Evidence map›Paper›PMID 42516261›Full record

ArticleInternational journal of exercise science2026

Non-local Muscle Fatigue in Young and Middle-Aged Women following Fast-Paced Walking.

Kaden R Buford, Lacey N Harper, Kayla R Anderson, William J Reed, Breanna S McDonald, Rachel S Carlstrom, Garrett M Hester

Abstract read
In one paragraph

Article in International journal of exercise science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Kaden R BufordDepartment of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, USA.
Lacey N HarperDepartment of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, USA.
Kayla R AndersonDepartment of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, USA.
William J ReedDepartment of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, USA.
Breanna S McDonaldDepartment of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, USA.
Rachel S CarlstromDepartment of Molecular and Cellular Biology, Kennesaw State University, Kennesaw, USA.
Garrett M HesterDepartment of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-local muscle fatigue (NLMF) has been well-studied in young individuals following acute, higher intensity exercise; however, the effects of age on NLMF are unclear and limited research exist in women. Research examining age-related differences in NLMF following tasks mimicking everyday life such as fast-paced walking is needed. The purpose of this study was to determine the potential differences in NLMF for maximal and rapid force capacity between young and middle-aged women following an acute bout of fast-paced walking. Young (YW; n=16; 21±2 yrs) and post-menopausal, middle-aged (MW; n=14; 55±3 yrs) women completed a testing visit following a familiarization session. Handgrip testing was performed before and after a 6-min, fast-paced walking task. Maximal force, and early (0-100 ms) and late (0-200 ms) rapid force metrics were calculated from the force-time curve captured during handgrip testing. Rating of perceived exertion (0-10) was also obtained. Two-way mixed group × time ANOVAs were used to compare changes between groups. RPE was similar for YW (3.00±1.16) and MW (3.29±1.45) (p=0.560;

Indexed as

aginghandgripmuscle strengthpost-menopauseRate of force development (RFD)

Identifiers

PMID42516261
PMCPMC13405662

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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.