Max Niemeyer1, Margrit Gündisch2, Gina Steinecke2, Raphael Knaier3,4, Ralph Beneke2. 1. Institute of Sports Science and Motologie, Abt. Medizin, Training und Gesundheit, Philipps-University Marburg, Jahnstr. 12, 35037, Marburg, Germany. niemeyer@staff.uni-marburg.de. 2. Institute of Sports Science and Motologie, Abt. Medizin, Training und Gesundheit, Philipps-University Marburg, Jahnstr. 12, 35037, Marburg, Germany. 3. Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA. 4. Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
Abstract
PURPOSE: There is no convincing evidence for the idea that a high power output at the maximal lactate steady state (PO_MLSS) and a high fraction of [Formula: see text]O2max at MLSS (%[Formula: see text]O2_MLSS) are decisive for endurance performance. We tested the hypotheses that (1) %[Formula: see text]O2_MLSS is positively correlated with the ability to sustain a high fraction of [Formula: see text]O2max for a given competition duration (%[Formula: see text]O2_TT); (2) %[Formula: see text]O2_MLSS improves the prediction of the average power output of a time trial (PO_TT) in addition to [Formula: see text]O2max and gross efficiency (GE); (3) PO_MLSS improves the prediction of PO_TT in addition to [Formula: see text]O2max and GE. METHODS: Twenty-one recreationally active participants performed stepwise incremental tests on the first and final testing day to measure GE and check for potential test-related training effects in terms of changes in the minimal lactate equivalent power output (∆PO_LEmin), 30-min constant load tests to determine MLSS, a ramp test and verification bout for [Formula: see text]O2max, and 20-min time trials for %[Formula: see text]O2_TT and PO_TT. Hypothesis 1 was tested via bivariate and partial correlations between %[Formula: see text]O2_MLSS and %[Formula: see text]O2_TT. Multiple regression models with [Formula: see text]O2max, GE, ∆PO_LEmin, and %[Formula: see text]O2_MLSS (Hypothesis 2) or PO_MLSS instead of %[Formula: see text]O2_MLSS (Hypothesis 3), respectively, as predictors, and PO_TT as the dependent variable were used to test the hypotheses. RESULTS: %[Formula: see text]O2_MLSS was not correlated with %[Formula: see text]O2_TT (r = 0.17, p = 0.583). Neither %[Formula: see text]O2_MLSS (p = 0.424) nor PO_MLSS (p = 0.208) did improve the prediction of PO_TT in addition to [Formula: see text]O2max and GE. CONCLUSION: These results challenge the assumption that PO_MLSS or %[Formula: see text]O2_MLSS are independent predictors of supra-MLSS PO_TT and %[Formula: see text]O2_TT.
PURPOSE: There is no convincing evidence for the idea that a high power output at the maximal lactate steady state (PO_MLSS) and a high fraction of [Formula: see text]O2max at MLSS (%[Formula: see text]O2_MLSS) are decisive for endurance performance. We tested the hypotheses that (1) %[Formula: see text]O2_MLSS is positively correlated with the ability to sustain a high fraction of [Formula: see text]O2max for a given competition duration (%[Formula: see text]O2_TT); (2) %[Formula: see text]O2_MLSS improves the prediction of the average power output of a time trial (PO_TT) in addition to [Formula: see text]O2max and gross efficiency (GE); (3) PO_MLSS improves the prediction of PO_TT in addition to [Formula: see text]O2max and GE. METHODS: Twenty-one recreationally active participants performed stepwise incremental tests on the first and final testing day to measure GE and check for potential test-related training effects in terms of changes in the minimal lactate equivalent power output (∆PO_LEmin), 30-min constant load tests to determine MLSS, a ramp test and verification bout for [Formula: see text]O2max, and 20-min time trials for %[Formula: see text]O2_TT and PO_TT. Hypothesis 1 was tested via bivariate and partial correlations between %[Formula: see text]O2_MLSS and %[Formula: see text]O2_TT. Multiple regression models with [Formula: see text]O2max, GE, ∆PO_LEmin, and %[Formula: see text]O2_MLSS (Hypothesis 2) or PO_MLSS instead of %[Formula: see text]O2_MLSS (Hypothesis 3), respectively, as predictors, and PO_TT as the dependent variable were used to test the hypotheses. RESULTS: %[Formula: see text]O2_MLSS was not correlated with %[Formula: see text]O2_TT (r = 0.17, p = 0.583). Neither %[Formula: see text]O2_MLSS (p = 0.424) nor PO_MLSS (p = 0.208) did improve the prediction of PO_TT in addition to [Formula: see text]O2max and GE. CONCLUSION: These results challenge the assumption that PO_MLSS or %[Formula: see text]O2_MLSS are independent predictors of supra-MLSS PO_TT and %[Formula: see text]O2_TT.