Demographic Variation and Childhood Predictors of Perceived Discrimination Across 22 Countries

doi:10.21203/rs.3.rs-5040031/v1

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Demographic Variation and Childhood Predictors of Perceived Discrimination Across 22 Countries

https://doi.org/10.21203/rs.3.rs-5040031/v1

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Discrimination remains widespread around the globe, but less is known about the prevalence, variability, and determinants of perceived discrimination across diverse cultures. This study investigates the variation in perceived discrimination across 22 countries and identifies key demographic and childhood factors shaping these perceptions. Using data from the Global Flourishing Study, we document substantial cross-national differences in perceived discrimination, with countries like Egypt, South Africa, and Nigeria reporting higher levels, while Sweden, Poland, and Tanzania exhibiting lower levels. Demographically, younger adults, separated individuals, the unemployed, frequent religious service attenders, and Muslims are more likely to report discrimination, although patterns vary by country. Importantly, we also identify significant childhood predictors of perceived discrimination in adulthood. Adverse childhood experiences (ACEs), including abuse and feeling like an outsider within the family, significantly increase the risk of perceived discrimination later in life. However, childhood predictors’ effects vary across countries, suggesting both universal and culturally specific influences. Our study underscores the enduring impact of early life experiences on adult perceptions of discrimination and highlights the need for targeted interventions to address these root causes globally. The findings provide crucial insights for policymakers and scholars aiming to reduce discrimination and promote social equity across diverse cultural contexts.

Scientific community and society/Social sciences/Sociology

Scientific community and society/Social sciences/Culture

Perceived discrimination – the feeling of being treated unfairly or differently because of one’s membership in a particular social group, such as race, gender, religion, age, or ethnicity¹ – remains widespread around the globe^2–4. Experiences of discrimination can be particularly harmful for individuals’ abilities to flourish in life. An extensive body of research across disciplines has documented the negative role of discrimination in economic equality^5–7, life satisfaction^8–10, and close social relationships^11–14. Relatedly, perceived discrimination has been shown to harm overall health^1,15–18. Recent research has also examined the detrimental impact of perceived discrimination among the young^19–22. Given these well-established consequences of discrimination for individual and collective welfare, it is essential to understand better the prevalence, variability, and determinants of perceived discrimination across nations.

Social scientists have proposed various theories to explain the mechanisms underlying discrimination. For example, sociological theories have generally focused upon institutional components of discrimination. Institutional theories of biased treatment, such as racism^23–26 and sexism^27–29, suggest that discrimination often comes out in practices, institutions, and policies that do not require personal animus against the minority group. Marxists have argued that discrimination is tied to economic inequality^30,31. In essence, capitalism is seen as reproducing inequalities³², and labor market segmentation is a vital source of various forms of differential treatment, such as racial³³ and sex³⁴ discrimination. Social psychologists argue that when groups compete for scarce, material, or symbolic resources like jobs, housing, or social status, discrimination can emerge as each group seeks to maximize its own gains^35,36. Others suggest that discrimination arises because people tend to favor their own group and evaluate it positively. This favoritism can lead to preferential treatment of in-group members vis a vis outgroup members^37,38. Economists tend to favor taste-based or statistical discrimination theories. Taste-based discrimination implies that employers, employees, or customers have a "taste" or preference for, or against, working with certain groups³⁹. Statistical discrimination posits that discrimination arises when decision-makers use statistical group averages rather than individual merit to judge individuals, leading to biased hiring practices and wage disparities^40,41. It follows that distinct societies may have differing propensities to foster discriminatory behavior based on differences in institutional practices, levels of socio-economic inequality, ethnocentric motivations, cultural preferences, or a combination of these and various other factors noted in this vast literature.

Every known society has some individuals who experience discrimination. For instance, sexism has been documented as a cultural, or near-cultural universal ^42,43. Individuals are often denied opportunities, benefits, or fair treatment in life because they are perceived as too old or too young ⁴⁴. Certain racial^8,25,45 or ethnic groups^42,46,47, particularly those linked to recent immigration^48,49, are found to be especially vulnerable to experiencing discrimination. Furthermore, some groups face significant state and societal discrimination on the basis of their religious beliefs and practices, or the lack thereof ^50–53. There is also evidence of discrimination based on socioeconomic factors, such as income, education, and employment status ^54–56. Although such groups have borne the brunt of discrimination to one extent or another worldwide, cultural context matters. Discrimination takes different forms across societies, shaped by how each society defines who is marginalized and who holds dominant status. Additionally, some countries have strong legal frameworks to protect individuals from discrimination based on certain of these characteristics, but not others. Still, some countries lack adequate protections altogether.

Thus, we first ask two questions: a) How do mean levels of perceived discrimination order across different countries? b) How do levels of perceived discrimination vary across different demographic categories such as age, gender, marital status, employment, religious service attendance, education, and immigration status?

Despite the continuous efforts to understand discriminatory practices and curb their deleterious effects, surprisingly, less is known about the potential antecedents of perceived discrimination. Yet, understanding the determinants of perceived discrimination is vital both for scientists and policymakers because it allows us to address the root causes of social inequality and promote inclusivity more effectively. By identifying the factors that contribute to discrimination, we can develop targeted interventions and policies to reduce its occurrence and mitigate its harmful effects on mental and physical health, social cohesion, and economic opportunities. This knowledge is also crucial for fostering environments where diverse groups can thrive without fear of prejudice or bias, ultimately contributing to a more equitable and just society.

A promising host of candidate predictors has to do with individuals’ early childhood experiences. Such formative experiences have a far-reaching impact on various outcomes throughout a person’s life, including well-being ^57,58, emotional and physical health ^59–61, social and behavioral outcomes ^62,63, and future victimization or revictimization ^64,65. Similarly, researchers have started exploring the link between early childhood experiences, particularly adverse ones, and perceived discrimination later in life. Studies have found that individuals with a history of adverse childhood experiences (ACEs), including various forms of abuse, neglect, and household dysfunction, are more likely to report experiences of perceived discrimination ^66–69. Such early life stressors often create an environment of social rejection ⁶⁷, which can condition individuals to expect and perceive negative cues more readily ⁶⁸, making them more susceptible to feelings of marginalization or social rejection later in life ¹⁶. The impact of ACEs on perceived discrimination is particularly pronounced in minority racial and ethnic groups. These groups often face systemic discrimination throughout their lives, and early childhood adversity can amplify their sensitivity to these experiences. For example, Vásquez and colleagues ⁶⁹ found that individuals exposed to ACEs were more likely to report perceived discrimination across racial and ethnic lines, indicating that early adversity compounds the effects of racial and ethnic discrimination. Such childhood experiences may universally influence current levels of perceived discrimination, though the strength and nature of these influences could vary across different countries.

Thus, we ask three additional questions: c) How do different aspects of a child's upbringing predict perceived discrimination in adulthood? d) Do these associations vary by country? e) To what extent are the observed relationships robust to potential unmeasured confounding?

To address these questions, we utilize the Global Flourishing Study, a novel, diverse, and international dataset of 202,898 individuals from 22 countries. First, we report estimates of perceived discrimination levels across countries and how they vary across demographic categories. Second, we assess how 11 aspects of a child’s upbringing predict perceived discrimination in adulthood and show whether and how these associations vary by country. The study provides comprehensive information about the prevalence, variability, and childhood determinants of perceived discrimination in a cross-national context. Such cross-cultural comparisons are essential in understanding which correlates of perceived discrimination are universal or culture-specific. Given that the vast majority of previous research on this topic is focused on single or Western countries (cf.^70–72), the current study is a first-of-its-kind comparative look at perceived discrimination across various nations.

We find that although all nations have some level of perceived discrimination, there is significant variation in the prevalence of perceived discrimination between countries. Countries like Egypt, South Africa, Nigeria, and Brazil are at the higher end of the distribution of perceived discrimination, while Sweden, Poland, Tanzania, and Germany are at the lower end. Demographically, young adults, separated individuals, the unemployed, frequent religious service attenders, and Muslims tend to report higher levels of perceived discrimination, although these trends are not uniform across all nations. We find no consistent links between perceived discrimination and education or immigration status, suggesting that the factors driving discrimination are complex and often context-dependent.

The findings also highlight the lasting impact of early childhood experiences on perceptions of discrimination in adulthood. Adverse childhood experiences, especially abuse, feeling as an outsider in one’s family, and household financial hardship strongly predict higher levels of perceived discrimination later in life. These relationships, however, differ across nations, indicating that both global and culturally specific influences are at play. These findings suggest that addressing childhood adversity may be crucial for reducing long-term discrimination. We need further cross-national research to understand the full range of factors contributing to discrimination, both globally and within specific national contexts, and the present study constitutes an important step forward.

Demographic variation in perceived discrimination across countries

Descriptive statistics

Wave 1 of the Global Flourishing Study included a total of 202,898 participants from 22 geographically and culturally diverse countries. The age distribution ranged from 18 to 24 years old (n = 27,007; 13%) to 80 years and older (n = 4,119; 2%). Gender distribution was nearly equal among males (n = 98,411; 49%) and females (n = 103,488; 51%), with only 0.3% of them identifying as other (n = 602). At the time of the interview, 39% of participants were employed by an employer (n = 78,815), 57% had completed 9–15 years of education (n = 115,097), and 53% of them reported being married (n = 106,354). Table 1 summarizes the descriptive statistics for the main demographic variables. Information about race or ethnicity and religious affiliation was not reported systematically across countries. Therefore, these are only included in the country-by-country analysis. All country-specific results and the variations in estimates across countries can be found in the Supplementary Information. We comment on these national variations further in the Results and Discussion sections.

Table 1

Nationally representative descriptive statistics of the observed sample
Characteristic	N = 202,898¹
Age group
18–24	27,007 (13%)
25–29	20,700 (10%)
30–39	40,256 (20%)
40–49	34,464 (17%)
50–59	31,793 (16%)
60–69	27,763 (14%)
70–79	16,776 (8.3%)
80 or older	4,119 (2.0%)
Missing	20 (< 0.1%)
Gender
Male	98,411 (49%)
Female	103,488 (51%)
Other	602 (0.3%)
Missing	397 (0.2%)
Marital status
Married	107,354 (53%)
Separated	5,195 (2.6%)
Divorced	11,654 (5.7%)
Widowed	9,823 (4.8%)
Never	52,115 (26%)
Domestic Partner	14,931 (7.4%)
Missing	1,826 (0.9%)
Employment
Employed for an employer	78,815 (39%)
Self-employed	36,362 (18%)
Retired	29,303 (14%)
Student	10,726 (5.3%)
Homemaker	21,677 (11%)
Unemployed and looking for a job	16,790 (8.3%)
None of these/other	8,431 (4.2%)
Missing	793 (0.4%)
Religious service attendance
> 1/week	26,537 (13%)
1/week	39,157 (19%)
1–3/month	19,749 (9.7%)
A few times a year	41,436 (20%)
Never	75,297 (37%)
Missing	722 (0.4%)
Education
up to 8 years	45,078 (22%)
9–15 years	115,097 (57%)
16 + years	42,578 (21%)
Missing	146 (< 0.1%)
Immigration
Born in this country	190,998 (94%)
Born in another country	9,791 (4.8%)
Missing	2,110 (1.0%)
COUNTRY
Argentina	6,724 (3.3%)
Australia	3,844 (1.9%)
Brazil	13,204 (6.5%)
Egypt	4,729 (2.3%)
Germany	9,506 (4.7%)
Hong Kong	3,012 (1.5%)
India	12,765 (6.3%)
Indonesia	6,992 (3.4%)
Israel	3,669 (1.8%)
Japan	20,543 (10%)
Kenya	11,389 (5.6%)
Mexico	5,776 (2.8%)
Nigeria	6,827 (3.4%)
Philippines	5,292 (2.6%)
Poland	10,389 (5.1%)
South Africa	2,651 (1.3%)
Spain	6,290 (3.1%)
Sweden	15,068 (7.4%)
Tanzania	9,075 (4.5%)
Turkey	1,473 (0.7%)
United Kingdom	5,368 (2.6%)
United States	38,312 (19%)
¹n (%)

Prevalence of perceived discrimination across countries

Next, we examined whether the levels of perceived discrimination vary across countries. Table 2 exhibits the results. The second column presents the proportion of participants in each national sample who reported experiencing discrimination often or always, ordered from highest to lowest. We observed that the proportion of perceived discrimination varied widely across countries, ranging from a low of 0.10 (95% CI 0.09–0.11, sd = 0.30) in Sweden to an astounding high of 0.47 (95% CI 0.46–0.49, sd = 0.50) in Egypt.

Table 2

Ordered means of perceived discrimination with standard deviations
Country	Mean	95% CI	Standard Deviation
Egypt	0.47	(0.46, 0.49)	0.50
South Africa	0.37	(0.35, 0.40)	0.48
Nigeria	0.34	(0.31, 0.36)	0.47
Brazil	0.31	(0.30, 0.32)	0.46
Kenya	0.30	(0.28, 0.31)	0.46
Turkey	0.29	(0.26, 0.32)	0.45
Hong Kong	0.28	(0.26, 0.30)	0.45
Philippines	0.26	(0.25, 0.28)	0.44
United States	0.26	(0.25, 0.27)	0.44
Argentina	0.24	(0.22, 0.25)	0.43
Mexico	0.23	(0.22, 0.24)	0.42
India	0.22	(0.21, 0.23)	0.41
United Kingdom	0.22	(0.21, 0.24)	0.42
Indonesia	0.21	(0.19, 0.23)	0.41
Israel	0.21	(0.18, 0.23)	0.40
Spain	0.19	(0.18, 0.21)	0.40
Australia	0.18	(0.16, 0.19)	0.38
Japan	0.16	(0.16, 0.17)	0.37
Germany	0.15	(0.14, 0.16)	0.35
Tanzania	0.14	(0.12, 0.15)	0.34
Poland	0.13	(0.11, 0.15)	0.34
Sweden	0.10	(0.09, 0.11)	0.30

As a post-hoc sensitivity analysis we provide the equivalent results of Table 2 with a different dichotomization point where perceived discrimination is treated as always (1) vs often/rarely/never (0) (see Table S2 in SI). We observe small deviations in how countries are ordered based on the proportion of perceived discrimination reported by the respondents, indicating that in some countries, like Turkey and India, the relative proportion of people who report experiencing discrimination “always” vs. “often” is much higher compared to other countries.

Differences in perceived discrimination across demographic categories

The random-effects meta-analysis revealed important differences in the proportions of perceived discrimination reported by different demographic categories across these 22 countries (Table 3). We discuss the most prominent results. In particular, younger adults were more likely to report perceived discrimination compared to older adults (p < .001). This trend was especially robust among participants aged 18–24 (µ = 0.27, 95% CI 0.23–0.31, SE = 0.02) and 25–29 (µ = 0.26, 95% CI 0.23–0.30, SE = 0.02) compared to those aged 60–69 (µ = 0.19, 95% CI 0.15–0.22, SE = 0.02) and 70–79 (µ = 0.16, 95% CI 0.12–0.20, SE = 0.02), as indicated by the non-overlapping confidence intervals.

Table 3

Random effects meta-analysis of perceived discrimination proportions by demographic category
					Prediction Interval
Variable	Category	Proportion	95% CI of Proportion	SE Analogue (CI Width/4)	LL	UL	tau (τ)	I^2	Global p-value
Age group									< .001**
	18–24	0.27	(0.23,0.31)	0.02	0.13	0.47	0.09	88.5
	25–29	0.26	(0.23,0.30)	0.02	0.14	0.46	0.08	86.9
	30–39	0.25	(0.22,0.29)	0.02	0.13	0.45	0.08	86.5
	40–49	0.24	(0.21,0.28)	0.02	0.12	0.45	0.08	88.5
	50–59	0.21	(0.18,0.25)	0.02	0.09	0.46	0.09	90.1
	60–69	0.19	(0.15,0.22)	0.02	0.06	0.44	0.08	89.5
	70–79	0.16	(0.12,0.20)	0.02	0.03	0.44	0.08	92.7
	80 or older	0.12	(0.06,0.23)	0.04	0.00	0.43	0.19	99.0
Gender									< .001**
	Male	0.24	(0.20,0.27)	0.02	0.11	0.45	0.08	88.7
	Female	0.22	(0.19,0.26)	0.02	0.10	0.47	0.08	88.7
	Other	0.48	(0.19,0.79)	0.15	0.00	1.00	0.69	99.7
Marital status									< .001**
	Married	0.21	(0.18,0.26)	0.02	0.08	0.46	0.09	90.8
	Separated	0.28	(0.24,0.31)	0.02	0.14	0.50	0.08	85.3
	Divorced	0.22	(0.18,0.27)	0.02	0.10	0.44	0.10	92.2
	Widowed	0.17	(0.13,0.22)	0.02	0.03	0.45	0.11	95.0
	Domestic partner	0.22	(0.18,0.25)	0.02	0.10	0.38	0.08	88.8
	Single, never married	0.26	(0.22,0.29)	0.02	0.14	0.45	0.08	85.6
Employment status									< .001**
	Employed for an employer	0.24	(0.20,0.28)	0.02	0.11	0.45	0.09	90.1
	Self-employed	0.24	(0.20,0.28)	0.02	0.11	0.48	0.09	90.7
	Retired	0.17	(0.14,0.21)	0.02	0.05	0.44	0.08	91.5
	Student	0.25	(0.21,0.29)	0.02	0.10	0.45	0.09	89.9
	Homemaker	0.22	(0.19,0.26)	0.02	0.13	0.46	0.07	85.9
	Unemployed and looking for a job	0.27	(0.24,0.31)	0.02	0.13	0.39	0.08	85.2
	None of these/other	0.27	(0.23,0.31)	0.02	0.13	0.43	0.09	89.7
Education									< .001**
	Up to 8 years	0.26	(0.22,0.31)	0.02	0.10	0.47	0.09	89.7
	9–15 years	0.22	(0.19,0.26)	0.02	0.11	0.46	0.08	89.3
	16 + years	0.21	(0.18,0.25)	0.02	0.09	0.41	0.08	88.7
Religious service attendance									< .001**
	> 1/week	0.31	(0.26,0.35)	0.02	0.13	0.61	0.10	90.5
	1/week	0.28	(0.24,0.33)	0.02	0.13	0.48	0.10	90.2
	1–3/month	0.28	(0.24,0.33)	0.02	0.12	0.50	0.10	89.7
	A few times a year	0.22	(0.18,0.25)	0.02	0.09	0.49	0.08	89.1
	Never	0.22	(0.18,0.26)	0.02	0.09	0.41	0.09	90.7
Immigration status									< .001**
	Born in this country	0.23	(0.19,0.26)	0.02	0.10	0.46	0.08	89.1
	Born in another country	0.25	(0.22,0.29)	0.02	0.07	0.40	0.08	87.9
Note: p < .05; p < .007 (Bonferroni corrected threshold). Proportion: Estimated overall proportion in the category. 95% CI of Proportion: The 95% CI for the estimated overall proportion of people who reported feeling discriminated always or often for each demographic category. SE Analogue (CI Width/4): Standard error for the estimated overall proportion for each demographic group. Prediction interval: Reflects how the country-specific proportion vary. LL: Lower limit of the 95% prediction interval. UP: Upper limit of the 95% prediction interval. “tau”: Measures the standard deviation of the distribution of means across countries. It is an estimate of how much the mean in that demographic category varies across countries. I^2: Estimates how much of the variability in means is due to heterogeneity across countries vs. sampling variability. Given that the sample sizes of this study are large, the I^2 is high. Global p-value*: Tests the null hypothesis that the demographic category does not matter in any of the 22 countries

Regarding gender, individuals who identified as Other reported higher levels of perceived discrimination on average (µ = 0.48, 95% CI 0.19–0.79, SE = 0.15) compared to those identified as male (µ = 0.24, 95% CI 0.20–0.27, SE = 0.02) or female (µ = 0.22, 95% CI 0.19–0.26, SE = 0.02), though the lower limit of the CI suggested considerable uncertainty due to small samples for the Other category.

When considering other social characteristics, the most pronounced differences in perceived discrimination were observed among respondents with different marital and employment statuses. Salient differences emerged between respondents who identified as separated (µ = 0.28, 95% CI 0.24–0.31, SE = 0.02), or single, never married (µ = 0.26, 95% CI 0.22–0.29, SE = 0.02), and those who identified as widowed (µ = 0.17, 95% CI 0.13–0.22, SE = 0.02). Additionally, retired individuals reported the lowest levels of perceived discrimination (µ = 0.17, 95% CI 0.14–0.21, SE = 0.02), whereas those unemployed and looking for a job (µ = 0.27, 95% CI 0.24–0.31, SE = 0.02), as well as those in the “none of these/other” category (µ = 0.27, 95% CI 0.23–0.31, SE = 0.02) reported the highest levels of perceived discrimination across employment categories.

Perceived discrimination was also associated with higher frequency of religious service attendance (p < .001). Thirty-one percent of participants who attend religious services more than once a week have report discrimination (95% CI 0.26–0.35, SE = 0.02) compared to only 22% of those who attend a few times a year (µ = 0.22, 95% CI 0.18–0.25, SE = 0.02), a 9-percentage point difference.

As a supplementary analysis, we also conducted population weighted meta-analyses. Table S1 in SI provides additional analyses using a population-weighted meta-analysis, adjusting results based on each country's 2023 population size. The findings from both approaches are largely consistent.

Cross-cultural variation in demographic differences

We note that the variation in estimates attributed to heterogeneity across countries was high with I² ranging from 85.2 to 99.7 and tau (τ) from 0.08 to 0.43. As such, caution must be taken in the interpretation of results of the meta-analysis as homogeneous patterns. Due to space constraints, we highlight selected examples of variability; full results are in the Supplementary Information. For instance, younger adults reported more perceived discrimination than older adults in 15 of 22 countries. However, in Kenya, adults aged 80 + reported more discrimination (µ = 0.41, 95% CI 0.21–0.61, SE = 0.10) than those aged 18–24 (µ = 0.28, 95% CI 0.26–0.30, SE = 0.01). In Mexico, both younger (18–24: µ = 0.28, 95% CI 0.24–0.31, SE = 0.02) and older adults (80 or older: µ = 0.31, 95% CI 0.12–0.49, SE = 0.09) reported higher discrimination than other age categories. No age-discrimination association was found in Egypt, India, Poland, Tanzania, and the Philippines.

While frequent religious service attenders generally reported higher discrimination, the opposite was observed in Kenya, Nigeria, Tanzania, and Turkey, where infrequent attenders reported more discrimination. In the United States, both participants who attend religious services more than once a week (µ = 0.30, 95% CI 0.26–0.34, SE = 0.02) and those who never attend (µ = 0.27, 95% CI 0.25–0.28, SE = 0.01) exhibited high levels of perceived discrimination. No association was found between religious service attendance and perceived discrimination in Indonesia and South Africa.

The meta-analysis results also indicated that individuals born outside the country of interview (µ = 0.25, 95% CI 0.22–0.29, SE = 0.02) reported only very slightly more discrimination compared to those born in the country (µ = 0.23, 95% CI 0.19–0.26, SE = 0.02). However, there was only strong statistical evidence for a difference in 6 of the 22 countries: Germany (µ_{in country} = 0.14, 95% CI 0.13–0.15, SE = 0.00; µ_{another country} = 0.19, 95% CI 0.15–0.23, SE = 0.02; p < .001), Japan (µ_{in country} = 0.16, 95% CI 0.16–0.17, SE = 0.00; µ_{another country} = 0.28, 95% CI 0.19–0.37, SE = 0.05; p < .001), Mexico (µ_{in country} = 0.23, 95% CI 0.21–0.24, SE = 0.01; µ_{another country} = 0.31, 95% CI 0.21–0.42, SE = 0.05; p = .009), Spain (µ_{in country} = 0.19, 95% CI 0.17–0.20, SE = 0.01; µ_{another country} = 0.24, 95% CI 0.20–0.27, SE = 0.02; p < .001), Sweden (µ_{in country} = 0.09, 95% CI 0.09–0.10, SE = 0.00; µ_{another country} = 0.23, 95% CI 0.20–0.26, SE = 0.02; p < .001), and the United Kingdom (µ_{in country} = 0.22, 95% CI 0.20–0.24, SE = 0.01; µ_{another country} = 0.26, 95% CI 0.22–0.31, SE = 0.02; p = .008). This association is heterogeneous and underlies a strong geographical component, with European Union countries predominantly shaping the pattern.

Next, we discuss notable patterns related to differences in perceived discrimination across religious affiliation and race and ethnicity categories, which were not included in the meta-analysis (see SI) because categories varied across countries. Regarding religious affiliation, Muslim respondents were more likely to report higher levels of perceived discrimination compared to the majority religious group in several countries. For example, in the United States, 45% of Muslim respondents have experienced discrimination (µ = 0.45, 95% CI 0.25–0.65, SE = 0.10, p < .001) compared to 25% of Christians (µ = 0.25, 95% CI 0.23–0.26, SE = 0.01; see Table S22b). Furthermore, participants who identified as Black reported higher levels of perceived discrimination on average compared to those identified with the majority racial group in Argentina (µ = 0.48, 95% CI 0.32–0.64, SE = 0.08, p < .001), the United Kingdom (µ = 0.47, 95% CI 0.36–0.58, SE = 0.05, p < .001), and the United States (µ = 0.38, 95% CI 0.34–0.42, SE = 0.02, p < .001; see Tables S1b, S21b, and S22b).

Further remarks on variation across countries are also given in the Discussion.

Childhood predictors of perceived discrimination in adulthood

Descriptive statistics

Table 4 shows the descriptive statistics for childhood predictors. Most respondents indicated they had a very good relationship with their mother (n = 127,836; 63%) and father (n = 107,742; 53%) in childhood. Seventy-five percent of participants grew up within marriage (n = 152,001). At age 12, 41% of the respondents (n = 83,237) attended religious services at least once a week, while 23% never attended (n = 47,445). Fourteen percent of all respondents (n = 29,139) experienced childhood abuse and another 14% (n = 28,732) felt as an outsider in their family growing up. Thirty-three percent of the participants rated their mental health during childhood as excellent (n = 67,121), 9.8% as fair (n = 19,877), and 2.4% as poor (n = 4,906).

Table 4

Nationally representative childhood descriptive statistics of the observed sample
Characteristic	N = 202,898¹
Relationship with mother
Very good	127,836 (63%)
Somewhat good	52,439 (26%)
Somewhat bad	11,060 (5.5%)
Very bad	4,642 (2.3%)
Does not apply	5,965 (2.9%)
Missing	956 (0.5%)
Relationship with father
Very good	107,742 (53%)
Somewhat good	55,714 (27%)
Somewhat bad	15,807 (7.8%)
Very bad	8,278 (4.1%)
Does not apply	13,985 (6.9%)
Missing	1,372 (0.7%)
Parent marital status
Yes, married	152,001 (75%)
No, divorced	17,726 (8.7%)
Never married	15,534 (7.7%)
No, one or both of them had died	7,794 (3.8%)
Missing	9,843 (4.9%)
Subjective financial status of family growing up
Lived comfortably	70,861 (35%)
Got by	82,905 (41%)
Found it difficult	35,852 (18%)
Found it very difficult	12,606 (6.2%)
Missing	674 (0.3%)
Abuse
Yes	29,139 (14%)
No	167,279 (82%)
Missing	6,479 (3.2%)
Outsider growing up
Yes	28,732 (14%)
No	170,577 (84%)
Missing	3,589 (1.8%)
Self-rated health growing up
Excellent	67,121 (33%)
Very good	63,086 (31%)
Good	47,378 (23%)
Fair	19,877 (9.8%)
Poor	4,906 (2.4%)
Missing	530 (0.3%)
Immigration status
Born in this country	190,998 (94%)
Born in another country	9,791 (4.8%)
Missing	2,110 (1.0%)
Age 12 religious service attendance
At least 1/week	83,237 (41%)
1–3/month	33,308 (16%)
< 1/month	36,928 (18%)
Never	47,445 (23%)
Missing	1,980 (1.0%)
Age group
1998–2005; current age: 18–24	27,007 (13%)
1993–1998; age: 25–29	20,700 (10%)
1983–1993; age: 30–39	40,256 (20%)
1973–1983; age 40–49	34,464 (17%)
1963–1973; age 50–59	31,793 (16%)
1953–1963; age 60–69	27,763 (14%)
1943–1953; age 70–79	16,776 (8.3%)
1943 or earlier; age 80+	4,119 (2.0%)
Missing	20 (< 0.1%)
Gender
Male	98,411 (49%)
Female	103,488 (51%)
Other	602 (0.3%)
Missing	397 (0.2%)
Country
Argentina	6,724 (3.3%)
Australia	3,844 (1.9%)
Brazil	13,204 (6.5%)
Egypt	4,729 (2.3%)
Germany	9,506 (4.7%)
Hong Kong	3,012 (1.5%)
India	12,765 (6.3%)
Indonesia	6,992 (3.4%)
Israel	3,669 (1.8%)
Japan	20,543 (10%)
Kenya	11,389 (5.6%)
Mexico	5,776 (2.8%)
Nigeria	6,827 (3.4%)
Philippines	5,292 (2.6%)
Poland	10,389 (5.1%)
South Africa	2,651 (1.3%)
Spain	6,290 (3.1%)
Sweden	15,068 (7.4%)
Tanzania	9,075 (4.5%)
Turkey	1,473 (0.7%)
United Kingdom	5,368 (2.6%)
United States	38,312 (19%)
¹n (%)

Childhood predictors of perceived discrimination

Table 5 shows the associations between perceived discrimination and childhood predictors from the random effects meta-analysis. A few childhood predictors were clearly linked to lower risk of perceived discrimination in adulthood. For example, those born in 1943–1953 (RR = 0.63, 95% CI 0.53–0.75, I² = 77.6, p < .001), 1953–1963 (RR = 0.74, 95% CI 0.66–0.82, I² = 72.9, p < .001), 1963–1973 (RR = 0.84, 95% CI 0.76–0.91, I² = 74.4, p < .001), and 1973–1983 (RR = 0.92, 95% CI 0.87–0.97, I² = 53.4, p < .001) were consistently less likely to report discrimination as adults compared to those born between 1998 and 2005. Other typically protective childhood experiences, such as very/somewhat good maternal (RR = 0.95, 95% CI 0.91-1.00, I² < 0.1, p < .001) or paternal relationship (RR = 0.96, 95% CI 0.92-1.00, I² < 0.1, p < .001) did not yield conclusive results, since both CIs included 1.00.

Table 5

Random effects meta-analysis of regression of perceived discrimination on childhood predictors

Variable	Category	RR	95% CI	< 0.90	> 1.10	I^2	Global p-value
Relationship with mother	(Ref: Very bad/somewhat bad)						< .001**
	Very good/somewhat good	0.95	(0.91,1.00)	0.00	0.00	< 0.1ǂ
Relationship with father	(Ref: Very bad/somewhat bad)						< .001**
	Very good/somewhat good	0.96	(0.92,1.00)	0.00	0.00	< 0.1ǂ
Parent marital status	(Ref: Parents married)						< .001**
	No, divorced	1.10	(1.01,1.19)	0.05	0.45	69.1
	Single, never married	1.09	(1.00,1.20)	0.05	0.32	74.1
	No, one or both of them had died	1.03	(0.93,1.12)	0.18	0.32	54.7
Subjective financial status of family growing up	(Ref: Got by)						< .001**
	Lived comfortably	1.00	(0.96,1.04)	0.05	0.05	54.4
	Found it difficult	1.05	(1.00,1.11)	0.05	0.23	55.0
	Found it very difficult	1.14	(1.08,1.20)	0.00	0.77	22.1
Abuse	(Ref: No)						< .001**
	Yes	1.44	(1.36,1.53)	0.00	1.00	76.2
Outsider growing up	(Ref: No)						< .001**
	Yes	1.35	(1.24,1.47)	0.00	0.77	86.4
Self-rated health growing up	(Ref: Good)						< .001**
	Excellent	0.96	(0.89,1.03)	0.36	0.14	77.0
	Very good	0.95	(0.91,1.00)	0.23	0.05	52.0
	Fair	1.06	(1.00,1.11)	0.00	0.32	34.1
	Poor	1.18	(1.11,1.26)	0.00	1.00	< 0.1ǂ
Immigration status	(Ref: Born in this country)						< .001**
	Born in another country	1.06	(0.98,1.15)	0.00	0.36	33.6
Age 12 religious service attendance	(Ref: Never)						< .001**
	At least 1/week	1.14	(1.03,1.25)	0.09	0.45	79.5
	1–3/month	1.18	(1.03,1.35)	0.09	0.50	88.8
	< 1/month	1.08	(1.00,1.17)	0.09	0.36	69.2
Year of birth	(Ref: 1998–2005; age 18–24)						< .001**
	1993–1998; age 25–29	0.99	(0.95,1.04)	0.00	0.00	12.3
	1983–1993; age 30–39	0.96	(0.91,1.01)	0.23	0.05	51.2
	1973–1983; age 40–49	0.92	(0.87,0.97)	0.36	0.00	53.4
	1963–1973; age 50–59	0.84	(0.76,0.91)	0.55	0.00	74.4
	1953–1963; age 60–69	0.74	(0.66,0.82)	0.77	0.00	72.9
	1943–1953; age 70–79	0.63	(0.53,0.75)	0.82	0.00	77.6
	1943 or earlier; age 80+	0.21	(0.04,1.15)	0.77	0.23	99.4
Gender	(Ref: Male)						< .001**
	Female	0.90	(0.86,0.94)	0.59	0.00	72.2
	Other	0.45	(0.07,2.93)	0.11	0.83	99.6
Note. p < .05; *p < .004 (Bonferroni corrected threshold); ǂ estimate of heterogeneity is likely unstable, please see our online supplement forest plots for more detail on heterogeneity of effects.

RR: Risk Ratio, the probability of perceived discrimination for a category of a childhood predictor to the probability of perceived discrimination to the reference category.

95% CI: The 95% CI for the estimated risk ratio of perceived discrimination for each childhood predictor.

Estimated Proportion of Effects by Threshold: Reflects the estimated proportion of effects (e.g. across the implied distribution of effects sizes within the 22 countries) that are either less than a RR of 0.9 or above a RR of 1.1.

I^2: Estimates how much of the variability in means is due to heterogeneity across countries vs. sampling variability. Given that the sample sizes of this study are large, the I^2 is high.

Global p-value: Tests the null hypothesis that the childhood predictor does not matter in any of the 22 countries

Regarding gender identification, females seemed to be 0.90 times as likely as males to report discrimination (95% CI 0.86–0.94, I² = 72.2, p < .001). In contrast, the meta-analysis suggested that those who identified their gender as “Other” might experience higher, similar, or lower discrimination compared to males (RR = 0.45, 95% CI 0.07–2.93, I² = 99.6) across countries.

Several childhood experiences were linked with increased risk of perceived discrimination in adulthood, such as (1) physical or sexual abuse growing up (RR = 1.44, 95% CI 1.36–1.53, I² = 76.2, p < .001), (2) feeling as an outsider in one’s family as a child (RR = 1.35, 95% CI 1.24–1.47, I² = 86.4, p < .001), (3) attending religious services at age 12, (a) at least once a week (RR = 1.14, 95% CI 1.03–1.25, I² = 79.5, p < .001) and (b) 1–3 times per month (RR = 1.18, 95% CI 1.03–1.35, I² = 88.8, p < .001), (4) poor health growing up (RR = 1.18, 95% CI 1.11–1.26, I² < 0.1, p < .001), (5) parental divorce (RR = 1.10, 95% CI 1.01–1.19, I² = 69.1, p < .001), and (6) very difficult family finances (RR = 1.14, 95% CI 1.08–1.20, I² = 22.1, p < .001). However, there was less evidence of a consistent association with other adverse household circumstances, such as being raised by a single parent or experiencing a parental death, as well as experiencing immigration in childhood.

Interestingly, the results of the post-hoc sensitivity analysis with a different dichotomization point in the outcome variable (see Table S5 in SI) indicate that all categories of childhood financial status (as compared to “got by”) increased the risk of perceived discrimination in adulthood (Lived comfortably: RR = 1.16, 95% CI 1.08–1.24, I² = 19.8, p < .001; found it difficult: RR = 1.08, 95% CI 1.01–1.16, I² = 2.9, p < .001); found it very difficult: RR = 1.31, 95% CI 1.17–1.47, I² = 31.6, p < .001), while it made the effects of childhood abuse (RR = 1.63, 95% CI 1.49–1.77, I² = 50.0, p < .001) and feeling as an outsider in one’s family as a child (RR 1.57, 95% CI 1.35–1.81, I² = 79.4, p < .001) more pronounced. In contrast, the association with religious service attendance and parental marital status did not hold.

The results of the population weighted meta-analysis were once again largely consistent with the primary analysis.

Cross-cultural variation in childhood predictors

As with demographic variation in perceived discrimination earlier, the meta-analysis of childhood predictors allowed us to identify wide variability in the heterogeneity of effects across countries. For example, although being abused in childhood universally increased the probability of feeling discriminated later in life, the magnitude of that effect varied considerably across countries (τ = .12, I² = 76.2), ranging from a low risk-ratio of 1.22 (95% CI 1.09–1.36, p < .001) in Japan to a high RR of 2.16 (95% CI 1.54–3.01, p < .001) in Poland. Growing up as an outsider in one’s family – one of the strongest predictors of perceived discrimination in adulthood – was associated with a lower risk of perceived discrimination in India (RR = 0.91, 95% CI 0.81–1.02, p = .014), but had no statistically significant effect in Egypt, Nigeria, South Africa, or Turkey.

Compared to having a very/somewhat bad maternal relationship, a very/somewhat good relationship was linked to a lower risk of perceived discrimination in adulthood only in Argentina (RR = 0.82, 95% CI 0.67-1.00, p < .001), Egypt (RR = 0.88, 95% CI 0.68–1.13, p = .005), Japan (RR = 0.92, 95% CI 0.84–1.02, p < .001), Kenya (RR = 0.88, 95% CI 0.74–1.05, p < .001), and Tanzania (RR = 0.76, 95% CI 0.51–1.12, p < .001). Conversely, it was linked to a higher risk of perceived discrimination in Israel (RR = 1.25, 95% CI 0.82–1.88, p = .009), Mexico (RR = 1.11, 95% CI 0.88–1.39, p = .039), Poland (RR = 1.31, 95% CI 0.75–2.30, p = .012), and Turkey (RR = 1.65, 95% CI 0.95–2.84, p < .001). Similarly, compared to a very/somewhat bad paternal relationship, a very/somewhat good relationship was associated with a lower risk of perceived discrimination in Argentina (RR = 0.90, 95% CI 0.75–1.08, p = .002), Brazil (RR = 0.94, 95% CI 0.86–1.03, p = < .001), Japan (RR = 0.90, 95% CI 0.81–0.99, p < .001), Tanzania (RR = 0.76, 95% CI 0.59–0.97, p < .001), and Turkey (RR = 0.76, 95% CI 0.60–0.97, p < .001). However, it increased the risk in Australia (RR = 1.11, 95% CI 0.87–1.41, p = .042), Indonesia (RR = 1.26, 95% CI 0.88–179, p < .001), and Mexico (RR = 1.14, 95% CI 0.94–1.38, p < .001).

While there is limited evidence linking experiencing immigration in childhood to perceived discrimination in adulthood, some exceptions were noted. Compared to being born in the country, experiencing discrimination in childhood was associated with a somewhat lower risk of adult discrimination in Kenya (RR = 0.76, 95% CI 0.52–1.09, p = .027) and the United States (RR = 0.85, 95% CI 0.71–1.02, p = .006), but a higher risk in Israel (RR = 1.25, 95% CI 1.01–1.55, p < .001) and Sweden (RR = 1.52, 95% CI 1.28–1.80, p < .001).

Country-by-country analysis also revealed that being affiliated with a minority religion at age 12 significantly increased the risk of perceived discrimination in adulthood in 11 out of 22 countries. For example, affiliation with a minority religion at age 12 was associated with higher risk of perceived discrimination by 93% in Germany (95% CI 1.57–2.39, p < .001) and by 197% in Poland (95% CI 1.32–6.72, p < .001). Participants who identified with a minority racial or ethnic group were also more likely to experience discrimination in adulthood in nine countries, with risk ratios ranging from 1.15 (Argentina: 95% CI 1.01–1.31, p < .001) to 1.79 (Israel: 95% CI 0.92–3.49, p = .007). However, the opposite pattern also emerged where race or ethnic minority status was associated with lower probability of feeling discriminated in adulthood in Kenya (RR = 0.83, 95% CI 0.74–0.93, p < .001) and Hong Kong (RR = 0.80, 95% CI 0.69–0.93, p < .001).

Sensitivity analysis

Subsequent sensitivity analysis with calculations of E-values suggested that a few of the correlations we reported were moderately to considerably robust to potentially unmeasured extraneous variables (see Table 6). For instance, an unmeasured variable, associated with both childhood abuse and adult perceived discrimination by risk ratios of 2.24-fold each, above and beyond the covariates we have already accounted for in our model, could explain away the observed association, but weaker joint confounder associations could not. To shift the 95% CI to include the null, an unmeasured confounder that was associated with both childhood abuse and adult perceived discrimination by risk ratios of 2.05-fold each, could suffice, while weaker joint associations with an extraneous variable could not. Some of the other relationships were vulnerable to potential unmeasured confounding as comparatively smaller correlations with unmeasured confounders would suffice to explain away these associations.

Table 6

Sensitivity of meta-analyzed childhood predictors to unmeasured confounding.
Variable	Category	evalue	evalue.limit
Relationship with mother	(Ref: Very bad/somewhat bad)
	Very good/somewhat good	1.27	1.06
Relationship with father	(Ref: Very bad/somewhat bad)
	Very good/somewhat good	1.25	1.06
Parent marital status	(Ref: Parents married)
	No, divorced	1.42	1.12
	Single, never married	1.41	1.00
	No, one or both of them had died	1.19	1.00
Subjective financial status of family growing up	(Ref: Got by)
	Lived comfortably	1.06	1.00
	Found it difficult	1.29	1.05
	Found it very difficult	1.53	1.36
Abuse	(Ref: No)
	Yes	2.24	2.05
Outsider growing up	(Ref: No)
	Yes	2.03	1.78
Self-rated health growing up	(Ref: Good)
	Excellent	1.25	1.00
	Very good	1.27	1.00
	Fair	1.30	1.07
	Poor	1.65	1.47
Immigration status	(Ref: Born in this country)
	Born in another country	1.33	1.00
Age 12 religious service attendance	(Ref: Never)
	At least 1/week	1.53	1.21
	1–3/month	1.64	1.22
	< 1/month	1.38	1.00
Year of birth	(Ref: 1998–2005; age 18–24)
	1993–1998; age 25–29	1.08	1.00
	1983–1993; age 30–39	1.26	1.00
	1973–1983; age 40–49	1.40	1.19
	1963–1973; age 50–59	1.68	1.41
	1953–1963; age 60–69	2.05	1.72
	1943 or earlier; age 80+	9.08	1.00
	1943–1953; age 70–79	2.53	1.98
Gender	(Ref: Male)
	Female	1.47	1.33
	Other	3.91	1.00

Discrimination is a global issue. Its forms vary across societies, depending on how each society defines who is marginalized and who is at the center. Yet, in all known societies, at least some people experience discrimination^2–4.

This paper sought to take the next step beyond such common knowledge. Using a general measure of perceived discrimination as reported by our respondents, we first asked whether the level of discrimination varies across nations. We found substantial variation across the 22 nations in our global sample. At the high end, about one-third of respondents in South Africa, Nigeria, Brazil, and Kenya reported that they experience discrimination often or always (hereafter, we will refer to those who report perceived discrimination often or always simply as experiencing discrimination). At the highest extreme, nearly half of our respondents in Egypt reported that they experienced discrimination. Conversely, in Japan, Germany, Tanzania, and Poland, only about 15% of respondents report having experienced discrimination. At the lowest extreme, just one in ten respondents in Sweden reported having experienced discrimination. This very low level exists despite much higher levels of perceived discrimination within Sweden by immigrants (23%), Muslims (34%), and Hindus (36%). Why these nations differ substantially in perceived discrimination is a clear next step in cross-national research and theory testing.

We explored the characteristics of people associated with increased perceptions of discrimination. After weighing the sample size across nations, we found with but a few exceptions that the young, not the old, perceive discrimination at higher levels. Those in our youngest age group—18 to 24—are more than 2.2 times as likely to perceive discrimination against them than those who are 80 or older. For marital status, overall those who are separated or single report more perceived discrimination than those who are married or widowed, perhaps reflecting the continued value societies attach to family formation.

We found a somewhat unexpected pattern by religious service attendance. The more frequently respondents attend religious services, the more likely they report experiencing discrimination. Whether this pattern reflects a secularization bias across nations—that modern people should not be religious—or religious conflict between religious groups—that religions are competing against one another, leading to prejudice and discrimination—will need to be studied to better understand this result. Supplementary analysis suggests that this pattern exists in 15 of the 22 study nations. In Kenya, Nigeria, Tanzania, and Turkey, a reverse pattern exists, whereby those who rarely or never attend express experiencing more discrimination than frequent attenders. Only in Indonesia and South Africa is there no clear pattern of perceived discrimination by religious attendance. We also found dramatic differences in the experience of discrimination by religious tradition across nations, with members of minority religions typically expressing the most experienced discrimination. But not all nations had such differences as Egypt, India, and Poland had no significant differences across religious traditions. Future research can build upon these findings and prior work^50–53 to investigate why such variations exist and why the dominant pattern is for the high attenders to express experiencing more discrimination.

Perhaps just as interestingly, several factors were significantly related to perceived discrimination in some but not all nations. These characteristics included education and immigration status. For instance, individuals born in another country report higher perceived discrimination in Germany, Japan, Mexico, Spain, Sweden, and the United Kingdom. We found no statistically significant differences in the other countries. Our supplementary analysis reveals a more complex pattern for education. In 13 out of 22 countries, those with fewer years of education were more likely to report discrimination. However, except for Hong Kong and Spain, the differences between educational categories in these countries are too small to draw firm conclusions. Additionally, in Nigeria and the United Kingdom, the trend is reversed: individuals with higher levels of education are more likely to report the experience of discrimination.

We went a step further in our analysis and considered if any childhood characteristics of the respondents mattered for reporting the experience of discrimination as an adult. Some factors did not have consistent results across nations, such as relationship quality with the respondents’ mothers and fathers. Parents' marital status often was not consistently related to the perception of discrimination by respondents as adults but with a clear exception. Those who grew up with divorced parents were more likely to report experiencing discrimination as adults. We also found that those who grew up in “very difficult” financial circumstances report more experience of discrimination as adults than those who grew up more financially comfortable. The enduring stigma associated with divorce and poverty may be part of the explanation for these associations. However, the strength of these associations clearly begs for further research on ACEs.

Two incredibly strong predictors of reporting the experience of adult discrimination are those who were abused as children and those who said they felt they were “outsiders” within their own family while growing up. It seems clear that family experiences as a child and youth play significant roles in subsequent adulthood experiences. Experiencing victimization at young ages likely leads individuals to feel more vulnerable and sensitive to other forms of victimization in adulthood^{16,64,65,67,68}. For governments, organizations, and persons seeking to reduce discrimination levels, lowering child abuse and perceptions of children feeling like outsiders may have the most powerful impact of any of our childhood measures.

As with the adult covariates of perceived discrimination, the childhood predictors’ impact on adult perceived discrimination often varied across nations. Child abuse matters for perceived discrimination in every nation, but the effect size varies across countries. In about half of the sampled nations, being a religious minority at age 12 or part of an ethnic minority group predicted more discrimination as adults, but no such patterns were found in the other half of the sampled nations. Such findings suggest that most factors associated with experiencing discrimination are socially created and amenable to change.

We note one important limitation of our study: the childhood predictors were reported retrospectively, and thus may be subject to recall bias. However, for recall bias to completely explain away the observed associations requires that the effect of adult perceived discrimination on biasing retrospective assessments of the childhood predictors be at least as strong as the observed associations themselves⁷³, yet, as just noted, many of these were quite substantial. We also found in the sensitivity analysis that several of the associations (such as abuse as a child and growing up as an outsider) were robust to potential unmeasured confounding variables. A few relationships, were susceptible to unmeasured cofounders, such as growing up in a single-parent household and being born in another country. Some caution is also needed in interpreting cross-national differences in proportions, as these may potentially be influenced by matters of translation, different modes of assessment, cultural norms, interpretation of items and of response scales, and seasonal effects arising from data being collected in different countries at different times of the year.

The purpose of this study was to provide a comprehensive description of demographic variation in, and childhood predictors of, perceived discrimination across 22 nations. Perhaps the most important finding in this research is the continued impact several childhood factors have on perceived discrimination as adults. Clearly, what happens in childhood profoundly impacts people across the life course, including, we have found, perceived discrimination. And as prior research shows, the long-term health impacts of childhood ACEs and perceived discrimination are considerable, producing tangible costs to societies^{57–61,67–69,72}.

We have offered a preliminary, exploratory examination of factors associated with perceived discrimination, providing vital background information. This is the most extensive study on the topic to date in its breadth of nations analyzed and the global assessment of perceived discrimination. But more research is needed. As cross-national research on discrimination delves deeper, a study comparing whether different characteristics within nations shape levels of discrimination should prove fruitful. We need both a knowledge of global factors, which this study has begun, and national factors to fully consider the causes and consequences of discrimination.

The description of the methods below have been adapted from VanderWeele et al.⁷⁴. Further methodological detail is available elsewhere^75–81.

Data

The Global Flourishing Study (GFS) is a study of 202,898 participants from 22 geographically and culturally diverse countries, with nationally representative sampling within each country, concerning the distribution of determinants of well-being. Wave 1 of the data included the following countries and territories: Argentina, Australia, Brazil, Egypt, Germany, Hong Kong, India, Indonesia, Israel, Japan, Kenya, Mexico, Nigeria, the Philippines, Poland, South Africa, Spain, Sweden, Tanzania, Turkey, United Kingdom, and the United States. The countries were selected to (a) maximize coverage of the world's population, (b) ensure geographic, cultural, and religious diversity, and (c) prioritize feasibility and existing data collection infrastructure. Data collection was carried out by Gallup Inc. Data for Wave 1 were collected principally during 2023, with some countries beginning data collection in 2022 and exact dates varying by country⁸⁰. Four additional waves of panel data on the participants will be collected annually from 2024–2027. The precise sampling design to ensure nationally representative samples varied by country and further details are available in Ritter et al.⁸⁰. Survey items included aspects of well-being such as happiness, health, meaning, character, relationships, and financial stability⁸², along with other demographic, social, economic, political, religious, personality, childhood, community, health, and well-being variables. The data are publicly available through the Center for Open Science (https://www.cos.io/gfs). During the translation process, Gallup adhered to TRAPD model (translation, review, adjudication, pretesting, and documentation) for cross-cultural survey research (ccsg.isr.umich.edu/chapters/translation/overview).

Measures

Demographics Variables. Continuous age was classified as 18–24, 25–29, 30–39, 40–49, 50–59, 60–69, 70–79, and 80 or older. Gender was assessed as male, female, or other. Marital status was assessed as single/never married, married, separated, divorced, widowed, and domestic partner. Employment was assessed as employed, self-employed, retired, student, homemaker, unemployed and searching, and other. Education was assessed as up to 8 years, 9–15 years, and 16 + years. Service attendance was assessed as more than once/week, once/week, one-to-three times/month, a few times/year, or never. Immigration status was dichotomously assessed with: “Were you born in this country, or not?” Religious tradition/affiliation with categories of Christianity, Islam, Hinduism, Buddhism, Judaism, Sikhism, Baha’i, Jainism, Shinto, Taoism, Confucianism, Primal/Animist/Folk religion, Spiritism, African-Derived, some other religion, or no religion/atheist/agnostic; precise response categories varied by country⁸³. Racial/ethnic identity was assessed in some, but not all, countries, with response categories varying by country. For additional details on the assessments see the COS GFS codebook or Crabtree et al.⁷⁵.

Childhood Demographic Variables. Relationship with mother during childhood was assessed with the question: “Please think about your relationship with your mother when you were growing up. In general, would you say that relationship was very good, somewhat good, somewhat bad, or very bad?” Responses were dichotomized to very/somewhat good versus very/somewhat bad. An analogous variable was used for relationship with father. “Does not apply” was treated as a dichotomous control variable for respondents who did not have a mother or father due to death or absence. Parental marital status during childhood was assessed with responses of married, divorced, never married, and one or both had died. Financial status was measured with: “Which one of these phrases comes closest to your own feelings about your family's household income when you were growing up, such as when YOU were around 12 years old?” Responses were lived comfortably, got by, found it difficult, and found it very difficult. Abuse was assessed with yes/no responses to “Were you ever physically or sexually abused when you were growing up?” Participants were separately asked: “When you were growing up, did you feel like an outsider in your family?” Childhood health was assessed by: “In general, how was your health when you were growing up? Was it excellent, very good, good, fair, or poor?” Immigration status was assessed with: “Were you born in this country, or not?” Religious attendance during childhood was assessed with: “How often did YOU attend religious services or worship at a temple, mosque, shrine, church, or other religious building when YOU were around 12 years old?” with responses of at least once/week, one-to-three times/month, less than once/month, or never. Gender was assessed as male, female, or other. Continuous age (year of birth) was classified as 18–24, 25–29, 30–39, 40–49, 50–59, 60–69, 70–79, and 80 or older. Childhood religious tradition/affiliation was had response categories of Christianity, Islam, Hinduism, Buddhism, Judaism, Sikhism, Baha’i, Jainism, Shinto, Taoism, Confucianism, Primal/Animist/Folk religion, Spiritism, African-Derived, some other religion, or no religion/atheist/agnostic; precise response categories varied by country⁸³. Racial/ethnic identity was assessed in some, but not all, countries, with response categories varying by country. For additional details on the assessments see the COS GFS codebook or Crabtree et al.⁷⁵.

Outcome Variable(s). Perceived discrimination was assessed with the following question: “How often do you feel discriminated against because of any group you are a part of? This might include discrimination because of your religion, political affiliation, race, gender, social class, sexual orientation, or involvement in civic organizations or community groups.” Response options include: always, often, rarely, never. In the primary analyses, perceived discrimination has been dichotomized as always/often (1) vs. rarely/never (0).

Analysis

Demographic variation. Descriptive statistics for the full sample, weighted to be nationally representative within each country, were estimated for each of the demographic variables. Nationally representative proportions for perceived discrimination were estimated separately for each country and ordered from highest to lowest along with 95% confidence intervals. Variation in proportions in perceived discrimination across demographic categories were estimated, with all analyses initially conducted by country (online supplement). Primary results consisted of a random effects meta-analyses of country-specific means of perceived discrimination in each specific demographic category^84,85 along with 95% confidence intervals, standard errors, upper and upper limits of a 95% prediction interval across countries, heterogeneity (τ), and I2 for evidence concerning variation within a particular demographic variable across countries⁸⁶. Forest plots of estimates are available in the online supplement. All meta-analyses were conducted in R⁸⁷ using the metafor package⁸⁸. Within each country, a global test of variation of outcome across levels of each particular demographic variable was conducted, and a pooled p-value⁸⁹ across countries reported concerning evidence for variation within any country. Bonferroni corrected p-value thresholds are provided based on the number of demographic variables^90,91. Religious affiliation/tradition and race/ethnicity were used, when available, as control variables within country, but were not included in the meta-analyses since the availability of these response categories varied by country. As a supplementary analysis, population weighted meta-analyses were also conducted. All analyses were pre-registered with COS prior to data access (Authors’ website link); all code to reproduce analyses are openly available in an online repository⁷⁸.

Childhood predictors. Descriptive statistics for the observed sample, weighted to be nationally representative within country, were estimated for each childhood demographic category. A weighted modified Poisson regression model with complex survey adjusted standard errors was fit within each country of perceived discrimination on all of the aforementioned childhood predictor variables simultaneously. In the primary analyses, random effects meta-analyses of the regression coefficients^84,85 along with confidence intervals, estimate proportions of effects across countries with effect sizes larger than 1.1 and smaller than 0.9, and I² for evidence concerning variation within a given demographic category across countries⁸⁶. Forest plots of estimates are available in the online supplement. Religious affiliation/tradition and race/ethnicity were used within country as control variables, when available, but these coefficients themselves were not included in the meta-analyses since categories/responses varied by country. All meta-analyses were conducted in R⁸⁷ using the metafor package⁸⁸. Within each country, a global test of association of each childhood predictor variable group with outcome was conducted, and a pooled p-value⁸⁹ across countries reported concerning evidence for association within any country. Bonferroni corrected p-value thresholds are provided based on the number of childhood demographic variables^90,91. For each childhood predictor, we calculated E-values to evaluate the sensitivity of results to unmeasured confounding. An E-value is the minimum strength of the association an unmeasured confounder must have with both the outcome and the predictor, above and beyond all measured covariates, for an unmeasured confounder to explain away an association⁹². As a supplementary analysis, population weighted meta-analyses of the regression coefficients were estimated. All analyses were pre-registered with COS prior to data access, with only slight subsequent modification in the regression analyses due to multicollinearity (Authors’ website link); all code to reproduce analyses are openly available in an online repository⁷⁸.

Missing Data

Missing data on all variables was imputed using multivariate imputation by chained equations, and five imputed datasets were used ^93–96. To account for variation in the assessment of certain variables across countries (e.g., religious affiliation/tradition and race/ethnicity), the imputation process was conducted separately in each country. This within-country imputation approach ensured that the imputation models accurately reflected country-specific contexts and assessment methods. Sampling weights were included in the imputation models to account for specific-variable missingness that may have been related to probability of inclusion in the study.

Accounting for Complex Sampling Design

The GFS used different sampling scheme across countries based on availability of existing panels and recruitment needs⁸⁰. All analyses accounted for the complex survey design components by including weights, primary sampling units, and strata. Additional methodological detail, including accounting for the complex sampling design, is provided elsewhere⁷⁷.

Author contributions

G.Y. Wrote the paper.

N.G. Conducted the data analysis, wrote the paper.

M.E. Wrote the paper.

T.J.V. Coordinated data collection, participated in survey design, coordinated creation of code for analysis, provided helpful comments to the written drafts.

B.R.J. Coordinated data collection, participated in survey design, coordinated creation of code for analysis, provided helpful comments to the written drafts.

Data availability

The data are publicly available through the Center for Open Science (https://www.cos.io/gfs).

Code availability

All code to reproduce analyses is openly available in an online repository⁷⁸.

Competing interests

The authors declare no competing interests.

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Demographic Variation and Childhood Predictors of Perceived Discrimination Across 22 Countries

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Abstract

Introduction

Results

Demographic variation in perceived discrimination across countries

Descriptive statistics

Prevalence of perceived discrimination across countries

Differences in perceived discrimination across demographic categories

Cross-cultural variation in demographic differences

Childhood predictors of perceived discrimination in adulthood

Descriptive statistics

Childhood predictors of perceived discrimination

Cross-cultural variation in childhood predictors

Sensitivity analysis

Discussion

Methods

Data

Measures

Analysis

Missing Data

Accounting for Complex Sampling Design

Declarations

References

Additional Declarations

Supplementary Files

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