Social network types and the health of older adults: Exploring reciprocal associations
Abstract
Social network types have been proved to have significant impacts on older population's health outcomes. However, the existing discoveries are still inconsistent, which may be attributed largely to the heterogeneous measures and methods scholars used and to the unidirectional causalities presumed in most research. This study addresses these gaps by using more-refined measures to explore whether the network types have differential impacts on older adults' health outcomes, and whether a reverse causal relationship exists between older adults' health conditions and the network types they adopted. Using data from three recent waves (2005, 2008, and 2012) of the Chinese Longitudinal Healthy Longevity Survey (n = 4190), we constructed four network types using the K-means clustering method (i.e., diverse, friend, family, and restricted), and examined their impacts on a variety of health outcomes (i.e., physical, cognitive, psychological, and overall well-being). Our results demonstrate that there are strong reciprocal associations between these two factors. On the one hand, a diverse network type yielded the most beneficial health outcomes as measured by multiple health indicators, and the friend-focused network type is more beneficial than the family-focused network type in physical outcomes but not in psychological outcomes. On the other hand, we found that a decrease in all health indicators leads to withdrawal from more-beneficial network types such as a diversified network type, and a shift to less-beneficial network types such as family-focused or restricted networks. The understanding of this reciprocal association could encourage programs designed to enhance healthy aging to focus on improving the bridging social capital of older adults so that they can break the vicious cycle between network isolation and poor health conditions.
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Measures described as assessing one particular social concept may contain elements that assess other distinct social concepts.
“Indeed, measures described as assessing one particular concept may contain elements that assess other distinct social concepts.”
From Social Isolation and Cognitive Function in Later Life: A Systematic Review and Meta-Analysis (2019) · cites this paper as [40]
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- Authors
- Li, T., & Zhang, Y.
- Affiliations
- Renmin University of China (CN)
- Peking University (CN)
- Corresponding author
- Zhang, Yanlong
- Venue
- Social Science & Medicine
- Publisher
- Elsevier BV
- Published
- 2015-04
- Volume
- 130
- Pages
- 59-68
- ISSN
- 0277-9536 (ISSN-L)
- OpenAlex
- W1971441902
- Cited by
- 218
- References
- 7
- Citations by year
- 2026: 15 · 2025: 19 · 2024: 19 · 2023: 25 · 2022: 20 · 2021: 33 · 2020: 18 · 2019: 26 · 2018: 16 · 2017: 17 · 2016: 9 · 2015: 1
- FWCI
- 17.79
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Social Science & Medicine (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Renmin University of China
- Project 985
- Ministry of Education of the People's Republic of China
- National Office for Philosophy and Social Sciences (14CRK007)
- Topics
- Social Sciences › Health › Health disparities and outcomes
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Aging, Health, and Disability
- Social Sciences › Psychology › Neuropsychology and Physiological Psychology › Aging and Gerontology Research
- Keywords
- social networks, older adults, bidirectional relationship, health outcomes, social capital, bridging social capital, network types, family networks, friendship networks, network isolation, healthy aging, physical health, cognitive function, psychological well-being, Chinese Longitudinal Healthy Longevity Survey
- MeSH terms
- Activities of Daily Living, Age Factors, Aged, Aged, 80 and over, Aging, China, Family, Female, Health Status, Humans, Interpersonal Relations, Longitudinal Studies, Male, Mental Health, Middle Aged, Residence Characteristics, Sex Factors, Social Isolation, Social Support, Socioeconomic Factors, Health Behavior, Friends
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