The Role of Community Factors in Predicting Depressive Symptoms Among Chinese Workforce: A Longitudinal study in Rural and Urban Settings

Abstract Background: The dual urban-rural division system in China has led to distinguishes in economic development, medical services, and education as well as in mental health disparities. This study examined whether community factors (community cohesion, supportive network size, foreseeable community threat, and medical benefits coverage) predict the depressive symptoms of Chinese workers and how community factors may work differently in rural and urban settings. Methods: This secondary data analysis was conducted using data from the 2014 and 2016 China Labor-force Dynamics Survey (CLDS). The sample includes 6157 rural workers and 2983 urban workers. Results: The results indicate that rural workers have higher levels of depressive symptoms than urban workers. Medical benefits coverage predicts depressive symptoms of rural workforces (B = -.326, p <. 10), and community supportive network size predicts depressive symptoms of urban workforces (B = -.531, p <. 01). Conclusions: Policymakers may reduce depressive symptoms of rural labor through improved coverage of medical benefits. In urban areas, efforts can be made to strengthen community supportive network for the urban labor force.