Joint trajectories of sleep deviation risk and frailty and their associations with cognitive decline in middle-aged and older adults: a population-based cohort study

Few studies have investigated how the joint dynamic evolution of sleep disorders and frailty affects cognitive functions. This prospective cohort study used data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020, ultimately including 7,749 participants. Sleep duration outside the 6–8 h reference range was used to quantify abnormal sleep duration, with greater departures from this range indicating higher sleep-duration deviation. A group-based trajectory model (GBTM) was used to identify joint longitudinal patterns of sleep deviation risk and frailty, resulting in four distinct joint trajectory groups. Subsequently, Multivariate linear mixed-effects models were then used to evaluate longitudinal changes in continuous cognitive function scores across trajectory groups, while Cox proportional hazards regression models were used to estimate the risk of incident mild cognitive impairment (MCI). Compared with Group 1 (stable sleep and non-frail), Groups 2 (persistently worsening sleep with pre-frailty), 3 (worsening sleep with progressive pre-frailty), and 4 (persistently worsening sleep with worsening frailty) showed faster cognitive decline (β = −0.017, − 0.022, and − 0.044 SD/year, respectively). Compared with Group 1, Group 4 had the highest risk of incident MCI (HR = 1.48, 95% CI: 1.20–1.82). Elevated risks were also observed in Group 2 (HR = 1.20, 95% CI: 1.04–1.39) and Group 3 (HR = 1.18, 95% CI: 1.02–1.36). Compared with models based on sleep trajectories or frailty trajectories alone, the joint trajectory model yielded a lower AIC and a higher C-index, indicating superior model fit and discriminatory ability for incident MCI. Worsening joint trajectories of sleep deviation risk and frailty were associated with progressively faster cognitive decline and a higher risk of incident MCI. These joint patterns may provide a useful approach for identifying older adults at elevated cognitive risk.