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Do non-elite older runners slow down more than younger runners in a 100 km ultra-marathon?

Overview of attention for article published in BMC Sports Science, Medicine and Rehabilitation, January 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

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1 news outlet
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8 X users

Citations

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30 Dimensions

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27 Mendeley
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Title
Do non-elite older runners slow down more than younger runners in a 100 km ultra-marathon?
Published in
BMC Sports Science, Medicine and Rehabilitation, January 2015
DOI 10.1186/2052-1847-7-1
Pubmed ID
Authors

Christoph A Rüst, Thomas Rosemann, Matthias A Zingg, Beat Knechtle

Abstract

This study investigated changes in normalised running speed as a proxy for effort distribution over segments in male elite and age group 100 km ultra-marathoners with the assumption that older runners would slow down more than younger runners. The annual ten fastest finishers (i.e. elite and age group runners) competing between 2000 and 2009 in the '100 km Lauf Biel' were identified. Normalised average running speed (i.e. relative to segment 1 of the race corrected for gradient) was analysed as a proxy for pacing in elite and age group finishers. For each year, the ratio of the running speed from the final to the first segment for each age cohort was determined. These ratios were combined across years with the assumption that there were no 'extreme' wind events etc. which may have impacted the final relative to the first segment across years. The ratios between the age cohorts were compared using one-way ANOVA and Tukey's post-hoc test. The ratios between elite and age group runners were investigated using one-way ANOVA with Dunnett's multiple comparison post-hoc tests. The trend across age groups was investigated using simple regression analysis with age as the dependent variable. Normalised average running speed was different between age group 18-24 years and age groups 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59 and 65-69 years. Regression analysis showed no trend across age groups (r(2) = 0.003, p > 0.05). To summarize, (i) athletes in age group 18-24 years were slower than athletes in most other age groups and (ii) there was no trend of slowing down for older athletes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 15%
Professor 3 11%
Student > Bachelor 3 11%
Student > Postgraduate 3 11%
Professor > Associate Professor 3 11%
Other 6 22%
Unknown 5 19%
Readers by discipline Count As %
Sports and Recreations 12 44%
Medicine and Dentistry 5 19%
Computer Science 1 4%
Arts and Humanities 1 4%
Psychology 1 4%
Other 1 4%
Unknown 6 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 July 2016.
All research outputs
#2,522,434
of 23,881,329 outputs
Outputs from BMC Sports Science, Medicine and Rehabilitation
#97
of 534 outputs
Outputs of similar age
#36,084
of 357,168 outputs
Outputs of similar age from BMC Sports Science, Medicine and Rehabilitation
#6
of 11 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 534 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.6. This one has done well, scoring higher than 82% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 357,168 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.