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A novel integrative procedure for identifying and integrating three-dimensions of objectively measured free-living sedentary behaviour

Overview of attention for article published in BMC Public Health, December 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
A novel integrative procedure for identifying and integrating three-dimensions of objectively measured free-living sedentary behaviour
Published in
BMC Public Health, December 2017
DOI 10.1186/s12889-017-4994-0
Pubmed ID
Authors

Anna Myers, Catherine Gibbons, Edward Butler, Michelle Dalton, Nicola Buckland, John Blundell, Graham Finlayson

Abstract

The widely accepted definition of sedentary behaviour [SB] refers to any waking behaviour characterized by an energy expenditure ≤1.5 metabolic equivalents [METs] while in a sitting or reclining posture. At present, there is no single field-based device which objectively measures sleep, posture and activity intensity simultaneously. The aim of this study was to develop a novel integrative procedure [INT] to combine information from two validated activity monitors on sleep, activity intensity and posture, the three key dimensions of SB. Participants in this analysis were initially recruited from a series of three studies conducted between December 2014 and June 2016 at the University of Leeds. Sixty-three female participants aged 37.1 (13.6) years with a body mass index of 29.6 (4.7) kg/m2 were continuously monitored for 5-7 days with the SenseWear Armband [SWA] (sleep and activity intensity) and the activPAL [AP] (posture). Data from both activity monitors were analysed separately and integrated resulting in three measures of sedentary time. Differences in Sedentary time between the three measurement methods were assessed as well as how well the three measures correlated. The three measures of sedentary time were positively correlated, with the weakest relationship between SEDSWA (awake and <1.5 METs) and SEDAP (awake and sitting/lying posture) [r(61) = .37,p = .003], followed by SEDSWA and SEDINT (awake, <1.5 METs and sitting/lying posture) [r(61) = .58,p < .001], and the strongest relationship was between SEDAP and SEDINT [r(61) = .91,p < .001]. There was a significant difference between the three measures of sedentary time [F(1.18,73.15) = 104.70,p < .001]. Post-hoc tests revealed all three methods differed significantly from each other [p < .001]. SEDSWA resulted in the most sedentary time 11.74 (1.60) hours/day, followed by SEDAP 10.16 (1.75) hours/day, and SEDINT 9.10 (1.67) hours/day. Weekday and weekend day sedentary time did not differ for any of the measurement methods [p = .04-.25]. Information from two validated activity monitors was combined to obtain an objective measure of free-living SB based on posture and activity intensity during waking hours. The amount of sedentary time accumulated varied according to the definition of SB and its measurement. The novel data integration and processing procedures presented in this paper represents an opportunity to investigate whether different components of SB are differentially related to health end points.

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The data shown below were collected from the profiles of 9 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 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 18%
Researcher 8 11%
Student > Bachelor 8 11%
Other 5 7%
Student > Master 5 7%
Other 12 17%
Unknown 20 28%
Readers by discipline Count As %
Sports and Recreations 12 17%
Nursing and Health Professions 10 14%
Medicine and Dentistry 7 10%
Social Sciences 3 4%
Arts and Humanities 3 4%
Other 10 14%
Unknown 26 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 03 January 2018.
All research outputs
#4,818,569
of 23,316,003 outputs
Outputs from BMC Public Health
#5,332
of 15,202 outputs
Outputs of similar age
#104,260
of 443,579 outputs
Outputs of similar age from BMC Public Health
#117
of 218 outputs
Altmetric has tracked 23,316,003 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,202 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 64% 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 443,579 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 218 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.