Investigating the impact of sleep traits on myocardial infarction: A systematic review and meta-analysis

Sleep characteristics such as insomnia and duration have become increasingly recognized as possible risk factors for cardiovascular outcomes. The purpose of this meta-analysis was to clarify the epidemiological and dose-response associations between specific sleep features and the risk of MI. A systematic review and meta-analysis were conducted following PRISMA guidelines. Literature was systematically searched through September 2024 in three biomedical and multidisciplinary databases, PubMed (Medline), Scopus, Web of Science. Random-effects meta-analysis were performed using REML estimation to account for between-study variability. Furthermore, a dose response meta-analysis was done to explore potential linear and/or non-linear associations between exposure and MI risk. All analyses were conducted in R using the meta, metafor, and dosresmeta packages. Additionally, sensitivity analysis was conducted to evaluate the robustness and stability of the findings. A total of 13 high-quality observational studies (11 cohort, 2 case-control) were included, with over 1.9 million participants and more than 41,000 incident MI events in various populations. Insomnia as the exposure was evaluated in 6 cohort studies. The summary effect estimate indicated 9% greater risk of MI (RR = 1.09; 95% CI: 1.03–1.17), consistent findings across types of studies and robust in sensitivity analyses. There was moderate heterogeneity (I² = 60%). Sleep duration was examined as the exposure in 5 cohort studies. The linear sleep duration model did not reach statistical significance (RR = 1.05; 95% CI: 0.94–1.17), but results from the dose-response analysis found a U-shaped pattern, with higher MI risk being associated with both short and long sleep durations. The lowest point of risk was found around 7.5–8 hours of sleep per night. This meta-analysis confirms the independent nature of Insomnia as a CVD risk factor, and underscores the complicated, non-linear relationship between sleep duration and MI. The addition of sleep phenotyping in the cardiovascular risk assessment model is clinically actionable and epidemiologically supported. Beyond this, future research should prioritize objective measures of sleep, longitudinal cohorts and genomic stratification to inform causal inference. At large, however, sleep ought to be understood as an active driver of CVH and given its due place in prevention of IHD.