» Articles » PMID: 35409696

The Impact of Social Network Characteristics on Health Among Community-Dwelling Older Adults in Korea: Application of Social Network Analysis

Overview
Publisher MDPI
Date 2022 Apr 12
PMID 35409696
Authors
Affiliations
Soon will be listed here.
Abstract

Objectives: Population aging is a reality in most developed countries. In this era, an important health issue for these countries is promoting health and quality of life in the elderly population. Older adults’ social networks are associated with health and quality of life. Therefore, this study examines the association between the characteristics of social networks (friendship networks) and the subjective well-being of community-dwelling older adults. Methods: This study was conducted between June 2015 and August 2015 with a total of 146 participants. The size and density of social networks were analyzed using social network analysis. Additionally, to investigate the impact of social networks on health, a multiple linear regression analysis was performed using NetMiner 4.0. Statistical significance was set at p < 0.05. Results: In terms of Model 1, which used social network characteristics as variables, the higher the out-degree (376.161) and in-closeness (201.825), the better the health. In contrast, the higher the in-degree (−279.167) and out-closeness (−52.620), the poorer the health. Regarding Model 2, which used sociodemographic characteristics as variables, the higher the out-degree (218.747) and in-closeness (170.075), the better the health. In addition, religion had a negative effect on health, and a high level of education had a positive effect on health. Conclusions: The findings suggest that higher out-degree and in-closeness intensity positively affect the health of older adults, but higher in-degree and out-closeness intensity negatively affect health. Therefore, health professionals should use appropriate strategies to increase the strength of social networks to improve the health of older adults living in the community.

Citing Articles

Decomposing differences in the chronic disease condition between rural and urban older adults in China: a cross-sectional analysis.

Zhang J, Zhang Y Front Public Health. 2024; 11:1298657.

PMID: 38249386 PMC: 10797097. DOI: 10.3389/fpubh.2023.1298657.


By Internal Network or by External Network?-Study on the Social Network Mechanism of Reducing the Perception of Old-Age Support Risks of Rural Elders in China.

Nie J, Fan R, Wu Y, Li D Int J Environ Res Public Health. 2022; 19(22).

PMID: 36430008 PMC: 9690998. DOI: 10.3390/ijerph192215289.


The Impact of Interface Design Element Features on Task Performance in Older Adults: Evidence from Eye-Tracking and EEG Signals.

Zhou C, Yuan F, Huang T, Zhang Y, Kaner J Int J Environ Res Public Health. 2022; 19(15).

PMID: 35954608 PMC: 9367723. DOI: 10.3390/ijerph19159251.

References
1.
Lin N, Ye X, Ensel W . Social support and depressed mood: a structural analysis. J Health Soc Behav. 2000; 40(4):344-59. View

2.
Kawada T . Self-rated health and life prognosis. Arch Med Res. 2003; 34(4):343-7. DOI: 10.1016/S0188-4409(03)00052-3. View

3.
Ayalon L, Levkovich I . A Systematic Review of Research on Social Networks of Older Adults. Gerontologist. 2018; 59(3):e164-e176. DOI: 10.1093/geront/gnx218. View

4.
Idler E, Benyamini Y . Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav. 1997; 38(1):21-37. View

5.
Valente T, Gallaher P, Mouttapa M . Using social networks to understand and prevent substance use: a transdisciplinary perspective. Subst Use Misuse. 2004; 39(10-12):1685-712. DOI: 10.1081/ja-200033210. View