Re-assessing accumulated oxygen deficit in middle-distance runners.


Bickham, D; Le Rossignol, P; Gibbons, C; Russell, AP; (2002) Re-assessing accumulated oxygen deficit in middle-distance runners. Journal of science and medicine in sport / Sports Medicine Australia, 5 (4). pp. 372-82. ISSN 1440-2440 DOI: https://doi.org/10.1016/S1440-2440(02)80026-3

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Abstract

The purpose of this study was to re-assess the accumulated oxygen deficit (AOD), incorporating recent methodological improvements i.e., 4 min submaximal tests spread above and below the lactate threshold (LT). We Investigated the Influence of the VO2 -speed regression, on the precision of the estimated total energy demand and AOD. utilising different numbers of regression points and including measurement errors. Seven trained middle-distance runners (mean +/- SD age: 25.3 +/- 5.4y, mass: 73.7 +/- 4.3kg. VO2max 64.4 +/- 6.1 mL x kg(-1) x min(-1)) completed a VO2max, LT, 10 x 4 min exercise tests (above and below LT) and high-intensity exhaustive tests. The VO2 -speed regression was developed using 10 submaximal points and a forced y-intercept value. The average precision (measured as the width of 95% confidence Interval) for the estimated total energy demand using this regression was 7.8mL O2 Eq x kg(-1) x min(-1). There was a two-fold decrease in precision of estimated total energy demand with the Inclusion of measurement errors from the metabolic system. The mean AOD value was 43.3 mL O2 Eq x kg(-1) (upper and lower 95% CI 32.1 and 54.5mL o2 Eq x kg(-1) respectively). Converting the 95% CI for estimated total energy demand to AOD or including maximum possible measurement errors amplified the error associated with the estimated total energy demand. No significant difference in AOD variables were found, using 10,4 or 2 regression points with a forced y-intercept. For practical purposes we recommend the use of 4 submaximal values with a y-intercept. Using 95% CIs and calculating error highlighted possible error in estimating AOD. Without accurate data collection, increased variability could decrease the accuracy of the AOD as shown by a 95% CI of the AOD.

Item Type: Article
Faculty and Department: Faculty of Public Health and Policy > Dept of Health Services Research and Policy
PubMed ID: 12585621
Web of Science ID: 180304300012
URI: http://researchonline.lshtm.ac.uk/id/eprint/12559

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