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Forever young? An analysis of the factors influencing perceptions of ageing

Published online by Cambridge University Press:  26 February 2019

Valeria Bordone*
Affiliation:
Department of Sociology, University of Munich (LMU), Munich, Germany
Bruno Arpino
Affiliation:
Department of Political and Social Sciences, Pompeu Fabra University, Barcelona, Spain
Alessandro Rosina
Affiliation:
Center for Applied Statistics in Business and Economics, Catholic University, Milan, Italy
*
*Corresponding author. Email: valeria.bordone@lmu.de
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Abstract

Drawing on the revived literature on the subjective dimension of ageing, this paper investigates whether people aged 65+, usually defined as old, do actually feel old and which events they associate with feeling old. Logistic models are used on unique data from the 2013 survey called ‘I Do Not Want to Be Inactive’, conducted on individuals aged 65–74 in Italy (N = 828). It is found that a large proportion of respondents do not feel old at all. The analyses show that women are more likely than men to feel old and to think that society considers them old. While men feel old mainly when they retire, women associate this feeling with loneliness, loss of independence and death of loved ones. Higher-educated people are less likely to associate feeling old with loneliness and boredom than their lower-educated counterparts. The findings have important implications for the conceptualisation of ageing. Most people who are old according to the standard threshold of 65 do not consider reaching this age as a distinctive marker of old age in their lifecourse. This suggests that absolute thresholds for setting the start of old age are questionable. Feeling old seems to be mainly influenced by events, such as retirement and death of loved ones, hinting to the importance of the social construction of ageing in addition to its biological dimension. Researchers and policy makers are encouraged to give more attention to layperson views on ageing.

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Copyright © Cambridge University Press 2019
Figure 0

Table 1. Descriptive statistics of the independent variables, by gender

Figure 1

Table 2. Descriptive statistics of the dependent variables, by gender

Figure 2

Table 3. Descriptive statistics of the dependent variables, by education

Figure 3

Table 4. Odds ratios estimates (standard errors in parentheses) from logistic regressions