ArticleBMC public health2025
Decomposition analysis of differences in depressive symptoms between agricultural and non-agricultural workers in China.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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- Gender disparities in eHealth literacy among Chinese university students and their decomposition.Frontiers in public health · 2026Article
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Abstract
backgroundChinese workers are confronted with severe mental health issues. This study aimed to investigate the reasons for the differences in depressive symptoms between agricultural and non-agricultural workers in China, and to measure the contribution of relevant influencing factors.
methodsThe data used in this study came from the 2018 China Family Panel Studies (CFPS) data. We used the brief 8-item Centre for Epidemiological Studies Depression Scale (CES-D8) to measure participants' depressive symptoms, and Fairlie decomposition model was used to analyze the influencing factors for the differences in depressive symptoms between agricultural and non-agricultural workers and their contribution.
resultsThe percentage of employed people with depressive symptoms was 14.44%. The percentage of agricultural workers (18.68%) with depressive symptoms was higher than that of non-agricultural workers (11.33%).The results of Fairlie decomposition analysis showed that 74.68% of the differences in depressive symptoms between agricultural and non-agricultural workers was due to observed factors, which were education level (39.63%), self-rated health (25.59%), marital status (-23.93%), residence (12.04%), job satisfaction (8.39%), chronic disease (5.52%), gender (5.11%), life satisfaction (3.59%), and body mass index (-1.28%) (all P < 0.05).
conclusionsThe percentage of depressive symptoms was higher in agricultural than in non-agricultural workers, which was primarily associated with differences in educational level, self-rated health, marital status, residence, job satisfaction, chronic disease, gender, life satisfaction, and body mass index between them.
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