A Model of Breathing Economy for Swimming

Introduction: A close relationship often exists between breathing frequency and exercise repetition rate, i.e., breathing is entrained to the rhythm of limb movements (Bechbache and Duffin 1977). This relationship is especially true for swimming where the athlete is not able to breathe on demand, but must wait for that portion of the stroke cycle that allows breathing to occur. Thus, a conflict can develop between respiratory demand and swimming technique. Although the concept of “swimming economy” (distance·stroke−1 × stroke rate) has been presented previously (Craig and Pendergast 1979), no such model exists to describe the impact of changes in ventilation during swimming with performance. Therefore, the purpose of the present study was to develop a model of breathing economy during swimming exercise. Methods: Sample: The athlete group consisted of 20 (11 females, 9 males) national caliber competitive swimmers, aged 16.9 ± 2.0y (mean ± SD). Data collection and analysis: Swim testing was conducted in a 50-m pool using the freestyle stroke, and consisted of a set of 5 × 200-m incremental velocity swims followed by a maximal effort 1 × 150-m freestyle swim. Data for swimming velocity, stroke rate, distance·stroke−1, breathing frequency and distance·breath−1 were recorded, and analyzed graphically to develop parameters for the breathing economy model. Results: Two measures of breathing economy parameters were examined: distance breath−1 (m·breath−1) during the maximal 150-m swim, and the change in breathing frequency per change in swimming velocity (breaths·min (m·s−1)−1) termed breathing frequency increment. The mean (± SD) distance·breath−1 was 3.03 ± 0.38 m·breath−1 and the mean breathing frequency increment was 40.8 ± 11.4 (breaths·min (m·s−1)−1). A significant correlation (r = 0.77) was detected between distance breath−1 and distance stroke−1 (p = 0.002). Discussion: As a result of the current research, two new performance variables for “breathing economy” were derived for assessing changes in swimming performance: breathing frequency increment (measured in breaths·min (m·s−1)−1), and distance·breath−1 (measured in m·breath−1). We suggest that these variables measure the ability to control breathing to increase swimming performance. Breathing control during performance would allow for improved technical efficiency and reduced drag, as the turning of the head to breathe in freestyle swimming could compromise optimal body position and stroke mechanics. Previously, it has been reported that increases in distance per stroke−1 are well correlated with improvements in swimming velocity (Craig and Pendergast 1979; Craig, Skehan et al. 1985). While a “swimming economy model” has been presented previously (Craig and Pendergast 1979), the concept of “breathing economy” has not been reported in the literature. The finding of a strong relationship between improvements in distance·breath−1 and distance·stroke−1 supports the concept of a “breathing economy” model for swimming performance. Future work will be directed at examining the effect of training on “breathing economy” and exploring the etiology of the changes in the drive to breathe resulting from training. Acknowledgements: This work was supported by the Graduate Department of Exercise Sciences, University of Toronto. We thank the Respiratory Research Group for their input, and the participating coaches and athletes for their time and effort.

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