No wink of sleep: Population sleep characteristics in response to the brexit poll and the 2016 US presidential election
Abstract
Introduction: Personal well-being, including peoples sleep characteristics, is affected by a variety of factors, one example of which is wide-ranging high-impact public events. In this study, we use a large sleep database obtained through a smartphone application for sleep tracking via anonymized time-sampled data to study the effect of two political events with a wide-ranging impact on peoples sleep characteristics: the Brexit referendum in June 2016, and the presidential election of Donald Trump in November 2016 Method: Using Sleep as Android - an actigraphy-based sleep monitoring smartphone application - we collected 10.5 million geo-located sleep records from more than 69,000 users in Europe and North America.
Population-based changes in sleep around each of these two events, in the United Kingdom and in the United States of America, were assessed using a non-parametric bootstrap test Results: The analysis revealed a significant reduction by 16 min and 21 s in the mean sleep duration of British people in the night after the Brexit poll (p < 0.001). Similarly, the analysis of the US presidential election revealed a significant 12 min 49 s drop in the mean sleep duration during the night following the event, in comparison with the whole studied region (p < 0.001), and an increase by 5 min and 9 s in the subsequent night (p = 0.0328).
Additional analysis comparing the election night to comparable days in preceding years revealed that the actual reduction in sleep length may have been even greater. There is also an increase in the proportion of subjects with very short sleep Conclusions: The results demonstrate a significant impact of two specific major political events on population sleep characteristics.
Our results further underline the potential of mobile applications and informatics approaches in general to provide data that enable us to investigate fundamental physiological variables over time and location.