Accumulation of Disadvantages: Prevalence and Categories of Old-Age Social Exclusion in Belgium
- 208 Downloads
This paper focuses on the prevalence and measurement of old-age social exclusion. Currently there is limited knowledge of the prevalence of old-age social exclusion in Belgium. Although studies have already shown that older adults can experience exclusion in more than one dimension, the multidimensional nature of social exclusion is often lost when constructing a scale. Consequently, this paper’s aim is twofold. First, it examines the prevalence of different dimensions of old-age social exclusion in Flanders and Brussels and seeks to demonstrate the influence of applying different measurement thresholds. Second, this study develops an old-age social exclusion measure that preserves its multidimensionality. Descriptive and Latent Class Analysis were performed on the Belgian Ageing Studies data (2008–2014), a survey among home-dwelling older adults (60 + years) (N = 20,275; 80 municipalities). Findings revealed that older adults are mainly digitally excluded and excluded from the neighbourhood, civic participation, and social relations. More than 60% older adults experience exclusion in two or more dimensions. The use of different thresholds, however, leads to different interpretations concerning the prevalence of social exclusion. Results of the Latent Class Analysis revealed four categories of old-age exclusion: those at “low risk”, “the non-participating financially excluded”, “the environmentally excluded” and the “severely excluded”. The discussion emphasizes the importance of preserving a multidimensional perspective when studying social exclusion. When addressing old-age exclusion, policy should be sensitive to the diverse categories and realize that one-size-fits-all policies and interventions are no solution.
KeywordsMultiple social exclusion Old-age social exclusion Social exclusion measurement Latent Class Analysis
We would like to acknowledge the four anonymous reviewers for the valuable suggestions on this article. We acknowledge the provincial and local governments of the participating municipalities for their support and cooperation throughout the research. We thank the older volunteers for their commitment throughout the research.
Compliance with Ethical Standards
Conflict of interest
The authors declare that they have no conflict of interest.
- Barnes, M., Blom, A., Cox, K., Lessof, C., & Walker, A. (2006). The social exclusion of older people: Evidence from the first wave of the English Longitudinal Study of Ageing (ELSA). London: Office of the Deputy Prime Minister.Google Scholar
- Beck, U. (1986). Risikogesellschaft. Auf dem Weg in eine andere Moderne. Frankfurt: Suhrkamp.Google Scholar
- Becker, E., Boreham, R., & National Centre for Social Research. (2009). Understanding the risks of social exclusion across the life course: Older age. London: Social Exclusion Task Force.Google Scholar
- De Donder, L., De Witte, N., Dury, S., Buffel, T., Brosens, D., Smetcoren, A. S., et al. (2015). Feelings of unsafety among older people: Psychometric properties of the EFU-scale. Procedia: Social and Behavioral Sciences, 191, 1095–1101.Google Scholar
- Dierckx, D., Coene, J., & Raeymaeckers, P. (2015). Armoede en sociale uitsluiting: Jaarboek 2014. Leuven: Acco.Google Scholar
- European Commission. (2014). Tacking stock of the Europe 2020 strategy for smart, sustainable and inclusive growth. European Commission. http://ec.europa.eu/europe2020/pdf/europe2020stocktaking_en.pdf. Accessed 24 June 2014.
- Eurostat. (2015). Labour force survey statistics—Transitions from work to retirement. Eurostat. http://ec.europa.eu/eurostat/statistics-explained/index.php/Labour_force_survey_statistics_-_transition_from_work_to_retirement/. Accessed 9 December 2015.
- Frétigné, C. (1999). Sociologie de l’exclusion. Paris: L’Harmattan.Google Scholar
- Kankaraš, M., Moors, G. B., & Vermunt, J. K. (2010). Testing for measurement invariance with Latent Class Analysis. In E. Davidov, P. Schmidt, & J. Billiet (Eds.), Cross-cultural analysis. Methods and applications (pp. 359–384). New York/Sussex: Routledge/Taylor & Francis Group.Google Scholar
- Kneale, D. (2012). Is social exclusion still important for older people?. London: The International Longevity Centre.Google Scholar
- Labonté, R. N., Hadi, A., & Kauffmann, X. E. (2011). Indicators of social exclusion and inclusion: A critical and comparative analysis of the literature (Vol. 2, no. 8). Working papers. Ottawa: Globalization and Health Equity Research Unit, Institute of Population Health, University of Ottawa.Google Scholar
- Levitas, R., Pantazis, C., Fahmy, E., Gordon, D., Lloyd, E., & Patsios, D. (2007). The multi-dimensional analysis of social exclusion. Bristol: Department of Sociology and School for Social Policy Townsend Center for the International Study of Poverty and Bristol Institute for Public Affairs University of Bristol.Google Scholar
- Magidson, J., & Vermunt, J. K. (2004). Latent class models. In D. Kaplan (Ed.), The Sage handbook of quantitative methodology for the social sciences (pp. 175–198). Thousand Oaks: Sage.Google Scholar
- Mezey, G., White, S., Thachil, A., Berg, R., Kallumparam, S., Nasiruddin, O., et al. (2013). Development and preliminary validation of a measure of social inclusion for use in people with mental health problems: The SInQUE. International Journal of Social Psychiatry, 59(5), 501–507.CrossRefGoogle Scholar
- Noppe, J., Vergeynst, T., & Jacques, A. (2016). Vlaamse Armoedemonitor. Brussel: Studiedienst Vlaamse Regering.Google Scholar
- Pannecoucke, I., Lahaye, W., Vranken, J., & Van Rossem, R. (2014). Armoede in België. Jaarboek 2014. Gent: Academia Press.Google Scholar
- Rodríguez-Mañas, L., Féart, C., Mann, G., Viña, J., Chatterji, S., Chodzko-Zajko, W., et al. (2013). Searching for an operational definition of frailty: A delphi method based consensus statement. The frailty operative definition-consensus conference project. The Journals of Gerontology: Series A, 68(1), 62–67.CrossRefGoogle Scholar
- Scharf, T., Phillipson, C., & Smith, A. E. (2005a). Multiple exclusion and quality of life amongst excluded older people in disadvantaged neighbourhoods. London: Office of the Deputy Prime Minister.Google Scholar
- Vermunt, J. K. (1997). LEM 1.0: A general program for the analysis of categorical data. Tilburg: Tilburg University.Google Scholar
- Ward, P., Walsh, K., & Scharf, T. (2014). Measuring old-age social exclusion in a cross-border context. Findings of a comparative secondary analysis in Ireland and Northern Ireland. Galway: Irish Centre for Social Gerontology.Google Scholar
- Whelan, C. T., & Maître, B. (2008). “New” and “old” social risks: Life cycle and social class perspectives on social exclusion in Ireland. Economic and Social Review, 39(2), 131–156.Google Scholar
- Wilks, R., Younger, N., Mullings, J., Zohoori, N., Figueroa, P., Tulloch-Reid, M., et al. (2007). Factors affecting study efficiency and item non-response in health surveys in developing countries: The Jamaica national healthy lifestyle survey. BMC Medical Research Methodology. https://doi.org/10.1186/1471-2288-7-13.CrossRefGoogle Scholar