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Article

Age Discrimination of Senior Citizens in European Countries

by
Agnes Santha
* and
Emese Emőke Tóth-Batizán
Department of Applied Social Sciences, Faculty of Technical and Human Sciences Targu Mures, Sapientia Hungarian University of Transylvania, 540485 Targu Mures, Romania
*
Author to whom correspondence should be addressed.
Societies 2024, 14(10), 198; https://doi.org/10.3390/soc14100198
Submission received: 23 July 2024 / Revised: 7 September 2024 / Accepted: 2 October 2024 / Published: 7 October 2024

Abstract

:
This paper addresses perceived age discrimination of older persons in European countries. This disturbing issue has become all the more prominent, having doubled over a relatively short period between 2018 and 2021. Strongly associated with bad health outcomes, low levels of wellbeing, and considerable social tensions, age-related discrimination against senior citizens is a sign of the lack of their social integration. Our study used secondary data analysis based on survey methodology. Statistical analysis was performed on data from the European Social Survey wave 10 (2021) subsample of people aged 65 and above to assess the senior population’s age-based discrimination experiences and its individual and macro-level determinants. The results indicate that in all European countries, low socioeconomic status, older age, and living alone are strongly associated with the experience of age discrimination. Having bad health and being functionally limited in everyday activities results in a state of dependency that is connected to a higher risk of perceived exposure to age discrimination. Smaller populations, such as those in villages, are protective against discrimination at older age. Finally, compared to other welfare regimes, in social democratic welfare states with egalitarian redistribution systems and high levels of social benefits, there is a significantly larger share of old people who reported to have been victims of age discrimination. Our results have implications for policy in the context of ageing societies.

1. Introduction

Human ageing is not only a biological process, when the human body goes through a change, but it is also embedded in a wider social context and is definitely shaped by social and cultural determinants. Also, usually, the societal discourse is about “the” process of aging, and the variety included into the ageing process is forgotten. As soon as this variety within the ageing process and within the group of the older people is neglected, a stereotypical construction of older people emerges, which can be labelled as “ageism”. Ageism is thus a complex, usually negative construction of certain ages. It can affect younger and older people as well; however, it most often affects older adults [1].
The COVID-19 pandemic has even pushed the cultural bias towards older people and has amplified their monolithic image, accentuating their portrayal as being unable to contribute towards the good of the society [2]. Age discrimination of senior citizens, that is, prejudices and unfavourable treatment toward older people, is thus a current and widespread social problem.
Discrimination can be defined as the actions arising from official institutions, profit-oriented entities, or individuals that disproportionately and systematically harm members of socially marginalised groups. Although discrimination can reveal itself in multiple forms such as ignoring, lack of respect, paternalism, marginalisation, humiliation, and even abuse, the narrow sense of the term refers to the perception that resources were denied to a person [3].
The perception and recognition of discrimination is one indicator of the success or otherwise of human rights and the equal treatment of citizens. Perceived discrimination leaves it to the people themselves to judge whether they perceive or experience discrimination or not. This approach is to some extent arbitrary, as people may perceive as discriminatory events that are not considered so according to the law or scientific definitions. By the same token, people may not perceive as discriminatory instances that are considered as such by law or scientific definition. The events perceived as discrimination may be intentional but may also be unintended by the other part [4].
Perceived discrimination is an important area of concern because it links structural inequalities to individual outcomes [5]. Experiencing discrimination has severe consequences for psychological and mental wellbeing and is one of the most important factors identified as a cause of mental health problems. As perceived discrimination is a stressor, it fosters negative emotions, so people’s satisfaction with life, their trust in other people, and ultimately their quality of life are strongly associated with this experience [6,7]. Perceived discrimination was found to mediate the association between low social status and mental health problems [8]. More so, experiencing long-term discrimination significantly increases the risk of mortality in adults [9].
Besides the better studied health consequences, there are other societal-level effects of perceived discrimination too. It can contribute to social tensions, and experiences of systematic discrimination have implications for the civic and political behaviour of discriminated groups. These groups may be motivated to express their grievances in political terms, to vote and protest their conditions [10], and eventually to engage in violent actions. Although this latter is not the particular case of senior citizens, any kind of discrimination threatens societal unity.
Among the main types of discrimination, the topic of age discrimination is receiving more and more sociological attention relative to class, race, and gender [5]. Nevertheless, ageism exists together with ableism, racism, sexism, classism, and other isms that jeopardise the opportunities of different individuals [11]. Intersectionality perspectives argue that not alone age but the interrelation of age with gender, age with race, age with sexual orientation, etc., is what finally results in discrimination [7]. According to the World Health Organisation, the intersectional approach takes into consideration different aspects of a person’s social and political identities and “their relation to hierarchies of privilege or disadvantage (e.g., age, sex, gender, race, ethnicity, class, socioeconomic status, religion, language, geographical location, disability status, migration status, gender identity and sexual orientation)” they way they interact with each other and reinforce each other, resulting in inequality [5] (p.10). Thus, it is of vital importance not to forget about the intersectionality perspective while discussing ageism. Probably the most widespread form of ageism is gendered ageism, described as a double jeopardy, “where two interacting power systems lead to an increased vulnerability” [12].
According to the modernisation theory, in societies shifting towards industrialisation, the societal status of older adults is undermined by the devaluation of their experience-based knowledge, and, in addition, traditional extended families are broken up [13]. At their workplace, older workers also experience a loss of social status due to a devaluation of their performance [1].
Today, within the ageing societies of Europe, age discrimination is on the increase and thus further gaining in relevance. Between the two latest data collections of the European Social Survey, within 3 years only, perceived age discrimination among the population aged 65 and above has, on the whole, more than doubled from 1.3% to 3%. This paper does not undertake a temporal analysis but focuses instead on the most recent data.
According to the intergroup threat theory, younger and active members of a society might perceive older persons as a threat, in a position to cause them harm, namely, a loss of resources [14]. Older people may be the target of contemptuous prejudice and seen as a burden to society who contribute less than they benefit [15].
Another possible reason for the observed sudden rise in age discrimination could be that during periods of detrimental conditions, old people themselves may experience increased anxiety about losing their existing privileges (i.e., social security through pensions) and could be more likely to perceive discrimination [16]. It is important to note here that perceived age discrimination is distinct from objective discrimination [17].
The perception of age discrimination is to a large extent an individual issue, for instance, susceptibility to forms of putative or real grievances may depend on personality traits such as general trust towards other people. Generally, people who perceive their own ageing positively rarely report age discrimination [18]. The impact of perceived discrimination on health and quality of life may also depend on the personality and on the ability to cope, but also on resources and other forms of support which buffer harmful influences.
There are macro-level factors shaping age discrimination such as attitudes and beliefs, which are embedded in a social and cultural context, originating in norms and customs, regulations, labour market, and laws [6]. Older people’s perceptions of age discrimination are influenced by their personal and by societal meta-perceptions of negative age stereotypes, but even more by social norms of intolerance toward age prejudice [15]. This study does not address these contexts but rather focuses on the personal characteristics, that is, individual-level demographic, socioeconomic, and health status characteristics of those who experience age discrimination, which have proven to impact far stronger incidents of perceived ageism than population-wide contexts [19]. In our analysis, the social context is indicated by the welfare regime type into which the countries are classified. This view provides the novelty of the research. By considering the welfare regime, we believe to address one important macro-level factor that influences societal attitudes towards its senior citizens.
Worldwide, one in six people who are older than 60 years tend to experience abuse in the community every year, with potentially severe consequences. Due to these alarming numbers, the WHO has set as their goal to combat ageism. Our study aims to fill a gap in the research, while contributing to understanding the nature of age discrimination, offering up-to-date empirical evidence and interpreting current data on the issue [5]. The aim of this paper was to assess the level of perceived age discrimination among the European senior population on a cross-sectional European population survey dataset and to draw the profile of the victims of ageism, that is, to identify the demographic, socioeconomic, and health-related determinants of such perceptions.

2. Literature Review

2.1. Welfare Regime as a Macro-Level Determinant of Ageism

It is reasonable to assume that older people’s place and judgement by society and, ultimately, their eventual discrimination is, at least in part, influenced by their social position within the particular setting. Therefore, this analysis calls upon the typology of welfare regimes which largely shapes the situation of inactive population groups, and among them, particularly within the context of ageing societies, that of older persons. Although criticised from time to time, the most established welfare regime typology is based on the categorisation of Esping-Andersen [20] with its later modifications by Ferrera [21], Szalai [22], and Kuitto [23].
The typology elaborated by Esping-Andersen has its origins in the mechanisms through which the state corrects market deficiencies. At one end of the continuum, there are market-based economies with low public social expenditure and low state involvement as the main determinants. The social policies of these countries are based on a strong political commitment to minimise public involvement, individualising risks and promoting market solutions. At the other end of the continuum, there is welfare capitalism, characterised by high public social expenditure and extensive state involvement [24].
Liberal welfare states leave it to the families and individuals to ensure their wellbeing through the market, and they only satisfy the residual needs by correcting the market irregularities. Thus, poverty is relatively widespread, and social rights are based upon needs. In liberal welfare regimes, there are modest state benefits based upon strict entitlement criteria, with recipients often being stigmatised [25]. In these countries, old-age pensions are more strongly regulated by market mechanisms and based on previous work performance [26], and there are low public pension benefits [27]. The United Kingdom and Ireland are European examples of the liberal welfare regime.
Conservative-corporatist welfare regimes do regulate income loss due to unemployment, but state redistribution is limited, and social rights including pension are based on employment and are largely determined by the contributions paid during active ages [28]. These systems offer relatively generous public benefits [27] but leave ground for larger pension inequalities, and, although lower than in liberal systems, there is a considerable rate of poverty in old age. Examples of this welfare regime are Austria, France, Germany, Belgium, the Netherlands, Switzerland, and Italy.
The social democratic welfare state is universalistic in its scope, and it offers income compensation based on needs, irrespective of previous employment. State redistribution is high; the welfare institutions aim at equalisation; and, accordingly, poverty levels are low. Old-age pension regulations are strongly based on needs, with nearly universal pension coverage [27]. This Scandinavian welfare model is defined by “unusually heavy social spending, benefits and services of high standards, and a high degree of government intervention” [24] (p. 791). Finland, Norway, Sweden, Denmark, and Iceland are examples of this most egalitarian welfare regime.
Although the original typology only contains the above three types, it was later completed with a fourth, the Mediterranean welfare regime [21], where the relative underdevelopment of the welfare state leaves it to the families and small communities to ensure welfare. Southern European states have income-tested pension systems [28]. Portugal, Spain, and Cyprus are examples of this fourth type.
Last but not least, in an attempt to capture the characteristics of the post-socialist welfare system, scholars have argued that this latter type is a combination of the elements of the previous four [23]. These societies are practically split in two, with rights and shares for ensuring welfare being largely unequal [22]. Post-socialist countries, apart from Visegrád countries, have low levels of minimum pensions and, accordingly, high rates of poverty in old age [29].
The data of the European Social Survey wave 10, on which this empirical study is conducted, was collected in the following post-socialist countries: Bulgaria, Czech Republic, Estonia, Croatia, Hungary, Latvia, Lithuania, Poland, Slovakia, and Slovenia.
Introducing the welfare regime type into the analysis next to individual-level characteristics is justified by our assumption supported by results from previous research that the social status of older persons in a given society, determined by their eligibility and the level of pension payments provided to this mostly inactive group, may shape societies’ attitudes towards them.
Due to cultural traditions and socioeconomic conditions, there are considerable differences between countries. In general, societal modernisation has an impact on the reduction of ageism [30]. Measured in a previous round of the ESS, countries in Northern Europe were found to be characterised by low perceived discrimination among older people, whereas in some Southern and post-socialist countries, perceived age discrimination was particularly high among older people, at least compared to the younger age groups [31]. Analysis of the European Social Survey year 2008 [6] found a north-west versus south-east European gradient in perceived age discrimination, with Swedish senior citizens being least often and Czech senior citizens most often discriminated against in various settings. That is, social security arrangements should decrease old-age discrimination. However, more recent studies have questioned the classical East–West divide and found the geographical distribution of age discrimination more diverse [19].

2.2. Individual Characteristics: Socioeconomic, Demographic, and Health-Related Determinants of Perceived Discrimination of Senior Citizens

Besides the macro-level context of age discrimination like the type of welfare regime presented above, there is variation in perceived discrimination at the individual level too. In this section, those socioeconomic, demographic, and health-related antecedents are presented that based upon results of previous empirical studies in different European settings presumably influence the experiences of discrimination at older age.
In all studies, age, gender, and socioeconomic status have been found to be associated with discrimination in general and age discrimination in particular. Older adults were found to perceive higher age discrimination than their younger fellows [6,32]; however, in one study, it disappeared following a peak at the age of 75 [33].
Studies have found women to be more at risk of age discrimination [6,12,34], and studies report a double discrimination on the basis of female gender and old age [35].
There are some unequivocal results that indicate that perceived age-related discrimination of older persons is also largely dependent on their socioeconomic status. Lower levels of household wealth predicted higher levels of perceived age discrimination [6,32,34].
Results are contradictory, however, when it comes to the impact of educational attainment upon perceived discrimination. Lower educational attainment was often found to be associated with the perception of being discriminated against due to age [6]; however, in other instances, higher education also predicted a higher risk [32].
The effect of labour market status is not univocal, either. There are studies that found being retired or not in employment to go hand in hand with higher levels of perceived discrimination [32]; however, in other instances such as a non-European setting, working status was also associated with increased experiences of age discrimination [36]. There are two types of age discrimination commonly occurring in the labour market: hard and soft practices [37]. Hard discrimination means not being able to apply for a position or remain in a position due to the biological age of a person, whereas soft discrimination is a set of practices that occur in the general atmosphere of the workplace. The soft discrimination is not regulated by law, and it is often not admitted as being a discriminatory act or set of actions. They can be ageist jokes or remarks, or unrespectful treatment of older colleagues.
With regards to perceived discrimination, the place of residence has only been found to be significant in non-European contexts, with Indian older persons from rural areas facing age discrimination to a larger extent than those in urban settings [36,38].
Single people are more prone to perceiving ageist attitudes from society than partnered persons, and thus partnership status is a significant predictor [19,39]. The association between single status and the increased experience of hostile attitudes can be twofold: first, single people might be less socially integrated, more marginalised, and possibly more sensitive towards all forms of grievances, due to a selection effect that regulates the partnership market, whereby hypersensitive and/or mistrustful people are less likely to find a partner [40]; second, in the classical Durkheimian sense, partnership should offer a protective effect against adverse external influences [41].
Last but not least, poor health status is often associated with age discrimination [34]. Having more chronic conditions and functional limitations, just as in other instances of dependency, increase the risk of perceiving discrimination.

3. Materials and Methods

The most recent open access dataset that addresses the issue of discrimination is the 10th wave of the European Social Survey, carried out in 2021 on nationally representative samples of a total size of 59,685 respondents. For this analysis, the subsample of respondents aged 65 and above was selected. This selection led to a sample size of 15,340 people from the following countries: Austria, Belgium, Bulgaria, Switzerland, Cyprus, Czechia, Germany, Estonia, Spain, Finland, France, the United Kingdom, Greece, Croatia, Hungary, Ireland, Iceland, Italy, Lithuania, Latvia, the Netherlands, Norway, Poland, Portugal, Sweden, Slovenia, and Slovakia. Countries were grouped into five welfare system types according to the literature [20,21,22,23,24]. Although there might be variation in perceived age discrimination among the countries grouped into one type, the welfare regime typology that serves as a theoretical background for the study suggests that countries belonging to one type have more in common than differences, and thus they are treated uniformly for the purpose of this study.
The survey instrument assessed the perception of age discrimination with one multiple choice question: “Would you describe yourself as being a member of a group that is discriminated against in this country? On what grounds is your group discriminated against?” The possible reasons for perceived discrimination were the following: colour or race, nationality, religion, language, ethnic group, age, gender, sexuality, and disability. Respondents were allowed to pick more than one answer option. For our analysis, those respondents who marked the answer option “age” are considered to have reported age discrimination. The variable is used in its original dichotomous form with the answer options “not marked” (0) and “marked” (1).
This study used descriptive and multivariate analysis. Post-stratification weights including design weights were applied as recommended by the ESS Data Service [42].
The analysis started with two-variable analyses, using crosstabs and independent samples t-test. Pearson chi-squared tests were performed to assess the association between the categorical variables perceived age discrimination and other reasons of discrimination. Then, crosstabs and the chi-squared test were used to study the association between perceived age discrimination and its possible antecedents in the case of nominal- and ordinal-level variables: socioeconomic, demographic, and health-related variables, as suggested by the existing literature on the topic. An independent samples t-test was performed to determine whether the mean age of respondents who reported age discrimination is similar or different from those who did not.
Thereafter, the possible antecedents of age discrimination were introduced in a logistic regression model to measure their impact, controlled for covariates. The model aims at identifying those characteristics that independently contribute to the experience of age discrimination. The outcome variable of the logistic regression model is the dummy variable whether the respondent did not mark (0) or marked (1) the perception of age-based discrimination.
The regression model contains micro-level and one macro-level explanatory variable which were identified by previous empirical research as possible determinants of perceived age discrimination and were presented in the section on variable selection.
Explanatory variables included in the logistic regression analysis and their measurement levels are as follows: age—scale level variable; gender—categorical variable (1: male, 2: female); subjective socioeconomic status—ordinal variable (1: living comfortably on present income, 2: coping on present income, 3: difficult on present income, 4: very difficult on present income); educational attainment—ordinal variable (1: low education, 2: medium education, 3: high education); labour market status—categorical variable (1: active, 2: inactive); domicile—categorical variable (1: a big city, 2: suburbs or outskirt of big city, 3: town or small city, 4: country village, 5: farm or home in countryside); partnership status—categorical variable (1: partnered, 2: single); functional limitation—ordinal variable (1: the respondent is hampered a lot due to a long-standing illness/disability/infirmity/mental problem, 2: is hampered to some extent, 3: is not hampered at all). The welfare regime type is a macro-level variable that is assumed to determine age discrimination experienced by senior citizens. This is measured with a categorical variable with the following values: 1: liberal, 2: conservative-corporatist, 3: social democratic, 4: Southern, 5: post-socialist welfare regime.
For categorical variables, reference groups are those values of variables which, according to the literature, are deemed more advantageous with respect to the studied phenomenon, that is, presumably associated with lower levels of discrimination. In case literature is inconclusive, the first value of the variable is used as a reference category.
When interpreting the result of the logistic regression, significant odds ratios (Exp(B) values) higher than 1 indicate a higher risk, whereas those lower than 1 point to a lower risk of experiencing age discrimination compared to the reference category, with all other variables being controlled for.

4. Results

In the subsample of senior Europeans, among the perceived reasons for discrimination, it was the age-based discrimination that occurred by far most frequently (3%). The prevalence of perceived discrimination for other reasons was as follows: 0.4% reported belonging to a group which is discriminated against due to colour or race, 0.5% due to nationality, 0.9% due to religion, 0.7% due to language, 0.5% due to ethnic group, 3% due to age, 1.2% due to gender, 0.3% due to sexuality, and 1.1% due to disability.
Next, the association of perceived age discrimination and perceived other reasons of discrimination was studied.
Among European senior citizens, the perception of being discriminated against due to age was significantly associated with gender- and disability-based discrimination only (see p-values in Table 1). Both features of the individuals, namely, gender and disability, were incorporated in the further analysis. Other grounds of discrimination assessed by the survey occurred independently of the experience of age-based discrimination.
Below, in Table 2, the prevalence of perceived age discrimination is presented by socioeconomic, demographic, and health-related characteristics and by welfare regime type.
On the average, the rate of Europeans aged 65 or above who perceive discrimination due to their age is 3%; however, differences across demographic features, socioeconomic status, subjective general health, and welfare regime type are considerable.
Two-variable analysis (crosstabs and chi-squared tests) unfold a significantly higher occurrence of age discrimination in women compared to men; in those having difficulties to cope on their income; in city, suburb, and town inhabitants; in singles compared to partnered people; in those with bad or very bad health and those hampered in their everyday lives by considerable functional limitations; and in older persons living in social democratic welfare regimes. Educational attainment and labour market status were not associated with the perception of age discrimination.
The results displayed in Table 3 reveal that those seniors who reported age discrimination were older than those who did not. That is, older age increases the prevalence of age discrimination.
These results are important, but they do not yield far-reaching conclusions with respect to the direct effect of each variable, as their mutual associations may bias the results. To control for these eventual covariates, logistic regression was performed which assesses the individual effect of each predictor while controlling for other effects. The outcome variable is the experience of age discrimination, and predictors are all the above variables except for the subjective general health which is largely covered by the variable on the extent of functional limitation. The logistic regression model is summed up in Table 4. The reduction in the sample size is due to the fact that the model only contains cases with valid data on all included variables.
Seen altogether, the cumulated explaining power in the logistic regression model is significant, as suggested by the significance of the chi-squared test. Individual-level variables and the macro-level regime type significantly contribute to the explanation of differences in the older persons’ experiences with age discrimination.
The greater the age, the more likely it is that the individual reported age discrimination. The risk of being discriminated against increases slowly, year by year (β = 1.024). The worse the subjective socioeconomic status, the higher the odds ratio of having experienced age discrimination, and those coping very poorly on their income are more than four times (β = 4.405) as likely to suffer age discrimination than their fellows with the highest socioeconomic status.
From types of domiciles, only the effect of country village was significant, pointing to attitudes towards senior citizens being more favourable in smaller settlements compared to big cities (β = 0.671). Old people living alone are much more likely to be victims of age discrimination than their partnered fellows (β = 1.726), and long-lasting disability or infirmity which goes together with high or moderate dependency also increases the risk of being discriminated against due to old age (β = 2.513 and β = 2.156, respectively).
Compared to the reference category liberal welfare regimes, in social democratic ones, old people are at much higher risk of experiencing ageist attitudes (β = 2.321).

5. Discussion

Our analysis revealed that there are considerable differences in the discrimination perceived by older persons due to their age. Subjective socioeconomic status is the most powerful determinant of whether a European senior citizen is feeling discriminated against due old age or not. Having financial resources is protective against such perceptions, whereas financial hardships significantly increase the risk of experiencing age-based discrimination.
When controlled for other variables, gender, educational attainment, and labour market status do not have an individual impact. Gender certainly makes a difference, and it did so in two-variable analysis too. The literature also suggests the existence of a gendered ageism with a double derogation of senior women [31]. Nevertheless, being a woman, in itself, independently of socioeconomic characteristics does not increase the risk of being discriminated against. Most probably, it is the socioeconomic status with its far-reaching impact that mediates the association between gender and the perception of hostile age attitudes. This result sheds light upon the necessity to review the notion of gendered ageism and to study the phenomenon in its more complex socioeconomic context. By the same token, educational attainment, a very strong predictor of a range of social encounters, remains irrelevant in the shadow of the overwhelming explanatory power of socioeconomic status with which it is strongly associated.
Although the most extensive body of literature on age discrimination focuses on the employment and workplace experiences, labour market status of respondents proves irrelevant in our analysis, that is, old adults who are still in employment and those who are not encounter ageist manifestations to similar extent.
So then, what makes the difference?
The impact of age, partnership status, and health status indicated by the level of functional limitation are in line with the results of other empirical studies from a variety of contexts [6,19,32].
The protective effect of smaller places is a novel finding in Europe, as domiciles have only been reported as significant predictors in a developing non-European country, namely, India [36], as well as in the United States. Moreover, a systematic review from US journal articles found, among the few studies on the topic, that people living in rural areas experienced more hostile attitudes [38]. Our findings related to European senior citizens suggest that, irrespective of their other demographic and socioeconomic characteristics, old people who live in villages and small settlements are more integrated in their microsocial environment and experience more favourable attitudes and treatment from others than do town and city inhabitants. Our findings concur with the group density theory, which states that even in the case of concentration of disadvantages, members of marginalised groups, or low-status residents, this situation might entail different advantages. This principle of group density can be applied to age too. Older adults are concentrated in rural areas and surrounded by older adults in a similar position—even if disadvantaged, they are in a way protected from discrimination [43]. Our findings reinforce the assumption which states that attachment to a place plays an important role in healthy ageing from a psychological point of view. Neighbours are important support for older people but also they mean constant social contact, resulting in less loneliness and lower level of perceived discrimination. This is actually the acknowledgement of the vital importance of Granowetter’s weak ties, where regular social interactions, the network of neighbours, familiar faces, and the sense of integration have a critical function in being more resilient [44].
The high level of perceived discrimination of older people, particularly in the Nordic countries well-known for their tolerance and previously having reported low ageism [45], comes as a surprise, and it is the most striking finding which needs further research. Analysis performed on a previous round of the European Social Survey dataset revealed excessive experience of discrimination in some post-socialist countries, but low levels in Scandinavian countries with social democratic welfare regimes [6].
One possible explanation could be the relatively late retirement age in these countries which might expose older people to detrimental differentiation in their workplace. Ageist attitudes and age discrimination cause lower levels of overall organisational commitment on the part of older workers and “push” them out of a particular workplace or full-time employment, and given the advanced age of these individuals, usually from the employment market as well. Researchers refer to this as a “push” rather than voluntary exit because ageist treatment causally precedes the employee’s decision to leave. The pressure of these “push” factors are not distributed equally towards older age workers in all types of positions but are rather directed toward skilled, ageing workers who may be seen as taking the best jobs. Thus, skilled and semi-skilled workers are likely the most vulnerable to age discrimination by younger workplace supervisors and colleagues [5]. However, in our study, labour market activity has not been proven to increase discrimination experiences. Alternatively, modern societies face a strain due to dramatic rises in population ageing, where ageism can be a function of intergenerational resource tensions. Younger active people are expected to provide greater support for their elders, and increasing dependency ratios might raise the issue of deservingness [46]. In such scenarios, the population may indeed be more biased against older persons, which can lead to hostile attitudes towards them, particularly in those countries with generous pensions and relative wellbeing of old people. A cross-cultural meta-analysis found an association between the share of older people in a country and negative attitudes towards them. The greater the percentage of old people, the higher the rate of ageism [47]. Moreover, according to a recent German study, only a relative minority—that is, about one in four people, predominantly young and educated—did explicitly consider that old people represented a serious financial burden for society as a whole and a serious burden for the health system; however, almost half of respondents avoided giving a concrete answer to these questions. This hiding attitude implies that a considerable part of society does consider that the subsistence of old people puts ageing societies to the trial [1].

6. Conclusions

In accordance with the priorities of the World Health Organisation, settled in its guiding document on combating ageism and tackling the abuse of older persons [5], the overall aim of this paper was to generate more and better data on the prevalence and on the risk of ageism. Although societal modernisation is supposed to reduce ageism, it is a fact that old people in Europe have recently experienced increasing age discrimination. Drawing on the subsample of respondents aged 65 years and above of the European Social Survey, year 2021, this study offers an up-to-date picture of the problem in ageing European societies and provides empirical evidence for the nature of age discrimination. We have explored the nature of age discrimination of senior citizens in contemporary Europe by drawing the socioeconomic and demographic profile of victims of perceived age discrimination.
Our findings reveal the vulnerability of certain groups of seniors for discrimination based on their age. Socioeconomic status was found to be by far the most powerful determinant of perceived age discrimination among senior citizens. Older and single seniors are at high risk of age discrimination, as are older persons with poor health and ongoing health conditions that hamper their performance of everyday tasks. The two most surprising results, both contradicting previous empirical research results, are that living in villages gives rise to protection against experiencing ageist encounters and that the risk of such encounters is significantly higher in social democratic welfare regimes than in other countries.
The empirical evidence that villages, smaller settlements, and neighbourhoods have a pre-discriminatory or discrimination reducing effect is a key claim of our study, which yearningly has a policy level implication as well. At the policy level, decisions should be taken and legislation should be proposed to encourage the provision of all the needs of older people in their small communities and encourage senior citizens to remain in their smaller localities through various local programmes.
This study attempted to explain the protective effect offered by smaller settlements with the group density theory, whereby the intensified exposure to ageist manifestations particularly in countries famous for their efficient welfare policy could be addressed, not only with the increasing hostility towards older persons due to economic burden of ageing societies but also through socio-psychological mechanisms such as the enhanced anxiety and susceptibility of senior citizens in challenging times.
In the context of ageing societies, the problem of age discrimination of senior citizens remains a challenge both for societies and for policy. In a broader view, we hope that this paper also contributes to further shaping attitudes and conscientising policy makers that appropriate resources and measures are needed to tackle the problem of discrimination in general and of age discrimination of seniors in particular, as well as to mitigate its harmful effects on individuals and society.

7. Limitations and Directions for Further Research

One limitation of the study is that the nature of perceived discrimination could not be assessed, as the ESS 10th wave measures discrimination with one question without further detailing its nature, manifestations or frequency.
Additionally, an important aspect of perceived discrimination, namely, race and ethnicity, could not be addressed in the study, as the European Social Survey assessed it with one single question, treating race and ethnicity as similar, not allowing to differentiate between indigenous ethnic minority populations and immigrants, nor between different races and ethnicities.
A psychological factor in perceptions might bias results. Feeling discriminated against is largely subjective and depends on individual interpretation, which potentially entails that discrimination is blamed for other types of conflicts too, particularly for people with emotional problems and/or other social disadvantages. On the other hand, seniors who report age discrimination may also be more conscious of it due to better education on the topic, or some of them might feel encouraged by the survey setting and its anonymity in admitting having experienced such problems. Thus, results might entail a potential bias in regard to self-reported measures.
Another concern is the extent to which self-reported ageism mirrors a de facto exposure to a discriminatory treatment as opposed to variation in how individuals identify different experiences in different circumstances as being discriminatory. This limitation could be addressed by collecting qualitative data about it, as well as about the types of discrimination the participants had suffered. A possible future research direction of our study would be exploring this question qualitatively. The qualitative methods we plan to use are semi-structured in-depth interviews and focus group interviews, with the latter being an excellent method to study this topic because it allows us to witness the development and formation of opinions as a consequence of the synergistic effect of group dynamics, as well as to obtain answers to the whys and hows.
Senior citizens who are still active in the labour market and those who are retired may be discriminated against for very different reasons but to the same level. This assumption needs further and more thorough analysis, preferably being completed with qualitative results. Similarly, the different pension schemes, the type and number of social benefits designed as incentives for remaining active as long as possible within the labour market, and the retirement age in different countries are all legal determinations that may have an impact on discriminatory practices towards older people. Thus, differentiating between countries and policies within the same welfare regime type is also an imminent task.

Author Contributions

Conceptualization, A.S. and E.E.T.-B.; methodology, A.S.; software, A.S.; writing—original draft preparation, A.S.; writing—review and editing, E.E.T.-B.; visualization, A.S.; supervision, E.E.T.-B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The original data presented in the study are openly available on the European Social Survey website, data portal at www.europeansocialsurvey.org (accessed on 12 June 2024).

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. The association of perceived discrimination due to age with perceived other reasons of discrimination. Pearson chi-squared tests. N = 15,340.
Table 1. The association of perceived discrimination due to age with perceived other reasons of discrimination. Pearson chi-squared tests. N = 15,340.
Discrimination Due to AgePearson Chi-Squaredp
Due to colour or race72.1870.189
Due to nationality142.2140.098
Due to religion43.1540.165
Due to language43.4780.265
Due to ethnic group41.1690.215
Due to gender401.0320.000
Due to sexuality17.9560.506
Due to disability289.4020.000
Table 2. Age discrimination across socioeconomic, demographic, and health-related variables and welfare regime type. Cross-tabulation of variables with age discrimination, row percent (%). N = 15,340.
Table 2. Age discrimination across socioeconomic, demographic, and health-related variables and welfare regime type. Cross-tabulation of variables with age discrimination, row percent (%). N = 15,340.
VariableValuesExperienced Age DiscriminationTotal
Row Percent
p
yesno
GenderMale2.597.51000.005
Female3.396.7100
EducationLow3.097.01000.875
Middle2.997.1100
High2.997.1100
Subjective SESLiving comfortably1.598.51000.000
Coping on income2.797.3100
Difficult to cope on income4.895.2100
Very difficult to cope on income6.893.2100
DomicileA big city3.296.81000.000
Suburbs of big city3.596.5100
Town or small city3.796.3100
Country village2.197.9100
Countryside1.998.1100
Partnership statusPartnered2.197.91000.000
Single4.495.6100
Labour market statusActive3.296.81000.396
Inactive3.097.0100
Welfare regimeLiberal2.697.41000.000
Conservative-corporatist1.498.6100
Social democratic5.095.0100
Southern3.396.7100
Post-socialist3.496.6100
Subjective healthVery good1.298.81000.000
Good1.998.1100
Fair3.296.8100
Bad5.494.6100
Very bad6.993.1100
Functional limitationYes, a lot5.194.91000.000
Yes, to some extent4.295.8100
No1.898.2100
Total sample 3.097.0100
Table 3. The association of age and the experience of age discrimination, independent samples t-test. N = 15,431.
Table 3. The association of age and the experience of age discrimination, independent samples t-test. N = 15,431.
Discrimination ExperienceNMean Age Standard DeviationStandard Error or Mean
Has not experienced age discrimination12,88173.726.5250.057
Has experienced age discrimination39775.087.0180.352
F: 10.164, p: 0.001, t: −4.080, df: 13276, p: 0.000
Table 4. The determinants of age discrimination among the senior citizens. Binary logistic regression model. Outcome variable: respondent has not vs. has experienced age discrimination.
Table 4. The determinants of age discrimination among the senior citizens. Binary logistic regression model. Outcome variable: respondent has not vs. has experienced age discrimination.
Explanatory VariablesN = 11,789, −2 Log Likelihood = 2793.155, Chi-Squared = 208.013, df = 16,
p = 0.000, Nagelkerke R Squared = 0.078
Bpβ95% Confidence Interval (CI) for β
LowerUpper
Age
0.0240.0071.0240.0061.042
Gender
Male
Female−0.0080.9500.9920.7811.261
Educational attainment
High * 0.252
Medium−0.0650.7050.9370.6701.311
Low−0.2610.1550.7700.5371.110
Subjective socioeconomic status
Living comfortably on present income * 0.000
Coping on present income0.7410.0002.0991.4533.032
Difficult on present income1.2970.0003.6592.4195.534
Very difficult on present income1.4830.0004.4052.6907.212
Domicile
A big city * 0.002
Suburbs or outskirt of big city−0.0240.9110.9760.6401.490
Town or small city−0.1350.3831.1440.8451.549
Country village−0.3990.0200.6710.4790.939
Farm or home in countryside−0.5760.0620.5620.3071.030
Labour market status
Active *
Inactive0.4120.0891.5100.9392.427
Partnership status
Partnered *
Single0.5460.0001.7261.3512.206
Functional limitation due to illness/disability/infirmity/mental problem
No * 0.000
Yes, to some extent0.7680.0002.1561.6612.799
Yes, a lot0.9210.0002.5131.7843.539
Welfare regime type
Liberal * 0.000
Conservative-corporatist−0.5920.0540.5530.3031.011
Social democratic0.8420.0052.3211.2854.191
Southern0.4440.1531.5580.8472.865
Post-socialist0.2410.4071.2730.7202.250
(constant)−5.7690.0010.003
* reference category.
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Santha, A.; Tóth-Batizán, E.E. Age Discrimination of Senior Citizens in European Countries. Societies 2024, 14, 198. https://doi.org/10.3390/soc14100198

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Santha A, Tóth-Batizán EE. Age Discrimination of Senior Citizens in European Countries. Societies. 2024; 14(10):198. https://doi.org/10.3390/soc14100198

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Santha, Agnes, and Emese Emőke Tóth-Batizán. 2024. "Age Discrimination of Senior Citizens in European Countries" Societies 14, no. 10: 198. https://doi.org/10.3390/soc14100198

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Santha, A., & Tóth-Batizán, E. E. (2024). Age Discrimination of Senior Citizens in European Countries. Societies, 14(10), 198. https://doi.org/10.3390/soc14100198

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