Running Endurance in Women Compared to Men: Retrospective Analysis of Matched Real-World Big Data
Sports medicine (Auckland, N.Z.)(2023)
摘要
Background and Objective To determine whether the gap in endurance performance between men and women is reduced as distances increase, i.e. if there is a sex difference in endurance, one can analyse the performance of elite runners, all participants, or one can pair women and men during short-distance events and examine the difference over longer distances. The first two methods have caveats, and the last method has never been performed with a large dataset. This was the goal of the present study. Methods A dataset including 38,860 trail running races from 1989 to 2021 in 221 countries was used. It provided information on 1,881,070 unique runners, allowing 7251 pairs of men and women with the same relative level of performance to be obtained, i.e. the same percentage of the winner time of the considered race on short races (25–45 km-effort) that were compared during longer races (45–260 km-effort). The effect of distance on sex differences in average speed was determined using a gamma mixed model. Results The gap between sexes decreased as distance increases, i.e. men's speed decreased by 4.02% (confidence interval 3.80–4.25) for every 10 km-effort increase, whereas it decreased by 3.25% (confidence interval 3.02–3.46) for women. The men-women ratio decreases from 1.237 (confidence interval 1.232–1.242) for a 25 km-effort to 1.031 (confidence interval 1.011–1.052) for a 260 km-effort. This interaction was modulated by the level of performance, i.e. the greater the performance level of the runner, the lower the difference in endurance between sexes. Conclusions This study shows for the first time that the gap between men and women shrinks when trail running distance increases, which demonstrates that endurance is greater in women. Although women narrow the performance gap with men as race distance increases, top male performers still outperform the top women.
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关键词
endurance,running,big data,women,real-world
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