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Social disadvantage, context and network dynamics in later life

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  • Nan Feng

    (Cornell University)

Abstract

How do personal networks evolve as individuals age? To what degree do social disadvantage and contextual factors matter for network dynamics in later life? This paper answers these two questions based on egocentric network data of older adults over a ten-year period. Specifically, I use longitudinal and nationally representative data on 1,168 older adults from the National Social Life, Health, and Aging Project. I use between-within models to separate the within- and between-individual effects of sociodemographic characteristics and contextual factors on three aspects of social connectedness in later life: network size, frequency of contact, and proportion of kin. Patterns of network change vary among people of different races and ethnicities as well as educational levels. Black and Hispanic respondents have a significantly smaller network size and a higher average frequency of contact with confidants. Moreover, Hispanic respondents have a higher proportion of kin in the network, compared to White respondents. Similarly, older adults with less education have a smaller network size, higher frequency of contact and higher proportion of kin in their confidant networks compared to those who attended college. Older adults who have better mental health are more likely to have a higher frequency of contact and higher proportion of kin. When an older adult starts to work for pay, their frequency of contact with confidants tends to increase. Older adults living in neighborhoods with stronger social ties are more likely to have a larger network size, higher frequency of contact, and lower proportion of kin in their confidant network. The above results show that disadvantaged backgrounds and contextual factors are associated with certain less favorable network characteristics, which helps to explain the concentration of social disadvantage on certain populations.

Suggested Citation

  • Nan Feng, 2023. "Social disadvantage, context and network dynamics in later life," European Journal of Ageing, Springer, vol. 20(1), pages 1-11, December.
  • Handle: RePEc:spr:eujoag:v:20:y:2023:i:1:d:10.1007_s10433-023-00767-w
    DOI: 10.1007/s10433-023-00767-w
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    References listed on IDEAS

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    1. Benjamin Cornwell & Alyssa Goldman & Edward O Laumann & Markus Schafer, 2021. "Homeostasis Revisited: Patterns of Stability and Rebalancing in Older Adults’ Social Lives," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 76(4), pages 778-789.
    2. Jens Ludwig & Greg J. Duncan & Lisa A. Gennetian & Lawrence F. Katz & Ronald C. Kessler & Jeffrey R. Kling & Lisa Sanbonmatsu, 2013. "Long-Term Neighborhood Effects on Low-Income Families: Evidence from Moving to Opportunity," American Economic Review, American Economic Association, vol. 103(3), pages 226-231, May.
    3. M. Kauppi & M. Virtanen & J. Pentti & V. Aalto & M. Kivimäki & J. Vahtera & S. Stenholm, 2021. "Social network ties before and after retirement: a cohort study," European Journal of Ageing, Springer, vol. 18(4), pages 503-512, December.
    4. Reinhard Schunck & Francisco Perales, 2017. "Within- and between-cluster effects in generalized linear mixed models: A discussion of approaches and the xthybrid command," Stata Journal, StataCorp LP, vol. 17(1), pages 89-115, March.
    5. Howard Litwin & Michal Levinsky & Ella Schwartz, 2020. "Network type, transition patterns and well-being among older Europeans," European Journal of Ageing, Springer, vol. 17(2), pages 241-250, June.
    6. Kristine J. Ajrouch & Toni C. Antonucci & Mary R. Janevic, 2001. "Social Networks Among Blacks and Whites," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 56(2), pages 112-118.
    7. Cornwell, Benjamin & Laumann, Edward O., 2015. "The health benefits of network growth: New evidence from a national survey of older adults," Social Science & Medicine, Elsevier, vol. 125(C), pages 94-106.
    8. Kyung-Won Choi & Gyeong-Suk Jeon, 2021. "Social Network Types and Depressive Symptoms among Older Korean Men and Women," IJERPH, MDPI, vol. 18(21), pages 1-14, October.
    9. Bianca Suanet & Oliver Huxhold & Markus SchaferPhD, 2020. "Cohort Difference in Age-Related Trajectories in Network Size in Old Age: Are Networks Expanding?," Journals of Gerontology: Series B, Gerontological Society of America, vol. 75(1), pages 137-147.
    10. Katherine L. Fiori & Toni C. Antonucci & Kai S. Cortina, 2006. "Social Network Typologies and Mental Health Among Older Adults," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 61(1), pages 25-32.
    11. Kira S. Birditt & Nicky Newton & Susannah Hope, 2014. "Editor's choice Implications of Marital/Partner Relationship Quality and Perceived Stress for Blood Pressure Among Older Adults," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 69(2), pages 188-198.
    12. Liping Ye & Xinping Zhang, 2019. "Social Network Types and Health among Older Adults in Rural China: The Mediating Role of Social Support," IJERPH, MDPI, vol. 16(3), pages 1-14, January.
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