today.ucsd.edu
Edward Wang, a faculty member in the UC San Diego Department of Electrical and Computer Engineering, is one of the paper's senior authors.
In this new paper published June 20, the research team modified the technique used in previous research that had been the largest similar investigation of sleep to date, which had drawn approximately 103,000 nights of data from the UK biobank. That previous study looked at sleep timing and awakenings and many related features, and then constructed a "landscape" of where nights fell in relation to each other. But prior researchers did not do two key things: they could not look across time, as they had only two to three nights per person; and they could not tie the resulting patterns of sleep to health outcomes.
Other large-scale sleep analyses looked at high-level differences in simple sleep characteristics, like the total time people spent asleep.
In contrast, this new work is the first to show that researchers can quantify the changing dynamics of people's sleep over time and use this quantification to give people better insights into their sleep health. The research also suggests that these changes in sleep may indicate a higher risk for a wide range of conditions.
Paper
“Five million nights: temporal dynamics in human sleep phenotypes” in the journal npj Digital Medicine
Paper authors
Varun K. Viswanath, Wendy Hartogenesis, Stephan Dilchert, Leena Pandya, Frederick M. Hecht, Ashley E. Mason, Edward J. Wang, and Benjamin L. Smarr
Author affiliations
Department of Electrical and Computer Engineering, Jacobs School of Engineering, University of California, San Diego; Osher Center for Integrative Health, University of California, San Francisco; Zicklin School of Business, Baruch College, The City University of New York; Shu Chien—Gene Lay Department of Bioengineering, Jacobs School of Engineering, University of California, San Diego; Halıcıoğlu Data Science Institute, University of California, San Diego
Corresponding author: Varun K. Viswanath vkviswan@ucsd.edu
Funding Acknowledgments
This effort was funded under MTEC solicitation MTEC-20-12-Diagnostics-023 and the USAMRDC under the Department of Defense (#MTEC-20-12-COVID19-D.-023). The #StartSmall foundation (#7029991), and Oura Health Oy (#134650) also provided funding for this work. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the U.S. Government.