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. Author manuscript; available in PMC: 2023 Jul 14.
Published in final edited form as: Stigma Health. 2021 Jan 21;8(2):170–178. doi: 10.1037/sah0000290

Structural-Level Racial-, Sexual Orientation-, and HIV-Related Discrimination and Subsequent Criminal Justice Involvement Among Young, Black, Men Who Have Sex With Men in North Carolina

Morgan M Philbin 1, Timothy W Menza 2, Sara H Legrand 3, Kathryn E Muessig 4, Lisa Hightow-Weidman 5
PMCID: PMC10348694  NIHMSID: NIHMS1672099  PMID: 37456791

Abstract

Multiple aspects of Black young men who have sex with men’s (YMSM) identities cause them to be differentially targeted for arrest and incarceration. However, limited research has explored structural drivers of Black YMSM’ criminal justice involvement, particularly co-occurring forms of discrimination. This article examines the temporal relationship between perceived racial discrimination, perceived sexual orientation discrimination, and community-level HIV discrimination and criminal justice involvement among Black YMSM in North Carolina. The study followed 465 Black YMSM from November 2013 to October 2016 who were recruited for a randomized controlled trial to test an internet-based intervention for Black YMSM living with, and at risk for HIV; participants completed online surveys at baseline, 3, 6, and 12 months. Logistic regression was used to explore the relationship between the three predictors at baseline (i.e., perceived racism and sexual orientation discrimination and community-level HIV discrimination) and criminal justice involvement at follow-up. All three predictor variables were significantly associated with subsequent criminal justice involvement in separate regression models that adjusted for other covariates: HIV discrimination (aOR = 1.06 [1.01–1.11]), perceived sexual orientation discrimination (aOR = 1.12 [1.00–1.27]), and perceived racism (aOR = 1.26 [1.12–1.42]). Perceived racism remained significant in the model with all three predictors (aOR = 1.29 [1.07–1.55]). Racism did not modify the relationship between HIV discrimination and perceived sexual orientation discrimination and criminal justice involvement. This study expands existing research by exploring racism as a structural driver of criminal justice involvement; we subsequently examined whether racism modified the effect of the two other predictors. It also contributes to research on co-occurring discrimination by examining their impact on an underrepresented population.

Keywords: discrimination, socio-structural factors, criminal justice involvement, sexual orientation, HIV-related discrimination

Structural-level racial-, sexual orientation-, and HIV-related discrimination and subsequent criminal justice involvement among young, Black, men who have sex with men in North Carolina

Research on the predictors of criminal justice involvement frequently focuses on individual- and community-level drivers such as race, homelessness, employment, or substance use (Drug Policy Alliance, 2016; Western & Pettit, 2010). Less work, however, has considered the structural drivers of criminal justice involvement, particularly the role of discrimination. Furthermore, despite the fact that approximately 20%−30% of detained adolescents identify as gender- and sexual-minority individuals (Hirschtritt et al., 2018), discrimination-based research on criminal justice involvement has disproportionately focused on race/ethnicity, or men as a disaggregated whole. Such approach overlooks the critical role of sexual orientation discrimination in shaping criminal justice outcomes among sexuality minority youth (Gunn et al., 2018; van Olphen et al., 2009).

This article examines the temporal relationship between criminal justice involvement and intersecting forms of discrimination—perceived racial and sexual orientation discrimination, and HIV discrimination—among Black young men who have sex with men (YMSM) in North Carolina. Discrimination is an important driver of population-level health because it directly influences physical and mental health outcomes (Link & Hatzenbuehler, 2016) and can constrain access to social structures (e.g., education, jobs, and housing) that affect individuals’ health and well-being (Link & Hatzenbuehler, 2016; Mizock et al., 2018). Discrimination occurs across all socioecological levels. In addition, the structural level is inextricably linked with community- and interpersonal- level discrimination, which is then enacted and reinforced through local and cultural values and interpersonal relationships (Hatzenbuehler & Link, 2014). However, the relationship between discrimination and criminal justice involvement remains underexplored.

Background

Individuals with intersecting marginalized identities (e.g., based on age, race, and sexual orientation) are frequently the target of arrest and incarceration, and therefore disproportionately represented in the criminal justice system (Schulz et al., 2006). Research often focuses on single categories of discrimination or disadvantage as if they were discrete. However, to understand the lived realities of these “multiply-marginalized” groups, research must incorporate the compounding nature of intersecting axes of social inequality (Bowleg et al., 2013; Logie et al., 2019; Potter et al., 2019).

Intersectionality theory recognizes the synergistic, mutually constitutive associations between intersecting axes of inequality (Crenshaw, 1991). While intersectionality theory is used across disciplines to examine psychological and inter-personal dynamics of social oppression, researchers have only relatively recently began expanding intersectionality to incorporate structural-level factors. The emergence of “intersectional discrimination” has created novel approaches for examining the additive effect of multiple, overlapping forms of structural oppression (Berger, 2010; Brinkley-Rubinstein, 2015; Logie et al., 2011). Incorporating an intersectional approach allows for a more robust understanding of the relationship between social identities, such as race, gender, and sexual orientation, and structural inequalities. For example, a study by Brinkely-Rubstein (Brinkley-Rubinstein, 2015) among African American men living with HIV and with a history of incarceration, found that the intersection of HIV-, racial-, and incarceration-related discrimination exacerbated negative health outcomes through its impact on participants’ self-esteem and health care-seeking behaviors. Men’s internalization of discrimination, particularly around the perceived dangerousness of African Americans, played a key role in their perceived self-esteem; these assumptions about perceived dangerousness may also be associated with criminal justice engagement (Brinkley-Rubinstein, 2015). Racial discrimination—perceived and structural—can occur at all stages of law enforcement including differential enforcement of being stopped, searched and/or threats of violence by police officers based on the race/ethnicity of the person in question (Brewer et al., 2014; Dunrose et al., 2005). Such work highlights the importance of attending to the interaction of multiple forms of discrimination across socio-ecological levels, and its potential impact on criminal justice involvement.

Identifying how forms of discrimination may intersect across levels of the social-ecological framework (e.g., individual-, interpersonal-, and community-levels) generates important insight into adaptive coping mechanisms, which could be promoted through interpersonal interventions as well as community- and institution-level practices (Logie et al., 2011). A study among Black women living with HIV in Chicago showed how women’s awareness of systemic inequality and the desire to work with others to enact change was associated with maintaining viral suppression (Kelso et al., 2014). Such findings identify the concrete relationships between intersecting forms of discrimination and health outcomes.

Indeed, there has been increasing discussion about the critical importance of incorporating a multi-scalar intersectional perspective into public health programming strategies. As Turan and colleagues assert (Turan et al., 2019; p. 2): “Interventions that deal solely with a single health-related stigma, without considering the co-experience of stigmas, marginalization, and resilience associated with other conditions, identities, or behaviors, are likely to have limited success in reducing health disparities and making lasting improvements in health.” In addition, Turan et al. contend that significant gaps remain in our understanding of the mechanisms and effects of intersectional stigma and discrimination, and call for new analytical approaches and conceptual models (Turan et al., 2019). Of particular concern is further elucidation of common drivers of co-occurring discrimination among under-represented and marginalized populations. There is also a need for systematic measurement of how shifts in one type of discrimination, such as racism, might affect other intersecting dimensions (Turan et al., 2019). In response, this article advances our understanding of the additive impacts of overlapping discrimination by examining discrimination related to a disease (i.e., HIV), sexual orientation, and race; it then explores how these discriminations may affect non-health related outcomes, specifically criminal justice involvement. The article also explores the central role that racism plays in the cumulative effect of overlapping discrimination. Our study findings suggest that interventions specifically targeting racism within the context of overlapping discrimination may produce the most significant shifts compared to interventions that focus on other forms of discrimination.

Such an approach is particularly relevant for exploring how multiple aspects of YMSM’s identities make them disproportionately targeted for arrest and incarceration. As of June 2019, Black men had an imprisonment rate nearly seven times that of White men and two and a half times that of Latino men (BOP Statistics: Inmate Race, n.d.). North Carolina’s incarceration rate is similar to the overall U.S. population, but racial disparities are stark: In 2015 22% of the population was Black, but Black individuals constituted 55% of the prison population (McGuire, 2019). These disparities are particularly stark among youth: As of 2015, Black youth were five times more likely to be incarcerated than their white peers of a similar age (The Sentencing Project, 2017), and in North Carolina, where this study was conducted, Black youth were 7.5 times more likely than white youth to receive jail time (The Sentencing Project, 2017). Sexual minority young adults are nearly three times more likely to report being criminally sanctioned (e.g., stops, arrests, convictions) compared to their heterosexual peers (Himmelstein & Brückner, 2011). In addition, 12.2% of young adults in state facilities self-identify as sexual minority indivdiuals, and 8% identify as MSM (Wilson et al., 2017). These disparities are particularly large for Black MSM: One study found an incarceration incidence of 35% across 1 year of study follow-up (Brewer et al., 2014). Disparities also exist by HIV status. The rate of HIV among prisoners was 5–7 times higher than the general population in 2010 (Centers for Disease Control and Prevention, 2018).

Public health research on criminal justice engagement frequently explores the role of race (Drug Policy Alliance, 2016; Western & Pettit, 2010) while less attention is given to the role of racism. Work on racism and incarceration rarely measures how an individual’s experiences of racism may prospectively influence incarceration: We found only one study that longitudinally explored the relationship between perceived racism among YMSM and criminal justice involvement (Brewer et al., 2014). In contrast, the relationship between perceived racism and mental health (Gibbons & Stock, 2018) and biological outcomes (Chae et al., 2014) is well established. While research demonstrates that sexual orientation-related discrimination can negatively impact health (Link & Hatzenbuehler, 2016), similar gaps exist in the study of sexual orientation-related discrimination and criminal justice involvement. Existing research on sexual minority health frequently predicts criminal justice involvement by using a dichotomous variable of whether somebody identifies as sexual minority (vs. heterosexual). While this may capture a relationship between sexual identity and criminal justice involvement, it fails to explore the complexity of sexual identity-related discrimination. Additionally, while individuals living with HIV are more likely to come into contact with the criminal justice system than HIV-negative individuals, we were unable to find research exploring whether current HIV-related discrimination is associated with future criminal justice engagement.

Understanding the intersectional drivers of incarceration is important for health because cumulative exposure to stressful life events, including incarceration, is associated with poorer health outcomes (Quinn et al., 2016). Arrest and incarceration subsequently constrain people’s access to material goods, employment, housing, and health care (Quinn et al., 2016), which furthers their risk of recidivism. Individuals who hold multiple forms of disadvantaged identities (e.g., race, sexual orientation, gender, HIV status) experience poorer health and greater exposure to multiple forms of discrimination compared to singularly privileged or disadvantaged peers (Grollman, 2012); these multiple forms of discrimination are associated with multiplicatively worse health outcomes compared to single forms of discrimination (Grollman, 2012).

Sexual orientation-related discrimination, HIV-related discrimination, and racism frequently overlap in the lives of Black YMSM and impact their health and well-being. In spite of our understanding that Black YMSM experience these overlapping discrimination, and despite the frequency with which Black YMSM are involved in the criminal justice system, the relationships between these forms of discrimination and criminal justice engagement remain underexplored. In order to help fill this gap in criminal justice research, we examined whether perceived sexual orientation discrimination, perceived racism, and HIV-related discrimination predict future criminal justice involvement among Black YMSM in North Carolina.

Data and Methods

Study Population

Men were included based on their participation in a randomized controlled trial of an internet-based intervention of Black YMSM living with and at risk for HIV (Hightow-Weidman et al., 2019). The intervention provided resources and personalized feedback around HIV and sexually transmitted infections (STIs) prevention and care information, as well as game-based elements and a social-networking platform. Recruitment occurred through local community-based organizations; HIV/STI clinics; college campuses; venues frequented by Black YMSM; and through online ads. This study was approved by the institutional review board (IRB) at [University of North Carolina at Chapel Hill], and men received $50 to complete the baseline survey and $30 for each follow-up survey.

The overall sample included 465 YMSM (ages 18–30) who identified as Black/African American, were assigned male at birth, and resided in North Carolina. Men also had to report at least one of the following in the last 6 months: (a) condomless anal sex with a male partner; (b) anal sex with >3 cisgender male or transgender female partners; (c) exchange of sex for money, gifts, shelter, or drugs; or (d) anal sex while under the influence of drugs or alcohol (i.e., 2 hr before or during sex). Participants completed online surveys at baseline, 3, 6, and 12 months. Follow-up rates were 85% at 3 months, 80% at 3 months, and 78.3% at 12 months. Data were collected from November 2013 to October 2016. This study excluded men with criminal justice involvement at baseline (n = 32) for a final sample of 433 individuals.

Outcome Measure

The outcome of interest was criminal justice involvement. Baseline and follow-up surveys asked participants: “in the last 3 months, have you ever been arrested?” and “in the last 3 months, have you spent any nights in jail/prison?” If a participant answered yes to either of these, they were categorized as having had criminal justice involvement in the past 3 months. Men were included in these analyses if they reported no criminal justice involvement in the past 3 months at baseline.

Predictors of Interest

We assessed socio-demographic information including age, identification with other race/ethnicities (i.e., multiracial, yes/no), relationship status (yes/no), HIV status (positive, negative, unsure/unknown), employment status (yes/no), educational attainment (no high school, high school graduation/General Educational Development (GED), college degree), sexual identity (gay, bisexual, queer/other/questioning, straight), and gender identity (cisgender or transgender). The Center for Epidemiologic Studies Depression Scale (CES-D), a validated 20-item survey, was used to measure depressive symptoms in the prior 2 weeks (Cronbach’s alpha = .90) (Weissman et al., 1977). A score of ≥16 indicated clinically significant depressive symptoms. We used the Medical Outcomes Study Social Support Survey (MOS-SSS) to assess perceived social support (Stewart & Ware, 1992).

We used the 10-item Multiple Discrimination Scale (MDS) to capture perceived discrimination in the past year based on being African-American/Black (MDS-Black) and perceived discrimination based on sexual orientation (MDS-Gay) (Bogart et al., 2011); scores on both scales range from 0–10. Participants responded yes/no to questions about whether they experienced any of 10 different discrimination events related to race or sexual identity. Examples of these include being treated with hostility/coldness by strangers, rejected by a potential sexual/romantic partner, denied a place to live, denied a job, and physically assaulted (Bogart et al., 2011). The same question prompts were used for the race and sexual identity sub-scales (e.g., “Have you been denied a job/lost a job because of your [race/ethnicity]” and “Have you been denied a job/lost a job because you are [insert sexual orientation].” Previous research with MDS-Black and MDS-Gay demonstrates excellent reliability and validity (Bogart et al., 2013), including among samples of racial/ethnic minority MSM (Bogart et al., 2013; Dale et al., 2016). While the MDS measures perceived discrimination, many of its questions assess discrimination related to structural factors (e.g., structural racism can drive somebody’s experience of being treated poorly, losing a job, or being denied a place to live). Cronbach’s alpha for both subscales was .88.

We used Steward et al.’s Experiences with HIV Discrimination (vicarious stigma) subscale, range 0–30, to assess community-based HIV discrimination (Cronbach’s alpha = .88) (Steward et al., 2008). This scale assesses community-level discrimination and can be used among both HIV-negative and HIV-positive individuals. All items begin with the words, “how often have you heard stories about...” with questions including “a healthcare worker not wanting to touch someone because of his/her HIV,” “people being mistreated by hospital workers because of their HIV,” and “people looking differently at those who have HIV.” This scale has been successfully used in samples that include MSM (Sengupta et al., 2010). The MDS assesses direct discrimination that an individual can experience based on their race and sexual orientation (i.e., among participants who are Black and sexual minority); Steward’s vicarious stigma subscale, which is asked of all individuals regardless of their HIV status, captures community-level stigma. Thus, while the MDS is assessing personal experiences with discrimination, the Steward scale includes an individuals’ observation of HIV-related discrimination in addition to personal experience.

Statistical Analyses

We used logistic regression to explore the relationship between perceived racism, perceived sexual orientation discrimination, and HIV discrimination at baseline and any criminal justice involvement at follow-up. Men with previous criminal justice involvement were excluded from the baseline sample because previous involvement is the stronger predictor of subsequent involvement, which could obscure the relationship between discrimination and criminal justice involvement. Excluding these men also allowed us to establish a temporal relationship between discrimination and criminal justice involvement. Men with no criminal justice involvement at baseline (n = 433) were followed to see if they reported any criminal justice involvement at 3-, 6-, or 12 months (the three follow-up periods were collapsed for the purposes of analysis).

We first conducted separate univariable regression models to assess the relationship between each predictor at baseline and any criminal justice involvement at subsequent study waves. These predictors included: (a) perceived racism, (b) perceived sexual orientation discrimination, and (c) HIV-related discrimination. Scores were evaluated as continuous variables, as they lack standardized cutoffs. Thus, the interpretation of the odds ratio (OR) is the change in the probability of reporting criminal justice involvement at follow-up for a one-unit change in the score on the discrimination scale. We then created multivariable models for each predictor that controlled for relevant demographic covariates that were not in the proposed pathway between discrimination at baseline and criminal justice involvement in future waves (i.e., homelessness, substance use, etc.); we also controlled for whether an individual was in the intervention or control group.

The final multivariate model used logistic regression with the same covariates and included all three predictors in one model. Since only perceived racism remained significant in the final, full model, we ran additional post-hoc models to assess whether racism moderated the relationship between HIV or perceived sexual orientation discrimination and criminal justice involvement. Specifically, we explored whether discrimination based on HIV status or sexual orientation played a role in criminal justice involvement among those who experienced racial discrimination above or below the mean. To explore this, we stratified each of the multivariable models for HIV discrimination and perceived sexual orientation discrimination by perceived racism (above or below the mean). We used p < .05 as the threshold for statistical significance. All analyses were conducted using Stata 14.2 (StataCorp., College Station, TX, USA).

Results

The median age was 24, the majority had completed high school or equivalent (66.5%) or a college degree (25.4%), and half earned less than $10,999/year (Table 1). The majority identified as gay (67.7%), and HIV-negative or of unknown status (58.9%). At baseline, two-thirds (66.7%) were currently employed and 20.3% reported homelessness in the past 3 months.

Table 1.

Baseline Study and Demographic Characteristics, Psychosocial Health of Black Young MSM

Total sample
(n = 433); N(%)
Demographic characteristics
Age
 Mean (SD) 24.27 (3.20)
Education
 <High school 35 (8.1)
 High school diploma/GED, some college 288 (66.5)
 College degree or more 110 (25.4)
Income
 ≤$10,999 219 (51.3)
 $11,000–$20,999 82 (19.2)
 $21,000–$30,999 66 (15.5)
 ≥$31,000 60 (14.1)
Arrested/jailed (last 3 months)
32 (6.9)
Health insurance
313 (72.3)
Relationship status
 In a relationship 152 (35.2)
HIV-status
 HIV-positive 178 (41.1)
 HIV-negative 236 (54.5)
 Unknown 19 (4.4)
Sexual identity
 Gay 293 (67.7)
 Bisexual 88 (20.3)
 Queer/others/questioning 44 (10.2)
 Straight 8 (1.9)
Gender identity
 Transgender 12 (2.8)
Currently employed
289 (66.7)
Multiracial/multiethnic
125 (30.1)
Substance use (last 3 months)
 Alcohol 364 (84.3)
 Marijuana 261 (60.2)
 Powder cocaine 37 (8.5)
Homeless (last 3 months)
88 (20.3)
Depressive symptoms (last 3 months)
227 (49.6)
Social support (standardized score)
 Mean (SD) [range 1–5] 3.91 (1.1)
Perceived sexual orientation discrimination
 Mean (SD) [range 0–10] 2.29 (2.8)
Perceived racism
 Mean (SD) [range 0-10] 2.12 (2.6)
HIV discrimination
 Mean (SD) [range 0-30] 10.08 (7.4)
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At baseline, approximately 7% reported arrest or incarceration (i.e., criminal justice involvement) in the previous 3 months and were therefore excluded from analyses for a final sample of 433 individuals. A total of 51 men experienced any criminal justice involvement over the year of follow-up (11.6%). The MDS perceived racism scale mean was 2.12 (range 0–10) while the perceived sexual orientation discrimination mean was 2.29 (range 0–10). Other studies among MSM of color reported mean racism scores ranging 1.18–1.50 and mean perceived sexual orientation scores ranging 1.0–1.5 (Bogart et al., 2013; Dale et al., 2016), which are lower than the mean of the men in this study. The mean for the perceived HIV discrimination scale was 10.08 (range 0–30). While this scale has not been normed for this population, our mean was higher than other populations with whom this scale has been used (e.g., 8.2) (Steward et al., 2008).

Univariable and Multivariable Models: Predictor-Specific Models

Table 2 presents the unadjusted bivariate analyses and adjusted multivariate analyses for each of the three predictor variables in separate regression models. All three predictor variables were significantly associated with criminal justice involvement in both unadjusted and adjusted models with the following odds: HIV discrimination (aOR = 1.06; 95% CI = 1.01–1.11), perceived sexual orientation discrimination (aOR = 1.12; 95% CI = 1.00–1.27), and perceived racism (aOR = 1.26; 95% CI = 1.12–1.42).

Table 2.

Separate Models of the Unadjusted and Adjusted Analyses of Predictor Variables at Baseline and Criminal Justice Involvement at Follow-Up Among Black Young MSM, 2013–2016

Unadjusted bivariate analyses
Odds ratio (OR) 95% CI P value
Model 1: HIV discrimination 2.08 1.00–1.09 .04*
Model 2: Perceived sexual orientation discrimination 1.12 1.02–1.23 .02*
Model 3: Perceived racism 1.17 1.05–1.30 <.01*
Adjusted multivariable analyses%
Adjusted odds ratio (aOR) 95% CI P value
Model 1: HIV discrimination 1.06 1.01–1.11 .01*
Model 2: Perceived sexual orientation discrimination 1.12 1.00–1.27 <.05*
Model 3: Perceived racism 1.26 1.12–1.42 <.001*
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Note:

%

Each of these three models controlled for age, multiracial, HIV status, relationship status, intervention group, employment, education, gender identity (transgender vs. cisgender), and sexual orientation.

*

Significant.

+

Though presented side by side in this table the analyses for HIV discrimination, perceived racism and sexual orientation stigma represent separate models.

Multivariable Model: Full Model

The final, full multivariable model included all three predictor variables in addition to the control variables (Table 3). In this model, only experiencing perceived racial discrimination in the past year remained significantly associated with criminal justice involvement at follow-up (aOR = 1.29; 95% CI = 1.07–1.55). To explore whether perceived racism modified the relationship between the other two predictors (i.e., HIV discrimination and perceived sexual orientation discrimination) and criminal justice involvement we then stratified perceived racism at the mean (Table 4). The associations between HIV discrimination and perceived sexual orientation discrimination and criminal justice involvement did not differ by level of perceived racial discrimination (i.e., above and below the mean).

Table 3.

Adjusted Analyses With All Three Baseline Predictors in One Model and Their Relationship With Criminal Justice Involvement at Follow-Up Among Black Young MSM, 2013–2016

Adjusted multivariable analyses with all predictors in one model%
Odds ratio (OR) 95% CI P value
HIV discrimination 1.03 0.99–1.09 .16
Perceived sexual orientation discrimination 0.92 0.76–1.11 .40
Perceived racism 1.29 1.07–1.55 <.01*
Age 0.84 0.73–0.98 .02*
Multiracial 1.57 0.78–3.15 .21
Living with HIV 0.55 0.30–1.02 .06
Currently single 3.18 1.58–6.39 .01*
Employed 0.55 0.25–1.20 .14
Less than college degree 1.26 0.56–2.75 .56
Transgender 1.69 0.27–10.44 .58
Sexual orientation
 Gay (ref) 1.00 — —
 Bisexual 0.55 0.20–1.55 .26
 Queer/questioning/others 0.46 0.11–2.00 .30
 Straight 1.64 0.19–2.0 .66
Intervention group 0.75 0.38–1.50 .42
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Note:

%

Each of these three models controlled for age, multiracial, HIV status, relationship status, intervention group, employment, education, gender identity (transgender vs. cisgender), and sexual orientation.

*

Significant.

Table 4.

Analyses of Separate Models+ for HIV Discrimination and Perceived Sexual Orientation Discrimination at Baseline—stratified by High and Low Perceived Racism—and Criminal Justice Involvement at Follow-up Among Black Young MSM, 2013–2016

Below mean racism score%
Odds ratio (OR) 95% CI P value
Model 1: HIV discrimination 1.07 0.97–1.19 .16
Model 2: Perceived sexual orientation discrimination 1.02 0.63–1.65 .92
Above mean racism score%
Adjusted odds ratio (aOR) 95% CI P value
Model 1: HIV discrimination 1.07 0.91–1.25 .41
Model 2: Perceived sexual orientation discrimination 1.03 0.97–1.10 .29
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Note:

%

Each of these three models controlled for age, multiracial, HIV status, relationship status, intervention group, employment, education, gender identity (transgender vs. cisgender), and sexual orientation.

+

Though presented side by side in this table the analyses for HIV discrimination and sexual orientation stigma represent separate models.

Discussion

Previous research has explored how perceived racism, perceived sexual orientation discrimination, and HIV-related discrimination influence health outcomes, but work has yet to examine their potential associations with criminal justice involvement. In addition, criminal justice-focused debates frequently focus on race (vs. racism), and pay less attention to other aspects of individuals’ lives that may also be particularly salient (e.g., discrimination associated with HIV status or sexual orientation). The high rates of incarceration among Black men, particularly Black YMSM, must be examined within the broader social-structural context. The men in our sample reported much higher experiences of perceived racism and perceived sexual orientation related discrimination compared to other demographically similar samples (i.e., among racial/ethnic minority MSM in the U.S.) (Bogart et al., 2013; Dale et al., 2016). This may be due to the fact that this research occurred in the southern U.S. where rates of racism and homophobia are much higher than in other parts of the country; HIV-related discrimination was also higher than in other samples (Fletcher et al., 2016).

Our analysis found a temporal association between past year racism experiences and Black YMSM’s subsequent involvement with the criminal justice system. Perceived racism’ s significance in the final model indicates that racism acts independently of other forms of discrimination (and other covariates in the model) in predicting criminal justice involvement. This work expands existing research on racism as a structural driver of health and behavioral outcomes. Previous work has identified racism as one of the most important drivers of health disparities in the U.S. (Bastos et al., 2014; Gibbons & Stock, 2018) but, aside from a few notable exceptions (Brewer et al., 2014; Taylor et al., 2018), little work exists on the relationship between perceived racism and criminal justice involvement. Instead, the majority of research has examined either the relationship between race/ethnicity and criminal justice involvement (Bland et al., 2012; Schulz et al., 2006) or racism and health (Bastos et al., 2014; Gibbons & Stock, 2018). Our findings suggest that addressing the effects of perceived racism, along with activities targeted at one or more other forms of discrimination, should be a key component in interventions that address overlapping forms of discrimination. Structural-level interventions should also address the drivers of the racism, sexual orientation, and HIV-related discrimination faced by the men in this study. Further research is needed to identify which other types of discrimination are best addressed in tandem with perceived racism to target criminal justice involvement as well as health-related outcomes.

Existing research on race-related discrimination suggests its association with criminal justice involvement may be due to youths’ internalization of dominant racial stereotypes that can lead to hopelessness regarding future trajectories (i.e., the inevitability of incarceration as part of their future trajectory) (Brinkley-Rubinstein et al., 2014) and the overall normalization of criminal justice engagement (Taylor et al., 2018). This is particularly salient for youth as early engagement with the criminal justice system can severely affect their developmental and life course trajectories (Taylor et al., 2018). Research on intersectional forms of discrimination suggests that internalization can manifest as feelings of disempowerment, a perceived diminished social status, hopelessness, lack of vigor, and lessened control of future trajectories, all which can affect individuals’ ability and desire to cope with obstacles, whether pre- or post-incarceration (Brinkley-Rubinstein, 2015). We identified one longitudinal study that explored perceived racism and subsequent criminal justice involvement, (Brewer et al., 2014) which found a significant relationship. A cross-sectional study found that Black men with previous criminal justice involvement reported more types of, and more frequent, discrimination than Black men without criminal justice involvement (Taylor et al., 2018). Research among previously incarcerated Black men found that half reported multiple forms of discrimination, most commonly for being formerly incarcerated, their race/ethnicity and, for 10%, their HIV status (LeBel, 2012).

The research linking racism and health also provides some suggestions about the pathways through which perceived racism might be associated with criminal justice involvement. Racism is related to stress and poorer mental health outcomes, both of which are related to criminal justice involvement (Paradies et al., 2015). Racism is also associated with stress-related behaviors such as substance use (Clark, 2014) which may be particularly relevant because men of color are disproportionately arrested and incarcerated for low-level drug crimes; they also face harsher sentencing policies for low-level drug offenses (Drug Policy Alliance, 2016). Lastly, racism drives structural-level factors such as segregation and unequal access to wealth, employment, and education options (Paradies et al., 2015) which, in turn, influence mortality rates (Lukachko et al., 2014) and subsequent violent crime (Sampson, 1987). These potential pathways also identify targets for future research in order to help explain the relationships identified in this study.

Similar to racism, research on sexual orientation-related discrimination has demonstrated its impact on biological (Link & Hatzenbuehler, 2016), mental health (Link & Hatzenbuehler, 2016), and substance use outcomes (Hatzenbuehler et al., 2015). Research has yet to explore sexual orientation discrimination’s association with criminal justice involvement, but does show how factors related to sexual orientation might influence such involvement—particularly through pathways like community-level discrimination and social disadvantage including YMSM being kicked out of their homes and lack of employment opportunities. Sexual orientation discrimination and marginalization can lead to substance use (Hatzenbuehler et al., 2015) and survival sex which, in turn, are associated with criminal justice involvement (Philbin et al., 2018); sexual orientation discrimination can also limit social engagement in community organizations and peer groups which facilitates healthy adolescent development (Meyer, 2003).

While research has not directly examined the relationship between perceived HIV discrimination and incarceration, HIV-related discrimination negatively impacts post-incarceration re-integration (Brinkley-Rubinstein, 2015). In addition, HIV-related discrimination is a barrier to HIV prevention, testing, treatment, and viral suppression (Turan et al., 2019). Other co-existing forms of discrimination (e.g., related to race and sexual orientation) may intersect to worsen the effects of HIV-related discrimination (Earnshaw et al., 2015) and exacerbate existing disparities in HIV prevention and treatment (Logie et al., 2019).

These relationships between discrimination and racism are also cyclical. Individuals who experience discrimination may have more contact with the criminal justice system and, once incarcerated, cycles of poverty, substance use, and stress are often exacerbated, which reinforces stigma and discrimination (Meyer et al., 2017). Youth who have been stopped or apprehended by police are also more likely to have subsequent police encounters compared to peers with no history of apprehension or arrest (Meyer et al., 2017). Youth stopped more frequently by police were more likely to report symptoms of post-traumatic stress and emotional distress (Jackson et al., 2019), which was commonly linked to feelings of stigma. In addition, incarcerated youth have higher rates of HIV-related risk behaviors and substance use than non-jailed peers, and have constrained access to adequate health care (Golzari et al., 2006). Long-term effects of incarceration on youths’ functioning later in life have also been well-documented, including increased recidivism, and increased difficulties securing employment, housing, and student and business loans (Denver et al., 2017). Marginalization can also limit individuals’ willingness to engage in supportive services such as job training, education, and health care, which could facilitate their ability to achieve increased stability (Western et al., 2015).

Directions for Future Work

While this research suggests that perceived sexual orientation discrimination, perceived racism, and perceived HIV discrimination are important predictors of criminal justice involvement, it is important to examine the mechanisms that drive these relationships. We did not include factors such as substance use and mental health in these models because they are on the proposed pathways, and future work could test them as potential mediators between the three predictors and criminal justice involvement. This should be done for each predictor, and through an intersectional lens, to identify potential intervention targets. There was also a relatively high correlation between perceived sexual orientation discrimination and racism among the men in our sample (.60) suggesting potential overlap in how these operate, a topic that future research should also explore; we computed the variance inflation factor (VIF) and tolerance (1/VIF) for each of the three predictors included in the final model to assess for collinearity. All tolerance values were greater than .1, indicating that each predictor was unlikely to be a linear combination of the others (Farrar & Glauber, 1967). This research should also be expanded to Black YMSM in other states beyond North Carolina to see if this relationship differs by geographic location—particularly given work suggesting that states’ political and racial composition influence incarceration rates (Percival, 2010). Finally, research may wish to explore the relationships between these forms of discrimination in other groups, such as sexual minority Black women, Black transgender women, and other YMSM of color.

Strengths and Limitations

This article has numerous strengths. First, the longitudinal design offers more validity for assessing causality. Second, the survey was completed on-line to minimize bias in the reporting of sensitive information, had a relatively large sample size and excellent follow-up rates (e.g., 78.3% at 12 months) (Hightow-Weidman et al., 2019). There are also some limitations. The research was conducted in North Carolina where experiences with racism, sexual orientation discrimination and HIV discrimination may differ from other regions. This was conducted as a secondary analysis of an internet-based intervention whose inclusion criteria included specific risk behaviors in the past 6 months (e.g., condomless anal sex or sex for drugs or money) which may limit the generalizability to the general population of Black YMSM—however, while the prevalence of criminal justice involvement may not be representative, we believe the relationship between perceived racism and criminal justice engagement remains relevant to a larger population of Black YMSM. We did not assess lifetime criminal justice involvement, so men who reported no criminal justice involvement at baseline may have had previous involvement; the most marginalized individuals with heavy criminal justice involvement might not have been recruited into the study. We also did not ask about reasons for arrest/incarceration so could not explore the mechanisms through which these predictors might influence criminal justice involvement.

Public Health Implications

Researchers have argued that racism is one of the most salient drivers of health disparities in the U.S. (Gibbons & Stock, 2018; Paradies et al., 2015). Research on the predictors of criminal justice involvement often occurs at the individual- or interpersonal-level, while the structural drivers receive less attention. This article helps fill that gap by demonstrating a relationship between perceived sexual orientation discrimination, perceived racism, and HIV discrimination and criminal justice involvement; we also found that perceived racism remained significant even when all factors were combined in one model. It is important to continue to explore how structural-level factors influence criminal justice involvement—and the mechanisms through which this occurs—in order to develop interventions and facilitate policy change to address these drivers of incarceration, and population-level health disparities more broadly, among marginalized populations.

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