Social support networks in Chinese older adults: health outcomes and health related behaviors: a path analysis

Abstract

Background: Population aging is a social and economic concern for China. It is essential to understand types of social support networks available to elderly people living in China.

Objectives: The aim of this research was to identify network types among Chinese older adults and to examine the differential relationship of the network types, health outcomes and health-related behaviors.

Methods: Secondary analysis of data compiled by the Chinese Longitudinal Healthy Longevity Survey (n = 9749) was extracted. Network types were derived through latent class analysis with Mplus 6.12 software. Statistical analysis included descriptive statistics, one-way ANOVA, multiple logistic regression and path analysis.

Results: Four types of social networks were identified, these included private (16%), non-couple-focused (15%), couple-focused (47%) and diverse (22%). Compared with elders belonging to other networks, elders in diverse network possessed the healthiest status and the highest health-related behaviors score. Health-related behaviors played a role in mediating social network types to health outcomes was identified. Findings were aligned to the conceptual model pathway proposed by Berkman (2000).

Conclusion: The findings demonstrate that types of social networks for elders are significantly correlated to health-related behaviors and health outcomes. Detail and understanding of the correlations are useful to inform healthcare practice and policy and to assist the development of appropriate interpersonal interventions.

Keywords:

• China
• health outcomes
• health-related behaviors
• path analysis
• social support network types

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Data of this study is from the Chinese Longitudinal Healthy Longevity Survey which was supported by the [funding Agency 1]; the National Natural Science Foundation of China under Grant [number 71110107025, 71233001], National Institute on Aging/National Institutes of Health under Grant [number R01AG023627]. This work was also supported by the National Natural Science Foundation of China under Grant [number 71573097].