Evidence map›Paper›PMID 34764435›Full record

ArticleScientific reports2021

Measurement of various intensities of physical activities and categorization of "Locomotive" and "Household" activities provide a subject-specific detailed assessment.

Ryuichiro Inaba, Satoshi Yamakawa, Takashi Kanamoto, Sho Ukimoto, Seira Sato, Issei Ogasawara, Shoji Konda, Teruki Yokoyama, Yuko Ueda, Takashi Onuki and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

11 authors.

Ryuichiro InabaDepartment of Medicine for Sports and Performing Arts, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan.
Satoshi YamakawaDepartment of Sports Medical Biomechanics, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan.
Takashi KanamotoDepartment of Medicine for Sports and Performing Arts, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan.
Sho UkimotoDepartment of Medicine for Sports and Performing Arts, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan.
Seira SatoDepartment of Medicine for Sports and Performing Arts, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan.
Issei OgasawaraDepartment of Biomechanics and Motor Control, Graduate School of Medicine, Osaka University, Toyonaka, Osaka, 560-0043, Japan.
Shoji KondaDepartment of Biomechanics and Motor Control, Graduate School of Medicine, Osaka University, Toyonaka, Osaka, 560-0043, Japan.
Teruki YokoyamaDepartment of Medicine for Sports and Performing Arts, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan.
Yuko UedaDepartment of Medicine for Sports and Performing Arts, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan.
Takashi OnukiDepartment of Sports Medical Science, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan.
Ken NakataDepartment of Medicine for Sports and Performing Arts, Graduate School of Medicine, Osaka University, Suita, Osaka, 565-0871, Japan. ken.nakata7@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to compare the physical activity (PA) measured by a wearable sensor device (WSD) and the step count measurement, and to investigate the association between PAs and lifestyle. Data of 301 participants were collected from March 2019 to March 2021. Step counts, sedentary behavior, performance time of light/moderate/vigorous PA, METs × hour of "Locomotive" and "Household" categorized activities, and energy expenditure (EE) were measured by the WSD, respectively. Furthermore, the participants were classified into student, standing worker, and sitting worker groups. Data were analyzed using the Steel-Dwass and Pearson correlation coefficient tests. The correlation between the performance time of each PA and step count was weak, except for moderate PA. "Household" EE and step count also had a weak correlation. In the comparison of lifestyle, there was a significant difference in the mean performance time of each type of PA between the groups. Additionally, the standing worker and sitting worker groups had a significant difference in METs × hour of "Household" activities, indicating that the difference between the occupations is reflected in "Household" activities. The WSD measurement can be used to evaluate detailed individual PA, whereas the step count measurement showed weakness in the PA estimation.

Indexed as

AccelerometryAdultEnergy MetabolismExerciseFemaleHumansLife StyleMaleMiddle AgedMotor ActivitySedentary BehaviorWearable Electronic DevicesYoung Adult

Identifiers

PMID34764435
PMCPMC8585886

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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.