Exploring the relationship between sleep patterns and cardio-renal-metabolic multimorbidity in Chinese and European...

To investigate the association between long-term sleep patterns and the incidence of cardio-renal-metabolic multimorbidity (CRMM) in Chinese and European populations, and to analyze the impact of sleep duration and quality on the risk of CRMM development.

Data were obtained from the CHARLS (n = 5,782) and SHARE (n = 12,677) cohorts, including individuals aged 45 years and older. Growth mixture modeling (GBTM) was used to identify trajectories of sleep duration, and latent class analysis (LCA) was applied to classify patterns of sleep quality. Associations between different sleep characteristics and CRMM incidence were estimated using Cox proportional hazards models, adjusting for demographic, lifestyle, and health-related covariates. Restricted cubic spline (RCS) models were employed to assess dose-response relationships, and subgroup analyses were conducted to evaluate effect modification. Finally, sensitivity analyses were performed using the Fine-Gray competing risks model, treating death as a competing event.

In the CHARLS cohort, long sleep duration was associated with a lower risk of CRMM compared with short sleep (HR = 0.64, 95% CI 0.49-0.82), whereas moderate sleep duration showed no significant difference. Compared with moderate sleep quality, good sleep quality was associated with a reduced risk of CRMM (HR = 0.58, 95% CI 0.46-0.72), while poor sleep quality was associated with an increased risk (HR = 1.30, 95% CI 1.02-1.64). In the SHARE cohort, long sleep duration (Q3) and good sleep quality were similarly associated with reduced CRMM risk (HR = 0.76, 95% CI 0.62-0.93; HR = 0.63, 95% CI 0.53-0.76, respectively). RCS analyses indicated a linear dose-response relationship, with CRMM risk decreasing as sleep duration increased. Subgroup analyses demonstrated that both long sleep duration and good sleep quality exerted beneficial effects across most population subgroups. These associations were further confirmed by sensitivity analyses using the Fine-Gray competing risks model.

Long-term sleep patterns, particularly longer sleep duration and good sleep quality, are associated with a lower risk of CRMM. Conversely, insufficient sleep and poor sleep quality increase the incidence of CRMM, underscoring the importance of adequate, high-quality sleep for CRMM prevention.