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Multidimensional Social Network Types and Their Correlates in Older Americans.
Ali, Talha; Elliott, Michael R; Antonucci, Toni C; Needham, Belinda L; Zelner, Jon; Mendes de Leon, Carlos F.
Affiliation
  • Ali T; Section of Geriatrics, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
  • Elliott MR; Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA.
  • Antonucci TC; Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA.
  • Needham BL; Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA.
  • Zelner J; Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA.
  • Mendes de Leon CF; Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA.
Innov Aging ; 6(1): igab053, 2022.
Article in En | MEDLINE | ID: mdl-35036584
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Aspects: Determinantes_sociais_saude Language: En Journal: Innov Aging Year: 2022 Document type: Article Affiliation country: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Aspects: Determinantes_sociais_saude Language: En Journal: Innov Aging Year: 2022 Document type: Article Affiliation country: Estados Unidos