Background: Retirement is a universal life stage, marking the culmination of an individual's working years. However, many people face financial challenges during retirement due to insufficient financial planning. Retirement preparedness is essential for ensuring economic security and maintaining a high quality of life in later years. Education is often viewed as a key driver of retirement preparedness, as it is linked to higher earnings, better financial literacy, and improved decision-making. However, the Minorities' Diminished Returns (MDRs) theory suggests that the economic, cognitive, and behavioral benefits of education are weaker for racial and ethnic minorities compared to non-Latino Whites. Objective: This study aims to examine the relationship between educational attainment and retirement preparedness, focusing on whether this association differs among Black, Latino, and non-Latino White individuals, using data from the Understanding America Study (UAS). Methods: Data were drawn from the UAS, a nationally representative internet-based panel survey. The sample included participants from diverse racial and ethnic backgrounds. Linear regression models were used to evaluate the association between educational attainment, measured in years of schooling, and retirement preparedness. Interaction terms were included to test whether the association varied by race and ethnicity. Models were adjusted for potential confounders, including age, sex, marital status, employment status, and immigration. Results: In the overall sample, higher educational attainment was significantly and positively associated with better retirement preparedness (p < 0.001). However, consistent with the MDRs framework, the strength of this association was significantly weaker for Black and Latino participants compared to non-Latino White participants (p < 0.05). Non-Latino Whites with higher education levels reported substantially better retirement preparedness, while the same level of education yielded smaller gains in retirement preparedness for Black and Latino individuals. Conclusion: The findings support the Minorities' Diminished Returns theory, showing that although educational attainment enhances retirement preparedness for all groups, Black and Latino individuals derive fewer benefits compared to their non-Latino White counterparts. These disparities point to persistent structural inequalities and systemic barriers within the education system and labor market, as well as the effects of segregation and discrimination, which undermine the economic benefits of education for marginalized populations. Addressing these disparities requires targeted policy interventions aimed at eliminating racial and ethnic inequalities in retirement outcomes and ensuring equitable benefits from educational attainment for all groups.

Background: Educational attainment is a well-established social determinant of various domains of cognitive function across the lifespan. However, the theory of Minorities' Diminished Returns (MDRs) suggests that the health benefits of educational attainment tend to be weaker for ethnic minorities compared to non-Latino Whites. This phenomenon may reflect the impact of structural inequalities, social stratification, and historical disadvantage. Objective: This study examines whether the association between educational attainment and numeracy score, one domain of cognitive function, is weaker in Latino individuals compared to non-Latino individuals, as predicted by the MDRs framework. Methods: Data were drawn from the 2014 wave of the Understanding America Study (UAS), a national internet-based panel. Numeracy score, a domain of the cognitive function was measured using an 8-item measure. Linear regression models were used to analyze the association between educational attainment and numeracy score, with an interaction term for ethnicity x educational attainment to explore differences between Latino and non-Latino participants. Models were adjusted for age, gender, marital status, immigration, and employment, and results were presented as beta coefficients, p-values, and 95% confidence intervals (CIs). Results: Overall, 5,659 participants entered our analysis. Higher educational attainment was positively associated with higher numeracy score for both Latino and non-Latino participants (p < 0.001). However, the interaction between education and ethnicity was significant (p < 0.05), indicating that Latino individuals experienced smaller numeracy benefits from education compared to non-Latino individuals. These results support the MDRs framework, suggesting that structural barriers may reduce the numeracy returns of education for Latino individuals. Conclusion: This study provides evidence of diminished returns of educational attainment in terms of numeracy scores among Latino individuals. While education is a key determinant of cognitive abilities such as numeracy, its benefits are not equitably distributed across ethnic groups. Structural inequalities particularly in educational opportunities likely contribute to this disparity. Addressing these underlying factors through targeted policy interventions is necessary to promote cognitive equity for Latino populations.

Intersectionality has significantly enhanced our understanding of how overlapping social identities—such as race, ethnicity, gender, sex, class, and sexual orientation—interact to shape individual experiences. However, despite its theoretical importance, much of the existing literature has relied on qualitative approaches to define and study intersectionality, limiting its application in predictive modeling, comparative analysis, and policy development. This paper introduces the concept of Quantitative Intersectionality Scoring System (QISS), a novel approach that assigns numerical scores to intersecting identities, thereby enabling a more systematic and data-driven analysis of intersectional effects. We argue that QISS can substantially enhance the utility and predictive validity of quantitative models by capturing the complexities of multiple, overlapping social determinants. By presenting concrete examples, such as the varying impacts of socioeconomic mobility on life expectancy among different intersectional groups, we demonstrate how QISS can yield more precise and reliable forecasts. Such a shift would allow policymakers and service providers to dynamically assess economic and health needs, as well as the uncertainties around them, as individuals move through different social and economic contexts. QISS-based models could be more responsive to the complexities of intersecting identities, allowing for a more quantified and nuanced evaluation of policy interventions. We conclude by discussing the challenges of implementing QISS and emphasizing the need for further research to validate these quantifications using robust quantitative methods. Ultimately, adopting QISS has the potential to improve the accuracy of predictive models and the effectiveness of policies aimed at promoting social justice and health equity.