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.
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Friday, November 22, 2019
Evidence for premature aging caused by insufficient sleep.
I have come to realize in the past year or so that my physical and mental robustness require getting at least seven, and preferably eight, hours of sleep every night. Thus I was intrigued by finding an extensive and well documented study by Teo et al. (open source) showing that telomeres, sequences of DNA on the end of chromosomes taken as a marker of biological aging, are, on average, 356 base pairs shorter in study participants who slept for fewer than five hours per night than in those who slept for seven hours.
They found that sleep metrics were reported more accurately by wearable fitness trackers than by self report. Here is the abstract of their article, titled "Digital phenotyping by consumer wearables identifies sleep-associated markers of cardiovascular disease risk and biological aging."
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