Our study contributes to the literature on neighborhoods and health and on race and health by constructing a dynamic, racial residential history typology and examining its association with adult self-rated health and mortality among black and white adults in the U.S. Our typology describes census tract changes in racial composition between 1970 and 1990, and characterizes neighborhoods as: established black, black transition, black entry, established interracial, or white. Applying this typology extends prior research on racial residential segregation and health by focusing on a smaller level of geography—the neighborhood—and by examining neighborhood racial context as dynamic rather than static.
We first note that our results show that the black disadvantage in self-rated health is no longer statistically significant after considering racial residential history. The types of neighborhoods that people live in help explain racial disparities in self-rated health. However, black disadvantage in mortality remained even after controlling for both racial residential history and neighborhood poverty, and the risk even increased slightly. Further controls for individual SES eliminated the race disparities in mortality. Black adults have worse mortality risk no matter where they live, with neighborhood residence more strongly associated with self-rated health than with mortality. Racial disparities in mortality are explained primarily by a combination of both individual SES and neighborhood socioeconomic context.
Our examination of the racial residential history typology and its associations with self-rated health and mortality demonstrates interesting but complex results. We expected that residents in both established black and black transitioning neighborhoods would have worse self-rated health and mortality risk (compared to residents of white neighborhoods), but found mixed results. Living in black transitioning neighborhoods (compared to white neighborhoods) was not associated with either self-rated health or mortality risk, which may be due to the small number of respondents living in this type of neighborhood (n=83). However, living in an established black neighborhood was associated with worse self-rated health (compared to living in a white neighborhood), but not after further controlling for neighborhood poverty. Although we cannot examine causal processes here, these latter results are consistent with an interpretation that living in an established black neighborhood may be associated with poor self-rated health through its impact on neighborhood poverty context as a more proximate determinant of access to material and social resources that affect health (Acevedo-Garcia, et al. 2003
; Collins and Williams 1999
; LaViest 1993
; Polednak 1993
; Schultz et al., 2002
; Williams 1997
In contrast, and contrary to our hypotheses, living in an established black neighborhood was associated with lower
mortality after controlling for neighborhood poverty or for both neighborhood poverty and individual SES. If this represents a true relationship, it would be consistent with a small literature that suggests that living in ethnic enclaves, and/or among people of the same race/ethnicity is protective of health (Fang et al. 1998
; Smaje 1995
). After controlling for the detrimental effects of living in lower SES neighborhoods, there may be a suppressed positive effect that emerges due to potential protective effects of living in an ethnic enclave. However, since we did not find this same association for self-rated health, we are hesitant to over-interpret this finding. Moreover, our data do not allow us to establish whether this effect holds for both black and white residents of established black neighborhoods.
An unexpected finding was that residents of established interracial neighborhoods had both better self-rated health and lower mortality risk, compared to the residents of white neighborhoods, after controlling for both individual and neighborhood SES. There may be some added value to health for those residing in a diverse neighborhood (Ellen 2000
). Again, we cannot account for the role of selection effects and other causal processes, but clearly examining whether diverse neighborhoods provide unique material or social resources to promote health should be explored further.
Finally, our analyses confirm that neighborhood poverty level is strongly associated with both self-rated health and mortality, and that neighborhood poverty is a more consistent predictor of self-rated health and mortality than is our racial residential history typology. These results are consistent with previous research using more static measures of racial segregation (Cagney, Browning, and Wen 2005
; LeClere et al. 1998
; Robert and Ruel 2006
; Robert 1998
; Subramanian et al. 2005
). It remains difficult to examine the reciprocal and overlapping effects of neighborhood racial and socioeconomic characteristics, selection effects of people into and out of neighborhoods based on race, SES, and other characteristics, and causal processes from neighborhood racial and socioeconomic contexts to individual socioeconomic and health outcomes. Much additional work is needed to tease out these causal processes.
One advantage of using the ACL data for this study is that we had access to geographic identifiers that we could match to three decades of census data to examine neighborhood change over time. However, a limitation is that the ACL sample was a national probability sample that was not designed to take representative samples from each neighborhood, so we do not have a large number of respondents within each census tract. Future work needs to replicate these analyses using larger national datasets with more individuals sampled within each census tract, or using a local sample of a large number of people within each of multiple neighborhoods.
There are three main caveats regarding our racial residential history typology. First, we began the analysis using a cutoff of 250 blacks as the basis for splitting white and black neighborhoods, following the procedures used by Duncan and Duncan (1957)
and Taeuber and Taeuber (1965)
for their analyses of 1940–1950 and 1950–1960 changes. It could be argued that basing the split on the relative distribution of blacks rather than the absolute numbers might be preferable. Fortunately, census tracts tend to average about 4,000 persons (ranging from 2,500 to 8,000), thus using an absolute number both makes our results somewhat comparable across census tracts and allows us to use a typology that replicates earlier work. As demonstrates, there are clear differences in the racial distribution within each neighborhood type, suggesting this procedure produced little or no misclassification bias. A second issue is that census tracts have increased in size over time and perhaps 250 is too limiting a number for an analysis from 1970 to 1990. In analyses not shown, we replicated the typology using 500 blacks as the basis for the cut. Doing this simply increases the number of white tracts at the expense of black tracts, thus we stayed with 250 blacks as the cutoff between white and black neighborhoods.
A third issue is that we eliminated all tracts with more than 250 residents that are neither black nor white, which means we primarily eliminated heavily Hispanic neighborhoods (see earlier note 1). Clearly, theory and research each needs to better account for these neighborhood changes, such as adding multiracial neighborhoods, and various neighborhood types that are transitioning from one racial minority to another racial minority (Frey and Farley 1996
; South, Crowder and Chavez 2005
). We did not address these important issues in this study because we were limited in the racial/ethnic diversity of the ACL sample, and because we wanted to be able to compare our neighborhood typology to results of prior work focusing on black and white people and neighborhoods.
The typology framework needs to be expanded, refined, and tested. Beyond including different types of neighborhood transitions by race/ethnicity, future typologies could simultaneously incorporate socioeconomic transitions of neighborhoods. The distribution of our data did not allow us to examine this. Moreover, although our research looked at how neighborhoods
transition, we did not attend to how individuals
transition between neighborhoods. A growing literature on residential mobility and racial residential segregation (South and Crowder 1998
), including some that focuses on agent-based dynamic processes (Bruch and Mare 2003
; Clark 1991
), would be interesting to integrate into studies on health outcomes.
In order to understand the complex processes that lead to and perpetuate racial disparities in health, future research must also attend to social and economic processes in rural areas. Since studies such as this one that focus on racial segregation include only urban/suburban areas, the large racial disparities in health that exist in rural areas get ignored (Robert and Ruel 2006
), and the processes creating and maintaining them remain understudied.
This study demonstrated that when examining the impact of neighborhood racial context on health, research needs to go beyond examining neighborhoods as static entities. We demonstrate that understanding the dynamic nature of neighborhoods over time may contribute to our understanding of how neighborhood context contributes to health, and specifically, to racial disparities in health in the U.S.