Correlations Between the Metabolic Costs of Level and Graded Running: A Secondary Analysis of the Literature
- PMID: 41493537
- DOI: 10.1007/s40279-025-02381-5
Correlations Between the Metabolic Costs of Level and Graded Running: A Secondary Analysis of the Literature
Abstract
Background: The metabolic cost of running (Cr) is one of the three main determinants of performance in distance running, along with maximum oxygen consumption and lactate threshold. However, level Cr is only weakly correlated with performance in trail running, which almost always involves uphill and downhill sections.
Objective: Through a secondary analysis of published data, the primary aim of this study was to characterize the correlations between individuals' level and graded (downhill and uphill) Cr. We took advantage of this database to also re-evaluate the pattern and critical points (i.e., optimum slope) of the relationship between Cr and slope.
Methods: We analyzed 23 studies evaluating level and graded Cr, published before August 2024. Both Cr and Pearson correlation coefficients between level and graded Cr were plotted as functions of slope.
Results: Using third-order polynomial functions, a correlation between level and graded Cr was a continuous function of slope in which correlation coefficients declined with progressively steep uphill or downhill slopes. Downhill Cr was minimized at - 18.8%, and a linear relationship was observed for uphill Cr with slope across the range of slopes analyzed (up to + 26.8%).
Conclusions: The present secondary analysis extends our knowledge on the influence of slope on Cr, showing that graded Cr is weakly correlated with level Cr when slope is steeper than ± 10%. Consequently, testing and training protocols for trail runners should incorporate steeper slopes (i.e., ± 15%) to provide more relevant assessments and preparation for mountainous trail races (including steep slopes).
© 2026. The Author(s), under exclusive licence to Springer Nature Switzerland AG.
Conflict of interest statement
Declarations. Conflict of interest: Loïc Espeit, Thibault Besson, Frederic Sabater-Pastor, Jeanne Tondut, Wouter Hoogkamer, Rodger Kram, Marcel Lemire, Grégoire P. Millet, Aldo Savoldelli, Fabrice Vercruyssen, Gianluca Vernillo, and Guillaume Y. Millet have no conflicts of interest, financial or otherwise, that are directly relevant to the content of this article. Wouter Hoogkamer and Guillaume Y. Millet are Editorial Board members of Sports Medicine but were not involved in the selection of peer reviewers for this article or any of the subsequent editorial decisions. Ethics approval: Not applicable. Consent to participate: Not applicable. Consent for publication: Not applicable. Availability of data and material: The data supporting the findings of this study are available within the article and its supplementary materials. Code availability: Not applicable. Author contributions: All authors (LE, TB, FSP, JT, WH, RK, ML, GPM, AS, FV, GV, GYM) contributed to the original idea and the study design of the manuscript. The literature search and data analysis were performed by LE. The first draft of the manuscript was written by LE and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
References
-
- Schmidt-Nielsen K. Locomotion: energy cost of swimming, flying, and running. Science. 1972;177(4045):222–8. - PubMed
-
- Anderson T. Biomechanics and running economy. Sports Med. 1996;22(2):76–89. - PubMed
-
- Barnes KR, Kilding AE. Running economy: measurement, norms, and determining factors. Sports Med Open. 2015;1:1–15.
-
- Fletcher JR, Esau SP, MacIntosh BR. Economy of running: beyond the measurement of oxygen uptake. J Appl Physiol. 2009;107(6):1918–22. - PubMed
-
- Margaria R, Cerretelli P, Aghemo P, Sassi G. Energy cost of running. J Appl Physiol. 1963;18(2):367–70. - PubMed
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