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Research report
Health and social exclusion in older age: evidence from Understanding Society, the UK household longitudinal study
  1. Amanda Sacker1,
  2. Andy Ross1,
  3. Catherine A MacLeod2,
  4. Gopal Netuveli3,
  5. Gill Windle2
  1. 1Department of Epidemiology and Public Health, University College London, London, UK
  2. 2Dementia Services Development Centre Wales, Bangor University, Bangor, UK
  3. 3Institute for Health and Human Development, University of East London, London, UK
  1. Correspondence to Professor Amanda Sacker, ESRC International Centre for Lifecourse Studies in Society and Health, Research Department of Epidemiology and Public Health, University College London, 1-19 Torrington Pace, London, WC1E 6BT, UK; a.sacker{at}ucl.ac.uk

Abstract

Background Social exclusion of the elderly is a key policy focus but evidence on the processes linking health and social exclusion is hampered by the variety of ways that health is used in social exclusion research. We investigated longitudinal associations between health and social exclusion using an analytical framework that did not conflate them.

Methods Data employed in this study came from 4 waves of Understanding Society, the UK Household Longitudinal Study 2009–2013. The sample comprised all adults who took part in all 4 waves, were 65 years or more in Wave 3, and had complete data on our variables of interest for each analysis. We used linear regression to model the relationship between Wave 2/3 social exclusion and Wave1–2 health transitions (N=4312) and logistic regression to model the relationship between Wave2/3 social exclusion and Wave 4 health states, conditional on Wave 3 health (N=4244).

Results There was a dose–response relationship between poor health in Waves 1 and 2 and later social exclusion. Use of a car, mobile phone and the internet moderated the association between poor health and social exclusion. Given the health status in Wave 3, those who were more socially excluded had poorer outcomes on each of the three domains of health in Wave 4.

Conclusions Use of the internet and technology protected older adults in poor health from social exclusion. Age-friendly hardware and software design might have public health benefits.

  • SELF-RATED HEALTH
  • SOCIAL EPIDEMIOLOGY
  • MENTAL HEALTH
  • LONGITUDINAL STUDIES
  • ELDERLY

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

https://doi.org/10.1136/jech-2016-208037

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    Footnotes

    • Contributors AS, AR, GW, CAM and GN developed the idea and contributed to the study design. AR and AS carried out the analysis and AS wrote the manuscript. AR, GW, CAM and GN commented on the paper and have seen and accepted the final version. AS takes responsibility for the overall content of the paper.

    • Funding This research was supported by Centre grants from the Economic and Social Research Council (AS, AR and GN: grant number ES/J019119/1; GW and CAM: grant number RES-060-25-0060).

    • Competing interests None declared.

    • Ethics approval The Understanding Society study was approved by the University of Essex Ethics Committee and the National Research Ethics Service. No additional ethical approval was necessary for this secondary data analysis.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement A working paper is referenced in the paper that gives detailed instructions on how we constructed our social exclusion indices from the Understanding Society data that are publicly available from the UK Data Service.