Evidence map›Paper›PMID 31137635›Full record

ArticleInternational journal of environmental research and public health2019

Different Predictor Variables for Women and Men in Ultra-Marathon Running-The Wellington Urban Ultramarathon 2018.

Emma O'Loughlin, Pantelis T Nikolaidis, Thomas Rosemann, Beat Knechtle

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Cortical and Subcortical Brain Volume Alterations Following Endurance Running at 38.6 km and 119.2 km in Male Athletes.Medical science monitor : international medical journal of experimental and clinical research · 2021
    Article
  9. Running Performance Variability among Runners from Different Brazilian States: A Multilevel Approach.International journal of environmental research and public health · 2021
    Article
  10. Article
  11. Article
  12. Article
  13. Tower Running-Participation, Performance Trends, and Sex Difference.International journal of environmental research and public health · 2020
    Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Emma O'LoughlinTrinity Centre for Health Sciences, St James's Hospital, Dublin 8, Ireland. emolough@tcd.ie.
Pantelis T NikolaidisExercise Physiology Laboratory, 18450 Nikaia, Greece. pademil@hotmail.com.ORCID 0000-0001-8030-7122
Thomas RosemannInstitute of Primary Care, University of Zurich, 8091 Zurich, Switzerland. thomas.rosemann@usz.ch.ORCID 0000-0002-6436-6306
Beat KnechtleInstitute of Primary Care, University of Zurich, 8091 Zurich, Switzerland. beat.knechtle@hispeed.ch.ORCID 0000-0002-2412-9103

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultra-marathon races are increasing in popularity. Women are now 20% of all finishers, and this number is growing. Predictors of performance have been examined rarely for women in ultra-marathon running. This study aimed to examine the predictors of performance for women and men in the 62 km Wellington Urban Ultramarathon 2018 (WUU2K) and create an equation to predict ultra-marathon race time. For women, volume of running during training per week (km) and personal best time (PBT) in 5 km, 10 km, and half-marathon (min) were all associated with race time. For men, age, body mass index (BMI), years running, running speed during training (min/km), marathon PBT, and 5 km PBT (min) were all associated with race time. For men, ultra-marathon race time might be predicted by the following equation: (r² = 0.44, adjusted r² = 0.35, SE = 78.15, degrees of freedom (df) = 18) ultra-marathon race time (min) = -30.85 ± 0.2352 × marathon PBT + 25.37 × 5 km PBT + 17.20 × running speed of training (min/km). For women, ultra-marathon race time might be predicted by the following equation: (r² = 0.83, adjusted r

Indexed as

Athletic PerformanceRunningAdultAge FactorsAlgorithmsBody Mass IndexFemaleForecastingHumansMaleMiddle AgedTime Factorsanthropometryathleteperformancerunningultramarathon

Identifiers

PMID31137635
PMCPMC6571892

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.