Depressive symptoms and gender differences in older adults in Hong Kong during the COVID-19 pandemic: a network analysis approach

Yu Jin, He Li Sun, Simon Ching Lam, Zhaohui Su, Brian J. Hall, Teris Cheung, Ming Zhao Qin, Chee H. Ng, Yu Tao Xiang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

15 Citations (Scopus)

Abstract

Background: The 2019 novel coronavirus disease (COVID-19) outbreak had a detrimental impact on the mental health of older adults. This study evaluated the central symptoms and their associations in the network of depressive symptoms and compared the network structure differences between male and female older adults in Hong Kong. Methods: Altogether, 3,946 older adults participated in this study. We evaluated the centrality indicators for network robustness using stability and accuracy tests, and examined the potential differences between the structure and connectivity of depression networks in male and female older adults. Results: The overall prevalence of depressive symptoms was 43.7% (95% CI=40.6-46.7%) in males, and 54.8% (95% CI=53.1-56.5%) in females (P<0.05). Sad Mood, Guilt, Motor problems and Lack of Energy were influential symptoms in the network model. Gender differences were found in the network global strength, especially in the following edges: Sad Mood--Guilt, Concentration--Guilt, Anhedonia--Motor, Lack of Energy--Suicide, Appetite--Suicide and Concentration--Suicide. Conclusions: Central symptoms in the depressive symptom network among male and female older adults may be prioritized in the treatment and prevention of depression during the pandemic.

Original languageEnglish
Pages (from-to)3934-3941
Number of pages8
JournalInternational Journal of Biological Sciences
Volume18
Issue number10
DOIs
Publication statusPublished - Aug 2022

Keywords

  • COVID-19
  • depression
  • Hong Kong
  • network analysis
  • older adults

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Applied Microbiology and Biotechnology
  • Molecular Biology
  • Developmental Biology
  • Cell Biology

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