Backgrounds: The prevalence of loneliness increases among older adults, varies across countries, and is related to within-country socioeconomic, psychosocial, and health factors. The 2000-2019 pooled prevalence of loneliness among adults 60 years and older went from 5.2% in Northern Europe to 24% in Eastern Europe, while in the US was 56% in 2012. The relationship between country-level factors and loneliness, however, has been underexplored. Because income inequality shapes material conditions and relative social deprivation and has been related to loneliness in 11 European countries, we expected a relationship between income inequality and loneliness in the US and 16 European countries.
Methods: We used secondary cross-sectional data for 75,891 adults age 50+ from HRS (US 2014), ELSA (England, 2014), and SHARE (15 European countries, 2013). Loneliness was measured using the R-UCLA three-item scale. We employed hierarchical logistic regressions to analyse whether income inequality (GINI coefficient) was associated with loneliness prevalence.
Results: The prevalence of loneliness was 25.32% in the US (HRS), 17.55% in England (ELSA) and ranged from 5.12% to 20.15% in European countries (SHARE). Older adults living in countries with higher income inequality were more likely to report loneliness, even after adjusting for the sociodemographic composition of the countries and their Gross Domestic Products per capita (OR: 1.52; 95% CI: 1.17-1.97).
Discussion: Greater country-level income inequality was associated with higher prevalence of loneliness over and above individual-level sociodemographics. The present study is the first attempt to explore income inequality as a predictor of loneliness prevalence among older adults in the US and 16 European countries. Addressing income distribution and the underlying experience of relative deprivation might be an opportunity to improve older adults' life expectancy and wellbeing by reducing loneliness prevalence.
Copyright: © 2022 Tapia-Muñoz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.