Imperial College London
Alternate

ProfessorStuartCook

Faculty of Medicine, Institute of Clinical Sciences

Visiting Professor
 
 
 
//

Contact

 

+44 (0)20 3313 1346stuart.cook

 
 
//

Location

 

RF 16Sydney StreetRoyal Brompton Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Teo:2019:10.1038/s42003-019-0605-1,
author = {Teo, JX and Davila, S and Yang, C and Hii, AA and Pua, CJ and Yap, J and Tan, SY and Sahlén, A and Chin, CW-L and Teh, BT and Rozen, SG and Cook, SA and Yeo, KK and Tan, P and Lim, WK},
doi = {10.1038/s42003-019-0605-1},
journal = {Commun Biol},
title = {Digital phenotyping by consumer wearables identifies sleep-associated markers of cardiovascular disease risk and biological aging.},
url = {http://dx.doi.org/10.1038/s42003-019-0605-1},
volume = {2},
year = {2019}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Sleep is associated with various health outcomes. Despite their growing adoption, the potential for consumer wearables to contribute sleep metrics to sleep-related biomedical research remains largely uncharacterized. Here we analyzed sleep tracking data, along with questionnaire responses and multi-modal phenotypic data generated from 482 normal volunteers. First, we compared wearable-derived and self-reported sleep metrics, particularly total sleep time (TST) and sleep efficiency (SE). We then identified demographic, socioeconomic and lifestyle factors associated with wearable-derived TST; they included age, gender, occupation and alcohol consumption. Multi-modal phenotypic data analysis showed that wearable-derived TST and SE were associated with cardiovascular disease risk markers such as body mass index and waist circumference, whereas self-reported measures were not. Using wearable-derived TST, we showed that insufficient sleep was associated with premature telomere attrition. Our study highlights the potential for sleep metrics from consumer wearables to provide novel insights into data generated from population cohort studies.
AU  - Teo,JX
AU  - Davila,S
AU  - Yang,C
AU  - Hii,AA
AU  - Pua,CJ
AU  - Yap,J
AU  - Tan,SY
AU  - Sahlén,A
AU  - Chin,CW-L
AU  - Teh,BT
AU  - Rozen,SG
AU  - Cook,SA
AU  - Yeo,KK
AU  - Tan,P
AU  - Lim,WK
DO  - 10.1038/s42003-019-0605-1
PY  - 2019///
TI  - Digital phenotyping by consumer wearables identifies sleep-associated markers of cardiovascular disease risk and biological aging.
T2  - Commun Biol
UR  - http://dx.doi.org/10.1038/s42003-019-0605-1
UR  - https://www.ncbi.nlm.nih.gov/pubmed/31925194
VL  - 2
ER  -
Download