Racial Segregation, Income Inequality, and Mortality in US Metropolitan Areas

Our findings support previous research showing a protective effect of income inequality on mortality once % black is accounted for. We also found a protective effect of income inequality prior to adjusting for % black, which may have to do with the dynamics between income inequality and mortality in areas with a higher density of blacks. We included only those MSAs that were at least 10% black. Our study sample was 72% white. The increase in income inequality in the United States largely reflects income inequalities between affluent whites and poor blacks. Therefore, findings for the full sample may reflect the net gain in health experienced by affluent whites.

Consistent with other literature, there was a significant positive association between both % black and black racial segregation and mortality.16 Hispanic segregation and % Hispanic, on the other hand, showed an inverse association with mortality rates, consistent with previous evidence demonstrating the protective effects of social support and coethnic ties among Hispanics.30 ^, 41‐45

The results show that racial segregation modifies the income inequality/mortality association. In the full sample, the inverse association between income inequality and mortality was greater in MSAs with higher versus lower levels of black racial segregation. The same was found among whites. Among blacks, there was a positive association between income inequality and mortality prior to the inclusion of the interaction term, after which the same graded inverse association between income inequality and mortality was found with increasing levels of black racial segregation. The strength of the inverse association, however, differed greatly between the 2 groups. Compared to the full sample, the protective effect of income inequality by levels of racial segregation was attenuated by roughly 25% among whites and 90% among blacks, suggesting that the harmful effects of racial segregation are more pronounced among blacks than among whites. In their study of 107 US cities with at least 10% black population, Collins and Williams also found the harmful effects of racial segregation on health to be greater among blacks than among whites.36

Metropolitan areas with the highest % of blacks and the highest degree of black–white racial residential segregation have the smallest ratio of city-to-suburban jobs per person, city family median income to suburban family median income, city to suburban total housing units, and suburban to city unemployment.21 Importantly, racial segregation has been positively associated with higher poverty and lower status occupations among blacks though not among whites, suggesting that racial segregation may concentrate social and material disadvantage, particularly among blacks.36 ^, 46 ^, 47 Racially segregated areas, particularly lower income areas, have been associated with lower quality schools, fewer employment and economic opportunities, exposure to crime, substandard housing, exposure to toxins and pollutants, and isolation from broader social networks,48 ^, 49 all of which have been associated with poorer health. We found a positive association between black–white racial segregation and mortality in the full sample and in race-specific models showing that racial segregation is independently associated with poorer health for all groups.

The protective effect of income inequality in areas with higher versus lower levels of racial segregation may reflect the protective effects of racial segregation. Previous work shows that black racially segregated areas have higher levels of black political empowerment and better investment in municipal services such as sewage, fire, and street services and social services such as social welfare, health, and protective services.35 ^, 48 Racial segregation has also been associated with higher levels of group social cohesion,50 which in turn is inversely associated with mortality.3

Although income inequality concentrates poverty among blacks and results in lower resource communities for both middle- and upper-income blacks, the protective effects of income inequality among blacks in areas with higher versus lower levels of black–white racial segregation are likely a reflection of high levels of social cohesion. Evidence suggests that the congruence of living around similar others is protective of health. One study found a significant positive gradient relation between income incongruence and mortality with higher mortality rates among low-income persons living in higher versus lower income neighborhoods.51 These findings suggest that the material disadvantages associated with low-income areas may be outweighed by the social advantages associated with social cohesion, collective efficacy, and group solidarity.30 ^, 41 ^, 42 ^, 50 Similarly, the stigma associated with being in the minority may confer health risks that outweigh the material advantages of higher income neighborhoods. Further research is needed to better understand the dynamics between risk factors and resilience factors in predicting mortality among blacks.

The protective effects of income inequality among whites may reflect more affluent living conditions due to the concentration of affluence among whites. MSAs with high levels of concentrated affluence and poverty also have high levels of black–white racial segregation,21 and increasing income inequality is associated with the concentration of poverty and affluence for blacks and whites, respectively.

Hispanic racial segregation also modifies the income inequality/mortality relation. There was a significant positive income inequality/mortality association in areas with higher versus lower levels of Hispanic racial segregation. This may also have to do with the concentration of poverty. However, previous work indicates that the protective effects of group density may outweigh the negative impact of low social status. Our sample of MSAs had an average of 5% Hispanics. Further research with a higher percentage of Hispanics is needed to better understand the factors associated with this finding.

Several factors should be considered in interpreting the study results. This cross-sectional ecological study does not draw causal inferences but rather highlights some of the place-level factors relevant for understanding racial differences in the income inequality/mortality relation. We examined 107 US metropolitan areas with a population of at least 100,000 and at least 10% black. Our findings are, therefore, representative of those MSAs. Further research is needed to distinguish between the dynamics of income inequality and racial segregation in areas with a lower versus higher density of blacks.

We chose the Dx as our measure of segregation. The Dx has many strengths including its common usage, which makes the results of our study comparable to many others. The Dx is also easy to compute, especially when comparing the distribution of 2 groups. When the number of groups exceeds 2, which would be the case when examining segregation between multiple ethnic groups, other measures of segregation, such as the Theil Index, the Multiethnic Entropy Index, and White's Index of Spatial Proximity, have been found to be less cumbersome and less prone to error.38 ^, 52‐55 Our results likely underestimate the degree of black and Hispanic racial segregation, possibly resulting in more conservative associations. We estimated the segregation of blacks and Hispanics from whites, which does not account for their segregation from other groups. Blacks are the most racially segregated group in the United States, followed by Hispanics.31 ^, 56 Whereas some studies suggest that black racial segregation is lower in areas with high multiethnic concentrations, that may depend on the degree of black racial concentration and clustering.31 ^, 54 ^, 57 ^, 58 Understanding how the levels of racial segregation for blacks change when looking at segregation from, or level of interaction with, other groups, versus whites alone—and how much of the association between racial segregation and mortality is attributable to the segregation of blacks from whites versus blacks from non-blacks—would inform the types of strategies most useful for improving health, and perhaps give a more accurate assessment of the degree of black racial segregation.53 For Hispanics, one might consider the difference between Mexican versus non-Mexican, Puerto Rican versus non-Puerto Rican, etc., rather than combining these distinct ethnicities into one panethnicity. We did not have access to data at that level of specificity. However, a multiethnic framework including consideration of other racial minority groups is warranted given the increasing levels of racial and ethnic diversity in the United States. Additionally, accounting for the multidimensional nature of racial segregation would be helpful in this regard.

We used the Gini to measure income inequality. One of the limitations of the Gini is that it is not sensitive to spatial redistributions of income among areas either above or below the proportionate distribution of income across areal units, commonly referred to as the transfer principle.38 ^, 52 The Gini also is not sensitive to the shape of the income distribution and is therefore not able to distinguish between 2 MSAs with the same value of income inequality but different income distributions. Despite these limitations, the Gini is highly correlated with other measures of income inequality and is similar to other measures in its association with mortality.3 Finally, income inequality and racial segregation data are from 1990. Mortality data are also from the 1990s. Importantly, levels of income inequality59 and racial segregation32 remained relatively stable for the time period 1990 to 2000, and black–white differences in mortality did not change appreciably during the 1990–2000 time period.60 Future studies examining the stability of these associations over time are warranted.

To our knowledge, this is only the second study to examine explicitly the role of racial residential segregation in the income inequality/mortality relationship,16 and the first to examine the potential moderating role of racial segregation, and to examine these associations in a sample of MSAs with a higher concentration of blacks (i.e., ≥10%). Previous work shows that the income inequality/mortality relation varies with the degree of black racial concentration. In their study of US counties, McLaughlin and Stokes found a positive income inequality/mortality association in areas with a low concentration of blacks.19 As % black increased, the nature of the relationship between income inequality and mortality changed such that higher inequality was associated with lower mortality, consistent with our study findings. Our finding of a positive association between black racial segregation and mortality and of an inverse income inequality/mortality association by degree of racial segregation may reflect dynamics unique to geographic areas with a higher concentration of blacks. It is curious that region of the country was more relevant in the full sample than in either of the race-specific groups, given both the historical and contemporary differences between regions both in levels of racial segregation and mortality. It is possible that mortality differences by region are more related to the cultural aspects of place than to cultural and other differences between racial groups in those places. Other outcomes have similarly shown strong regional variations that cut across racial groups.61 Future research is needed to further explore these associations.

Given the mixed evidence, there continues to be some debate about whether studying the health effects of income inequality is a worthwhile pursuit. However, some of that uncertainty may be related to the omission of important variables such as racial segregation that modify associations differently for different groups. Mixed methods approaches may help in further exploring the social realities of racial segregation for different groups. Qualitative methods such as focus groups and key informant interviews, as well as area-based audits capturing the social, economic, and physical trends of places over time, would be particularly illuminating. Additionally, examination of cause-specific morbidities and mortalities may help inform the mechanisms through which income inequality impacts health differently for different racial groups. Understanding the dynamics of income inequality, racial segregation, and mortality for other groups, particularly Hispanic groups given their growing representation in the US population, would also inform the ways in which these associations vary across groups. Another important direction for future research is examining the interaction between racial segregation and socioeconomic status (SES) among minority group members. Specifically, whether SES modifies the association of racial segregation and mortality among minority group members and whether that interaction modifies the association between income inequality and mortality.

In summary, our finding that racial segregation does not operate the same across groups highlights the social aspects of place that matter over and above material resources and calls attention to the need to further examine both the social and economic correlates of racial segregation and how those factors affect groups differently.