The competing effects of racial discrimination and racial identity on the predicted number of days incarcerated in the US: A national profile of Black, Latino/Latina, and American Indian/Alaska Native populations

Abstract

Objective Racial discrimination and racial identity may compete to influence incarceration risk. We estimated the predicted days incarcerated in a national US sample of Black, Latino/Latina, and American Indian/Alaska Native (AI/AN) individuals. Methods We used the 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions-III (n = 14,728) to identify individual incarceration history. We used zero-inflated Poisson regression to predict the number of days incarcerated across racial discrimination and racial identity scores. Results Racial discrimination and identity varied between races/ethnicities, such that racial discrimination exposure was highest among Hispanic individuals, while racial identity was highest among Black individuals. Racial discrimination was positively associated with days incarcerated among Black individuals (β = 0.070, p<0.0001) and AI/AN individuals (β = 0.174, p<0.000). Racial identity was negatively associated with days incarcerated among Black individuals (β = -0.147, p<0.0001). The predicted number of days incarcerated was highest among Black individuals (130 days) with high discrimination scores. Conclusion Racial discrimination and racial identity were associated with days incarcerated, and the association varied by racial/ethnic sub-group. Informed by these findings, we suggest that intervention strategies targeting incarceration prevention should be tailored to the unique experiences of racial/ethnic minoritized individuals at the greatest risk. Policies aimed at reversing mass incarceration should consider how carceral systems fit within the wider contexts of historical racism, discrimination, and structural determinants of health.

We are complex beings: comparison of statistical methods to capture and account for intersectionality

“…The limitations of this study include the use of older data and smaller sample sizes of less than 1% in seven of the 16-level categorical predictors used in approach 2. As a newer version of NESARC-III has not yet been collected, coauthors had significant experience analysing this publicly available dataset, [21][22][23][24][25] and variables were collected to represent the four categories of race/ethnicity, poverty level, sexual orientation and disability status, we chose familiarity with the data over a more recent publicly available dataset. These analyses include individual-level variables based on self-identified identity, and do not include systems-level variables, an important extension of intersectionality research.…”