Adjusted sleep efficiency (A-SE): A novel metric for assessing depression and anxiety associations in longitudinal...

Traditional sleep efficiency metrics (H-SE) incorporate non-sleep activities, potentially confounding mental health associations in bed. We proposed Adjusted Sleep Efficiency (A-SE), focusing on sleep initiation-to-maintenance process, and evaluated its depression/anxiety correlations.

Using Western China Natural Population Cohort Study data (N=3,100; 2020-2023), we compared H-SE (sleep duration/time in bed) with A-SE [sleep duration/ (sleep duration + onset latency)] × 100%. Depression (PHQ-9) and anxiety (GAD-7) symptoms were assessed. Mixed-effects models with sleep duration interaction terms evaluated associations between sleep efficiency and mental health, adjusting for covariates (e.g., age, gender). Cross-lagged panel models (CLPM) examined bidirectional relationships.

A-SE showed stronger negative correlations than H-SE with depressive (β=-0.25 vs -0.16) and anxiety symptoms (β=-0.15 vs -0.10) (all p <0.001), with a particularly pronounced association observed for depressive symptoms. A-SE's associations were independent of sleep duration, while H-SE only correlated in <7-hour sleepers (p<0.05). Females exhibited stronger A-SE-depression links (β=-0.27 vs males' -0.19). Moreover, the superior performance of A-SE remained consistent across all age groups. CLPM further confirmed that A-SE demonstrated significantly stronger negative associations with subsequent depressive symptoms (β = -0.13, p < 0.05) compared to H-SE (β = -0.11).

A-SE, by excluding non-sleep time and incorporating sleep onset latency, significantly improved the assessment accuracy of the association between sleep efficiency and mental health, particularly for depression screening and mental health monitoring in female populations. Its stability and independence establish A-SE as a valuable tool for both clinical practice and research applications.