Latent Class Analysis of Shift Work Patterns Among Nurses and Its Impact on Anxiety–Depression Comorbidity: A Multicenter Cross‐Sectional Study

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Objective: Relatively few population-based studies have explored the relationship between shift work patterns and anxiety-depression comorbidity among nurses. This study aimed to identify different patterns of nurse shift work and assess their association with anxiety-depression comorbidity. Design: This study was based on the Nurses' Environmental and Occupational Exposure and Health Nexus (NEON) cohort. A self-designed questionnaire was used to collect general demographic information and shift work details. Anxiety and depressive symptoms were evaluated using the generalized anxiety disorder-7 (GAD-7) and the patient health questionnaire-9 (PHQ-9), respectively. Latent class analysis (LCA) was performed to identify homogeneous groups of shift work. A three-step approach of LCA, involving logistic regression models, was applied to examine associations between various shift patterns and anxiety-depression comorbidity. Sleep quality served as a stratification factor for the subgroups. Results: = 1515, 54.28%). Binary logistic regression analysis showed that, compared with Class 2, Class 3 had increased risks of anxiety, depression, and comorbid anxiety and depression by 54.8% (OR = 1.548, 95% CI 1.304-1.838), 30.6% (OR = 1.306, 95% CI 1.096-1.555), and 47.6% (OR = 1.476, 95% CI 1.245-1.749), respectively. Moreover, Class 1 had the highest risk of these conditions in both unadjusted and adjusted models. Sleep quality had no significant modifying effect. Conclusions: This study identified distinct patterns in nurses' shift work. Different patterns were significantly associated with anxiety-depression comorbidity. Targeted interventions addressing specific shift patterns may improve nurses' mental health and contribute to achieving broader health goals.

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