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Racial Arrest Disparities in the USA by Rural-Urban Location and Region

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Abstract

Background

Urban racial arrest disparities are well known. Emerging evidence suggests that rural policing shares similar patterns as urban policing in the USA, but without receiving the same public scrutiny, raising the risk of biased rural policing going unnoticed.

Methods

We estimated adult and adolescent arrest rates and rate ratios (RR) by race, rural-urban status, and US region based on 2016 Uniform Crime Reporting Program arrest and US Census population counts using general estimating equation Poisson regression models with a 4-way interaction between race, region, age group, and urbanicity.

Results

With few exceptions, arrest rates were highest in small towns and rural areas, especially among Black and American Indian populations. Arrest rates differed between US regions with highest rates and racial disparities in the Midwest. For example, arrest rates among Black adults in the rural Midwest were 148.6 arrests [per 1000 population], 95% CI 131.4–168.0, versus 94.4 arrests, 95% CI 77.2–115.4 in the urban Midwest; and versus corresponding rural Midwest arrests among white adults, 32.7 arrests, 95% CI 30.8–34.8, Black versus white rural RR 4.54, 95% CI 4.09–5.04. Racial arrest disparities in the South were lower but still high, e.g., rural South, Black versus White adults, RR 1.86, 95% CI 1.71–2.03.

Conclusions

Rural areas and small towns are potential hotspots of racial arrest disparities across the USA, especially in the Midwest. Approaches to overcoming structural racism in policing must include strategies targeted at rural/small town communities. Our findings underscore the importance of dismantling racist policing in all US communities.

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Acknowledgements

We would like to thank Dr. Jacob Kaplan, PI on the Open ICPSR UCR project, for his helpful input on the UCR arrest data.

Funding

There was no external funding specifically for this study. Carrie Henning-Smith was supported by the NIH National Center for Advancing Translational Sciences, grant UL1TR002494.

Author information

Authors and Affiliations

Authors

Contributions

Patricia I. Jewett: initial study idea; conception and design; download and analysis of data; interpretation and contextualization of the results; article draft and revision; final approval of the manuscript. Ronald E. Gangnon: statistical method supervision; analysis of data and validation; interpretation of the results; article review and revision; final approval of the manuscript. Anna K. Hing, Carrie Henning-Smith, Tongtan Chantarat, and Eunice M. Areba: conception and design; interpretation and contextualization of the results; article review and revision; final approval of the manuscript. Iris W. Borowsky: supervision; conception and design; interpretation and contextualization of the results; article review and revision; final approval of the manuscript.

Corresponding author

Correspondence to Patricia I. Jewett.

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Conflict of Interest

The authors declare no competing interests.

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Supplementary information

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Appendices

Appendix A

Hypothetical example calculation of group-specific population weights based on the number of months with reported data in each agency

Region

State

County

Agency

Number of months reported

Inflation factor

Group: adult White

Group: adult Black

Group: juvenile White

Group: juvenile Black

Actual arrest counts

Inflated arrest counts

Actual arrest counts

Inflated arrest counts

Actual arrest counts

Inflated arrest counts

Actual arrest counts

Inflated arrest counts

1

2

3

A

12

1 (= 12/12)

100

100 (= 100*1)

60

60

20

20

20

20

B

6

2 (= 12/6)

50

100 (= 50*2)

40

80

10

20

7

14

C

7

1.714 (= 12/7)

58

99.429 (= 58*1.714)

50

85.714

11

18.857

22

37.714

D

9

1.333 (= 12/9)

75

100 (= 75*1.333)

50

66.667

13

17.333

10

13.333

E

1

12 (= 12/1)

8

96 (= 8*12)

5

60

2

24

6

72

Actual arrest sum in county

291

 

205

 

56

 

65

 

Inflated arrest sum in county

 

495.429

 

352.381

 

100.190

 

157.048

County population weight

0.587 (= 291/495.429)

0.582

0.559

0.414

  1. The White adult population in state 2, county 3 gets multiplied by 0.587; the Black adult population by 0.582; the White juvenile population by 0.559; and the Black juvenile population by 0.414
  2. The race/age group-specific population weights are applied to the 2016 American Community Survey county population counts before the log-transformation of the county population counts to calculate the offset for the Poisson regression model

Appendix B

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Jewett, P.I., Gangnon, R.E., Hing, A.K. et al. Racial Arrest Disparities in the USA by Rural-Urban Location and Region. J. Racial and Ethnic Health Disparities (2023). https://doi.org/10.1007/s40615-023-01703-5

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