Evidence map›Paper›PMID 32001789›Full record

ArticleScientific reports2020

Estimation of energy consumed by middle-aged recreational marathoners during a marathon using accelerometry-based devices.

Carlos Hernando, Carla Hernando, Ignacio Martinez-Navarro, Eladio Collado-Boira, Nayara Panizo, Barbara Hernando

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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

8 citing papers in PubMed.

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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

6 authors.

Carlos HernandoSport Service, Jaume I University, Castellon, Spain. hernando@uji.es.
Carla HernandoDepartment of Mathematics, Carlos III University of Madrid, Madrid, Spain.
Ignacio Martinez-NavarroDepartment of Physical Education and Sport, University of Valencia, Valencia, Spain.
Eladio Collado-BoiraFaculty of Health Sciences, Jaume I University, Castellon, Spain.
Nayara PanizoFaculty of Health Sciences, Jaume I University, Castellon, Spain.
Barbara HernandoDepartment of Medicine, Jaume I University, Castellon, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As long-distance races have substantially increased in popularity over the last few years, the improvement of training programs has become a matter of concern to runners, coaches and health professionals. Triaxial accelerometers have been proposed as a one of the most accurate tools to evaluate physical activity during free-living conditions. In this study, eighty-eight recreational marathon runners, aged 30-45 years, completed a marathon wearing a GENEActiv accelerometer on their non-dominant wrist. Energy consumed by each runner during the marathon was estimated based on both running speed and accelerometer output data, by applying the previously established GENEActiv cut-points for discriminating the six relative-intensity activity levels. Since accelerometry allowed to perform an individualized estimation of energy consumption, higher interpersonal differences in the number of calories consumed by a runner were observed after applying the accelerometry-based approach as compared to the speed-based method. Therefore, pacing analyses should include information of effort intensity distribution in order to adjust race pacing appropriately to achieve the marathon goal time. Several biomechanical and physiological parameters (maximum oxygen uptake, energy cost of running and running economy) were also inferred from accelerometer output data, which is of great value for coaches and doctors.

Indexed as

AccelerometryAdultAthletesAthletic PerformanceEnergy MetabolismExerciseFemaleHumansMaleOxygenOxygen ConsumptionRunningOxygen

Identifiers

PMID32001789
PMCPMC6992743

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.