Factors associated with depressive symptoms among the elderly in China: structural equation model.

OBJECTIVES

To establish a structural equation model for exploring the direct and indirect relationships of depressive symptoms and their associated factors among the Chinese elderly population.

DESIGN

A cross-sectional research. The 2015 data from the China Health and Retirement Longitudinal Study (CHARLS) were adopted.

SETTING

CHARLS is an ongoing longitudinal study assessing the social, economic, and health status of nationally representative samples of middle-aged and elderly Chinese residents.

PARTICIPANTS

A total of 5791 participants aged 60 years and above were included.

MEASUREMENTS

Depressive symptoms were used as the study outcome. Sociodemographic characteristics, poor health status, unhealthy habits, and sleep duration were used as predictors. Confirmatory factor analysis was first conducted to test the latent variables. Structural equation model was then utilized to examine the associations among latent variables and depressive symptoms.

RESULTS

The mean age of the participants was 68.82 ± 6.86 years, with 55.53% being males. The total prevalence of depressive symptoms was 37.52%. The model paths indicated that sociodemographic characteristics, poor health status, unhealthy habits, and sleep duration were directly associated with depressive symptoms, and the effects were 0.281, 0.509, -0.067, and -0.162, respectively. Sociodemographic characteristics, unhealthy habits, and sleep duration were indirectly associated with depressive symptoms, mediating by poor health status. Their effects on poor health status were -0.093, 0.180, and -0.279, respectively. All paths of the model were significant (P < 0.001). The model could explain 40.9% of the variance in the depressive symptoms of the Chinese elderly population.

CONCLUSIONS

Depressive symptoms were significantly associated with sociodemographic characteristics, poor health status, unhealthy habits, and sleep duration among Chinese elderly population. The dominant predictor of depressive symptoms was poor health status. Targeting these results might be helpful in rationally allocating health resources during screening or other mental health promotion activities for the elderly.