Beyond Stress: Altered Sleep-Wake Patterns are a Key Behavioral Risk Factor for Acute Insomnia During Times of Crisis

ABSTRACT

Background

Stress is a common precipitant of acute insomnia; however, reducing stress during times of crisis is challenging. This study aimed to determine which modifiable factors, beyond stress, were associated with acute insomnia during a major crisis, the COVID-19 pandemic.

Participants/Methods

A global online survey assessed sleep/circadian, stress, mental health, and lifestyle factors between April-May 2020. Logistic regression models analyzed data from 1319 participants (578 acute insomnia, 731 good sleepers), adjusted for demographic differences.

Results

Perceived stress was a significant predictor of acute insomnia during the pandemic (OR 1.23, 95% CI1.19–1.27). After adjusting for stress, individuals who altered their sleep-wake patterns (OR 3.36, CI 2.00–5.67) or increased technology use before bed (OR 3.13, CI 1.13–8.65) were at increased risk of acute insomnia. Other sleep factors associated with acute insomnia included changes in dreams/nightmares (OR 2.08, CI 1.32–3.27), increased sleep effort (OR 1.99, CI1.71–2.31) and cognitive pre-sleep arousal (OR 1.18, CI 1.11–1.24). For pandemic factors, worry about contracting COVID-19 (OR 3.08, CI 1.18–8.07) and stringent government COVID-19 restrictions (OR 1.12, CI =1.07–1.18) were associated with acute insomnia. Anxiety (OR 1.02, CI 1.01–1.05) and depressive (OR 1.29, CI 1.22–1.37) symptoms were also risk factors. A final hierarchical regression model revealed that after accounting for stress, altered sleep-wake patterns were a key behavioral predictor of acute insomnia (OR 2.60, CI 1.68–5.81).

Conclusion

Beyond stress, altered sleep-wake patterns are a key risk factor for acute insomnia. Modifiable behaviors such as maintaining regular sleep-wake patterns appear vital for sleeping well in times of crisis.

Acknowledgments

Thank you to all individuals who participated in this study. We appreciate the time and energy you took to complete this survey during the COVID-19 pandemic. We want to thank those who assisted with participant recruitment, including Dr David Cunnington, Dr Julia Stone and Ms Helen Burdette. A big thank you to our interns Stephen Ghosh, Shelley Webb, and Will Saunders, who assisted with data cleaning and coding. Lastly, thank you to A/Prof Sean W Cain, Prof David J Berlowitz and Dr Bei Bei for the valuable feedback and advice provided about this project. Hailey Meaklim is supported by an Australian Government Research Training Program Scholarship administered through Monash University.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15402002.2022.2074996

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.