Literature DB >> 32667039

Investigating the within-person relationships between activity levels and sleep duration using Fitbit data.

Yue Liao1, Michael C Robertson1, Andrea Winne2, Ivan H C Wu3, Thuan A Le1, Diwakar D Balachandran4, Karen M Basen-Engquist1.   

Abstract

The advancement of wearable technologies provides opportunities to continuously track individuals' daily activity levels and sleep patterns over extended periods of time. These data are useful in examining the reciprocal relationships between physical activity and sleep at the intrapersonal level. The purpose of this study is to test the bidirectional relationships between daily activity levels and sleep duration. The current study analyzed activity and sleep data collected from a Fitbit device as part of a 6 month employer-sponsored weight loss program. A total of 105 overweight/obese adults were included (92% female, 70% obese, and 44% Hispanic). Multilevel models were used to examine (a) whether daily active and sedentary minutes predicted that night's sleep duration and (b) whether sleep duration predicted active and sedentary minutes the following day. Potential extended effects were explored by using a 2 day average of the activity minutes/sleep duration as the predictor. No significant relationships between active minutes and sleep duration were found on a daily basis. However, having less sleep over two nights than one's usual level was associated with an increased likelihood of engaging in some physical activity the following day. There was a significant bidirectional negative association between sedentary minutes and sleep duration for both the daily and 2 day models. Data from wearable trackers, such as Fitbit, can be used to investigate the daily within-person relationship between activity levels and sleep duration. Future studies should investigate other sleep metrics that may be obtained from wearable trackers, as well as potential moderators and mediators of daily activity levels and sleep. © Society of Behavioral Medicine 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Free-living; Multilevel modeling; Obesity; Physical activity; Sleep tracker; Wearable technologies

Year:  2021        PMID: 32667039      PMCID: PMC7963288          DOI: 10.1093/tbm/ibaa071

Source DB:  PubMed          Journal:  Transl Behav Med        ISSN: 1613-9860            Impact factor:   3.046


  32 in total

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