the standard method of Fisher’s z-transformation. An alpha level of 0.05 was assumed in all analyses. To control to control for Type I error for multiple effects, false discovery rate (FDR) correction was applied, specifically using the Benjamini–Hochberg method [ 33 ]. Intraclass correlation coefficients (ICC) were calculated for the oxygen uptake and the average pulling force (six measures). Two-way mixed model was applied and mean consistency among measures was calculated. Following published guidelines [ 34 ] it was assumed that ICC < 0.50 indicates poor, ICC between 0.50—0.75: moderate, between 0.75—0.90: good, and above 0.90: excellent reliability, respectively. An alpha level of 0.05 was assumed in all analyses. The preliminary differences between the groups concerning biological variables calculated by means of the Student t-tests were expressed as Cohen’s d . For ANOVA, the effect sizes were expressed as partial eta-squares ( . Effect sizes were assumed for Cohen’s d : small: d = 0.2, medium: d = 0.5, and large: d = 0.8; as well as for Cohen’s eta-squares: small: = 0.01, medium: = 0.06, large: = 0.14 [ 35 ]. Power analysis The analysis of the statistical power was performed in order to determine the probability of discovering a significant effect if it existed, given the number of participants. Two analyses were carried out, one for the mixed ANOVA, one for the correlations. The analyses were performed for a small, medium, and large effect sizes. As for ANOVA, the power to detect a significant interaction between a grouping factor and the within-subject one was sought. Three effect sizes were assumed: small: f = 0.10, medium: f = 0.25, and large: f = 0.40. The achieved power for the sample of 41 participants was 0.34, 0.99, and > 0.99, respectively. For correlations, the assumed effect sizes (r) equaled 0.10, 0.30, and 0.50. The achieved power was 0.10, 0.50, and 0.95. In sum, for ANOVA, the sample size was satisfactory with regard to medium and large effects, but not to small ones. For correlations, the sample size was only enough to detect large effects. The statistical analyses were conducted by using the Statistica 13.3 software (TIBCO Software Inc., Palo Alto, CA, USA). The power analyses were performed with the G*Power software [ 36 ]. Results The swimmers participating in this study, arbitrarily divided into 2 BA groups: late mature and early mature, differed significantly in terms of BA (Fig. 1 ), as well as BM and body length, as measured by the BM , FFM , BH , and TBL indicators, being bigger among the older individuals (Fig. 3 ). Fig. 3. Open in a new tab Body weight indicators: body mass ( BM ) and fat-free mass ( FFM ) (left panel) and body height ( BH ) and total body length ( TBL ) (right panel) of late mature and early mature swimmers. Bars indicate standard deviation and the box plot analysis involves means and 0.95 confidence intervals Mean ICC consistency for the oxygen uptake ( ) (l∙min –1 ) across the six measures was 0.86 [CI₉₅% ≈ 0.78, 0.92], and for the swimmers’ average pulling force ( F ave ) it was 0.51 [CI₉₅% ≈ 0.21, 0.71]. Therefore, the test–retest reliability was satisfactory for oxygen uptake but was rather poor for the average pulling force. Early mature swimmers exhibited higher cardiorespiratory capacity, measured in the 1-min tethered test; differences comparing with the late mature group were more significant in the 2 last 10-s periods (Fig. 4 ). Fig. 4. Open in a new tab The swimmers’ oxygen uptake ( ) (l∙min –1 ) in the 10-s periods measured in the 1-min tethered test. The upper curve shows in the early mature group and the lower curve depicts in the late mature group. Bars represent standard errors, # indicates significant differences between early mature and late mature participants. # p ≤ 0.05; ## p ≤ 0.01 The pulling force generated during tethered swimming in relation to was higher in early mature swimmers; the statistical effect calculated in the Student t-test showed no differences at any measurement time in this test. The Pearson correlation coefficient calculated for entire group between F ave and showed raising relationship in six 10-s periods [following r and (CI₉₅% ≈): 0.16 (−0.15; 0.45); 0.24 (−0.07; 0.51); 0.30 (−0.01; 0.56); 0.46 (0.18; 0.67); 0.60 (0.35; 0.76); 0.63 (−0.40; 0.79)] (Fig. 5 ). To control for multiple effects, false discovery rate (FDR) correction was applied, specifically using the Benjamini–Hochberg method (Benjamini, Y., & Hochberg, Y. (1995). After the correction, Pearson r values ​​equal to or greater than 0.40 remained statistically significant. These are marked with asterisks. The test–retest reliability, as measured by the ICC, was relatively low for the average pulling force. Therefore, interpretations involving this parameter should be made with caution. Fig. 5. Open in a new tab The swimmers’ average pulling force ( F ave ) relative to oxygen uptake ( ) (N∙l –1 ∙min) in the 10-s periods measured in the 1-min tethered test and the Pearson correlations between the results of F ave and . The upper curve shows F ave in the early mature group and the lower curve depicts F ave in the late mature group. Bars represent standard errors, # indicates significant differences between early mature and late mature participants. The Pearson correlation level between F ave and at each of the 6 periods for the entire 41 swimmers, * showed significant correlation. *: p significant at 0.05 after Benjamini-Hochberg correction After taking into account BM , the results of the pulling force in relation to were higher in late mature athletes; the statistical effect was more significant in the second part of the test (Fig. 6 ). Fig. 6. Open in a new tab The swimmers’ average pulling force ( F ave ) relative to oxygen uptake ( ) and body mass ( BM ) (N∙l –1 ∙min∙kg –1 ) in the 10-s periods measured in the 1-min tethered test. The upper curve shows F ave in the late mature group and the lower curve depicts F ave in the early mature group. Bars represent standard errors; # indicates significant differences between late mature and early mature participants. # p ≤ 0.05; ## p ≤ 0.01 The interrelationship of and the swimming results with τ, somatic indicators, and F ave1-60 showed that higher physical characteristics, BA , and thrust force correlated with greater . Slower acquired τ was negatively correlated with the swimming results and also (as an additional result) with (r = –0.23), but without statistical significance (Table 1 ). Table 1. The Pearson correlations of oxygen uptake ( ) (l∙min –1 ) in the subsequent 10-s periods and the 100-m and 800-m swimming velocity ( V 100 and V 800 ) with the time constant (τ), biological age ( BA ), total body length ( TBL ), predicted skeletal muscle mass for specific body segments: arms ( arM ), legs ( lgM ), and trunk ( trM ), as well as average pulling force ( F ave1-60 ) of the 1-min tethered test ( n = 41) in 10-s periods τ [s] 39.61 ± 7.43 BA [years] 12.87 ± 0.66 TBL [cm] 217.17 ± 35.54 arM [kg] 4.05 ± 1.06 lgM [kg] 13.89 ± 3.48 trM [kg] 23.30 ± 3.94 F ave1-60 [N] 56.7 ± 14.21 1–10 0.74 ± 0.37 0.24 (−0.08; 0.51) 0.24 (−0.08; 0.51) –0.02 (−0.32; 0.29) 0.27 (−0.04; 0.53) 0.24 (−0.07; 0.51) 0.31 (0.00; 0.56) 0.21 (−0.10; 0.49) 11–20 0.98 ± 0.42 –0.16 (−0.44; 0.16) 0.25 (−0.06; 0.52) 0.09 (−0.22; 0.39) 0.30 (0.00; 0.56) 0.32 (0.02; 0.57) 0.36 (0.06; 0.60) 0.30 (−0.01; 0.56) 21–30 1.34 ± 0.63 –0.72* (−0.84; −0.53) 0.26 (−0.06; 0.52) 0.21 (−0.11; 0.48) 0.30 (−0.01; 0.55) 0.31 (0.01; 0.57) 0.32 (0.01; 0.57) 0.39 (0.09; 0.62) 31–40 1.90 ± 0.85 –0.75* (−0.86; −0.58) 0.39 (0.09; 0.62) 0.32 (0.01; 0.57) 0.38 (0.08; 0.61) 0.37 (0.07; 0.61) 0.42* (0.13; 0.64) 0.46* (0.18; 0.67) 41–50 2.69 ± 0.84 –0.52* (−0.71; −0.25) 0.60* (0.35; 0.76) 0.44* (0.15; 0.66) 0.53* (0.26; 0.72) 0.49* (0.21; 0.69) 0.62* (0.39; 0.78) 0.63* (0.40; 0.79) 51–60 3.16 ± 0.77 –0.16 (−0.45; 0.15) 0.74* (0.56; 0.85) 0.46* (0.18; 0.68) 0.70* (0.50; 0.83) 0.61* (0.38; 0.77) 0.75* (0.57; 0.86) 0.80* (0.65; 0.89) V 100 [m·s –1 ] 1.49 ± 0.11 –0.11 (−0.40; 0.21) 0.62* (0.38; 0.78) 0.38 (0.08; 0.61) 0.63* (0.40; 0.78) 0.60* (0.36; 0.77) 0.60* (0.36; 0.77) 0.80* (0.66; 0.89) V 800 [m·s –1 ] 1.24 ± 0.09 –0.19 (−0.47; 0.12) 0.47* (0.19; 0.68) 0.34 (0.03; 0.58) 0.41* (0.11; 0.64) 0.47* (0.19; 0.68) 0.44* (0.16; 0.66) 0.70* (0.50; 0.83) Open in a new tab * : p significant correlation at 0.05 after Benjamini–Hochberg correction; 95% confidence intervals lower; upper for the correlation below in each cell F ave in the 10-s periods, a key indicator of swimming speed, was very strongly related to BA , physical body dimensions (moderately to TBL ), and the aerobic capacity achieved in the 1-min test (Table 2 ). Table 2. Average pulling force ( F ave ) (N) in the subsequent 10-s periods of the 1-min tethered test and the Pearson correlations with oxygen uptake amplitude ( ), biological age ( BA ), total body length ( TBL ), and predicted skeletal muscle mass for specific body segments: arms ( arM ), legs ( lgM ), and trunk ( trM ) ( n = 41) F ave in 10-s periods [l] 2.60 ± 0.81 BA [years] TBL [cm] arM [kg] lgM [kg] trM [kg] 1–10 0.69* (0.48; 0.82) 0.78* (0.40; 0.79) 0.40* (0.10; 0.63) 0.75* (0.58; 0.86) 0.70* (0.50; 0.83) 0.77* (0.61; 0.87) 11–20 0.72* (0.53; 0.84) 0.78* (0.62; 0.88) 0.39 (0.10; 0.62) 0.77* (0.60; 0.87) 0.69* (0.49; 0.82) 0.77* (0.61; 0.87) 21–30 0.62* (0.39; 0.78) 0.76* (0.59; 0.87) 0.37 (0.07; 0.61) 0.74* (0.56; 0.86) 0.69* (0.48; 0.82) 0.76* (0.59; 0.87) 31–40 0.66* (0.45; 0.81) 0.81* (0.66; 0.89) 0.38 (0.08; 0.62) 0.83* (0.70; 0.91) 0.76* (0.59; 0.86) 0.81* (0.66; 0.89) 41–50 0.68* (0.47; 0.82) 0.82* (0.69; 0.90) 0.40* (0.10; 0.63) 0.83* (0.69; 0.90) 0.76* (0.60; 0.87) 0.83* (0.69; 0.90) 51–60 0.53* (0.27; 0.72) 0.80* (0.65; 0.89) 0.33 (0.03; 0.58) 0.85* (0.74; 0.92) 0.77* (0.61; 0.87) 0.82* (0.68; 0.90) Open in a new tab * : p significant correlation at 0.05 after Benjamini–Hochberg correction; 95% confidence intervals lower; upper for the correlation below in each cell indices ( 31–60 , 1–60 , ) generally presented a higher relationship with the swimming results than with somatic indicators (Table 3 ). Table 3. The Pearson correlations between indices of kinetics (l∙min –1 ) and biological age ( BA ), total body length ( TBL ), fat-free mass ( FFM ), average pulling force ( F ave 1–60 ), and the 100-m and 800-m swimming velocity ( V 100 and V 800 ) ( n = 41) BA [years] TBL [cm] FFM [kg] F ave1-60 [N] V 100 [m·s –1 ] V 800 [m·s –1 ] 31–60 2.58 ± 0.77 0.61* (0.37; 0.77) 0.43* (0.14; 0.65) 0.60* (0.36; 0.77) 0.67* (0.45; 0.81) 0.70* (0.50; 0.83) 0.64* (0.41; 0.79) 1–60 1.80 ± 0.51 0.57* (0.31; 0.74) 0.37 (0.08; 0.61) 0.58* (0.34; 0.76) 0.64* (0.42; 0.79) 0.66* (0.44; 0.81) 0.60* (0.36; 0.77) 2.60 ± 0.81 0.63* (0.40; 0.78) 0.44* (0.16; 0.66) 0.61* (0.37; 0.77) 0.70* (0.50; 0.83) 0.66* (0.44; 0.80) 0.64* (0.42; 0.79) Open in a new tab * : p significant correlation at 0.05 after Benjamini–Hochberg correction; 95% confidence intervals lower; upper for the correlation below in each cell Discussion In the current study of young pubertal swimmers, the observed differences in BA , with the division of participants into older and younger mature ones, revealed further differences in their aerobic energy production capacity. This was due to the higher capacity of ; going further, the pulling force in relation to and, moreover, also in relation to BM ( F ave / / BM ) was higher in early mature swimmers. It could result from age-related immaturity in the muscle phosphate controllers (phosphocreatine and adenosine diphosphate), which may therefore contribute to a lower kinetics, or from other metabolic intramuscular factors; or younger BA swimmers were just smaller, with lower muscle mitochondrial volume [ 37 ]. Indeed, in this and earlier observations [ 9 , 38 ], less physically developed late mature swimmers presented lower levels of kinetics. In the current study, during the test was related to robust body size indicators ( TBL , FFM ); in particular, the relationship between and muscle mass for specific body segments ( arM , lgM , trM ) increased with each successive 10-s period of the test. Along with differences in BA and anthropometric parameters, variances in swimming performance were also observed in pre-pubertal individuals [ 39 ]. A higher level of kinetics is definitely dependent on muscle mass and circulating blood volume; this difference was noticeable from the beginning of the 1-min test and the discrepancy increased at 50 and 60 s as musculature is generally associated with elevated oxidative enzyme activity within trained muscles [ 3 ]. As noted in the introduction to this study, the relative aerobic contribution to the total energy output in high-intensity effort, such as during 100-m swimming, may exceed 50% [ 40 ]. Therefore, generating propulsive force from a more economical energy pathway, which may delay fatigue may contribute on swimming performance [ 12 ]. Also, a smaller τ value means that the lag in (i.e., the oxygen deficit) would be smaller and thus the requirement for anaerobic energy provision during the transition from rest to exercise would be reduced. On the other hand, faster kinetics could predispose to enhance exercise tolerance by reducing the oxygen deficit incurred across the transition, with the assumption that the anaerobic capacity is not prematurely expended [ 1 ]. This is particularly relevant to longer distance races in pool swimming. Our data can only modestly support this statement because we obtained a correlation between τ and V 100 , V 800 on the level of r = –0.11, –0.19, respectively. This may be because, as in adult teenagers [ 10 ], to a general adaptation to training in swimming due to the relatively short duration of most swimming events and the predominant use of similar, mostly interval training with relatively high intensity. However, a study conducted by McNarry et al. [ 8 ] found training to be associated with a significantly faster phase II and τ (main growth phase of ) in pubertal swimmers. It has been implied once again [ 14 ] that tethered swimming can reliably examine the behavior of forces and metabolic responses during swimming. Also training protocol involving technical tethered swimming can positively affect front crawl kinematics in pubertal swimmers [ 16 ] when applied over the long term, towards elite swimming [ 41 ]. This time, the finding referred to an intense, 1-min effort in which aerobic and anaerobic sources provided similar energy to generate pulling force. As yet Sokołowski et al. [ 38 ] reported that the strength variables measured in 1-min tethered swimming (peak and average pulling force and average impulse per single cycle) showed positive correlations with the performance responses measured in the maximum 200-m or 400-m freestyle swimming [ 9 ]. Notably that F ave , strongly integrated with BA , noticed in other water sports [ 19 ], exhibited almost the same level of relationships with arM or trM (Table 2 ), also strongly interplaying with , which creates a logical clarification of its production and subsequent impact on performance ( V 100 , V 800 ). These results also indicate that TBL , as a length indicator that well differentiates young talented swimmers [ 42 ] and as a factor related to progression in puberty [ 43 ], was not so strongly associated with F ave , , or swimming performance in comparison with muscle mass in body segments ( arM , lgM , trM ). Geithner et al. [ 44 ] noted that correlation coefficients among ages at peak height velocity, peak weight velocity, and peak velocity of peak suggested a general maturity factor for body size and aerobic power. Espada et al. [ 45 ] reported multiple positive correlations of regional body composition variables ( FFM ) and aerobic variables ( max, respiratory compensation point, and gas exchange threshold); moreover, max showed significant relationships with swimming speeds in middle and long races. In puberty, this may be the case, although in general there are no short freestyle swimmers in elite swimming, with the average BH in adulthood of around 185 cm [ 46 ]. Finally, that in the present study, the indices ( 31–60 , 1–60 , _ A ) and F ave1-60 were strongly related to each other and to BA and exerted the greatest impact on V 100 , V 800 . This may mean that among pubertal swimmers, those stronger, denser, shorter in stature with more muscle mass, and physiologically more mature are more trainable and achieve better sports results. However, this does not necessarily have to be the best prognosis for later adulthood achievements [ 47 ] . A superficial view, primarily through current sporting performance, of identifying talent development is likely to exclude many children, especially those maturing late and showing promise, from development programs due to the dynamic and multidimensional nature of sporting talent [ 48 ]. Limitations and future directions One important limitation of this study is the small sample size (N = 41). Power analysis indicates that this sample size is insufficient to detect effects smaller than average with a sufficiently high probability. This means, in particular, that nonsignificant effects (including correlations) should not be taken as arguments for the absence of an effect. Statistically nonsignificant effects are simply inconclusive—it is unclear whether the effect exists in the population. Also, the sample sizes were unequal ( n = 22 early mature, n = 19 late mature), which further reduces statistical power for between-group comparisons. Future studies should use larger samples (which, unfortunately, is not easy, as recruiting a large number of swimmers with the required skills is a significant challenge). Conclusions This study implies that kinetic indices measured during 1-min of extremely intensive swimming is an appropriate indicator of well-trained physiological predispositions, which translate into the ability to skillfully perform front crawl races ( V 100 , V 800 ). It turned out that the obtained indicators of oxygen kinetics were strongly related to the muscle mass of young swimmers, tethered force, and, though less significantly, to TBL . BA strongly differentiated swimmers into early and late mature ones, presenting a strong relationship with the studied predictors of swimming results: and F ave or F ave BM . Future studies of post-pubertal athletes should examine the significance of appropriate body length and leanness as they grow up, which may be important in the long term (and not developing excessive muscle mass as these results might indicate). In addition, with a larger sample of athletes and with greater biological and chronological age, the attainment of a faster VO₂ τ may be more pronounced. Acknowledgements We would like to thank the Regional Swimming Association in Kraków, Poland and the coaches of the participants for their valuable commitment. Abbreviations arM , lgM , trM Predicted skeletal muscle mass for body segments: arms, legs, trunk BA Biological age CA Chronological age BH Body height FFM Fat-free mass BM Body mass F ave Pulling force F ave1-60 Value of force in entire 1-min tethered test τ Time constant TBL Total body length Oxygen uptake Oxygen uptake amplitude 1 – 60 Oxygen uptake in entire1-minute tethered test 31 – 60 Oxygen uptake in entire last 30-s of 1-min tethered test V 100 , V 800 100-M and 800-m front crawl velocity Authors’ contributions Conceptualization, M.S., R.B.; methodology, M.S., P.K. and R.B.; formal analysis, M.S.; investigation, M.S., Ł.W, K.S. and Ł.K; data curation: M.S., Ł.W, K.S. and Ł.K.; writing—original draft preparation, M.S., R.B.; writing—review and editing, M.S., R.B., M.M. and P.K.; supervision, M.M.; project administration, M.S. All authors have read and agreed to the published version of the manuscript. Funding The authors received no specific funding for this work. Data availability No datasets were generated or analysed during the current study. Declarations Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethics Committee at the Regional Medical Chamber (No.94/KBL/OIL/2020; 5 June 2020). Participants and also participants’ parents (or legal guardians) received appropriate information about the study procedure and provided their written informed consent. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Footnotes Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Burnley M, Jones AM. Oxygen uptake kinetics as a determinant of sports performance. Eur J Sport Sci. 2007;7(2):63–79. 10.1080/17461390701456148. [ Google Scholar ] 2. Jones AM, Poole DC. Oxygen uptake kinetics in sport, exercise and medicine. 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