Literature DB >> 34182553

Social Network Characteristics Predict Loneliness in Older Adults.

Hairin Kim1, Seyul Kwak1, Yoosik Youm2, Jeanyung Chey1.   

Abstract

INTRODUCTION: Social isolation is detrimental to late-life health outcomes. Although objective social isolation is a major source of perceived loneliness, how different layers of social disconnection systematically constitute the subjective experience of loneliness remains unclear.
METHODS: This study focused on older adults who participated in the Korean Social Life, Health, and Aging Project (KSHAP) (n = 1,724; mean age = 72.91 years) and examined how the proximal and distal characteristics of social networks predict loneliness using a hierarchical linear regression model. The study also investigated whether the major loss of social roles (marital and working status) influences perceived loneliness through the proximal and distal aspects of social networks by cross-sectional mediation analysis.
RESULTS: This study found that the proximal (subjective number of connections) and distal (brokerage and embeddedness) aspects of social networks additively explained the frequency of loneliness. Moreover, the loss of late-life social roles (marital and working status) was related to an increase in loneliness, where the distal characteristic of social networks mediated this relationship. DISCUSSION/
CONCLUSION: The results of this study suggest that the proximal and the distal characteristic of social networks is a social determinant predicting loneliness in late life. Besides, the loss of bridging and cohesive position among community networks may be a critical pathway to psychosocial transition after marital and working status changes. The Author(s). Published by S. Karger AG, Basel.

Entities:  

Keywords:  Loneliness; Marital status; Retirement; Social network analysis

Mesh:

Year:  2021        PMID: 34182553      PMCID: PMC8985000          DOI: 10.1159/000516226

Source DB:  PubMed          Journal:  Gerontology        ISSN: 0304-324X            Impact factor:   5.140


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