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BCS70队列中日常活动水平、姿势分布、步行动态和步频之间的关系。

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

作者信息

Speirs Craig, Ahmadi Matthew, Hamer Mark, Stamatakis Emmanuel, Granat Malcolm

机构信息

PAL Technologies Ltd., Glasgow G4 0TQ, UK.

Department of Computer and Information Sciences, University of Strathclyde, Glasgow G1 1XH, UK.

出版信息

Sensors (Basel). 2024 Dec 20;24(24):8135. doi: 10.3390/s24248135.

DOI:10.3390/s24248135
PMID:39771870
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11678979/
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, < 0.05), lying (8.0 to 9.1 h, < 0.05), and sedentary (7.0 to 13.0 h, < 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.

摘要

本研究调查了步数定义的日常活动水平、在不同姿势下花费的时间以及步行行为的模式和强度之间的关系。使用佩戴在大腿上的三轴加速度计,对3547名参与者的7天有效身体活动数据进行了分析。我们根据步数对天数进行分类,并对姿势和步行行为进行量化,区分室内、社区和休闲步行。结果表明,不同活动水平下,站立(2.5至8.9小时,<0.05)、躺卧(8.0至9.1小时,<0.05)和久坐(7.0至13.0小时,<0.05)姿势所花费的时间存在显著差异。在较高的日常活动水平(10000 - 15000步)下,个体在每种姿势下花费的时间大致相等(躺卧8小时、坐着8小时、站立8小时)。研究发现,在步数定义的较低活动水平下,步数主要由室内步行驱动,而在较高活动水平下,户外和休闲步行的贡献更大。此外,与户外步行相比,室内步行的步频明显较慢。这些发现表明,步行行为的组成和强度随每日活动量的变化而显著不同,为加强旨在促进身体活动的公共卫生信息传播和干预措施提供了见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de1a/11678979/499d43ed10c6/sensors-24-08135-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de1a/11678979/af667ff312fb/sensors-24-08135-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de1a/11678979/3fea41afbbc1/sensors-24-08135-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de1a/11678979/1168efcf34ab/sensors-24-08135-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de1a/11678979/499d43ed10c6/sensors-24-08135-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de1a/11678979/af667ff312fb/sensors-24-08135-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de1a/11678979/3fea41afbbc1/sensors-24-08135-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de1a/11678979/1168efcf34ab/sensors-24-08135-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de1a/11678979/499d43ed10c6/sensors-24-08135-g004.jpg

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本文引用的文献

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