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健康习惯与可穿戴活动追踪器设备:分析性横断面研究。

Health Habits and Wearable Activity Tracker Devices: Analytical Cross-Sectional Study.

机构信息

Unidad de Investigación en Fisioterapia, Universidad de Zaragoza, Domingo Miral, s/n, 50009 Zaragoza, Spain.

School of Health Professions, University of Mary Hardin Baylor, 900 College St., Belton, TX 76513, USA.

出版信息

Sensors (Basel). 2022 Apr 12;22(8):2960. doi: 10.3390/s22082960.

DOI:10.3390/s22082960
PMID:35458945
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9031391/
Abstract

Wearable activity trackers are electronic devices that facilitate self-monitoring of information related to health. The purpose of this study was to examine the use of tracker devices to record daily activity (calories) and its associations with gender, generation, BMI, and physical activity behavior of United States of America resident adults; a cross-sectional study in 892 subjects recruited to participate in an anonymous online survey was performed. Being female increased the odds of using a tracker device by 2.3 times. Having low cardiovascular disease mortality risk related to time spent sitting increased the odds for using a tracker device by 2.7 times, and having medium risk 1.9 times, with respect to having high risk. For every 1-point increase in BMI, the odds for using a tracker device increased by 5.2%. Conclusions: Subjects who had ever used any tracker device had a higher BMI. The use of tracker devices was related to lower cardiovascular disease mortality risk related to sitting time. The amount of physical activity and the time spent walking were not associated with the usage of tracker devices. It is possible that the user of tracker devices should be supported by professionals to implement deep change in health habits.

摘要

可穿戴活动追踪器是一种电子设备,方便人们自我监测与健康相关的信息。本研究旨在探讨追踪器设备在记录日常活动(卡路里)方面的使用情况,及其与美国居民成年人的性别、代际、BMI 和身体活动行为的关系;对 892 名参与匿名在线调查的受试者进行了横断面研究。女性使用追踪器设备的几率增加了 2.3 倍。与久坐时间相关的心血管疾病死亡率低风险使使用追踪器设备的几率增加了 2.7 倍,而中风险增加了 1.9 倍,高风险增加了 2.7 倍。BMI 每增加 1 点,使用追踪器设备的几率就会增加 5.2%。结论:曾经使用过任何追踪器设备的受试者 BMI 更高。使用追踪器设备与与久坐时间相关的心血管疾病死亡率低风险有关。身体活动量和步行时间与追踪器设备的使用无关。可能需要专业人员支持追踪器设备的使用者,以实现健康习惯的深刻改变。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60a6/9031391/3ec39547a3ed/sensors-22-02960-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60a6/9031391/d1b729d5b778/sensors-22-02960-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60a6/9031391/c8a7b25b2387/sensors-22-02960-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60a6/9031391/3ec39547a3ed/sensors-22-02960-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60a6/9031391/d1b729d5b778/sensors-22-02960-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60a6/9031391/c8a7b25b2387/sensors-22-02960-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/60a6/9031391/3ec39547a3ed/sensors-22-02960-g003.jpg

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Sensors (Basel). 2022 Feb 10;22(4):1348. doi: 10.3390/s22041348.
3
Sleep and COVID-19. A Case Report of a Mild COVID-19 Patient Monitored by Consumer-Targeted Sleep Wearables.睡眠与 COVID-19:通过面向消费者的睡眠可穿戴设备监测的轻度 COVID-19 患者病例报告。
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J Cardiovasc Dev Dis. 2024 Oct 21;11(10):336. doi: 10.3390/jcdd11100336.
4
Body Mass Index and Its Influence on Chronic Low Back Pain in the Spanish Population: A Secondary Analysis from the European Health Survey (2020).体重指数及其对西班牙人群慢性下腰痛的影响:来自欧洲健康调查(2020年)的二次分析
Biomedicines. 2023 Aug 2;11(8):2175. doi: 10.3390/biomedicines11082175.
5
Association of Generation and Group Size With the Usage of a Mobile Health App in Thailand: Secondary Analysis of the ThaiSook Cohort Study.泰国世代和群体规模与移动健康应用程序使用的关联:泰国 Sook 队列研究的二次分析。
J Med Internet Res. 2023 Aug 17;25:e45374. doi: 10.2196/45374.
6
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JMIR Form Res. 2023 Jun 30;7:e45298. doi: 10.2196/45298.
7
Are Activity Wrist-Worn Devices Accurate for Determining Heart Rate during Intense Exercise?活动腕戴式设备在剧烈运动期间测定心率准确吗?
Bioengineering (Basel). 2023 Feb 15;10(2):254. doi: 10.3390/bioengineering10020254.
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4
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8
Using Fitbit data to examine factors that affect daily activity levels of college students.利用 Fitbit 数据来研究影响大学生日常活动水平的因素。
PLoS One. 2021 Jan 6;16(1):e0244747. doi: 10.1371/journal.pone.0244747. eCollection 2021.
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Behavior Change Techniques in Wrist-Worn Wearables to Promote Physical Activity: Content Analysis.腕戴可穿戴设备中促进身体活动的行为改变技术:内容分析。
JMIR Mhealth Uhealth. 2020 Nov 19;8(11):e20820. doi: 10.2196/20820.
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Wearable device adoption among older adults: A mixed-methods study.老年人对可穿戴设备的采用情况:一项混合方法研究。
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