Pre-existing sleep disturbances and risk of COVID-19: a meta-analysis

Background Sleep disturbances are widespread but usually overlooked health risk factors for coronavirus disease 2019 (COVID-19). We aimed to investigate the influence of pre-existing sleep disturbances on the susceptibility, severity, and long-term effects of COVID-19. Methods We searched PubMed, Web of Science, and Embase for relevant articles from inception to October 27, 2023 and updated at May 8, 2024. Sleep disturbances included obstructive sleep apnea (OSA), insomnia, abnormal sleep duration, night-shift work, and any other sleep disturbances. Outcomes were COVID-19 susceptibility, hospitalization, mortality, and long COVID. The effect sizes were pooled odds ratios (ORs) and 95% confidence intervals (95% CIs). This study is registered with PROSPERO (CRD42024503518). Findings A total of 48 observational studies (n = 8,664,026) were included. Pre-existing sleep disturbances increased the risk of COVID-19 susceptibility (OR = 1.12, 95% CI 1.07-1.18), hospitalization (OR = 1.25, 95% CI 1.15-1.36), mortality (OR = 1.45, 95% CI 1.19-1.78), and long COVID (OR = 1.36 95% CI 1.17-1.57). Subgroup analysis showed that younger individuals with sleep disturbances were associated with higher susceptibility and hospitalization and a lower risk of mortality than older individuals. Males with sleep disturbances were associated with higher mortality. For specific sleep disturbances, the susceptibility and hospitalization of COVID-19 were associated with OSA, abnormal sleep duration, and night-shift work; mortality of COVID-19 was linked to OSA; risk of long COVID was related to OSA, abnormal sleep duration and insomnia. Interpretation Pre-existing sleep disturbances, especially OSA, increased the risk of COVID-19 susceptibility, hospitalization, mortality, and long COVID. Age and sex played important roles in the effect of sleep disturbances on COVID-19. Funding The National Natural Science Foundation of China and the Key Laboratory of Respiratory Diseases of Liaoning Province. Copyright (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).