ArticleBMC public health2022
The role of community factors in predicting depressive symptoms among Chinese workforce: a longitudinal study in rural and urban settings.
Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 13 citations in OpenAlex.
- Decomposition analysis of differences in depressive symptoms between agricultural and non-agricultural workers in China.BMC public health · 2025Article
- Urban-Rural Disparities in Depressive Symptoms Among Employed Individual: Education Plays an Important Role.Psychology research and behavior management · 2025Article
- Psychache status and associated contributing factors among the Hakka elderly in Fujian, China.BMC psychiatry · 2024Article
- Inequity in the healthcare utilization among latent classes of elderly people with chronic diseases and decomposition analysis in China.BMC geriatrics · 2022Article
- Article
- Influence of Sociodemographic, Socioeconomic, and Health Factors on Depression in the Peruvian Population: A Cross-Sectional Study.Journal of primary care & community healthArticle
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Authors and funding
4 authors at 3 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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 insurance coverage) predict the depressive symptoms of Chinese workers and how community factors may work differently in rural and urban settings.
methodsThis secondary data analysis was conducted using data from the 2014 and 2016 China Labor-force Dynamics Survey (CLDS). The sample of this study includes 9,140 workers (6,157 rural labors and 2,983 urban labors) who took part in both the 2014 and 2016 CLDS. This study discusses the relation between community factors and depressive symptoms of Chinese workers by correlation analysis and regression analysis. All analyses were conducted using SPSS 24.0.
resultsThe results indicate that rural workers have higher levels of depressive symptoms than urban workers. Medical benefits coverage predicts depressive symptoms of rural workforces (B = -0.343, 95%CI = -0.695 ~ 0.009, p < . 10), and community supportive network size predicts depressive symptoms of urban workforces (B = -.539, 95%CI = -0.842 ~ 0.236, p < . 01).
conclusionsPolicymakers may address 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.
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