(Converted as ePoster, See Poster Gallery) Intersectionality at a Macro Level: Challenges Confronting Rural, Majority Black, Southeastern Counties

Background: Intersectionality theory (Crenshaw, 1989) conceptualizes distinct sources of oppression as compounding when individuals experience multiple forms. The theory has been applied primarily to understand the experiences of individuals. Yet forms of oppression are often exerted and experienced at larger levels of the social ecology, such as neighborhood, city, or county. Geographic areas can experience marginalization or oppression due to multiple demographic characteristics, including racial/ethnic composition and location, which raises a question of whether the intersection of multiple forms of geographic area marginalization compounds consequences of oppression. Is there evidence of intersectionality at the macro level? Focusing on three potential sources of geographic area marginalization or oppression: rural status, majority Black population, and US Southeast region, this study investigates potential effects of intersectionality at the county level. We hypothesize that geographic indicators of marginalization or oppression will intersect to compound two potential adverse consequences: unemployment and child poverty.

Methods: The study uses 2015 county level data from all US counites with populations of at least 1,000 people (n = 3,005). Using the FIPS Code, we linked data from multiple sources including the US Census and the Bureau of Labor Statistics. Rural status includes counties with a US Census-designated rural percentage of 50% or greater. Majority Black population includes counties whose Black/African-American population percentage is 50% or greater. Southeast region includes counties in seven US states designated by the US Geological Survey to be in the Southeast region (Alabama, Florida, Georgia, Mississippi, North Carolina, South Carolina, and Tennessee). We conducted bivariate t-tests, to compare the mean unemployment and child poverty rates in counties with each individual source of marginalization to other counties. We then compared counties experiencing all three potential sources of marginalization to other counites. Finally, we assessed three-way interaction effects in multi-level multiple regression models.

Results: All three county characteristics were independently associated with poorer outcomes in rates of unemployment and child poverty. For example, the child poverty rate was 24.9% vs. 21% in rural vs. non-rural counties (t =11.5, p<.01); 42.6% vs. 22.7% in majority Black vs. other counties (t = 21.5, p<01); and 30.4% vs. 21.5% (t = 22.7, p<.01) in counties in Southeastern states vs. other counties. Yet, the mean child poverty rate in rural, majority Black counties in Southeastern states was 44%, which is higher than the mean among counties with any single indicator of marginalization. We found similar patterns for the unemployment rate. Moreover, in multiple regression models, the interaction of rural status, majority Black status, and Southeastern State status also indicated a compounded effect beyond the main effects, supporting the study hypothesis.

Discussion: Intersectionality theory fostered a more complex conceptualization of oppression facing individuals. This study’s findings suggest that intersecting influences of marginalization or oppression may apply at a macro level in addition to the individual level. Greater attention to the various forms of marginalization and oppression affecting geographic areas is warranted, as well as greater attention to the consequences of intersecting and compounding effects of macro-level sources of marginalization and oppression.