Multidimensional Social Network Types and Their Correlates in Older Americans

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 out...

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Veröffentlicht in:Innovation in aging 2022-01, Vol.6 (1), p.igab053-igab053
Hauptverfasser: Ali, Talha, Elliott, Michael R, Antonucci, Toni C, Needham, Belinda L, Zelner, Jon, Mendes de Leon, Carlos F
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container_end_page igab053
container_issue 1
container_start_page igab053
container_title Innovation in aging
container_volume 6
creator Ali, Talha
Elliott, Michael R
Antonucci, Toni C
Needham, Belinda L
Zelner, Jon
Mendes de Leon, Carlos F
description 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.
doi_str_mv 10.1093/geroni/igab053
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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.</description><identifier>ISSN: 2399-5300</identifier><identifier>EISSN: 2399-5300</identifier><identifier>DOI: 10.1093/geroni/igab053</identifier><identifier>PMID: 35036584</identifier><language>eng</language><publisher>US: Oxford University Press</publisher><subject>Demographic aspects ; Original ; Social networks</subject><ispartof>Innovation in aging, 2022-01, Vol.6 (1), p.igab053-igab053</ispartof><rights>The Author(s) 2022. Published by Oxford University Press on behalf of The Gerontological Society of America. 2022</rights><rights>The Author(s) 2022. 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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.</description><subject>Demographic aspects</subject><subject>Original</subject><subject>Social networks</subject><issn>2399-5300</issn><issn>2399-5300</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><recordid>eNqFkcFr2zAUh8XoWEva647DsEt3SCtZliVdCiF0W6FpD83OQpafE22ylEp2R_77KSQtLRSGDk88fe_jiR9Cnwm-IFjSyxXE4O2lXekGM_oBnZRUyimjGB-9uh-js5R-Y4yJpJWsyk_omDJMayaqE7RYjG6wre3BJxu8dsVDMDaXOxj-hvinWG43kArt22K5BhuLeYgRnB5y0_ri3rUQi1kP0Rrt0yn62GmX4OxQJ-jX9-vl_Of09v7HzXx2OzWVJMNUdgC4KU1TVUJS0gpDmpZLbnQtseFMcNqUXHAhdN0KKQynhAAzVPIOOiroBF3tvZux6aE14IeondpE2-u4VUFb9fbF27VahSclOKuJYFlwfhDE8DhCGlRvkwHntIcwJlXWJeZ1yeoqo1_36Eo7UNZ3IRvNDlczTnDNSsJopi7eofJpobcmeOhs7r83YGJIKUL3sj3Bapeu2qerDunmgS-v__yCP2eZgW97IIyb_8n-AVECsCA</recordid><startdate>20220101</startdate><enddate>20220101</enddate><creator>Ali, Talha</creator><creator>Elliott, Michael R</creator><creator>Antonucci, Toni C</creator><creator>Needham, Belinda L</creator><creator>Zelner, Jon</creator><creator>Mendes de Leon, Carlos F</creator><general>Oxford University Press</general><scope>TOX</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-1420-5328</orcidid><orcidid>https://orcid.org/0000-0003-3020-826X</orcidid><orcidid>https://orcid.org/0000-0003-4895-3583</orcidid></search><sort><creationdate>20220101</creationdate><title>Multidimensional Social Network Types and Their Correlates in Older Americans</title><author>Ali, Talha ; Elliott, Michael R ; Antonucci, Toni C ; Needham, Belinda L ; Zelner, Jon ; Mendes de Leon, Carlos F</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c491t-9fee0b2cb448931d8c1bd797ca690c75873b278788a6d898c7311e5c397fef383</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Demographic aspects</topic><topic>Original</topic><topic>Social networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ali, Talha</creatorcontrib><creatorcontrib>Elliott, Michael R</creatorcontrib><creatorcontrib>Antonucci, Toni C</creatorcontrib><creatorcontrib>Needham, Belinda L</creatorcontrib><creatorcontrib>Zelner, Jon</creatorcontrib><creatorcontrib>Mendes de Leon, Carlos F</creatorcontrib><collection>Oxford Journals Open Access Collection</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Innovation in aging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ali, Talha</au><au>Elliott, Michael R</au><au>Antonucci, Toni C</au><au>Needham, Belinda L</au><au>Zelner, Jon</au><au>Mendes de Leon, Carlos F</au><au>Savla, J Tina</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multidimensional Social Network Types and Their Correlates in Older Americans</atitle><jtitle>Innovation in aging</jtitle><addtitle>Innov Aging</addtitle><date>2022-01-01</date><risdate>2022</risdate><volume>6</volume><issue>1</issue><spage>igab053</spage><epage>igab053</epage><pages>igab053-igab053</pages><issn>2399-5300</issn><eissn>2399-5300</eissn><abstract>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. 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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. 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subjects Demographic aspects
Original
Social networks
title Multidimensional Social Network Types and Their Correlates in Older Americans
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