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抑郁症状与中国员工退休的关联:来自 2011 年至 2018 年全国纵向调查的证据。

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

机构信息

Department of Nursing, Hubei College of Chinese Medicine, Jingzhou, China.

Health Science Center, Yangtze University, Jingzhou, China.

出版信息

BMC Public Health. 2023 May 26;23(1):961. doi: 10.1186/s12889-023-15971-7.

DOI:10.1186/s12889-023-15971-7
PMID:37237309
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10214712/
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.

摘要

背景

抑郁症状与退休之间的关系仍存在争议。因此,我们旨在探讨退休对中国员工个体抑郁症状的影响。

方法

本队列数据分析采用了中国健康与养老追踪调查(CHARLS)2011 年、2013 年、2015 年和 2018 年的数据,共纳入了 1390 名年龄≥45 岁且在四个时间点均有完整随访资料的员工。采用随机效应逻辑回归分析退休与抑郁症状之间的关联。

结果

在调整了几个社会人口学变量后,退休仍然会增加退休人员出现抑郁症状的风险(比值比 1.5,95%置信区间 1.14-1.97)。通过亚组分析,我们发现男性、受教育程度较低、已婚、居住在农村地区、患有慢性病以及不参加社会活动的人在退休后更容易出现抑郁。

结论

退休会增加中国员工的抑郁风险。有必要制定相关的支持政策,以降低抑郁风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ea/10214712/1e61decdcce5/12889_2023_15971_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ea/10214712/e36a210fe48a/12889_2023_15971_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ea/10214712/e32f7fee414e/12889_2023_15971_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ea/10214712/1e61decdcce5/12889_2023_15971_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ea/10214712/e36a210fe48a/12889_2023_15971_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ea/10214712/e32f7fee414e/12889_2023_15971_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01ea/10214712/1e61decdcce5/12889_2023_15971_Fig3_HTML.jpg

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