About

The Racial Concentration measures the concentration of White and Black populations in comparison to each other in a county. Individuals from both Hispanic and non-Hispanic ethnicities are included. According to the 2020 U.S. Census, there were 47.5 million Americans who identified as Black (either alone or in combination), accounting for 14.2% of the U.S. population ¹. Throughout the country, there were 104 counties or equivalents where over 50% of the population identified as Black (either alone or in combination): 25 of these were counties in Mississippi, 22 were counties in Georgia, and 11 of them were in Alabama. Whereas, the five least diverse counties in the U.S. with almost 100% White populations were in the states of Kentucky, Nebraska, South Dakota, and West Virginia.

Why is the Racial Concentration important to the Structural Racism and Discrimination (SRD) Index?

Historically discriminatory housing policies such as redlining and exclusionary zoning laws have led to significant racial segregation in the neighborhoods in the U.S., with minoritized racial and ethnic groups disproportionately living in poor neighborhoods ^2,3. For instance, the neighborhoods with a higher concentration of Black population often lack essential resources—such as high-quality housing, access to education, green spaces, and quality healthcare— necessary for avoiding harmful behaviours and following healthy lifestyles, further exacerbating health disparities ^4,5. Studies have also indicated that the concentration of racial minority populations in areas affects their social mobility by restricting access to high-quality public services, job markets, and networks that foster economic advancement in their communities living in these areas ^6,7. Addressing racial segregation, i.e., desegregation or diversifying segregated neighborhoods, is essential for promoting equity and reducing systemic barriers that perpetuate discrimination, leading to social and economic inequities and health disparities. 

What is the expected relation to Structural Racism and Discrimination?

A higher value of racial concentration in a county contributes to the higher value or score of the SRD Index.

How is the Racial Diversity calculated?

Data Source

We obtained data from the IPUMS National Historical Geographic Information System (NHGIS) ⁸. The data is publicly available.

Data

We used the following three variables at the county level.

Variables*	Year	Unit
Total Population by County	1990 | 2000 | 2010 | 2020	Number
Black or African American alone population	1990 | 2000 | 2010 | 2020	Number
White alone population	1990 | 2000 | 2010 | 2020	Number

* Individuals from both Hispanic and non-Hispanic ethnicities are included.

Methodology

We calculated the Racial Concentration using the measure of Index of Concentration at the Extremes (ICE) where the White and Black populations were considered as the dominant/privileged and minority/under-privileged racial groups, respectively ^9,10. Individuals from both Hispanic and non-Hispanic ethnicities are included. We used the following formula:
$$
ICERace = \frac{(White – Black)}{TotPop}
$$

Where:
ICERace: Index of Concentration at the Extremes (ICE) for Race
White: White alone population in a countyWhite: White alone population in a county
Black: Black or African American alone population in a county
TotPop: Total Population in a county

The ICE is designed to reveal the extent to which an area’s (here a county) residents are concentrated into groups at the extremes of dominant race (Whites) and minorty race (Blacks): a value of −1 means that 100% of the population is concentrated in the minority group and a value of 1 means that 100% of the population is concentrated into the most privileged group ^9.

Missing Data

We have 13 counties with no data in 2020, and none for the 2010, 2000, and 1990 years.

References

1. U.S. Census Bureau. (n.d.). County population by characteristics: 2020-2023. U.S. Department of Commerce. Retrieved March 2, 2025, from https://www.census.gov/data/tables/time-series/demo/popest/2020s-counties-detail.html

2. Winling, L. C., & Michney, T. M. (2021). The roots of redlining: academic, governmental, and professional networks in the making of the new deal lending regime. Journal of American History, 108(1), 42-69.

3. Swope, C. B., Hernández, D., & Cushing, L. J. (2022). The relationship of historical redlining with present-day neighborhood environmental and health outcomes: a scoping review and conceptual model. Journal of Urban Health, 99(6), 959-983.

4. Williams, D. R., & Collins, C. (2001). Racial residential segregation: A fundamental cause of racial disparities in health. Public Health Reports, 116(5), 404-416.

5. Schwartz, G. L., Wang, G., Kershaw, K. N., McGowan, C., Kim, M. H., & Hamad, R. (2022). The long shadow of residential racial segregation: Associations between childhood residential segregation trajectories and young adult health among Black US Americans. Health & place, 77, 102904.

6. Massey, D. S., & Denton, N. A. (1993). American apartheid: Segregation and the making of the underclass. Harvard University Press.

7. Sharkey, P. (2013). Stuck in place: Urban neighborhoods and the end of progress toward racial equality. University of Chicago Press.

8. Manson, S., Schroeder, J., Van Riper, D., Knowles, K., Kugler, T., Roberts, F., & Ruggles, S. (2024). IPUMS National Historical Geographic Information System: Version 19.0 [Dataset]. IPUMS.

9. Krieger, N., Waterman, P. D., Spasojevic, J., Li, W., Maduro, G., & Van Wye, G. (2016). Public health monitoring of privilege and deprivation with the index of concentration at the extremes. American journal of public health, 106(2), 256-263.

10. Massey, D. S., & Brodmann, S. (2014). Spheres of influence: The social ecology of racial and class inequality. Russell Sage Foundation.