Social network types, health, and well-being of older Asian Americans

Abstract

Objectives: The purposes of this study were to: (1) develop an empirical typology of the social networks in diverse groups of older Asian Americans using both structural and subjective criterion variables; and (2) examine the relationship of the social network types to the measures of the health and well-being (self-rating of health, mental distress, and life satisfaction).

Method: The participants included 533 older Asian Americans (Chinese, Asian Indian, Korean, Vietnamese, and other Asians) who participated in the 2015 Asian American Quality of Life Survey in Central Texas. Latent profile analysis (LPA) was conducted using seven social network-related variables. The identified typologies were then regressed on the indicators of health and well-being (poor rating of health, probable mental distress, and dissatisfaction with life).

Results: The LPA identified the model with four network types as being most optimal. The groups were named “diverse-integrated” (37.5%), “moderately diverse-integrated” (21.2%), “marginally restricted-noncongregant” (22.1%), and “restricted-congregant” (19.1%). The results suggested that compared to the “diverse-integrated” group, the “marginally restricted-noncongregant type” fared worse than “the restricted-congregant group” in that the former had greater odds of both mental distress and dissatisfaction with life while the latter had higher odds only for dissatisfaction with life.

Conclusion: Unlike previous network studies, network types were shaped in the continuum of different social ties and subjective evaluation on strength of social ties. Certain ethnic groups were over-represented in specific network types. Such findings suggest the importance of understanding ethnic group variations in network vulnerabilities when considering interventions.

Keywords:

• Social network types
• older Asian Americans
• physical and mental health

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Data collection was supported by the City of Austin’s Asian American Quality of Life initiative (Contract No. 26-8275-39, PI: Yuri Jang, Ph.D.). This work was supported in part by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2016-S1A3A2924582, PI: Soondool Chung, Ph.D.)