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Diminished Returns in Europe: Socioeconomic Status and Ethno-Racial Health Disparities Across 30 Countries in the European Social Survey

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Abstract

Ethnic and racial minorities in many countries experience worse relative health outcomes and earlier mortality compared to national averages or outcomes of the majority population. Although socioeconomic status often contributes to a portion of ethno-racial health disparities, there are many unanswered questions about the relationship between socioeconomic status and ethno-racial health disparities across contexts. Recent scholarship in the USA has found support for a “diminished returns” effect in which the socioeconomic health gradient is systematically smaller for marginalized groups, yet it is unclear whether this pattern exists in other national contexts. This study tests the interaction between socioeconomic status and ethno-racial minority status in 30 countries across six waves of the European Social Survey. The results include evidence of the diminished returns pattern, particularly for populations with origins in Sub-Saharan Africa and the Middle East. Multilevel mixed-effects models find variation across countries in the interaction between socioeconomic status and ethno-racial minority status. The findings suggest racism and socioeconomic status interact to affect health and health disparities in multiple contexts and highlight the importance of cross-national comparison to further understand variation across countries.

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Code Availability

A replication package with the author’s code is available upon request and will be posted to an online repository upon publication.

Notes

  1. The sample begins with survey round 4 because the ESS switched its question for measuring household income in 2008 to reflect country-specific income decile rankings. Prior survey waves used different income questions that make cross-survey and cross-national comparison less straightforward.

  2. Table 7 in the Appendix depicts the number of missing values for each variable. More than 20% of values for the household income variable were missing, whereas for most other variables included less than 1% were missing.

  3. Because the analysis hinges on comparison of interaction effects at multiple levels, linear probability models offer a more straightforward interpretation of coefficients than logistic regression and similar methods that can be affected by omitted variables and are challenging to compare across models [64].

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Appendix

Appendix

Table 6 Sample size by country and survey round, ESS (n = 192,080)
Table 7 Missing data in ESS sample

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Bakhtiari, E. Diminished Returns in Europe: Socioeconomic Status and Ethno-Racial Health Disparities Across 30 Countries in the European Social Survey. J. Racial and Ethnic Health Disparities 9, 2412–2426 (2022). https://doi.org/10.1007/s40615-021-01178-2

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