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Exercise Modality Effect on Bioenergetical Performance at ...O2max Intensity.

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Title: Exercise Modality Effect on Bioenergetical Performance at ...O2max Intensity.
Authors: SOUSA, ANA1 sousa.acm@gmail.com, FIGUEIREDO, PEDRO1,2, ZAMPARO, PAOLA3, PYNE, DAVID B.4, VILAS-BOAS, JOÃO P.1,5, FERNANDES, RICARDO J.1,5
Source: Medicine & Science in Sports & Exercise. Aug2015, Vol. 47 Issue 8, p1705-1713. 9p.
Subject Terms: *Statistical correlation, *Exercise, Cycling, Energy metabolism, Heart beat, Regression analysis, Rowing, Running, Swimming, T-test (Statistics), Oxygen consumption, Data analysis software, Descriptive statistics, One-way analysis of variance
Abstract: Purpose: A bioenergetical analysis of different exercise modes near maximal oxygen consumption (...O2max) intensity is scarce, hampering the prescription of training to enhance performance. We assessed the time sustained in swimming, rowing, running, and cycling at an intensity eliciting ...O2max and determined the specific oxygen uptake (...O2) kinetics and total energy expenditure (Etot-tlim). Methods: Four subgroups of 10 swimmers, 10 rowers, 10 runners, and 10 cyclists performed (i) an incremental protocol to assess the velocity (v...O2max) or power (w...O2max) associated with ...O2max and (ii) a square wave transition exercise from rest to v...O2max/w...O2max to assess the time to voluntary exhaustion (Tlim-100%...O2max). The ...O2 was measured using a telemetric portable gas analyzer (K4b², Cosmed, Rome, Italy) and ...O2 kinetics analyzed using a double exponential curve fit. Etot-tlim was computed as the sum of its three components: aerobic (Aer), anaerobic lactic (Analac), and anaerobic alactic (Analac) contributions. Results: No differences were evident in Tlim-100% ...O2max between exercise modes (mean ± SD: swimming, 187 ± 25; rowing, 199 ± 52; running, 245 ± 46; and cycling, 227 ± 48 s). In contrast, the ...O2 kinetics profile exhibited a slower response in swimming (21 ± 3 s) compared with the other three modes of exercise (rowing, 12 ± 3; running, 10 ± 3; and cycling, 16 ± 4 s) (P < 0.001). Etot-tlim was similar between exercise modes even if the Analac contribution was smaller in swimming compared with the other sports (P < 0.001). Conclusion: Although there were different ...O2 kinetics and ventilatory patterns, the Tlim-100%...O2max was similar between exercise modes most likely related to the common central and peripheral level of fitness in our athletes. [ABSTRACT FROM AUTHOR]
Copyright of Medicine & Science in Sports & Exercise is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Exercise Modality Effect on Bioenergetical Performance at ...O&lt;subscript&gt;2max&lt;/subscript&gt; Intensity.
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– Name: Abstract
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  Data: Purpose: A bioenergetical analysis of different exercise modes near maximal oxygen consumption (...O2max) intensity is scarce, hampering the prescription of training to enhance performance. We assessed the time sustained in swimming, rowing, running, and cycling at an intensity eliciting ...O2max and determined the specific oxygen uptake (...O2) kinetics and total energy expenditure (Etot-tlim). Methods: Four subgroups of 10 swimmers, 10 rowers, 10 runners, and 10 cyclists performed (i) an incremental protocol to assess the velocity (v...O2max) or power (w...O2max) associated with ...O2max and (ii) a square wave transition exercise from rest to v...O2max/w...O2max to assess the time to voluntary exhaustion (Tlim-100%...O2max). The ...O2 was measured using a telemetric portable gas analyzer (K4b&#178;, Cosmed, Rome, Italy) and ...O2 kinetics analyzed using a double exponential curve fit. Etot-tlim was computed as the sum of its three components: aerobic (Aer), anaerobic lactic (Analac), and anaerobic alactic (Analac) contributions. Results: No differences were evident in Tlim-100% ...O2max between exercise modes (mean &#177; SD: swimming, 187 &#177; 25; rowing, 199 &#177; 52; running, 245 &#177; 46; and cycling, 227 &#177; 48 s). In contrast, the ...O2 kinetics profile exhibited a slower response in swimming (21 &#177; 3 s) compared with the other three modes of exercise (rowing, 12 &#177; 3; running, 10 &#177; 3; and cycling, 16 &#177; 4 s) (P &lt; 0.001). Etot-tlim was similar between exercise modes even if the Analac contribution was smaller in swimming compared with the other sports (P &lt; 0.001). Conclusion: Although there were different ...O2 kinetics and ventilatory patterns, the Tlim-100%...O2max was similar between exercise modes most likely related to the common central and peripheral level of fitness in our athletes. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Medicine &amp; Science in Sports &amp; Exercise is the property of Lippincott Williams &amp; Wilkins and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1249/MSS.0000000000000580
    Languages:
      – Code: eng
        Text: English
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        PageCount: 9
        StartPage: 1705
    Subjects:
      – SubjectFull: Statistical correlation
        Type: general
      – SubjectFull: Exercise
        Type: general
      – SubjectFull: Cycling
        Type: general
      – SubjectFull: Energy metabolism
        Type: general
      – SubjectFull: Heart beat
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      – SubjectFull: Regression analysis
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      – SubjectFull: Rowing
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      – SubjectFull: Running
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      – SubjectFull: Swimming
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      – SubjectFull: T-test (Statistics)
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      – SubjectFull: Oxygen consumption
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      – SubjectFull: Data analysis software
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      – SubjectFull: Descriptive statistics
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      – SubjectFull: One-way analysis of variance
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              Text: Aug2015
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