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Changes in rural older adults’ sedentary and physically-active behaviors between a non-snowfall and a snowfall season: compositional analysis from the NEIGE study

Overview of attention for article published in BMC Public Health, August 2020
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  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

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6 X users

Citations

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8 Dimensions

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34 Mendeley
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Title
Changes in rural older adults’ sedentary and physically-active behaviors between a non-snowfall and a snowfall season: compositional analysis from the NEIGE study
Published in
BMC Public Health, August 2020
DOI 10.1186/s12889-020-09343-8
Pubmed ID
Authors

Shiho Amagasa, Shigeru Inoue, Hiroshi Murayama, Takeo Fujiwara, Hiroyuki Kikuchi, Noritoshi Fukushima, Masaki Machida, Sebastien Chastin, Neville Owen, Yugo Shobugawa

Abstract

Levels of physical activity change throughout the year. However, little is known to what extent activity levels can vary, based on accelerometer determined sedentary and physically-active time. The aim of this longitudinal study was to examine older adults' activity changes from a non-snowfall season to a subsequent snowfall season, with consideration of the co-dependence of domains of time use. Participants were 355 older Japanese adults (53.1% women, aged 65-84 years) living in a rural area of heavy snowfall who had valid accelerometer (Active style Pro HJA-750C) data during non-snowfall and snowfall seasons. Activity was classified as sedentary behavior (SB), light-intensity PA (LPA), and moderate-to-vigorous PA (MVPA). Compositional changes from the non-snowfall to the snowfall season were analyzed using Aitchison's perturbation method. The ratios of each component in the composition, such as [SBsnow/SBnon-snow, LPAsnow/LPAnon-snow, MVPAsnow/MVPAnon-snow] for seasonal changes, were calculated and were then divided by the sum of these ratios. In men, the percentages of time spent in each activity during the non-snowfall/snowfall seasons were 53.9/64.6 for SB; 40.8/31.6 for LPA; and 5.3/3.8 for MVPA; these corresponded to mean seasonal compositional changes (∆SB, ∆LPA, ∆MVPA) of 0.445, 0.287, and 0.268 respectively. In women, the percentages of time spent in each activity during the non-snowfall/snowfall seasons were 47.9/55.5 for SB; 47.9/41.0 for LPA; and 4.2/3.5 for MVPA; these corresponded to mean seasonal compositional changes (∆SB, ∆LPA, ∆MVPA) of 0.409, 0.302, and 0.289 respectively. The degree of seasonal change was greatest in men. In older adults, activity behaviors were changed unfavorably during snowfall season, particularly so for men. The degree of seasonal change was greatest for SB. Development of strategies to keep rural older adults active during the snowfall season may be needed for maintaining a consistently-active lifestyle for their health.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 12%
Student > Bachelor 3 9%
Researcher 3 9%
Professor > Associate Professor 2 6%
Student > Master 2 6%
Other 3 9%
Unknown 17 50%
Readers by discipline Count As %
Nursing and Health Professions 4 12%
Medicine and Dentistry 4 12%
Sports and Recreations 2 6%
Materials Science 2 6%
Social Sciences 1 3%
Other 3 9%
Unknown 18 53%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 August 2020.
All research outputs
#6,370,681
of 23,232,430 outputs
Outputs from BMC Public Health
#6,659
of 15,166 outputs
Outputs of similar age
#137,534
of 400,498 outputs
Outputs of similar age from BMC Public Health
#132
of 283 outputs
Altmetric has tracked 23,232,430 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 15,166 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one has gotten more attention than average, scoring higher than 55% 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 400,498 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 283 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 52% of its contemporaries.