Nat Sci Sleep. 2025 Aug 16;17:1853-1862. doi: 10.2147/NSS.S536854. eCollection 2025.

ABSTRACT

OBJECTIVE: This study aims to explore the independent and combined effects of sleep duration and sleep quality on depressive symptoms in the medical graduate student population, utilizing causal inference methods, in order to provide more informative evidence to support mental health interventions in this group.

METHODS: A cross-sectional study was conducted among 2591 medical graduate students from Sun Yat-sen University in Guangdong, China. Participants completed self-administered questionnaires, including the Center for Epidemiological Survey Depression Scale (CES-D) for depressive symptoms and the Pittsburgh Sleep Quality Index (PSQI) scale for sleep quality. Sleep duration was categorized based on hours of sleep per night. A causal inference approach using inverse probability weighting (IPW) was employed to evaluate the relationship between sleep factors and depression risk.

RESULTS: Individuals sleeping less than 7 hours had a 1.65-fold higher depression risk (95% CI: 1.26-2.14), while those sleeping ≥9 hours had a 0.67-fold lower risk (95% CI: 0.47-0.95). High sleep quality reduced depression risk. In the low sleep quality group, short sleep increased depression risk by 1.40-fold (95% CI: 1.02-1.94), while long sleep decreased it by 0.66-fold (95% CI: 0.45-0.97). In the high sleep quality group, sleeping 8-9 hours increased depression risk by 1.80-fold (95% CI: 1.10-2.95) compared to 7-8 hours. Sensitivity analyses confirmed the robustness of these findings across different IPW models.

CONCLUSION: Both sleep duration and quality are significantly associated with depressive symptoms among medical graduate students. These findings may support targeted interventions that improving sleep hygiene, particularly for those with low sleep quality, while also emphasizing the importance of maintaining an optimal sleep duration of 7-8 hours for those with high-quality sleep.

PMID:40852620 | PMC:PMC12367923 | DOI:10.2147/NSS.S536854