Depression and anxiety · 2026
Latent Class Analysis of Shift Work Patterns Among Nurses and Its Impact on Anxiety-Depression Comorbidity: A Multicenter Cross-Sectional Study.
СтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Zhao Chen, Shi Xuezhi, Fan Meng, Huang Min, Yang Yajuan, Niu Yaqian, Zhang Miao, Xu Wendi, Deng Yapeng, Jin Mei, Hu Xinyu, Tang Ying, Jiang Minmin, Tao Fangbiao, Wang Heping, Wu Xiaoyan
Аннотация
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: Three latent classes were identified among 2791 shift nurses: Class 1: high-frequency, high-seniority group (N = 441, 15.80%); Class 2: low-frequency, low-seniority group (N = 835, 29.92%); Class 3: low-frequency, high-seniority group (N = 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.
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: Three latent classes were identified among 2791 shift nurses: Class 1: high-frequency, high-seniority group (N = 441, 15.80%); Class 2: low-frequency, low-seniority group (N = 835, 29.92%); Class 3: low-frequency, high-seniority group (N = 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.