Multidimensional Social Network Types and Their Correlates in Older Americans

Talha Ali; Michael R Elliott; Toni C Antonucci; Belinda L Needham; Jon Zelner; Carlos F Mendes de Leon

doi:10.1093/geroni/igab053

Multidimensional Social Network Types and Their Correlates in Older Americans

Innov Aging. 2022 Jan 12;6(1):igab053. doi: 10.1093/geroni/igab053. eCollection 2022.

Authors

Talha Ali¹, Michael R Elliott^{2

3}, Toni C Antonucci⁴, Belinda L Needham⁵, Jon Zelner⁵, Carlos F Mendes de Leon⁵

Affiliations

¹ Section of Geriatrics, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
² Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA.
³ Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA.
⁴ Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA.
⁵ Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA.

Abstract

Background and objectives: Social support networks of older adults have been linked to their health and well-being; however, findings regarding the effects of specific network characteristics have been mixed. Additionally, due to demographic shifts increasing numbers of older adults live outside of traditional family structures. Previous studies have not systematically examined the resulting complexity and heterogeneity of older adults' social networks. Our objectives were to examine this complexity and heterogeneity by developing a multidimensional typology of social networks that simultaneously considers multiple structural and functional network characteristics, and to examine differences in network type membership by sociodemographic characteristics, health characteristics, and birth cohort.

Research design and methods: Participants included 5,192 adults aged 57-85 years in the National Social Life, Health, and Aging Project at rounds 1 (2005-2006) and 3 (2015-2016). Data were collected on social relationships including network size, diversity, frequency of contact, and perceived support and strain in relationships. We used latent class analysis to derive the network typology and multinomial logistic regression to examine differences in network type membership by sociodemographic characteristics, health characteristics, and birth cohort.

Results: Older adults were classified into 5 distinct social network types: (i) large, with strain; (ii) large, without strain; (iii) small, diverse, low contact; (iv) small, restricted, high contact; and (v) medium size and support. Membership in these network types varied by age, gender, marital status, race/ethnicity, education, mental health, and birth cohort.

Discussion and implications: Network typologies can elucidate the varied interpersonal environments of older adults and identify individuals who lack social connectedness on multiple network dimensions and are therefore at a higher risk of social isolation.

Keywords: Network typology; Older adults; Social relationships; Social strain; Social support.