Biomechanics and Medicine in Swimming XI

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swimming power and dryland power to sprint freestyle performance: A mul-tiple regression approach. Journal of Swimming Research, 9, 10-14. Keskinen, K., Tilli, L., & Komi, P. (1989). Maximum velocity swimming: Interrelationships of stroking characteristics, force production and anthropometric variables. Scandinavian Journal of Sports Science, 11(2), 87-92. Konstantaki, M., Trowbridge, E. A., & Swaine, I. L. (1998). The relationship between blood lactate and heart rate responses to swim bench exer-cise and women’s competitive water polo. Journal of Sports Sciences, 16, 251-256. Konstantaki M. & Swaine I. L. (1999). Lactate and cardiopulmonary responses to simulated arm-pulling and leg-kicking in collegiate and recreational swimmers. International Journal of Sports Medicine, 20, 118-121. Maglischo E. W. (2003). Swimming Fastest. Champaign IL: Human Kinetics. Mitchell J. B. & Huston J. S. (1993). 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Champaign, II, U.S.A.: Human Kinetics. chaPter3.PhysioLogyandBioenergetics Blood Lactate Concentration and Clearance in Elite Swimmers During Competition Vescovi, J.d. 1,3 , Falenchuk, o. 4 , Wells G.d. 1,2 1Canadian Sport Centre Ontario, Toronto, Canada 2Faculty of Medicine, University of Toronto, Toronto, Canada 3School of Kinesiology and Health Science, York University, Toronto, Canada 4Ontario Institute of Secondary Educ., University of Toronto, Toronto, Canada Blood lactate [BLa] concentrations after swimming events may be influenced by demographic features and characteristics of the swim race, whereas active recovery (AR) enhances [BLa] removal. Our aims were to examine how sex, age, race distance, and swim stroke influenced [BLa] after competitive swimming events and to develop a model based on AR swim distance to help optimize [BLa] removal. Post-race [BLa] from 100 swimmers competing in the finals at the Canadian Swim Championships were retrospectively anaysed. [BLa] was also assessed repeatedly during AR. Post-race [BLa] was highest after 100 and 200 m events and lowest after 50 and 1500 m races. There was a negligible effect of age on post-race [BLa]. The following model can be used to estimate the change in [BLa] during AR: Δ[BLa] after AR = –3.374 + 1.162 (male=0;female=1) + 0.789 *post-race [BLa]+ 0.003 * AR distance. Key Words: blood lactate, active recovery, sex differences, swimming IntroductIon Short duration bouts of high intensity exercise rely largely on nonoxidative energy metabolism, resulting in the accumulation of muscle and blood lactate. Peak blood lactate concentrations ([BLa]) following maximal exercise has a direct relationship with performance in swim events ranging between 100 and 800 m (Benelli et al., 2007; Bonifazi et al., 1993). Evaluation of [BLa] following competitive races also provides evidence of the physiological stress for an individual swimmer in a given event. Thus, the utility of assessing [BLa] for swimmers is important for a variety of training and competitive purposes. Swimming provides an ideal model for characterizing [BLa] response with events ranging from ~20 s (50 m freestyle) to 15 min (1500 m freestyle). Swimmers commonly compete in multiple events throughout a single day, which requires them to recover from and prepare for several races. Strategies that increase the return rate of post-race [BLa] to resting values are often used by coaches in an effort to optimize subsequent performance. In an effort to expedite blood lactate removal while maximizing energy conservation between swimming events it would be of practical use to know if there is an optimal distance or time to recommend for active recovery (Toubekis et al., 2008). Research on the effect of sex, age and race characteristics on postrace [BLa] during competitive swim events remains equivocal. Additionally, sport scientists, coaches and swimmers continually search for practical strategies to maximize recovery after an event in preparation for subsequent heat or final races. The aims of this study were to examine how sex, age, race distance, and swim stroke influenced [BLa] after competitive swimming events and to develop a practical model based on recovery swim distance to help optimize blood lactate removal. Methods Post-race [BLa] after the final races in male and female swimmers competing in the 2009 Canadian National Swimming Championships were assessed. The effect of active recovery distance on [BLa] disappearance and a model that could be used by coaches as a practical tool during competitions was also examined. Data from one hundred swimmers (n=50 male and n=50 females) were included in this analysis. Multiple races from the same person were included and thus data from 156 races 233
BiomechanicsandmedicineinswimmingXi were collected, however because of missing data the final analysis included 149 finals races swam by 98 swimmers. The age of the swimmers ranged between 14 and 29 years. Race results were collected from the host organizing committee and used to determine FINA points. Blood samples were collected within three to five minutes after completing the race. Samples were obtained from finger stick and analyzed with a Lactate ProTM (Arkray Lt., Japan). Swimmers then proceeded to the recovery pool and performed their own coach-directed active recovery. [BLa] was repeatedly assessed until it was below 2 mmol•L-1. The distance of each active recovery segment as well as the total active recovery distance and the change in [BLa] from post-race to the lowest concentration achieved following the active recovery were recorded. Several swimmers competed in more than one final race and had data from multiple races included in the analysis, therefore the assumption of independence was violated. To evaluate the relationship between post-race [BLa] and swimmers characteristics (age and sex) and the races (stroke and distance) the Generalized Estimating Equations (GEE) technique was used (Hardin & Hilbe, 2002), which accommodates for a violation of the independence assumption. To evaluate active recovery distance on [BLa] disappearance an exploratory model building approach was used with [BLa] following active recovery as the dependent variable, while sex was entered in the model as a two-level factor. Age, post-race [BLa], and active recovery distance were entered as covariates. The maximal model was developed, then non-significant effects were removed until the most parsimonious model was achieved. Each model was compared with the previous using Quasi Likelihood under Independence Model Criterion (QIC) index to determine whether removal of non-significant parameters improved the fit of the model. Values are expressed as mean ± SD and statistical significance was set at p
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Pahlen Norge AS Pahlen Norge AS Cha
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