The Swimming Index And Lactic Acid In Higher Aerobic Effort

Abstract

Introduction: Swimming represents a physical activity that involves moving the body through water and is characterised by cyclical arm and leg movements coordinated with breathing. The concept of total training brings a new approach to training factors, with global repercussions on the performance components. The time pressure put on coaches and athletes brings into focus the use of sprint means to improve higher aerobic endurance, thus reducing the training volume (number of hours and kilometres). Knowing the metabolic effort zones encountered in the training of swimmers and the subtle connections between these zones allows improving the effects of training through apparently paradoxical means. Nowadays, field specialists talk about aerobic and anaerobic powers and capacities, about the development of VO₂ max through alactacid and lactacid anaerobic efforts. Hypothesis: Using short-term sprint exercises can lead to an increase in aerobic endurance (VO₂ max). The research subjects are 15 senior athletes, members of the Tunisian National Swimming Team. Methods: The research is focused on the ascertaining pedagogical experiment with one variable. Maximum oxygen consumption was assessed by applying the T-2000 test correlated with the items: swimming index and post-exercise lactic acid value. Mathematical and statistical methods: arithmetic mean, standard deviation, Pearson correlation coefficient, coefficient of determination (r²), graphical representation. Results: The analysed data highlight a strong correlation between the two parameters (swimming index and lactic acid), r = 0.869, which shows a very strong association. Therefore, the use of short-term sprint exercises can increase aerobic endurance; thus, the research hypothesis is validated.

Keywords: Swimming indexlactic acidT-2000 testhigher aerobic effort

Introduction

Swimming represents a physical activity that involves moving the body through water and is characterised by cyclical arm and leg movements coordinated with breathing. Specialists in the field show that maximum aerobic endurance (MAE) delays exhaustion of the swimmer’s body through means achieved in percentages of VO2 max (maximum oxygen consumption), MAP (maximum aerobic power) or MAS (maximum aerobic speed); all these parameters are influenced by the energy potential, the cardiac cost of the body, but also by the technical efficiency, the volume of swimming over a given distance (Guedj, Brunet, Girardier, & Moyen, 2006). Influencing performance according to the quantification and efficiency of the technique can be achieved by calculating the swimming index, namely by multiplying the swimming speed by distance per stroke (DPS). This index assumes that, at a given speed, the athlete who swims with the highest DPS value has the most efficient swimming technique (Costill, Maglischo, & Richardson, 1994). The concept of total training brings a new reorientation/approach to training factors, with global repercussions on the performance components. The time pressure put on coaches and athletes brings into focus the use of sprint means to improve higher aerobic endurance, thus reducing the training volume (number of hours and kilometres). The new concept of High-Intensity Interval Training (HIIT)/ 10-20-30 Interval Training Model, which highlights the maximum effort intensity reached through short-term ultrafast sprints, has an impact on improving higher aerobic exercise capacity/ MAE, where the swimming index and lactic acid production are parameters that, if correlated, can provide data about the specificity of the research (Kenney, Wilmore, & Costill, 2015). Knowing the metabolic effort zones encountered in the training of swimmers and the subtle connections between these zones allows improving the effects of training through apparently paradoxical means. Nowadays, field specialists talk about aerobic and anaerobic powers and capacities, about the development of VO2 max through alactacid and lactacid anaerobic efforts.

Problem Statement

The stimulation of higher aerobic exercise capacity through sprint-specific anaerobic means generates problems, questions, permissive and restrictive assertions.

The connexion of the vectors: exercise intensity, swimming index and lactic acid generates the future premise and hypothesis of the research.

Research Questions

Are there connections between the lactic acid accumulation and the swimming index calculation? Can the use of short-term sprint exercises determine the increase in higher aerobic endurance?

Purpose of the Study

Identification of the means and methods to invalidate or confirm the responses to the research problems/hypothesis. This is for the first time in the world that a comparison is made between the two parameters.

Research Methods

Findings

The results obtained in the initial and final tests are shown and analysed in Tables 01 and 02 .

Regarding the time achieved in the T-2000 test, its average is 25:10:00 minutes in the initial testing and 25:03:00 minutes in the final testing, the difference between the two tests being 07:00 seconds in favour of the second testing; the minimum value recorded within the group in the initial test is 22:20:00 minutes, and the maximum value is 26:56:00 minutes, the difference between these values being 04:36:00 minutes; in the final test, the minimum value is 22:15:00 minutes, and the maximum value is 26:46:00 minutes, the difference between these values being 04:31:00 minutes. Standard deviation in the initial test is equal to ± 01:06:97 minutes, and in the final test, it is equal to ± 01:05:89 minutes in favour of the second testing; the coefficient of variation in the initial test is 4.43%, and in the final test, it is 4.38%, which shows a high level of homogeneity of the results obtained in this test. Figure 01 graphically presents the differences between the values recorded in the two tests.

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As for the average time per 100m within the T-2000 test, it is 01:15:52 minutes in the initial testing and 01:15:14 minutes in the final testing, the difference between the two tests being 00:38 seconds in favour of the second testing; the minimum value recorded within the group is 01:07:00 minutes in the initial test, and the maximum value is 01:20:80 minutes, the difference between these values being 13:80 seconds; in the final test, the minimum value is 01:06:75 minutes, and the maximum value is 01:20:30 minutes, the difference between these values being 13:55 seconds. Standard deviation in the initial test is equal to ± 03:34 seconds, and in the final test, it is equal to ± 03:29 seconds in favour of the second testing; the coefficient of variation in the initial test is 4.43%, and in the final test, it is 4.38%, which shows a high level of homogeneity of the results obtained in this test. Figure 02 graphically presents the differences between the values recorded in the two tests.

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Concerning the swimming index, its average is 2.412m/s in the initial test and 2.567m/s in the final test, the difference between the two tests being 0.155m/s in favour of the second testing; the minimum value recorded within the group in the initial test is 1.89m/s, and the maximum value is 2.9m/s, the difference between these values being 1.01m/s; in the final test, the minimum value is 2.1m/s, and the maximum value is 2.9m/s, the difference between these values being 0.8m/s. Standard deviation in the initial test is equal to ± 0.305m/s, and in the final test, it is equal to ± 0.247m/s in favour of the second testing; the coefficient of variation is 12.66% in the initial test, and in the final test, it is 9.61%, which shows a moderate level of homogeneity of the results obtained for this parameter. Figure 03 graphically presents the differences between the values recorded in the two tests.

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As regards the value of lactic acid accumulated in the blood at the end of the T-2000 test, its average is 12.44 mmol in the initial test and 11.75 mmol in the final test, the difference between the two tests being 0.69 mmol in favour of the second testing; the minimum value recorded within the group in the initial test is 10.24 mmol, and the maximum value is 14.06 mmol, the difference between these values being 3.82 mmol; in the final test, the minimum value is 10.2 mmol, and the maximum value is 12.9 mmol, the difference between these values being 2.7 mmol. Standard deviation in the initial test is equal to ± 1.129 mmol, and in the final test, it is equal to ± 0.736 mmol in favour of the second testing; the coefficient of variation in the initial test is 9.07%, and in the final test, it is 6.26%, which shows a high level of homogeneity of the results obtained for this parameter. Figure 04 graphically presents the differences between the values recorded in the two tests.

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Tables 03 and 04 show the correlation between the post-exercise LA parameter (lactic acid value) and the swimming index parameter, a correlation achieved in the two tests. In the initial test, we notice a very strong positive association between the two parameters (LA and swimming index), the correlation coefficient being r = 0.869. Also, the r² value indicates that the dispersion of each of the two parameters is influenced by the other parameter in a proportion of 75.5%. In the final test, we notice a very strong positive association between the two parameters (LA and swimming index), the correlation coefficient being r = 0.917. Also, the r² value indicates that the dispersion of each of the two parameters is influenced by the other parameter in a proportion of 84%.

Conclusion

High performance in world swimming depends on several factors: height of the athletes, the stroke rate and range of motion, coordination of the upper limbs, propulsive forces, accumulated lactic acid and ways of removing it, maximum heart rate etc., and there are many cases where, at a distance of a few hundredth of a second from the first time, an athlete is not on the podium or even in the final of the event.

Regarding our experiment, in the final test, an improvement in the studied parameters is noted for all parameters; average times for the T-2000 test are improved by 7 seconds, and there is only one case where the time achieved in the final test is identical to the time achieved in the initial test: the athlete F.H., with 25:02:00 minutes in both tests.

As for the average time per 100m in the T-2000 test, there is an improvement of 00:38 seconds, which, in our opinion, is significant, because it is about the training of high-performance athletes.

The swimming index has a moderate value in the initial test, 2.412m/s, and in the final test, 2.567m/s, the difference being 0.155m/s in favour of the second testing, which shows that the stroke efficiency has also improved due to the increase in the DPS parameter.

The post-exercise lactic acid parameter shows that the effort provided by athletes during the initial test falls within the metabolic zone of tolerance to lactic acid accumulation (LA > 12 mmol, X = 12.44 mmol), and in the final test, within the VO₂ max effort zone (LA < 12 mmol and > 4-6 mmol, X = 11.75 mmol). Thus, the research hypothesis that using short-term sprint exercises can lead to an increase in aerobic endurance (VO₂ max) is checked and confirmed.

Regarding the correlation between the two parameters, the swimming index and the value of post-exercise lactic acid, there is a very strong positive association between them: in the initial test, r = 0.869, and the determination coefficient r² shows that the dispersion of each of the two parameters is influenced by the other parameter in a proportion of 75.5%; in the final test, r = 0.917, and the determination coefficient r² shows that the dispersion of each of the two parameters is influenced by the other parameter in a proportion of 84%.

Acknowledgments

We thank the athletes involved in this research and the National Sports Research Institute for the support provided.

References

1. Cardelli, C., Chollet, D., & Lerda, R. (1999). Analysis of the 100-m front crawl as a function of skill level in non-expert swimmers. Journal of Human Movement Studies, 36(2), 51-74.
2. Costill, D. L., Maglischo, B. W., & Richardson, A. B. (1994). La natation. Paris: Vigot.
3. Guedj, E. B., Brunet, B., Girardier, J., & Moyen, B. (2006). Médecine du sport (7e éd.). Paris: Masson.
4. Kenney, W. L., Wilmore, J. H., & Costill, D. L. (2015). Physiology of sport and exercise (6th ed.). USA: Human Kinetics.
5. Marinescu, Gh., Ticală, L. D., Rădulescu, A., Bidiugan, S., & Petre, A. T. (2016). Educational perspectives opened by the use of T-2000 software in the preparation of water polo players. In I. Roceanu (Ed.), Proceedings of the 12th International Scientific Conference “eLearning and Software for Education”, April 21-22, 2016 (Vol. 3, pp. 417-422). Bucharest: Carol I National Defence University. DOI: 10.12753/2066-026X-16-239
6. Popa, M. (2008). Statistică pentru psihologie – Teorie și aplicații SPSS (Ed. a II-a). Iași: Polirom.