Meta-analysis of associated factors of sleep disorders in elderly patients with coronary heart disease.

BACKGROUND: This meta-analysis aimed to identify the factors associated with sleep disorders in elderly patients with coronary heart disease. METHODS: All eligible published studies were retrieved via comprehensive manual and electronic searches across eight mainstream Chinese and English databases, including PubMed, Embase, Web of Science, the Cochrane Library, CBM, CNKI, Wanfang Database, and VIP. The search period covered all records from the establishment of each database up to January 1, 2026. Two independent researchers separately performed literature screening, methodological quality evaluation, and data extraction to avoid mutual interference. All quantitative pooled analyses were conducted using Stata 14.0 statistical software. RESULTS: This study ultimately incorporated 22 eligible studies involving 19, 454 elderly patients with coronary heart disease (CHD). Among these enrolled studies, 9 were included for quantitative pooled analysis. Pooled estimates demonstrated significant associations between multiple clinical and demographic factors and sleep disorders in this elderly CHD patient population. Specifically, meta-analysis results showed that diabetes (OR = 1.24, 95% CI: 1.08-1.43), female sex (OR = 2.32, 95% CI: 1.71-3.13), low monthly household income (OR = 3.21, 95% CI: 2.12-4.84), and chronic gastritis (OR = 2.17, 95% CI: 1.54-3.05) were significant risk factors for sleep disorders (all p < 0.05). CONCLUSION: Sleep disorders are a critical comorbidity in elderly patients with coronary heart disease, underscoring the urgent need to explore the underlying factors linked to such sleep disturbances. Healthcare administrators can leverage these findings to optimize relevant prevention and management strategies. Identification of high-risk individuals and implementation of targeted interventions enables clinicians to effectively reduce the incidence and severity of sleep disturbances in this CHD patient population.Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD420251117697.