Corresponding author: Jitka Rychtaříková ( rychta@natur.cuni.cz ) © 2019 Jitka Rychtaříková.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Rychtaříková J (2019) Perception of population ageing and age discrimination across EU countries. Population and Economics 3(4): 1-29. https://doi.org/10.3897/popecon.3.e49760
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Population ageing is the most dominant demographic challenge that the European Union is experiencing in the 21st century. This may create negative attitudes and lead to discrimination against persons of advanced age. Age-related stereotypes and prejudice can result in age discrimination, termed ageism. This research concerns the question of perceived ageism towards older people in 25 EU countries, surveyed in 2015 using the Special Eurobarometer 437. The analytical section includes descriptive findings and the results of three multi-level regression models addressing three domains (explained variables) of perceived ageism: 1) discrimination in general, 2) discrimination during economic crisis, and 3) discrimination when electing an older person as a high official. The two-level regression allowed simultaneous modelling of individual-level (gender, age, partnership status, social class, and life satisfaction) and of country-level (life expectancy at 55, perceived start of old age, and HDI) effects. The personal characteristics impacted much stronger perceived ageism than country contexts. Ageist perception in general has mostly been noted at pre-retirement age, but the age profile has not been the same across three regression models. The East-West gradient, frequently reported, is questioned because the geographical picture of perceived ageism is rather puzzling.
Key words population ageing, perceived ageism, age discrimination, European Union
The objective of the study is twofold: firstly, to describe briefly the main trends related to population ageing and, secondly, as the key point, to address the theme of old age discrimination in Europe.
The size and age composition of a population are determined by three demographic processes: fertility, mortality and migration. The change in age structure when the proportion of people aged 60 or 65 and over is increasing is called population ageing. In developed countries the age of 65 years is referred to as ‘old age’, because retirement schemes typically consider this age as the ‘normal’ retirement age. Declining fertility and increasing longevity are key drivers of population ageing, while migration contributes to this phenomenon to a lesser extent. Population ageing is the most dominant demographic challenge that the European Union is experiencing in the 21st century. The social and economic implications of such a historically unprecedented development will affect everybody. The shift in age structure raises concerns about the long-term viability of intergenerational social support systems: as more people live longer, retirement, pensions and other social benefits tend to extend over longer periods of time, making it necessary for social security systems to change substantially to remain effective. Increasing longevity can also result in rising medical costs and in increasing demands for health services, since older people are typically more vulnerable to chronic diseases (
At present, almost every country is experiencing growth in the number and proportion of older persons in their population. The share of older persons in the total population will further increase significantly in the coming decades. Looking back in history, no country had more than 11 % of its population aged 65 and over, apart from in 1950, but in 2018 the highest figures already amounted to 27.6 % in Japan and 22.8 % in Italy (
The population of the EU-28 on 1 January 2018 was estimated at 512.4 million. Young people (0 to 14 years old) made up 15.6 % of the EU-28’s population, while persons considered to be of working age (15 to 64 years old) accounted for 64.7 % of the population. Older persons (aged 65 or over) had a 19.7 % share. Consequently, Europe is and will remain the world’s oldest region throughout the 21st century. Moreover, the older population itself is ageing and the oldest-old (aged 80+) represent the fastest growing age group (Eurostat Database). Across the EU member states the highest share of people aged 65 and older was observed on 1 January 2018 in Italy (22.6 %) and Greece (21.8 %), while Ireland (13.8 %) and Slovakia (15.5 %) had the lowest percentages (Figure
The share of population of 65 years and older and 80 years and older 1.1.2018 (% of total population of a respective country). Source: EUROSTAT; EU countries having more than one million inhabitants.
Figure
The experience of intense population ageing is historically new and brings new challenges including people’s perception and expectations about older people. This new experience might create negative attitudes and lead to discrimination against persons of advanced age. Research shows that age, together with gender, are the most frequently mentioned reasons for discrimination in the EU (
Getting older today is often viewed as a biological process of senescence due to the gradual deterioration of body and to some degree it is also seen as a limitation of mental functions. This is manifested, in general, by an increasing risk of morbidity and mortality with age. Consequently, there is a stereotyping belief that old age is a uniform stage of the end of life when people are mostly sick, dependent, weak, incompetent, poor or lonely. Older people are consequently considered as one homogeneous group despite their diverse living situations.
Research showed that age related cognitive changes start usually after the age of 85 (
Age stereotypes and prejudice can result in age discrimination, termed ageism (
Looking back in history, definitions and concepts of ageism have changed over time. R. Butler was the first to introduce the term ageism (
Perceptions of ageing and ageism are multi-dimensional and can encompass both positive and negative views. The notion of positive and negative ageism was first introduced by E. Palmore in 1999. He defined nine major stereotypes that reflect negative prejudice toward old people: illness, impotency, ugliness, mental decline, mental illness, uselessness, isolation, poverty, and depression. Positive ageism is less common; E. Palmore listed eight major positive stereotypes: kindness, wisdom, dependability, affluence, political power, freedom, eternal youth, and happiness. The combination of negative and positive stereotypes is summarised in the Stereotype Content Model (SCM) proposed in 2002 (
The next analytical section addresses perceived ageism towards older people in 25 EU countries from three perspectives: a) Perception of discrimination in general, b) Age discrimination in hard economic times, c) Age prejudice against old age high officials. The results are discussed within the framework of above theories and other research.
People’s attitudes and stereotypes are formed at individual as well as at societal levels. Individual characteristics such as gender, age, socio-economic status etc. can influence one’s way of judging people. Societal context can shape the attitudes towards old age. Since Europe is diverse regarding its political, socio-economic and cultural contexts, it is important to explore the impact of country differences, besides individual characteristics. The study of differentiation between macro-(country) and micro-(individual) level predictors provides information on how much of variability in ageist statements is due to country socio-cultural contexts and what extent can be attributed to individual differences.
The present research primarily concerns the question of perceived ageism towards older people; therefore, we do not explore experienced ageism. Perceived discrimination is the perception of being treated unfairly by others because of personal attributes and also due to country contexts. Data primarily come from 25 countries of EU surveyed in 2015 with the Special Eurobarometer 437 (Malta, Cyprus and Luxembourg were omitted because of their small population size, which might reflect a special social climate). The respondents represent the resident population aged 15 years and over
In order to grasp the contextual differences between countries, relevant country-level variables were collected independently from the Eurobarometer survey data. Available macro-level statistics often reflect shared underlying factors (for example a degree of economic development). Our aim was to select relevant macro-indicators that could provide unique information and that were statistically significant in at least one of three final regression models. We first selected the following macro-level indicators: proportion of population aged 55 and over, prospective proportion old, life expectancy at age 55 for both sexes, perceived start of old age, old-age dependency ratio (OADR), prospective old-age dependency ratio (POADR), Gross Domestic Product per capita in Purchasing Power Standards (GDP PPS), Gini coefficient, Active Ageing Index (AAI), Human Development Index (HDI), and Human Life Indicator (HLI). The results of bivariate correlations of the above mentioned indicators with three variables are: a) percentage of people answering that discrimination on the basis of being over 55 years old is very or fairly widespread, b) percentage of people stating that to tackle the economic crisis, people aged 55 and over should be excluded from recovery measures (answer = yes definitely), c) percentage of people saying that they would not feel comfortable at all having a person over 75 years of age in the highest elected political position, showed that the strongest correlations are for life expectancy at age of 55 for both sexes, perceived start of old age, and Human Development Index.
The three selected country macro-indicators were then linked with the following micro-level survey data. For regression modelling the individual (micro)-level variables were transformed into categorical variables with the use of the subsequent reference-coding scheme; reference categories are in bold:
Three regression models address three different types of perceived discrimination against older people and are specified with the following outcome variables: 1) discrimination in general against 55+, 2) discrimination during economic crisis against 55+, and 3) discrimination when electing an old person (75+) as a high official. The independent variables are the same for all three models: at individual level- categorical predictors- (gender, age, partnership status, social class, and life satisfaction) and at country level- covariates- (human development index, life expectancy at age 55, perceived start of old age). Multi-level modelling is suitable when data are grouped (clustered), because individual attitudes can be affected by a country context (
To model these effects SAS 9.4 software was used (Linear Mixed Models - LMM, proc mixed). In order to maximize the explanatory power, the predictors were restricted to those that were most central theoretically and statistically significant. Categorized individual (micro)-level predictors and continuous country (macro)- level predictors transformed into Z-scores were used for parameter estimates. Interaction terms were not statistically significant and therefore the model is limited to main effects only. A two-level model (level 1 = respondents, level 2 = countries) with random intercept (intercepts are permitted to vary by country) was applied. The decision was supported by the fact that when trying to perform random intercept and random slope modelling, only intercept random effects were statistically significant, while all slope effects were insignificant. To estimate parameters, maximum likelihood (ML) was used, which is better for unbalanced data. All three regressions start with an ‘unconditional’ or means-only model and then the following variables are added: 1) macro-level predictors, 2) micro-level variables, 3) both macro and micro indicators, and 4) final model consists of only significant predictors. Intraclass Correlation Coefficient (ICC: the ratio of the between-cluster variance to the total variance) shows how much of the overall variation in the response is explained by countries. Intraclass correlation takes values from 0 to 1
Three different indicators of perceived discrimination against older people are included as outcome variables in multilevel regression models:
In contrast to the original coding, the codes were rearranged in the same direction: going from lower discrimination (low values) towards higher discrimination (higher values). Answers DK (don’t know) were excluded, resulting in slightly different numbers of respondents for each of the three above mentioned models.
The analytical section first includes descriptive findings and then presents the results of the multi-level regression modelling in the second part.
The distribution of three different types of perceived discrimination against old people across 25 EU countries have been examined: a) Perception of discrimination in general, b) Age discrimination in hard economic times, c) Age prejudice against old age high officials.
a) Perception of discrimination in general
The Figure
Perception of discrimination in general Sorted according to “very widespread”+”fairly widespread” N=23 872. Question: Could you please tell me whether, in your opinion a discrimination on the basis of being over 55 years old is very widespread, fairly widespread, fairly rare or very rare in your country? Coding: 5=very widespread, 4=fairly widespread, 3= fairly rare, 2=very rare, 1=non-existent. Source: Special Eurobarometer 437
Often, differences in values and beliefs are inferred from broad classification into ‘Eastern’ versus ‘Western Europe’. This cannot be applied here, because Denmark and Poland show weak ageist attitudes (Figure
b) Age discrimination in hard economic times
Ageism, primarily at work, can emerge strongly during economic crises. Older employees may be perceived as more expensive and less efficient than their younger counterparts, which might exacerbate the crisis further.
During difficult economic times, intensified discrimination can occur in the recruitment process by refusing to hire an older person or by making someone redundant because of his or her age. This type of discrimination where older workers for instance are paid less than younger workers are or are left out of promotions, is referred to as hard discrimination. Soft discrimination consists of practices that occur in the interpersonal sphere, such as ageist jokes or remarks, receiving lower evaluation of work, being treated disrespectfully, etc. (
Figure
Discrimination against people aged 55+ during economic crisis Sorted according to yes definitely N=22 421 Question: Do you think that measures to fight the economic crisis and policies to promote recovery are excluding people aged 55 and over? Coding: 4=Yes, definitely 3=Yes, to some extent, 2=No, not really 1=No, definitely not. Source: Special Eurobarometer 437
c) Age prejudice against old age high officials
Some older adults retain outstanding cognitive function well into their 70s and 80s. In general, speech and language processing are good in older adults under normal conditions and they may even have a more extensive vocabulary compared to younger people (
Six former socialist countries (Lithuania, Latvia, Romania, Bulgaria, Czechia, Slovakia, and Slovenia) appear to be unwilling to have an old person in the highest political position (Figure
Ageist prejudice against old aged high officials Sorted according to Not at all comfortable N=22 728 Question: Using a scale from 1 to 10, please tell me how you would feel about having a person over 75 years old in the highest elected political position? Coding: scale from 10=not at all comfortable to 1=totally comfortable Source: Special Eurobarometer 437
To summarize the descriptive findings related to three different types of perceived discrimination: a) against elders in general, b) during hard economic times, and c) against old people in high political position, we conclude that an increased expression of age discrimination is more noticeable in the former socialist countries with the exception of Poland. Concerning ‘Western’ Europe, the picture is more ambiguous; while Denmark held non-ageist position for the first two questions only, the ranking of the United Kingdom or Italy was variable across the discrimination types. For a further in-depth investigation of matters related to ageism, a more sophisticated analytical approach based on multilevel modelling and micro-, macro-level selected explanatory factors has been applied in the next section.
This section addresses individual and contextual perspectives by means of two-level modelling (level 1 = respondent characteristics, level 2 = country background). This integrated analysis enables to show how individual- (micro) level variables and macro- (country) level indicators impact age discrimination, taking into account personal and regional contexts.
Two key questions are addressed:
a) Perceived discrimination on the basis of being over 55 years old
Table
Random intercept model predicting discrimination based on being over 55 years old (Model 1).
Unconditional model | Model with macro-level predictors | Model with micro-level predictors | Model with all predictors | Model with all relevant predictors at p<0.05 | |
---|---|---|---|---|---|
Intercept | 3.2602 | 3.2604 | 2.8217 | 2.8224 | 2.8223 |
Micro-level predictors | |||||
Gender | |||||
Man (ref) | 0 | 0 | 0 | ||
Woman | 0.139 | 0.1389 | 0.1388 | ||
Age | |||||
15-24 (ref) | 0 | 0 | 0 | ||
25-34 | 0.1996 | 0.2003 | 0.2002 | ||
35-44 | 0.2366 | 0.2375 | 0.2374 | ||
45-54 | 0.2885 | 0.2897 | 0.2896 | ||
55-64 | 0.3107 | 0.312 | 0.3119 | ||
65-74 | 0.2328 | 0.2344 | 0.2343 | ||
75+ | 0.1665 | 0.1683 | 0.1682 | ||
Partnership status | |||||
(Re-)Marries/single with partner (ref) | 0 | 0 | 0 | ||
Divorced or separated | 0.0861 | 0.087 | 0.0869 | ||
Widowed | 0.0083 | 0.0081 | 0.008 | ||
Single | 0.0025 | 0.0035 | 0.0035 | ||
Social class | |||||
Middle class (ref) | 0 | 0 | 0 | ||
Working class | 0.0457 | 0.0454 | 0.0455 | ||
Lower middle class | 0.0217 | 0.0218 | 0.0219 | ||
Upper middle class | 0.0741 | 0.0749 | 0.0747 | ||
Higher class | -0.0533 | -0.0531 | -0.0534 | ||
Life satisfaction | |||||
Very satisfied (ref) | 0 | 0 | 0 | ||
Fairly satisfied | 0.1066 | 0.1046 | 0.1048 | ||
Not very satisfied | 0.199 | 0.1955 | 0.1958 | ||
Not at all satisfied | 0.3928 | 0.3889 | 0.3893 | ||
Macro-level predictors | |||||
Life expectancy at 55 | 0.0666 | 0.0543 | |||
Perceived start of old age | -0.0173 | -0.0178 | |||
Human development index | -0.197 | -0.1556 | -0.1187 | ||
ICC (intraclass correlation coefficient) | 0.057 | 0.04 | 0.051 | 0.04 | 0.04 |
AIC (Akaike Information Criterion) | 72 221 | 72 218 | 71 826 | 71 825 | 71 822 |
N (number of respondents in 25 countries) | 23 872 | 23 872 | 23 872 | 23 872 | 23 872 |
The last option with statistically significant coefficients shows that women perceive higher age discrimination (0.1388) compared to men (0). The marginalization of women was observed throughout history when they occupied a lower social status and were disadvantaged at labour markets. Even today, after adjusting for the remaining variables in the model, this discrimination is significant. We also talk about gendered ageism, which refers to the difference in stereotyping and discriminating older men versus older women, and which leads to faster deterioration of older women’s status compared to men (
The Modernization Theory explains the loss of social status experienced by older workers in modern times due to a devaluation of their performance (
Belonging to upper middle class (0.0747) or working class (0.0455) compared to middle class (0) also generates a sentiment of perceived discrimination. Social or socioeconomic status affects overall human functioning, including physical and mental health. Those with lower levels of socioeconomic status or social class are more likely to experience worse health and have a greater risk of depression. Belonging to a lower social class also means benefitting less from educational or employment opportunities that would eventually increase social mobility, which in turn could improve personal situation (
When looking at country differences (although weak; ICC= 4 %; last model option) as shown in Figure
Country ranking according to perceived discrimination against people 55+ years old. Source : author’s calculations
b) Potential discrimination of people over 55 years old during economic crisis
Competition over scarce resources can lead to negative intergroup attitudes or hostility. During hard times, as in periods of economic crisis, the idea to exclude people over 55 years of age from recovery initiatives, like protecting or retraining unemployed, can be appealing. Intergroup Threat Theory or Intergenerational Conflict Theory are grounded on expectations that participation in activities by older people should be regulated or better, reserved for younger people, because older generations’ more limited consumption. Model 2 addresses this issue (Table
Random intercept model predicting a discrimination of people aged 55 and over during an economic crisis (Model 2).
Unconditional model | Model with macro-level predictors | Model with micro-level predictors | Model with all predictors | Model with all relevant predictors at p<0.05 | |
---|---|---|---|---|---|
Intercept | 2.5561 | 2.5562 | 2.431 | 2.4317 | 2.4315 |
Micro-level predictors | |||||
Gender | |||||
Man (ref) | 0 | 0 | 0 | ||
Woman | 0.0776 | 0.0777 | 0.0777 | ||
Age | |||||
15-24 (ref) | 0 | 0 | 0 | ||
25-34 | 0.0254 | 0.025 | 0.0253 | ||
35-44 | -0.0055 | -0.0061 | -0.0057 | ||
45-54 | 0.0182 | 0.0175 | 0.018 | ||
55-64 | 0.0686 | 0.0678 | 0.0685 | ||
65-74 | 0.046 | 0.0449 | 0.0456 | ||
75+ | 0.0526 | 0.0516 | 0.0522 | ||
Partnership status | |||||
(Re-)Marries/single with partner (ref) | 0 | 0 | 0 | ||
Divorced or separated | -0.0035 | -0.0028 | -0.0029 | ||
Widowed | -0.0655 | -0.0646 | -0.0647 | ||
Single | 0.024 | 0.0237 | 0.0239 | ||
Social class | |||||
Middle class (ref) | 0 | 0 | 0 | ||
Working class | 0.0479 | 0.0481 | 0.0477 | ||
Lower middle class | 0.0394 | 0.0398 | 0.0392 | ||
Upper middle class | -0.0153 | -0.0158 | -0.0151 | ||
Higher class | -0.1475 | -0.1468 | -0.1459 | ||
Life satisfaction | |||||
Very satisfied (ref) | 0 | 0 | 0 | ||
Fairly satisfied | 0.0288 | 0.0287 | 0.0284 | ||
Not very satisfied | 0.0896 | 0.089 | 0.0889 | ||
Not at all satisfied | 0.1737 | 0.173 | 0.1728 | ||
Macro-level predictors | |||||
Life expectancy at 55 | 0.2044 | 0.1913 | 0.2573 | ||
Perceived start of old age | 0.0707 | 0.0741 | |||
Human development index | -0.1997 | -0.1752 | -0.2011 | ||
ICC (intraclass correlation coefficient) | 0.053 | 0.024 | 0.051 | 0.023 | 0.027 |
AIC (Akaike Information Criterion) | 61 181 | 61 167 | 61 103 | 61 089 | 61 090 |
N (number of respondents in 25 countries) | 22 421 | 22 421 | 22 421 | 22 421 | 22 421 |
The dependent variable is based on the question whether measures or policies to tackle the economic crisis and to promote recovery should exclude people over 55 years of age. Intercepts (mean scores of discrimination) have similar values for each model option (null model; model with macro- or micro-level predictors; with all predictors; and relevant predictors). The model with macro-level predictors only (Table
Scatter plot of discrimination of people 55+ old during economic crises versus a) Life expectancy at 55 and b) Human Development Index Note: Discrimination is defined as the percentage of answers 3=yes to some extent + 4= yes definitely
Table
Figure
Country ranking according to discrimination against people 55+ year old during an economic crisis. Source : author’s calculations
c) Age discrimination in elections for a high political position
Understanding age-related changes in cognition is particularly important when considering positions with high responsibility. There is evidence that alternations in the brain structure and function impact cognitive functions as age advances (
People have different roles and power in society. Positive personal relationships across intergroups are likely to produce less stereotypes of the outgroup as a whole. However, people feel rather more favourable towards their own age groups. Table
Random intercept model predicting ageist prejudice against old aged high officials (Model 3).
Unconditional model | Model with macro-level predictors | Model with micro-level predictors | Model with all predictors | Model with all relevant predictors at p<0.05 | |
---|---|---|---|---|---|
Intercept | 5.2153 | 5.2152 | 4.6079 | 4.6075 | 4.6086 |
Micro-level predictors | |||||
Gender | |||||
Man (ref) | 0 | 0 | 0 | ||
Woman | 0.1164 | 0.1162 | 0.1161 | ||
Age | |||||
15-24 (ref) | 0 | 0 | 0 | ||
25-34 | 0.0707 | 0.071 | 0.0718 | ||
35-44 | 0.1395 | 0.14 | 0.141 | ||
45-54 | 0.3972 | 0.398 | 0.3992 | ||
55-64 | 0.8051 | 0.8059 | 0.8073 | ||
65-74 | 0.6707 | 0.6721 | 0.6736 | ||
75+ | 0.504 | 0.5063 | 0.5078 | ||
Parnership status | |||||
(Re-)Marries/single with partner (ref) | 0 | 0 | 0 | ||
Divorced or separated | 0.2298 | 0.2308 | 0.2315 | ||
Widowed | -0.0343 | -0.0353 | -0.035 | ||
Single | 0.0323 | 0.0334 | 0.0342 | ||
Social class | |||||
Middle class (ref) | 0 | 0 | 0 | ||
Working class | 0.2463 | 0.2459 | 0.2453 | ||
Lower middle class | 0.1265 | 0.1267 | 0.1264 | ||
Upper middle class | -0.1727 | -0.1723 | -0.1714 | ||
Higher class | 0.2743 | 0.2723 | 0.2735 | ||
Life satisfaction | |||||
Very satisfied (ref) | 0 | 0 | 0 | ||
Fairly satisfied | -0.0052 | -0.0056 | -0.0079 | ||
N | 0.1609 | 0.1594 | 0.1558 | ||
0.2956 | 0.2944 | 0.2902 | |||
Macro-level predictors | |||||
Life expectancy at 55 | -0.9759 | -0.9787 | -0.5306 | ||
Perceived start of old age | 0.1378 | 0.1321 | |||
Human development index | 0.4331 | 0.4617 | |||
ICC (intraclass correlation coefficient) | 0.104 | 0.074 | 0.103 | 0.073 | 0.08 |
AIC (Akaike Information Criterion) | 115 969 | 115 965 | 115 706 | 115 703 | 115 701 |
N (number of respondents in 25 countries) | 22 728 | 22 728 | 22 728 | 22 728 | 22 728 |
The highest coefficients of disagreement are found in ages 55-64 (0.8073) and 65-74 (0.6736). For young people, this issue seems not important. The results contradict the Social Identity Theory stating that people identify with an own group and are more likely to defend its status. Women are less comfortable (0.1161) with an old political official than men (Table
Figure
Population ageing, as a global phenomenon of the 21st century, will affect everybody. Looking presently at the 25 analysed countries, the proportion of seniors primarily puts former socialist countries (younger population age structure) and Southern Europe, where populations are much older, at opposite ends. However, the picture is somewhat ambiguous as Latvia and Bulgaria, due to very low fertility levels, already belong to ‘old populations’. Both are likely frontrunners for the remaining post-socialist countries, as their populations are predicted to age fast because of the recent profound fertility decline.
Within the context of ongoing and future uneven global population ageing, old age discrimination - ageism can, in a number of ways, impact social cohesion, health and wellbeing of European societies. However, the research of perceived discrimination based on three different domains has shown that the traditional East-West gap does not appear in this context. The picture is neither clear in the ‘East’ nor in the ‘West’. Czechia is the only Eastern country showing consistent results of ingrained discriminatory attitudes towards the elderly population across all three examined domains of discrimination. Polish citizens on the other hand, perceive much less frequent discrimination in general and consider it acceptable to elect an old person into high political position. Unlike Poland, Slovakia does not support discriminatory measures against the elderly during the times of economic crisis. In the ‘West’, the Netherlands and Finland show discrimination against old age in all three domains, while in France ageism is reported for the first question on perceived discrimination in general and when electing a person aged 75 and over into high political office.
The regression analysis has shown that the effects of personal characteristics are much significant than country contexts in perceived ageism. Ageism perceived by women appears stronger when compared to men across all three models. Older chronological age is expected to be associated with more intense perception of ageism. However, it is mostly notable for pre-retirement ages related to the question about general ageist perception; this age specificity is intensified in times of economic crisis. Individuals belonging to higher social groups and those in partnerships usually enjoy better life satisfaction, which the results showing a reduced disposition or sensitivity towards ageism confirm.
The Eurobarometer 2015 data on perceived ageism provide a framework for understanding people’s attitudes across three domains (in general, during hard times, and in politics) according to individual characteristics as well as country contexts. The impact of gender, age or wellbeing show to some extent similar directions already presented by ESS studies. However, the East-West gradient, frequently reported, is questioned when considering our findings, as the geographical picture is rather puzzling.
The studies of this type, combining micro- and macro-level indicators, are important and of enduring importance, because they provide not only information about people’s potential isolation and exclusion at old age, but can help in guiding policies on issues of age equality, specifically for each country. These findings can indicate opportunities for changing negative perceptions or stigmas of ageing that will affect everyone. Future research could further explore the differences between countries on the opposite ends of the geographical ageist spectrum (Czechia versus Poland or Finland versus Denmark), however this is beyond scope of this contribution.
The study was supported by the Czech Science Foundation, project GA ČR No.18-12166S
Jitka Rychtaříková, PhD, Professor, Department of Demography and Geodemography, Faculty of Science, Charles University (Prague). E-mail: jitka.rychtarikova@natur.cuni.cz
Macro-indicators of selected countries.
Country | Macro-region | Life expectancy at age 55 both sexes (e55), 2015 | Perceived start of old age, 2012 | Human development index (HDI), 2015 |
Austria | W | 28.3 | 61.9 | 0.893 |
Belgium | W | 28.2 | 67.9 | 0.896 |
Bulgaria | E | 23.3 | 63.8 | 0.794 |
Croatia | E | 25.0 | 62.9 | 0.827 |
Czechia | E | 25.9 | 59.5 | 0.878 |
Denmark | W | 27.7 | 64.3 | 0.925 |
Estonia | E | 26.3 | 62.4 | 0.865 |
Finland | W | 28.6 | 65.2 | 0.895 |
France | W | 29.9 | 65.9 | 0.897 |
Germany | W | 27.8 | 60.1 | 0.926 |
Greece | W | 28.3 | 65.7 | 0.866 |
Hungary | E | 23.7 | 58.0 | 0.836 |
Ireland | W | 28.4 | 64.2 | 0.923 |
Italy | W | 29.3 | 67.6 | 0.887 |
Latvia | E | 24.2 | 61.5 | 0.830 |
Lithuania | E | 24.3 | 65.3 | 0.848 |
Netherlands | W | 28.3 | 70.4 | 0.924 |
Poland | E | 25.7 | 62.8 | 0.855 |
Portugal | W | 28.5 | 67.9 | 0.843 |
Romania | E | 23.8 | 60.5 | 0.802 |
Slovakia | E | 24.8 | 57.7 | 0.845 |
Slovenia | E | 27.9 | 66.4 | 0.890 |
Spain | W | 29.7 | 65.5 | 0.884 |
Sweden | W | 29.0 | 66.6 | 0.913 |
United Kingdom | W | 28.3 | 61.9 | 0.909 |
Sources: | e55, year 2015; | Human Mortality Database | ||
Perceived start of old age | Special Eurobarometer 378/EB76.2. | |||
HDI | Human Development Report 2016, p.198 |
Descriptive indicators.
Country | Macro- region | Number of respondents | Mean score | Men | Women | ||||||||||
Mean age | Mean age | ||||||||||||||
N | N1 | N2 | N3 | 1 | 2 | 3 | MA1 | MA2 | MA3 | MA1 | MA2 | MA3 | |||
Austria | W | 1035 | 965 | 921 | 814 | 3.17 | 2.55 | 4.71 | 47.5 | 48.1 | 47.2 | 46.8 | 46.8 | 46.8 | |
Belgium | W | 1012 | 915 | 889 | 920 | 3.28 | 2.52 | 4.76 | 55.3 | 55.1 | 55.4 | 52.5 | 52.5 | 52.7 | |
Bulgaria | E | 1058 | 919 | 827 | 835 | 3.64 | 2.66 | 6.16 | 49.5 | 49.7 | 49.4 | 49.6 | 49.4 | 49.5 | |
Croatia | E | 1003 | 944 | 866 | 922 | 3.35 | 2.45 | 3.91 | 45.2 | 45,0 | 45.1 | 44.9 | 44.6 | 44.9 | |
Czechia | E | 1008 | 934 | 890 | 877 | 3.64 | 2.55 | 6.76 | 46,0 | 45.6 | 46.2 | 48.4 | 48.3 | 48.4 | |
Denmark | W | 1016 | 946 | 900 | 906 | 2.61 | 2.15 | 5.58 | 55.8 | 55.5 | 56.1 | 54.8 | 55.1 | 55.0 | |
Estonia | E | 1018 | 808 | 747 | 712 | 2.97 | 2.32 | 5.78 | 51.3 | 51.1 | 51.5 | 55.3 | 55.7 | 55.9 | |
Finland | W | 1004 | 936 | 864 | 865 | 3.31 | 2.76 | 6.28 | 53.9 | 53.6 | 55,0 | 53.5 | 53.5 | 54.4 | |
France | W | 1000 | 920 | 850 | 941 | 3.57 | 2.67 | 5.87 | 52.3 | 52.7 | 52.8 | 51,0 | 51,0 | 51,0 | |
Germany | W | 1513 | 1400 | 1323 | 1251 | 2.86 | 2.33 | 5.41 | 52.2 | 52.2 | 52.2 | 51.5 | 51.4 | 51.8 | |
Greece | W | 1009 | 955 | 940 | 943 | 3.21 | 2.92 | 4.71 | 45.8 | 46.1 | 45.9 | 48.6 | 48.5 | 48.8 | |
Hungary | E | 1051 | 990 | 964 | 945 | 3.57 | 2.36 | 4.84 | 48.9 | 48.9 | 48.8 | 51.1 | 51.7 | 51.4 | |
Ireland | W | 1004 | 932 | 890 | 928 | 2.95 | 2.53 | 3.49 | 49,0 | 49.1 | 48.5 | 47.1 | 47.4 | 47.2 | |
Italy | W | 1040 | 956 | 932 | 872 | 3.09 | 2.76 | 3,50 | 48.2 | 47.7 | 48.9 | 47,0 | 47.3 | 47.5 | |
Latvia | E | 1003 | 845 | 728 | 831 | 3.34 | 2.33 | 6.62 | 46.1 | 46.8 | 45.6 | 50.1 | 49.6 | 50.4 | |
Lithuania | E | 1004 | 943 | 852 | 944 | 3.37 | 2.81 | 7.53 | 46.4 | 46.0 | 46.9 | 54.3 | 53.5 | 54.8 | |
Netherlands | W | 1008 | 929 | 922 | 929 | 3.29 | 2.54 | 5,50 | 53.2 | 53.5 | 53.7 | 52.4 | 52.7 | 52.6 | |
Poland | E | 1005 | 864 | 768 | 863 | 2.73 | 2.49 | 4,60 | 46.5 | 47.0 | 46.7 | 47.1 | 46.7 | 47.9 | |
Portugal | W | 1005 | 904 | 861 | 793 | 3.45 | 2.79 | 4.14 | 48.9 | 49.1 | 48.8 | 49.5 | 49.1 | 49.2 | |
Romania | E | 1012 | 909 | 831 | 851 | 3.59 | 2.48 | 5.78 | 45.5 | 45.1 | 45.6 | 47.1 | 46.3 | 48,0 | |
Slovakia | E | 1016 | 929 | 896 | 855 | 3.52 | 2,20 | 6.52 | 49.2 | 49.1 | 49.9 | 50,0 | 50.2 | 50.4 | |
Slovenia | E | 1019 | 903 | 838 | 833 | 3.29 | 2.66 | 5.34 | 49.9 | 49.5 | 49.2 | 51.1 | 50.8 | 50.9 | |
Spain | W | 1000 | 954 | 919 | 887 | 3.15 | 3.17 | 3.92 | 48.7 | 48.2 | 49.2 | 49,0 | 48.4 | 49.3 | |
Sweden | W | 1066 | 983 | 929 | 1005 | 3.17 | 2.46 | 4.66 | 54.4 | 54.4 | 54.1 | 58.4 | 58.6 | 57.7 | |
United Kingdom | W | 1306 | 1189 | 1074 | 1206 | 3.40 | 2.41 | 4.02 | 50.6 | 50.4 | 50.5 | 51.5 | 51.3 | 51.5 | |
Total | 26215 | 23872 | 22421 | 22728 |
Annex II (continued)
Notes: | N | number of respondents in the original data file |
N1 | number of respondents for model1 | |
N2 | number of respondents for model2 | |
N3 | number of respondents for model3 | |
Mean score | 1: Question | Could you please tell me whether, in your opinion, a discrimination on the basis of being over 55 years old is very widespread, fairly widespread, fairly rare or very rare in your country? |
Coding: 5=very widespread, 4=fairly widespread, 3= fairly rare, 2=very rare, 1=non-existent | ||
2: Question | Do you think that measures to fight the economic crisis and policies to promote recovery are excluding people aged 55 and over? | |
Coding: 4=Yes, definitely, 3=Yes, to some extent, 2=No, not really, 1=No, definitely not | ||
3: Question | Using a scale from1 to 10, please tell me how you would feel about having a person over 75 years old in the highest elected political position? | |
Coding: 10=not at all comfortable, 9, 8, 7,…2, 1=totally comfortable | ||
Mean age of respondents | MA1 | for model 1 |
MA2 | for model 2 | |
MA3 | for model 3 |