Prevalence and factors influencing depression among empty nesters in China: A meta-analysis

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Abstract

Background

Empty nesters are older people who live alone or an older couple without children to care for them. In China, empty nesters make up a significant community and are more likely to experience emotional issues, particularly depression. This study investigated the prevalence of depression and the factors influencing depression among Chinese home-bound empty nesters using meta-analysis.

Methods

Based on previous studies, we used search terms relating to empty nesters and depression in English and Chinese. Databases, including China Journal Full Text Database (CNKI), Wanfang, Wipu, China Biomedical Literature Database (CBM), PubMed, Web of Science, Embase, The Cochrane Library, and UptoDate, were searched in April 2022, for relevant articles. Details including names of authors, year of publication, region of investigation, study type, sample size, depression detection scale, depression detection rate, and influencing factors were captured. The heterogeneity of the studies was assessed based on the I ² index, and data analysis was performed using Stata 16.0 software.

Results

A total of ten research articles involving 5337 Chinese empty nesters were evaluated in the present meta-analysis. The overall prevalence of depression among empty nesters in China was 43%. The prevalence of depression among urban empty nesters was 38% (95% CI: 0.24,0.52), and 36% (95% CI: 0.18,0.55) among rural empty nesters. Many factors, including female, income, marital status, chronic illness, relationship with children, and social support were linked to depression among urban empty nesters.

Conclusion

The prevalence of depression among empty nesters was 43%. Therefore, based on the factors influencing depression, government departments can intervene early to improve the mental health of empty nesters.

Limitations

The meta-analysis only included cross-sectional studies. Therefore, there is a need for more future original studies investigating depression among empty nesters in China.

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Most cited references 30

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The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

Matthew J L Page, Joanne E McKenzie, Patrick Bossuyt … (2025)

The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.

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Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses.

Andreas Stang (2010)

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Prevalence and determinants of depression among old age: a systematic review and meta-analysis

Yosef Zenebe, Baye Akele, Mulugeta W/Selassie … (2021)

Background Depression is a leading cause of disability worldwide and is a major contributor to the overall global burden of disease. It is also one of the most common geriatric psychiatric disorders and a major risk factor for disability and mortality in elderly patients. Even though depression is a common mental health problem in the elderly population, it is undiagnosed in half of the cases. Several studies showed different and inconsistent prevalence rates in the world. Hence, this study aimed to fill the above gap by producing an average prevalence of depression and associated factors in old age. Objective This study aims to conduct a systematic review and meta-analysis to provide a precise estimate of the prevalence of depression and its determinants among old age. Method A comprehensive search of PubMed, Scopus, Web of sciences, Google Scholar, and Psych-info from database inception to January 2020. Moreover, the reference list of selected articles was looked at manually to have further eligible articles. The random-effects model was employed during the analysis. Stata-11 was used to determine the average prevalence of depression among old age. A sub-group analysis and sensitivity analysis were also run. A graphical inspection of the funnel plots and Egger’s publication bias plot test were checked for the occurrence of publication bias. Result A search of the electronic and manual system resulted in 1263 articles. Nevertheless, after the huge screening, 42 relevant studies were identified, including, for this meta-analysis, n = 57,486 elderly populations. The average expected prevalence of depression among old age was 31.74% (95% CI 27.90, 35.59). In the sub-group analysis, the pooled prevalence was higher among developing countries; 40.78% than developed countries; 17.05%), studies utilized Geriatrics Depression Scale-30(GDS-30); 40.60% than studies that used GMS; 18.85%, study instrument, and studies having a lower sample size (40.12%) than studies with the higher sample; 20.19%. Conclusion A high prevalence rate of depression among the old population in the world was unraveled. This study can be considered as an early warning and advised health professionals, health policymakers, and other pertinent stakeholders to take effective control measures and periodic care for the elderly population.

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Author and article information

Contributors

Lihua Liu: llh1395@163.com

Journal

Journal ID (nlm-ta): BMC Geriatr

Journal ID (iso-abbrev): BMC Geriatr

Title: BMC Geriatrics

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2318

Publication date (Electronic): 30 May 2023

Publication date PMC-release: 30 May 2023

Publication date Collection: 2023

Volume: 23

Electronic Location Identifier: 333

Affiliations

[1 ]GRID grid.411427.5, ISNI 0000 0001 0089 3695, Department of Nursing, College of Medicine, , Hunan Normal University, ; Hunan Province, China

[2 ]GRID grid.508008.5, ISNI 0000 0004 4910 8370, Minimally Invasive Surgery Center of The First Hospital of Changsha, ; Hunan Province, China

[3 ]GRID grid.477407.7, ISNI 0000 0004 1806 9292, Department of Respiratory Medicine, , Hunan Provincial People’s Hospital, ; Hunan Province, China

Article

Publisher ID: 4064

DOI: 10.1186/s12877-023-04064-0

PMC ID: 10228112

PubMed ID: 37254062

SO-VID: c09cd209-76e5-4b24-9dd1-be0516cb59c5

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 20 July 2022

Date accepted : 24 May 2023

Funding

Funded by: Hunan Postgraduate Scientific Research Innovation Project

Award ID: CX20220521

Funded by: FundRef http://dx.doi.org/10.13039/100009377, Education Department of Hunan Province;

Award ID: HNJG-2020-0172

Funded by: Changsha City Soft Science Research Program Project

Award ID: kh2302026

Custom metadata

ScienceOpen disciplines: Geriatric medicine

Keywords: depression,empty-nesters,influencing factors,meta-analysis

Data availability:

ScienceOpen disciplines: Geriatric medicine

Keywords: depression, empty-nesters, influencing factors, meta-analysis

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Prevalence and factors influencing depression among empty nesters in China: A meta-analysis

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Abstract

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Limitations

Related collections

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Most cited references 30

The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses.

Prevalence and determinants of depression among old age: a systematic review and meta-analysis

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