The micro-macro interplay of economic factors in late-life loneliness: Evidence from Europe and China.

Jing Wu, Jing Zhang, Tineke Fokkema
Author Information
  1. Jing Wu: Department of Sociology and Work Science, University of Gothenburg, Gothenburg, Sweden.
  2. Jing Zhang: Department of Public Administration and Sociology, Erasmus University Rotterdam, Rotterdam, Netherlands.
  3. Tineke Fokkema: Department of Public Administration and Sociology, Erasmus University Rotterdam, Rotterdam, Netherlands.

Abstract

Individual socioeconomic status has a significant impact on whether older adults can initiate and maintain social relationships and participate in society, hence it affects loneliness. At the macro level, income inequality is expected to increase the risk of loneliness by eroding social cohesion and trust, while welfare generosity might protect people from loneliness. The aim of the study is to explore whether income inequality and welfare generosity at the country level moderate the effect of socioeconomic status at the individual level on late-life loneliness. Data were obtained from the HRS family of surveys - the Survey of Health, Aging and Retirement in Europe (SHARE) (wave 5, 2011/12) and China Health and Retirement Longitudinal Study (CHARLS) (wave 2, 2012/13). Respondents aged 50 years and older from twelve European countries and China were included in the study. Logistic country fixed effect models were used in the analysis. The findings show a stronger effect of individual socioeconomic status on late-life loneliness in more income-unequal societies and a weaker effect in more welfare-generous societies. There is a need to consider the impact of income distribution and welfare spending on the risk of loneliness among those older adults with low socioeconomic status when tailoring preventive programs and interventions to reduce loneliness among this vulnerable group.

Keywords

References

  1. Front Psychol. 2022 May 12;13:895141 [PMID: 35645921]
  2. Res Gerontol Nurs. 2010 Apr;3(2):113-25 [PMID: 20415360]
  3. Gerontologist. 2018 Nov 3;58(6):1096-1108 [PMID: 29237019]
  4. J Gerontol B Psychol Sci Soc Sci. 2014 Jul;69(4):633-45 [PMID: 24550354]
  5. Psychol Med. 2021 Oct;51(14):2414-2421 [PMID: 32338228]
  6. J Gerontol B Psychol Sci Soc Sci. 2008 Nov;63(6):S375-84 [PMID: 19092047]
  7. J Gerontol B Psychol Sci Soc Sci. 2005 Nov;60(6):S311-S317 [PMID: 16260713]
  8. Pers Soc Psychol Bull. 2019 May;45(5):780-793 [PMID: 30264659]
  9. Eur J Ageing. 2008 May 22;5(2):103 [PMID: 28798565]
  10. Int Psychogeriatr. 2016 Apr;28(4):557-76 [PMID: 26424033]
  11. BMC Public Health. 2020 May 27;20(1):778 [PMID: 32456626]
  12. Eur J Ageing. 2018 Sep 6;16(2):133-143 [PMID: 31139028]
  13. Eur J Ageing. 2011 Mar;8(1):31-38 [PMID: 21475393]
  14. J Gerontol B Psychol Sci Soc Sci. 2015 Jan;70(1):132-42 [PMID: 24997286]
  15. Aging Ment Health. 2015;19(5):409-17 [PMID: 25126996]
  16. Soc Sci Med. 2007 Nov;65(9):1965-78 [PMID: 17618718]
  17. Eur J Ageing. 2009 Nov 6;6(4):267 [PMID: 28798610]
  18. Eur J Ageing. 2021 Sep 16;19(3):485-494 [PMID: 36052198]
  19. Int J Environ Res Public Health. 2022 Jan 12;19(2): [PMID: 35055639]
  20. Soc Sci Med. 2019 Jul;232:120-128 [PMID: 31077973]
  21. Eur J Ageing. 2009 Jun;6(2):91-100 [PMID: 19517025]
  22. Eur J Ageing. 2012 Oct 13;9(4):285-295 [PMID: 28804428]
  23. Psychol Health Med. 2015;20(3):332-44 [PMID: 25058303]
  24. Aging Ment Health. 2020 Apr;24(4):564-574 [PMID: 30773894]
  25. J Psychol. 2012 Jan-Apr;146(1-2):201-28 [PMID: 22303621]

MeSH Term

Aged
China
Economic Factors
Humans
Loneliness
Longitudinal Studies
Middle Aged
Socioeconomic Factors

Word Cloud

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