The Relationship Between Daily Activity Level, Posture Distribution, Stepping Patterns, and Cadence in the BCS70 Cohort

This study investigated the relationship between stepping-defined daily activity levels, time spent in different postures, and the patterns and intensities of stepping behaviour. Using a thigh-mounted triaxial accelerometer, physical activity data from 3547 participants with seven days of valid data were analysed. We classified days based on step count and quantified posture and stepping behaviour, distinguishing between indoor, community, and recreation stepping. The results indicated significant differences in time spent in upright (2.5 to 8.9 h, <i>p</i> < 0.05), lying (8.0 to 9.1 h, <i>p</i> < 0.05), and sedentary (7.0 to 13.0 h, <i>p</i> < 0.05) postures across activity levels. At higher daily activity levels (10,000-15,000 steps), individuals tended to spend approximately equal time in each posture (8 h lying, 8 h sitting, and 8 h upright). The study found that at lower stepping-defined activity levels, step volumes were driven primarily by indoor stepping, while at higher activity levels, outdoor and recreation stepping were larger contributors. Additionally, stepping classified as indoor had significantly slower cadences compared to outdoor stepping. These findings suggest that the composition and intensity of stepping behaviours vary significantly with daily activity volumes, providing insights that could enhance public health messaging and interventions aimed at promoting physical activity.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2024-12-20
DOI
https://doi.org/10.3390/s24248135
Citations
1
Primary Topic
Physical Activity and Health
Type
article
Field-Weighted Citation Impact
0.33

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Relationship Between Daily Activity Level, Posture Distribution, Stepping Patterns, and Cadence in the BCS70 Cohort

Malcolm Granat, Emmanuel Stamatakis, Mark Hamer, Matthew N. Ahmadi et al.
1 citations
Sensors
Physical Activity and Health
0.33
article

The Relationship Between Daily Activity Level, Posture Distribution, Stepping Patterns, and Cadence in the BCS70 Cohort

Malcolm Granat, Emmanuel Stamatakis, Mark Hamer, Matthew N. Ahmadi, Craig Speirs
article en
1 citations

Abstract

This study investigated the relationship between stepping-defined daily activity levels, time spent in different postures, and the patterns and intensities of stepping behaviour. Using a thigh-mounted triaxial accelerometer, physical activity data from 3547 participants with seven days of valid data were analysed. We classified days based on step count and quantified posture and stepping behaviour, distinguishing between indoor, community, and recreation stepping. The results indicated significant differences in time spent in upright (2.5 to 8.9 h, <i>p</i> < 0.05), lying (8.0 to 9.1 h, <i>p</i> < 0.05), and sedentary (7.0 to 13.0 h, <i>p</i> < 0.05) postures across activity levels. At higher daily activity levels (10,000-15,000 steps), individuals tended to spend approximately equal time in each posture (8 h lying, 8 h sitting, and 8 h upright). The study found that at lower stepping-defined activity levels, step volumes were driven primarily by indoor stepping, while at higher activity levels, outdoor and recreation stepping were larger contributors. Additionally, stepping classified as indoor had significantly slower cadences compared to outdoor stepping. These findings suggest that the composition and intensity of stepping behaviours vary significantly with daily activity volumes, providing insights that could enhance public health messaging and interventions aimed at promoting physical activity.

SensorsVol. 24(24)
The University of Sydney (AU), University of Strathclyde (GB), University College London (GB), University of Salford (GB)
British Heart Foundation
Openalex Percentile: Top 35%
Physical Activity and Health
0.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.