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Association of depressive symptoms with retirement in Chinese employees: evidence from national longitudinal surveys from 2011 to 2018.


ABSTRACT:

Background

The relationship between depressive symptoms and retirement remains controversial. Thus, we aimed to explore the effect of retirement on individuals' depressive symptoms in Chinese employees.

Methods

In this panel data analysis, a data set from China Health and Retirement Longitudinal Study (CHARLS) in 2011, 2013, 2015 and 2018 was adopted with a total of 1390 employees aged ≥ 45-years-old who had complete follow-up for the four waves. Random-effects logistic regression was used to examine the associations between retirement and depressive symptoms.

Results

After adjusting several socio-demographic variables, retirement still increases the risk of depressive symptoms in the retirees (odds ratio 1.5, 95% CI 1.14-1.97). Through subgroup analysis, we found that people who are male, with lower education level, married, living in rural areas, suffering from chronic diseases, and those who do not participate in social activities are more likely to experience depression after retirement.

Conclusions

Retirement can increase the depression risk of Chinese employees. It is necessary to formulate relevant supporting policies to reduce the risk of depression.

SUBMITTER: Xu F 

PROVIDER: S-EPMC10214712 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Publications

Association of depressive symptoms with retirement in Chinese employees: evidence from national longitudinal surveys from 2011 to 2018.

Xu Fenglin F   Yuan Jingmin J   Wu Hongxia H  

BMC public health 20230526 1


<h4>Background</h4>The relationship between depressive symptoms and retirement remains controversial. Thus, we aimed to explore the effect of retirement on individuals' depressive symptoms in Chinese employees.<h4>Methods</h4>In this panel data analysis, a data set from China Health and Retirement Longitudinal Study (CHARLS) in 2011, 2013, 2015 and 2018 was adopted with a total of 1390 employees aged ≥ 45-years-old who had complete follow-up for the four waves. Random-effects logistic regression  ...[more]

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