Types of Non-kin Networks and Their Association With Survival in Late Adulthood: A Latent Class Approach

Abstract

Objectives: Integration into social networks is an important determinant of health and survival in late adulthood. We first identify different types of non-kin networks among older adults and second, investigate the association of these types with survival rates. Method: Official register information on mortality is combined with data from the Longitudinal Aging Study Amsterdam (LASA). The sample includes 2,440 Dutch respondents aged 54-85 at baseline in 1992 and six follow-ups covering a time span of 20 years. Using latent class analysis, respondents are classified into distinct types of non-kin networks, based on differences in number and variation of non-kin relations, social support received from non-kin, and contact frequency with non-kin. Next, membership in network types is related to mortality in a Cox proportional hazard regression model. Results: There are four latent types of non-kin networks that vary in network size and support. These types differ in their associations with mortality, independent of sociodemographic and health confounders. Older adults integrated into networks high in both number and variation of supportive non-kin contacts have higher chances of survival than older adults embedded in networks low in either amount or variation of support or both. Discussion: A combination of structural and functional network characteristics should be taken into account when developing intervention programs aiming at increasing social integration outside the family network. Keywords: Epidemiology-Mortality-Social networks-Social supportOver the last four decades, social epidemiologists have convincingly demonstrated positive effects of integration into social networks on survival (Berkman & Syme, 1979;Ellwardt, van Tilburg, Aartsen, Wittek, & Steverink, 2015;Holt-Lunstad, Smith, & Layton, 2010; Litwin & ShiovitzEzra, 2006), with evidence being relatively congruent across general and specific populations, countries, time, and gender. At the same time, social isolation has been argued to be a chronically stressful condition contributing to the accumulation of age-related morbidity and functional decline over the life course, thereby bearing the risk of accelerated aging (Berkman, 1988). As there is large variability in survival, and integration in social networks varies within and across people, there is a growing interest in determining which types of social networks relate to high chances of survival in old age.Most studies developing network typologies have so far focused on the overall social network including kin and non-kin (e.g., family-based network vs. friends-based network) and subsequently related types to mental health (Fiori & Jager, 2012;Gibney & McGovern, 2011;Litwin & Stoeckel, 2014) Gerontol B Psychol Sci Soc Sci, 2017, Vol. 72, No. 4, 694-705 doi:10.1093 Advance Access publication October 17, 2016 Downloaded from https://academic.oup.com/psychsocgerontology/article-abstract/72/4/694/2328824 by guest on 07 June 2019 friends and confidants protect against mortality, whereas ...

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