How Narrow is the Spectrum of Submaximal Speeds in Swimming?

Greco, Camila Coelho; Oliveira, Maria Fernanda de; Caputo, Fabrízio; Denadai, Benedito Sérgio; Dekerle, Jeanne

doi:10.1519/jsc.0b013e318265a6ce

Cited by 14 publications

(26 citation statements)

References 17 publications

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“…Similar alterations have been mentioned in female swimmers during continuous swimming [4]. These physiological alterations occurring after small speed increments probably confirm previous reports for a very narrow spectrum of submaximal speeds in swimming around the LT [34]. The slight differences between methods and the increased metabolic response even after small speed changes highlight the need of choosing the most appropriate method for sLT evaluation to avoid underestimation or overestimation of sMLSS.…”

Section: Discussionsupporting

confidence: 86%

Lactate Threshold Evaluation in Swimmers: The Importance of Age and Method

Nikitakis

Toubekis

2021

Int J Sports Med

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The purpose of the study was to define the most appropriate method for the calculation of the speed corresponding to lactate threshold (sLT) in male swimmers. Eight boys and eight adolescents (age: 11.4±0.5 and 15.8±0.8 years) performed 7×200-m swimming front-crawl and after drawing the speed vs. lactate curve, the sLTs were calculated using five methods: i) the intersection of two linear regression lines, ii) visual inspection, iii) D-max, iv) D-max modified, v) intersection of combined linear and exponential regression lines. All methods were compared to the speed corresponding to maximal lactate steady state (sMLSS). Two to four 30-min efforts of continuous swimming at imposed constant pace were used for sMLSS calculation. In both groups, speed of D-max modified was similar to sMLSS (children, 1.061±0.073 vs. sMLSS: 1.071±0.072 m·s−1; p>0.05; effect size: ES=0.15, small; adolescents, 1.318±0.060 vs. sMLSS: 1.284±0.047 m·s−1; p>0.05; ES=0.64, medium). In adolescents, sLT calculated by intersection of two regression lines and by visual inspection presented medium ES (0.22–0.24) and were no different to sMLSS (1.296 ± 0.051, 1.295±0.053 m·s−1, p>0.05). When testing children, D-max modified is the most appropriate method to estimate sMLSS. The intersection of the linear regression lines and visual inspection are suggested for sMLSS determination in adolescents.

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Section: Discussionsupporting

confidence: 86%

Lactate Threshold Evaluation in Swimmers: The Importance of Age and Method

Nikitakis

Toubekis

2021

Int J Sports Med

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“…In the present study, all participants were able to comply with the imposed speed (the CS), but some of them failed to maintain it for 30 min. Thus, our findings suggest that great inter-individual differences may appear between CS and sMLSS (−6% to 4%) that may critically alter sustainability or metabolic responses despite that the range of mean speeds corresponding to various aerobic indices is very narrow in swimming [27]. Moreover, the selection of distances for CS calculation in the present study (200 and 400-m) may overestimate the “ideal” CS calculation and this should be considered as a limitation of the current study.…”

Section: Discussionmentioning

confidence: 99%

Physiological Responses of Continuous and Intermittent Swimming at Critical Speed and Maximum Lactate Steady State in Children and Adolescent Swimmers

Nikitakis

Paradisis

Bogdanis

et al. 2019

Sports

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Background: The purpose of this study was to compare physiological responses during continuous and intermittent swimming at intensity corresponding to critical speed (CS: slope of the distance vs. time relationship using 200 and 400-m tests) with maximal lactate steady state (MLSS) in children and adolescents. Methods: CS and the speed corresponding to MLSS (sMLSS) were calculated in ten male children (11.5 ± 0.4 years) and ten adolescents (15.8 ± 0.7 years). Blood lactate concentration (BL), oxygen uptake (V·O2), and heart rate (HR) at sMLSS were compared to intermittent (10 × 200-m) and continuous swimming corresponding to CS. Results: CS was similar to sMLSS in children (1.092 ± 0.071 vs. 1.083 ± 0.065 m·s−1; p = 0.12) and adolescents (1.315 ± 0.068 vs. 1.297 ± 0.056 m·s−1; p = 0.12). However, not all swimmers were able to complete 30 min at CS and BL was higher at the end of continuous swimming at CS compared to sMLSS (children: CS: 4.0 ± 1.8, sMLSS: 3.4 ± 1.5; adolescents: CS: 4.5 ± 2.3, sMLSS: 3.1 ± 0.8 mmol·L−1; p < 0.05). V·O2 and HR in continuous swimming at CS were not different compared to sMLSS (p > 0.05). BL, V·O2 and HR in 10 × 200-m were similar to sMLSS and no different between groups. Conclusion: Intermittent swimming at CS presents physiological responses similar to sMLSS. Metabolic responses of continuous swimming at CS may not correspond to MLSS in some children and adolescent swimmers.

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“…For instance, unless an incremental and maximal protocol is implemented it seems that the changes in dv are quite low. Even so, most of the time the protocols include a very narrow pace range (Greco et al., ). A second explanation for the lower sensitivity is that, according to some determinist models, dv is an intermediate variable between the energetic and biomechanical fields, depending on third‐party variables.…”

Section: Discussionmentioning

confidence: 99%

Hydrodynamic profile of young swimmers: Changes over a competitive season

Barbosa

Morais

Marques

et al. 2014

Scandinavian Med Sci Sports

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The aim of this study was to analyze the changes in the hydrodynamic profile of young swimmers over a competitive season and to compare the variations according to a well-designed training periodization. Twenty-five swimmers (13 boys and 12 girls) were evaluated in (a) October (M1); (b) March (M2); and (c) June (M3). Inertial and anthropometrical measures included body mass, swimmer's added water mass, height, and trunk transverse surface area. Swimming efficiency was estimated by the speed fluctuation, stroke index, and approximate entropy. Active drag was estimated with the velocity perturbation method and the passive drag with the gliding decay method. Hydrodynamic dimensionless numbers (Froude and Reynolds numbers) and hull velocity (i.e., speed at Froude number = 0.42) were also calculated. No variable presented a significant gender effect. Anthropometrics and inertial parameters plus dimensionless numbers increased over time. Swimming efficiency improved between M1 and M3. There was a trend for both passive and active drag increase from M1 to M2, but being lower at M3 than at M1. Intra-individual changes between evaluation moments suggest high between- and within-subject variations. Therefore, hydrodynamic changes over a season occur in a non-linear fashion way, where the interplay between growth and training periodization explain the unique path flow selected by each young swimmer.

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How Narrow is the Spectrum of Submaximal Speeds in Swimming?

Cited by 14 publications

References 17 publications

Lactate Threshold Evaluation in Swimmers: The Importance of Age and Method

Lactate Threshold Evaluation in Swimmers: The Importance of Age and Method

Physiological Responses of Continuous and Intermittent Swimming at Critical Speed and Maximum Lactate Steady State in Children and Adolescent Swimmers

Hydrodynamic profile of young swimmers: Changes over a competitive season

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