October 2025
Global experiences of discrimination
The promotion of equality and non-discrimination are key Sustainable Development Goals, but there is a paucity of data to analyse the experiences of groups at risk of discrimination across the globe. In particular, there are significant deficiencies in data pertaining to discrimination based on sexual orientation, ethnicity, race and religion.
Newly available survey data enable an assessment of worldwide self-reported discrimination, which when coupled with objective measures of inequality, values surveys and qualitative information, paint a detailed picture of the factors associated with discrimination, as well as the nature and consequences of discrimination.
The results indicate that almost a quarter of people report experiencing discrimination in their lifetime, with rates especially high in Northern America and Oceania, and Latin America and the Caribbean (and lower in in Asia, Europe, and Africa and the Middle East). Regional variations in self-reported discrimination correlate positively with inequality, and rates are higher in more diverse regions with higher average living standards (which likely relates to individuals’ expectations for equal treatment and awareness of discrimination).
Quantitative evidence shows that women, young people and those on low incomes are most likely to self-report discrimination across the globe (although data on some key at-risk groups are missing). Complementing the quantitative analysis, qualitative evidence covering OECD countries highlights the ways in which individuals’ intersecting risk factors shape experiences of discrimination including their sexuality, ethnicity, disability, age and sex. People with several risk factors commonly describe experiencing multiple forms of discrimination in employment, public spaces, healthcare environments and government administrative settings, and the toll it takes on their mental health, finances, productivity and safety.
For the purposes of tracking the Sustainable Development Goals (SDGs) linked to equality and non‑discrimination, the United Nations (UN) annually publishes the proportion of a country’s population that has personally felt discriminated against on a ground protected by international law (called “self‑reported discrimination rates” in this brief). Statistics are gathered from official national sources and non-official surveys (e.g. Afrobarometer and Eurobarometer) and are published for 119 countries, with data disaggregated by sex for all countries, by disability in nearly 40% of countries, and with 6% showing breakdowns by income and education (UN Department of Economic and Social Affairs, 2025[1]).
These rates are considered to be a “starting point” because additional information, which is not routinely or consistently collected, is necessary to understand the nature and effects of discrimination (Office of the UN High Commissioner for Human Rights, n.d.[2]). This includes information on key protected grounds and individual risk factors such as ethnic or racial background, sexual orientation and religion or beliefs. To meet these identified needs, the UN Praia Group on Governance Statistics (2021[3]; 2024[4]) is working with National Statistical Offices and international agencies to develop guidance on the collection of enhanced data on individuals’ risk factors and experiences of discrimination, attitudes towards groups most at risk of discrimination and perceptions of discrimination. This guidance is set to be published in 2026, and is likely to increase the comparability and consistency of discrimination measures across the globe, along with providing new information on groups most at risk of discrimination.
In the interim period, however, examining the extent of discrimination across the globe remains partly challenging because some of the available data sources miss key groups at risk of discrimination (and grounds of discrimination) and the statistics tend to be presented without reference to the broader social, cultural, institutional and economic factors that shape discrimination. Without understanding these contextual factors, high‑level self-reported discrimination rates can give a misleading picture of the state of discrimination across the globe. For instance, they can ignore differences in the size of at-risk groups across countries, and overlook some downsides of using self-reported discrimination data, such as differences in awareness of discrimination and misalignments between perceptions and reality (the advantages and limitations of self-reported discrimination data are discussed in detail in OECD (2025[5])).
This brief draws on recently released global discrimination surveys, world values surveys, objective measures of inequality and qualitative information on individuals’ experiences of discrimination to provide new evidence on the key factors associated with self-reported discrimination and the nature and consequences of discrimination. Results are presented at the regional level to make it easier to observe patterns that emerge across countries with similar cultural values and shared histories. Unlike the statistics published by the UN, this brief draws exclusively on high-quality non‑official surveys that are used for cross-national policy analysis, as they have a wider country coverage (137 compared to 119) and more complete information on income, which is an important analytical variable. The data sources enable a broad range of experiences to be analysed, including discrimination based on ethnicity/nationality, skin colour, religion, sex and disability.
However, some key grounds of discrimination cannot be covered due to data limitations (e.g. sexual orientation). It is also not possible to quantitatively analyse the prevalence of discrimination for all groups at risk (e.g. ethnic minorities), as information on respondents’ identities is only available for certain factors: primarily sex, age and income. Nevertheless, the experiences of at‑risk groups missing in the quantitative analysis are revealed through qualitative evidence from OECD countries. Even though it is not possible to analyse all grounds of discrimination protected by international law and all at‑risk groups, this brief includes the broadest analysis of self-reported discrimination to date – both in terms of the forms of discrimination and array of countries covered – thereby showcasing the type of analysis of discrimination that can be possible with comprehensive and internationally consistent data.
Almost one quarter of people in the world have experienced discrimination at some point in their lives, according to the World Risk Poll (right-hand axis in Figure 1). Across the globe, discrimination based on ethnicity/nationality and sex are most frequently cited (each selected by 10% of the general population), followed by religion (9%), skin colour (9%) and disability (6%) (left-hand axis in Figure 1). This pattern is broadly consistent with UN (2025[6]; 2025[1]) annual statistics and a recent UNESCO (2024[7]) internet scan, which found that global news articles on discrimination primarily cover race, sex and ethnicity, with fewer mentioning religion, and only a small minority referring to disability or socio-economic status.
While the global results are illuminating in terms of the extent of different forms of discrimination, they mask key regional differences. For instance, more than one in two people in Northern American and Oceania report experiencing discrimination in their lives, compared to 31% of people in Latin America and the Caribbean, 26% of those in Africa and the Middle East, 23% of Europeans and 20% of Asians (right-hand axis in Figure 1). Self-reported discrimination rates are consistently higher in Northern America and Oceania across a number of groups including sex (29%), ethnicity/nationality (28%), skin colour (25%) and disability (12%), while religious discrimination is relatively higher in Latin America and the Caribbean, and Africa and the Middle East (left-hand axis in Figure 1). By contrast, discrimination rates are generally low in Asia and Europe (except for sex-based discrimination in Europe, which is in line with the global average).
Forms of discrimination and overall self-reported discrimination rates by region, 2024
Note: Survey respondents were asked whether they have ever personally experienced any discrimination because of the following: the colour of their skin, their religion, their nationality/ethnic group/race, their gender or their disability, if they have one. The response categories were “yes”, “no”, “does not apply”, “don’t know” and “refused”. Self-reported discrimination rates are calculated as the proportion of respondents in each region who respond affirmatively to the question for any ground, weighted by the population size, sex, age and socio‑economic status or education level, where reliable data are available. Analysis is restricted to the 137 countries where all discrimination questions were asked.
Source: OECD analysis of Llyod’s Register Foundation (2024), World Risk Poll, https://www.lrfoundation.org.uk/wrp/world-risk-poll-data.
The regional patterns in self-reported discrimination rates may look surprising at first glance, given the relatively strong legal protections in Northern America and Oceania and their generally high levels of acceptance of at-risk groups (Flores, 2021[8]; Fleming et al., 2018[9]). Indeed, countries in this region were early adopters of anti-discrimination laws – instituting anti-discrimination laws for race/ethnicity, sex and disability 20‑30 years before many other countries (25% of which still do not have laws prohibiting racial/ethnic discrimination in the workplace, 20% do not prohibit workplace disability discrimination and a further 10% do not prohibit sex discrimination) (Heymann et al., 2021[10]; Carlson, 2017[11]).
That said, investigating some of the factors associated with self‑reported discrimination reveals a coherent narrative – although data limitations make it difficult to isolate every relevant factor (Box 1). Global self‑reported discrimination rates are influenced by a range of institutional, demographic, economic, cultural and knowledge‑related factors (Figure 2). These factors can both affect the reality of how people are treated and their perceptions (i.e. whether they attribute their treatment to discrimination). Regression analysis reveals that unequal institutional arrangements and socio-economic divides – respectively measured in terms of social institutions related to gender equality (SIGI) and income inequality (Gini index) – are strongly correlated with self-reported discrimination, particularly in Asia, Africa and Middle East, and Latin America and the Caribbean. Social, cultural and economic divides create conditions for discrimination by permitting unequal treatment, narrowing the horizon of possibilities for people to thrive (e.g. via discriminatory cultural norms) (OECD, 2023[12]) and encouraging prejudicial attitudes and inter-group conflict (UNESCO, 2024[7]). Inequality can hence be a reason why people may attribute their adverse life outcomes to discrimination (even where this may not be the case). At the same time, discrimination can reinforce and deepen inequality: when people are denied equal opportunities or fair treatment because of their immutable characteristics, group-based gaps in income, wellbeing, and social status widen. In this way, inequality and discrimination operate as a two-way street, mutually reinforcing one another over time.
Contribution (%) of different factors to self-reported discrimination rates, by region
Note: This figure is derived from a country-level weighted linear regression of self-reported discrimination rates, using the self-reported rates calculated as described in Figure 1. The model excludes a constant term and includes, as explanatory variables, religious minority share (defined as the proportion of a country’s population adhering to a religious group different from the national majority), the average level of education (where a value of 1corresponds to up to elementary education, 2-3 years of tertiary education, and 3-4+ years of tertiary education), percentage of migrants in the population, the OECD Social Institutions and Gender Index (SIGI), the Gini Index, and GDP per capita (current USD). Migrant share is included in the regression, but not shown because it had a small coefficient that was insignificant at the 10% level (unlike all other explanatory variables shown in the figure). The rationale for including these regressors is outlined in Box 1. The figure shows the regional-level averages of the country results, with the observed self-reported discrimination rate corresponding to the rates in Figure 1, the predicted rates from the regression model and the contributions of the statistically significant explanatory variables.
Source: OECD analysis using Llyod’s Register Foundation (2024), World Risk Poll, https://www.lrfoundation.org.uk/wrp/world-risk-poll-data, OECD (2023[12]), SIGI 2023 Global Report: Gender Equality in Times of Crisis, Social Institutions and Gender Index, OECD Publishing, Paris, https://doi.org/10.1787/4607b7c7-en, Haerpfer, C. et al. (2022), World Values Survey: Round Seven–Country-Pooled Datafile, JD Systems Institute & WVSA Secretariat, Version. 5.0.0, https://doi.org/10.14281/18241.24, World Bank (2024), World Development Indicators: GDP (current US$), 2023 data, https://databank.worldbank.org/source/world-development-indicators.
By contrast, the average level of education is negatively associated with global self-reported discrimination. More educated populations tend to be more accepting of at-risk groups, as average levels of education are positively correlated with indicators of acceptance (such as trust in, and willingness to work with, people with different ethnic or religious backgrounds and views on gender equality). In turn, more accepting and educated populations may be more aware of what constitutes discrimination and attempt to act in ways that promote equal treatment, even though there may be other forces, such as population diversity and level of economic development that work in the opposite direction. For example, in Europe, Northern America and Oceania, population diversity – as controlled for by the share of religious minorities – make relatively large positive contributions to self-reported discrimination rates. While these regions have high levels of acceptance of at-risk groups, their highly diverse populations likely create more chances for different groups to come into contact, which can have the potential for conflict and unequal treatment (particularly if these interactions are of poor quality or negative). In addition, these regions also have high levels of development and living standards (as indicated by GDP per capita) as well as relatively equal institutions, which are likely to be associated with high expectations of equal treatment and awareness of rights and discrimination (OECD, 2025[5]). As such, self-reported discrimination rates may be higher in more equal and developed regions because members of society have high expectations of equal treatment and a greater understanding of when the treatment they receive does not measure up.
This brief presents the results of a linear regression model that explores the main factors associated with self‑reported discrimination rates across the globe (the analysis is conducted at the country level, but for presentational clarity, the results are shown for regions). Internationally comparable data are difficult to find, and as such this brief draws on a range of experiential and values surveys and measures of inequality (such as the OECD’s SIGI, which captures the degree of gender inequality inherent in countries’ laws, social norms and practices that contribute to disparities in education, health and economic outcomes, and the Gini Index, which can be an indicator of structural inequalities more broadly) to round out the analysis. In terms of surveys used, the analysis draws on the World Risk Poll, which includes questions on people’s lifetime experiences of discrimination based on their nationality/ethnicity, disability, religion, sex and skin colour (as well as information on their education), and the combined European and World Values Survey, which was used to develop measures of population diversity (primarily religious minority and migrant population shares).
Ideally, data for each factor would be readily available, but this is not always the case, and as such, this brief used proxies – including the general level of education (as a proxy for the acceptance of at-risk groups and awareness of discrimination), share of religious minorities and share of migrants (as markers of population diversity), and GDP per capita (to signify individuals’ expectations for equality and awareness). Some proxies capture various factors, and thus it is not possible to isolate the contribution each factor makes – although the expected direction of the factors is the same, which means the effect of each factor is likely not being cancelled out. The analysis is also limited by the lack of comprehensive data on population diversity (only with respect to religious diversity and migration background) and institutional inequality (mainly focussed on gender inequalities captured by the SIGI). For a subset of 45 countries, there is more information on population diversity (e.g. ethnic make-up) and for 72 countries there is more information on societal inclusion (measured using the University of California Berkely’s Inclusiveness Index). Sensitivity analysis using these additional markers of population diversity and the alternative measure of inclusion did not change the results materially. Even still, future analysis would benefit from more complete information on population diversity (e.g. sexual minorities) and by extending indicators like SIGI beyond gender equality.
The preceding analysis assessed on the frequency with which different forms or grounds of discrimination were selected by survey respondents, but an alternative way is to examine the characteristics of people who are most likely to self-report experiences of discrimination. Focussing on particular groups is important because their life outcomes may be shaped by their experiences of discrimination. Across the globe, women's labour force participation is 25% lower than men's, often reflecting discriminatory norms that prioritise the male breadwinner, place women in unpaid caregiving roles, and perpetuate occupational segregation between men and women (OECD, 2023[12]). At the same time, people with disabilities are 25% less likely to be in the labour market globally compared to those without disabilities, partly due to limited workplace accommodations, discrimination, and fewer opportunities for education and work experience (Ananian and Dellaferrera, 2024[13]). While global studies on other groups exposed to discrimination is limited, OECD research reveals self‑reported rates of discrimination are highest for people who belong to an ethnic, racial, religious or sexual minority – with more than half stating that they experienced discrimination in Europe in the previous year, compared to 20% of non‑minorities (OECD, 2025[5]).
The World Risk Poll includes information on individuals’ lifelong experiences of discrimination and socio‑demographic characteristics such as their sex, age and income level, which enables a partial analysis of the characteristics of people who self-report discrimination (although key risk factors such as self-identified minority status are not captured in the survey). Most prominently, women experience discrimination at higher rates than men in all regions, with women in Northern America and Oceania reporting the highest rates in the world (Figure 3, Panel A). Women are also more likely than men to experience multiple forms of discrimination in Northern America and Oceania (37% vs 28%) and Latin America and the Caribbean (16% vs 14%). The disparities between men and women’s self-reported discrimination rates primarily reflect women’s higher exposure to sex-based discrimination – a finding consistent with studies from Europe that show that the overall higher rates of discrimination women experience are driven by sex‑based discrimination, as they experience other forms of discrimination at similar rates to men (Hardy and Schraepen, 2024[14]; OECD, 2025[5]). Nevertheless, in regions where women face higher risks of multiple discrimination, there are gender disparities across other forms of discrimination, such as disability discrimination in Northern America and Oceania, and religious discrimination in Latin America and the Caribbean.
Differences in self-reported discrimination rates are not as stark across the age distribution, even though there is a gradual decline in reported rates of sex, religion, ethnicity and skin colour discrimination in older‑age populations. The lower rates of self-reported discrimination among older people may reflect their propensity to minimise their experiences, differences in the way they interpret survey questions, as well as their lower awareness of discrimination compared to younger people who are more exposed to discrimination-related content online (OECD, 2025[5]). By contrast, disability discrimination rises with age in most global regions, in part because disability rates rise with age (Figure 3, Panel B).
In terms of income, individuals in the bottom 20% of their country’s distribution experience the highest rates of discrimination and, in general, rates of self‑reported discrimination decline with income – particularly in Africa and the Middle East and in Latin America and the Caribbean (Figure 3, Panel C). However, this pattern differs in Asia, Europe, Northern America and Oceania, where discrimination tends to decrease with income only up to a point. In these regions, individuals in the top income quintile report relatively high levels of discrimination (only slightly lower than those in the bottom quintile) resulting in a U-shaped relationship. This pattern is largely driven by higher rates of sex-based discrimination among top earners, although in Northern America and Oceania, similar trends are also seen for discrimination based on skin colour and ethnicity.
The U-shaped relationship between self-reported discrimination and income in some regions could be due to a number of reasons. Unlike sex and age, which are key reasons why a person may experience discrimination, an individual’s income may be both a source of discrimination (e.g. experiencing discrimination due to socio‑economic status) and an outcome of discrimination (i.e. discrimination limits earning potential) – which could indicate why lower-income individuals face higher rates. At the same time, income may correlate with education and awareness, meaning higher-income individuals might have stronger expectations for fair treatment and be more likely to report discrimination. Unfortunately, the cross‑sectional data used in this brief do not enable these possibilities to be disentangled.
Self-reported forms of discrimination experienced by region, sex, age and income quintile
Note: Survey respondents were asked whether they have ever personally experienced any discrimination because of the following: the colour of their skin, their religion, their nationality/ethnic group/race, their gender or their disability, if they have one. The response categories were “yes”, “no”, “does not apply”, “don’t know” and “refused”. Self-reported discrimination rates are calculated as the proportion of respondents in each region who respond affirmatively to the question for any ground, weighted by the size of the population in each region, gender, age and socio-economic status or education level, where reliable data are available. The differences discussed in the text are statistically significant at the 5% level.
Source: OECD analysis using Llyod’s Register Foundation (2024), World Risk Poll, https://www.lrfoundation.org.uk/wrp/world-risk-poll-data.
In the absence of more comprehensive information on the characteristics of people who self-report discrimination in global surveys, this brief turns to the results of the 2022 OECD Risks that Matter Survey to showcase the nature and experiences of discrimination. This survey, conducted in 27 OECD countries, allowed respondents to share their thoughts on any social or economic risks they or their family face – including discrimination – and what actions governments should take to address them.
Respondents who shared stories about their experiences of discrimination had various demographic features that compounded their risk of discrimination, including being a lesbian or bisexual woman, being an older woman, being a religious and ethnic minority woman, being a gay, bisexual or transgender migrant man, being a woman with a disability or a religious minority with a disability (Figure 4). Those disclosing their experiences of discrimination also had diverse life experiences – with various educational backgrounds, employment statuses and countries in which they reside. Discrimination stories came from virtually every region covered in the 2022 OECD Risks that Matter Survey.
Notwithstanding the diversity of the respondents revealing their discrimination experiences, key themes repeated throughout their stories. Many of the examples provided involved discrimination on multiple grounds – with discrimination occurring because of a person’s age and sex, or their nationality and lesbian, gay, bisexual or transgender (LGBT) status, or their disability and LGBT status. As highlighted in Figure 4, many survey respondents described incidents where other individuals explicitly discriminated against them (i.e. interpersonal discrimination), while others pointed to the way in which the design and operation of government systems make it difficult for them to be included in society and live with dignity (i.e. systemic discrimination). In some cases, the stories include both interpersonal and systemic elements.
When it comes to interpersonal discrimination, respondents often spoke about being denied employment due to their sex, age and/or nationality, with older women in particular remarking that they face age and sex discrimination when looking for work. Respondents also commonly shared stories of housing evictions and violence and harassment in public – especially among LGBT individuals, people with disabilities and people from racialised communities. The stories highlighted the difficulty of proving discrimination occurred, as it was never officially stated as the reasons for a lost employment opportunity or a housing eviction. Examples of systemic discrimination tended to come from people with disabilities or women caring for children and family members with disabilities. They spoke of systems that are not inclusive and do not support their individualised needs, such as a lack of accessible childcare and inadequate financial support, health care, transport and access to justice for persons with disabilities and their carers (Figure 4). These inflexibilities make it difficult for those affected to participate in society and the world of work; depriving them of fundamental rights (such as the freedom of association and the freedom of expression).
Another key theme that emerged was the stark descriptions of the consequences of discrimination. Many respondents spoke of the fear they experienced because of discrimination – a fear that worsened their mental health, prevented them from seeking help when needed (which led to serious health consequences) and pushed them to consider leaving their home countries. What also resonates is a sense of frustration and hopelessness at unfulfilled efforts to contribute to society and realise potential. That said, respondents offered hopeful solutions for a more equitable future. The solutions were shaped by individuals’ own experiences of discrimination and the ways in which they have been failed. Some respondents spoke about the need for stronger anti-discrimination laws, the implementation of international human rights law (particularly for disability rights), the need for better enforcement of law by equipping complaint bodies with the authority and resources to act, and promoting greater transparency to achieve pay equality. Other solutions were less legalistic, and focussed on building trust within bureaucracies and greater awareness among future generations.
Note: Survey respondents were asked if they have ever experienced discrimination and an optional question if they wanted to share their thoughts on what social and economic risks they and their family face, and whether and how governments should address them. Respondents were able to write a free text answer and DeepL was used to translate responses into English. All respondents answered affirmatively to the survey question on whether they have experienced discrimination and used the optional question to reveal more about their experiences. Bolded text was added by the authors, but the capitalised text is original. Text in brackets has been edited to ensure the anonymity of respondents.
Source: OECD analysis of the OECD (2022), Risks that Matter Survey, https://www.oecd.org/en/publications/main-findings-from-the-2022-oecd-risks-that-matter-survey_70aea928-en.html.
National Statistical Offices should follow the forthcoming UN Praia Group guidance on discrimination statistics, especially with respect to collecting and publishing data that elucidates the experiences of groups at risk of discrimination that are under-represented in existing data sources. This includes ethnic/racial minorities, religious minorities, sexual minorities and persons with disabilities.
By drawing on a range of quantitative and qualitative information sources, this brief has contextualised the annual statistics published to track the Sustainable Development Goals and underlined the importance of supporting UN Praia Group efforts to improve data collection. While almost 25% of people across the globe have experienced discrimination in their life, regional disparities underscore the importance of understanding the broader contextual factors that influence self-reported discrimination, such as institutional and structural inequalities, population diversity, individuals’ expectations for equal treatment, and awareness of discrimination. Moreover, the analysis has highlighted the need for data on all groups at risk of discrimination. The available quantitative evidence revealed that women, young people and those on low incomes have the highest rates of self-reported discrimination, but some of the key at-risk groups remained invisible due to data limitations. As such, this brief turned to qualitative evidence to describe the experiences of LGBT people, ethnic minorities, persons with disabilities, women and older people. The qualitative stories of discrimination illustrated how risk factors intersect to shape the nature and effects of discrimination, as well as options for policy and legislative reform.
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