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Depressive symptoms in three Chinese older workforce groups: the interplay of work stress with family and community factors

  • Fei Sun (a1), Wanlian Li (a2), Lin Jiang (a3) and Jaewon Lee (a1)



More people remain in the workforce into their late life as people’s life expectancy increases. This study examined the relationship between work stress and depressive symptoms of older workers in mainland China, focusing on the interplay between work stress with family and community factors in three (i.e., urban, rural, and migrant) settings.


National representative survey data on the Chinese labor force collected by the Social Science Research Center of Sun-Yetsen University in 2014 were used. The sample consisted of 5,751 workers aged 50 and above recruited from 29 out of 31 provinces in mainland China.


Work stress had a consistent and robust effect on depressive symptoms across older worker groups. Moreover, it interacted with family and community factors differentially in three settings. For migrant older workers, work stress was a dominant factor affecting their depressive symptoms. Among rural older workers, the influence of work stress on depressive symptoms depended on their family debt and neighborhood cohesion levels.


Stressors from work, family, and community comprised a general model that explains depressive symptoms in Chinese older workers. Interventions or service programs aimed at reducing work stress and improving mental health among older adults should consider the complexity of intertwining family and community dynamics as well as respective strengths in urban, rural, and migrant communities.


Corresponding author

Correspondence should be addressed to: Wanlian Li, School of Public Management, College of Public Administration and Law, Hunan Agricultural University, Nongda Rd, Furong Qu, Changsha City, Hunan Province, China 410125. Phone: 86-073184617003; Fax: 86- 073184611473. Email:


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Depressive symptoms in three Chinese older workforce groups: the interplay of work stress with family and community factors

  • Fei Sun (a1), Wanlian Li (a2), Lin Jiang (a3) and Jaewon Lee (a1)


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