An International Study on the Determinants of Poor Sleep Amongst 15,000 Users of Connected Devices

Background: sleep is a modifiable lifestyle factor that can be a target for efficient intervention studies to improve the quality of life and decrease the risk or burden of some chronic conditions. knowing the profiles of individuals with poor sleep patterns is therefore a prerequisite. wearable devices have recently opened new areas in medical research as potential efficient tools to measure lifestyle factors such as sleep quantity and quality.objectives: the goal of our research is to identify the determinants of poor sleep based on data from a large population of users of connected devices.methods: we analyzed data from 15,839 individuals (13,658 males and 2181 females) considered highly connected customers having purchased and used at least 3 connected devices from the consumer electronics company withings (now nokia). total and deep sleep durations as well as the ratio of deep/total sleep as a proxy of sleep quality were analyzed in association with available data on age,sex,weight,heart rate,steps,and diastolic and systolic blood pressures.results: with respect to the deep/total sleep duration ratio used as a proxy of sleep quality,we have observed that those at risk of having a poor ratio (≤0.40) were more frequently males (odds ratio [or]female vs male=0.45,95% ci 0.38-0.54),younger individuals (or>60 years vs 18-30 years=0.47,95% ci 0.35-0.63),and those with elevated heart rate (or>78 bpm vs ≤61 bpm=1.18,95% ci 1.04-1.34) and high systolic blood pressure (or>133 mm hg vs ≤116 mm hg=1.22,95% ci 1.04-1.43). a direct association with weight was observed for total sleep duration exclusively.conclusions: wearables can provide useful information to target individuals at risk of poor sleep. future alert or mobile phone notification systems based on poor sleep determinants measured with wearables could be tested in intervention studies to evaluate the benefits. ©guy fagherazzi,douae el fatouhi,alice bellicha,amin el gareh,aurélie affret,courtney dow,lidia delrieu,matthieu vegreville,alexis normand,jean-michel oppert,gianluca severi. originally published in the journal of medical internet research (http://www.jmir.org),23.10.2017.