A population-based observational study using statistical modeling to assess the association between depressive symptom severity and sleep disorders in postmenopausal women.

BACKGROUND

This study aimed to investigate the association between depressive symptom severity and sleep disorders in postmenopausal women.

METHODS

This observational study included data from 4808 postmenopausal women derived from a nationally representative sample in the USA. Depressive symptom severity was assessed using the Patient Health Questionnaire-9, while sleep disorders were identified based on self-reported physician diagnoses. Weighted multivariable logistic regression models were used to analyze the association between depressive symptom severity and sleep disorders, adjusting for potential confounders. Restricted cubic splines were applied to evaluate possible nonlinear relationships, and subgroup analyses were conducted across key sociodemographic, health, and behavioral factors. Additionally, Lasso regression and logistic regression were used to identify the most influential predictors of sleep disorders. Supplementary and sensitivity analyses were performed using alternative sleep outcomes and modified depressive symptom scales to test robustness and item-level overlap.

RESULTS

Depressive symptom severity was positively associated with sleep disorders, demonstrating a dose-response relationship (P for trend < 0.001). Each unit increase in depressive symptom score was associated with a 10% higher risk of sleep disorders (OR = 1.10, 95% CI: 1.07-1.13). RCS analysis confirmed a linear association (P for nonlinear = 0.4696). Subgroup analyses identified CVD as a significant effect modifier (P for interaction = 0.019), with a stronger association in individuals with CVD (OR = 1.11, 95% CI: 1.09-1.13) compared to those without (OR = 1.07, 95% CI: 1.03-1.11). Lasso and logistic regression analyses consistently ranked depressive symptoms as the strongest predictor of sleep disorders. The association remained robust and specific across both supplementary outcomes and sensitivity models using modified depressive symptom scales.

CONCLUSIONS

This study demonstrated a linear dose-response association between depressive symptom severity and sleep disorders in postmenopausal women, which was further amplified among individuals with CVD. Depressive symptoms were identified as the most critical predictor, underscoring the importance of mental health in managing sleep health. These findings highlight the need for integrated interventions combining mental health screening, lifestyle modifications, and community-based care approaches to mitigate the dual burden of depressive symptoms and sleep disorders in this vulnerable population.