Socioeconomic status (SES) indicators shape populations’ health and illness (1–3). Among SES indicators, educational attainment and income show the strongest influences on a wide range of health outcomes including but not limited to morbidity and mortality (1, 4–10). Highly educated and high income individuals are less likely to have chronic medical conditions (4, 5, 7, 10, 11) and depression (12–14), and report better self-rated health (SRH) (15–17).
Racial and ethnic groups, however, widely differ in the effects of SES indicators on the health outcomes (18–21). Known as Minorities’ Diminished Returns (MDRs)(22, 23), SES indicators tend to generate fewer health outcomes for non-Hispanic Blacks compared to non-Hispanic Whites (24). This literature has shown that particularly educational attainment and income have weaker correlations with health in non-Hispanic Blacks than non-Hispanic Whites (11, 24, 25). Compared to non-Hispanic Whites, non-Hispanic Blacks show education and income gradient in depression(26, 27), smoking(28, 29), number of chronic medical conditions (11), disability(30), hospitalization(31), and mortality (32, 33). Although the same MDRs are also seen for Hispanics (34, 35) (36), Asian Americans(37), Native Americans(38), and even lesbians, gays, and bisexuals (39–41), these patterns are most pronounced for non-Hispanic Black people(22, 42).
While almost all of this literature is on national samples (11, 24, 25), exceptional cases have shown similar patterns in local data in Michigan (43). Thus, there is still a need to study these patterns in other settings such as California, which has different policy set than the average US as well as Michigan (43). This is particularly important because SES indicators show effects that vary across regions (18, 20, 21). Multiple cross-country comparisons have shown that the effects of education and income on populations SRH differ in the United States than other settings (19, 20). Overall, these SES indicators may influence SRH in one but not in another setting (19, 20). As a result, local policymaking requires locally originated information on how to promote health (18, 20, 21). Instead of universal guidelines, policymakers require local data-driven protocols and guidelines that can inform their policies and programs on how to narrow the gap within and between populations (19, 20).
Due to multiple societal mechanisms, SES indicators may generate less outcomes for non-Hispanic Blacks than non-Hispanic Whites (11, 24, 25). The first proposed mechanisms is the labor market discrimination (44). Under labor market discrimination, highly educated Blacks may have a lower chance to secure high quality, low stress, and high paying jobs (45–47). Thus highly educated non-Hispanic Blacks make lower income and are more likely to live under poverty despite high educational level, compared to non-Hispanic Whites with the same education (44, 48, 49). On top of labor market discrimination, interpersonal discrimination is a major risk in the life of highly educated Blacks, because highly educated Blacks are likely to have higher not lower exposure and vulnerability to discrimination (27, 50–52). This is in part because highly educated non-Hispanic Blacks are at a closer proximity to non-Hispanic Whites in their work environment, which means discrimination (39, 50–53). Another mechanism is that even psychological traits and coping that are expected to mediate the effects of educational attainment (e.g. mastery and perceived control) may generate less health effects for non-Hispanic Blacks than non-Hispanic Whites (54–56). Another mechanism is that due to racism, upward social mobility is associated with additional level of stress and psychological tax for non-Hispanic Blacks than non-Hispanic Whites (57–60). Even parental resources also generate less health for non-Hispanic Blacks than non-Hispanic Whites that contribute to trans-generational transmission of poor health and poverty for Blacks, despite their education levels (61–63). Finally, highly educated Black are more likely to remain at behavioral and environmental risk (29, 64–66), which reduces the protective effect of education on health for non-Hispanic Blacks than non-Hispanic Whites (29, 36).
As mentioned above, however, most of this data is derived from studies that are conducted in a national sample. That is, we are still unaware of these patterns at local levels. As states and locations may vary in the resources and how resources can operate (67–69), it is important to conduct local research on whether or not educational attainment, income, and employment generate similar or different health gain for non-Hispanic Blacks than non-Hispanic Whites. The results derived from such studies can potentially inform local policy on the most effective interventions that can equalize health across racial groups, particularly non-Hispanic Blacks and non-Hispanic Whites.
This cross-sectional study used a representative sample of adult residents of California to explore racial variation in the effects of educational attainment and income on SRH. In line with the MDRs literature, we expected weaker effects for non-Hispanic Blacks and non-Hispanic Whites. As we expect MDRs to be related to labor market discrimination and differential availability of jobs in non-Hispanic Black and non-Hispanic White communities, we expected MDRs of education to be partially explained by income (44). That is, one reason education generates less SRH for non-Hispanic Blacks and non-Hispanic Whites is that education generates less income for non-Hispanic Blacks and non-Hispanic Whites.