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Social support networks of older migrants in England and Wales: the role of collectivist culture

  • VANESSA BURHOLT (a1), CHRISTINE DOBBS (a1) and CHRISTINA VICTOR (a2)
Abstract
ABSTRACT

This article tests the fit of a social support network typology developed for collectivist cultures to six migrant populations living in England and Wales. We examine the predictive utility of the typology to identify networks most vulnerable to poor quality of life and loneliness. Variables representing network size, and the proportion of the network classified by gender, age, kin and proximity, were used in confirmatory and exploratory latent profile analysis to fit models to the data (N = 815; Black African, Black Caribbean, Indian, Pakistani, Bangladeshi and Chinese). Multinomial logistic regression examined associations between demographic variables and network types. Linear regression examined associations between network types and wellbeing outcomes. A four-profile model was selected. Multigenerational Household: Younger Family networks were most robust with lowest levels of loneliness and greatest quality of life. Restricted Non-kin networks were least robust. Multigenerational Household: Younger Family networks were most prevalent for all but the Black Caribbean migrants. The typology is able to differentiate between networks with multigenerational households and can help identify vulnerable networks. There are implications for forecasting formal services and variation in networks between cultures. The use of a culturally appropriate typology could impact on the credibility of gerontological research.

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Copyright
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Corresponding author
Address for correspondence: Vanessa Burholt, Room 20 Haldane Building, Centre for Innovative Ageing, College of Human and Health Sciences, Swansea University, Singleton Park, Swansea SA2 8PP, UK E-mail: v.burholt@swansea.ac.uk
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This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

G. McLachlan and D. Peel 2000. Finite Mixture Models. Wiley, New York.

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Ageing & Society
  • ISSN: 0144-686X
  • EISSN: 1469-1779
  • URL: /core/journals/ageing-and-society
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