Black men are disproportionately impacted by incarceration in the United States.1–6 Of the estimated 2 million men and women who are currently incarcerated, more than 40% are black men.7 Stratifying by gender, black men represent more than 60% of the male prison population; yet, they comprise just 13% of the US male population.7,8 Even more striking is the observed racial disparity for young men aged between 18 and 24 years. Black men in this age group are only 2.6 times more likely to be in college than in prison compared with white men who are 28 times more likely to be in college than in prison—a nearly 10-fold difference between the 2 groups.7
The mass incarceration of black men in the United States has been described as a contributor to the burden of HIV in black communities.6 Incarceration concentrates individuals at high risk for substance abuse, mental illness, and infectious diseases such as HIV.9 The social inequality produced by mass incarceration is also invisible, cumulative, and intergenerational.10 Incarceration adversely affects employment, housing, and access to care for ex-offenders.10,11 Upon release, bans on welfare, public housing, educational aid, employment, and voting make it virtually impossible for ex-offenders to have a real chance at life, almost guaranteeing recidivism.7 The mass incarceration of black men damages broader social norms in several ways.12 It disrupts family life and pushes children into foster care.9 It damages networks by removing fathers, brothers, and other male figures from a web of mutually supportive family and community relationships.12 In addition, the absence of black men has a strong impact on the adolescent boys who are left behind. It creates conditions where incarceration becomes a community norm or “rite of passage” for young black boys.6 It also creates a sense of contempt toward law enforcement against who become regarded as an oppressive force in the community rather than partners in protecting the safety and well being of the community.12 Finally, it affects sexual norms and sexual behaviors, resulting in concurrent partnerships (based on insecurity about the stability of monogamous relationships) and risky sexual practices.6,13
Race and education are directly associated with incarceration risk in the United States. For example, 1 in every 15 adult (aged at least 18 years) black men is currently incarcerated compared with 1 in every 106 white adult men.1 In addition, more than one third of black men aged 20–34 years in 2008 who had dropped out of high school were also in prison.10 Therefore, the probability that a black man will go to prison is increased 3-fold if he is a high school dropout.7
Little is known about the specific predictors of new incarceration among black men who have sex with men (BMSM) and the relationship between incarceration and HIV among BMSM.14 The purpose of this study was to determine an “incident” incarceration estimate among a cohort of BMSM enrolled in the HIV Prevention Trials Network (HPTN) 061 study, examine the demographic, behavioral, and psychosocial predictors of new incarcerations, and explore the relationship between incarceration and incident HIV.
HPTN 061 was a longitudinal study designed to determine the feasibility and acceptability of a multicomponent intervention to reduce HIV infection among BMSM in 6 US cities. The study was conducted in Boston, Atlanta, Los Angeles, New York City, San Francisco, and Washington, DC. Enrollment occurred over a 2-year period from July 2009 to December 2011, but BMSM were only followed up for 1 year from enrollment. Participants were recruited directly from the community or as sexual network partners referred by index participants. Men were eligible to participate in the study if they: self-identified as a man or male at birth; identified as African American, black, Caribbean black, or multiethnic black; were aged at least 18 years; reported at least 1 instance of unprotected anal intercourse with a man in the past 6 months; resided in the metropolitan area and did not plan to move within the next year; and provided informed consent for the study. Participants who were newly identified with HIV infection, who were previously diagnosed with HIV infection but were not in HIV care, or who tested HIV negative at enrollment were eligible for follow-up visits. Participants completed a behavioral assessment using audio computer-assisted self-interview (ACASI) technology. HIV and sexually transmitted infection testing and risk reduction counseling were offered to all participants at enrollment, 6-month follow-up, and 12-month follow-up.
The main outcome variable assessed for this analysis was incarceration during study follow-up. Participants were asked the following question at their 6- and 12-month follow-up visits: “How many times in the last 6 months have you spent 1 or more nights in jail or prison?” Individuals who reported at least 1 instance in the past 6 months of being in jail or prison were considered as being incarcerated. Raw ACASI data indicated that some participants might have misunderstood the question and reported the number of nights spent in jail or prison. Therefore, if the reported number was greater than 1, it was set to 1 in the incidence calculation. A dichotomized outcome variable was derived to indicate whether a participant was ever incarcerated during the study follow-up. For those participants who missed their follow-up visit as a result of incarceration, which was documented on the missed visit form, the outcome was set to yes. For the purposes of this analysis, those who missed 1 visit and reported no incarceration at the other visit were considered as not being incarcerated during follow-up.
The demographic characteristics assessed at enrollment for this analysis included city of enrollment, gender (male, female, or transgender), sexual identity (heterosexual or straight and gay, bisexual, or other MSM category such as same gender loving), age at study enrollment, household income, employment status, country of birth, student status, education level, if they had health care coverage, housing status, and relationship status (single, divorced, or widowed was classified as not being in a relationship, and married, living with partner, or have a partner but not living together were classified as currently in a relationship).
Behavioral questions included age at first intercourse, frequency of recreational drug use (ie, opiates, poppers, stimulant, marijuana, and injection drugs) in the past 6 months before study enrollment, and specific drug use in the past 6 months before study enrollment.
Several barriers to effective HIV prevention and treatment efforts for BMSM have been identified in the literature. They include the barriers related to social networks, barriers related to personal, social, and institutional racism, barriers related to religion, and barriers related to the interconnectedness of poverty, violence, and substance use.15 The following psychosocial characteristics were therefore included in this study: incarceration history at enrollment; incarceration frequency at enrollment; level of social support; belief in the use of meditation/prayer; belief in God or higher power; belief in an overall purpose and life plan; frequency of religious or spiritual services; affiliation with a church or religious institution; childhood involvement in a religious or spiritual body; depressive symptomatology; internalized homophobia (IHP); perceived racism; early childhood (younger than 12 years) physical violence, including being hit, punched, kicked, or beaten up in a way that resulted in injury, severe pain, or other serious harm; early childhood (younger than 12 years) sexual experience, including sexual touching and sexual intercourse; and any form of intimate partner violence. Social support was assessed using an adapted version of a social support scale from the Human Population Laboratory survey.16 Depressive symptomatology was measured using the Center for Epidemiologic Studies Depression Scale, a 20-item measure for symptoms of clinical depression.17
Perceived racism was based on a scale of 28 questions with scores 1–5 for “does not bother me at all,” “only bothers me a little,” “bothers me somewhat,” “bothers me a lot,” and “bothers me extremely,” respectively, and score 0 for “has never happened to me.” All 28 questions must be answered to calculate the sum score. Perceived racism was categorized to high (sum ≥ 95), medium (48 ≤ sum < 95), and low (sum <48) based on the sum score. IHP was collected using a 7-question scale. Scores 1, 2, 3, 4, and 5 were assigned for “disagree strongly,” “disagree,” “neither agree nor disagree,” “agree,” and “agree strongly,” respectively. All 7 questions must be answered to compute the sum score. A participant was categorized as “low/medium” IHP if the sum score was ≤25 or as “high” IHP if the sum score was >25. The social support scale had 6 questions with answers “none of the time,” “a little of the time,” “some of the time,” “most of the time,” and “all of the time.” Each answer was assigned a score of 1–5, respectively. All questions must be answered to compute the sum score. A participant was considered as having “low social support” if the sum was ≤ 13 or as having “moderate/high social support” if the sum was 14 and more.
To be included in the analysis, participants had to be eligible for follow-up visits (must not have been previously diagnosed with HIV at enrollment) and provide information about incarceration at enrollment and at least 1 of the follow-up visits. Incarceration events during study follow-up were used to estimate the incident incarceration rate for this sample of BMSM. Given the concern that there may be overreporting of incarceration events because of misunderstanding of the ACASI question, if the reported incarceration number at a visit was great than 1, it was set to 1 in the incidence calculation, which resulted in a conservative incident estimate. Poisson regression with robust standard errors was used for incarceration incidence and confidence interval estimation. Univariate logistic regression model was used to assess associations between incarceration during study follow-up (a binary outcome variable) and predefined baseline demographic, psychosocial, and behavioral characteristics. Covariates that were statistically significant at P = 0.1 level were included in the multivariable model (MVM), which also adjusted for enrollment city and incarceration frequency at enrollment. Even though the binary incarceration variable (incarceration history at enrollment) was significantly associated with incarceration during study follow-up, it was not included in the MVM because it was highly correlated with incarceration frequency at enrollment. In addition, the specific drug use variables (opiate use, popper use, stimulant use, and marijuana use) were not included in the MVM because they were all correlated with drug use, which was included in the MVM.
Cox proportional hazards regression model stratified by city was conducted to assess whether (time-updated) incarceration during the past 6 months was a predictor of HIV acquisition, in bivariate model and in MVM controlling for demographics and sexual risk behavior (ie, unprotected receptive anal intercourse with male partner, also time updated). Only HIV-negative participants at enrollment were included in this analysis. SAS version 9.2 statistical software was used to perform all the analyses.18
The study enrolled 1553 BMSM from the 6 US sites. Eighty-six participants were not eligible to attend follow-up visits (ie, previously diagnosed with HIV and in care), 28 participants did not respond to the incarceration question at enrollment, and an additional 161 participants who did not provide any information regarding incarceration during study follow-up were excluded from the analysis. As a result, the final cohort for this analysis included 1278 participants who responded to the incarceration question at enrollment and at least 1 of the follow-up visits. Twenty-four percent (n = 305) of participants reported a recent incarceration during 12 months of study follow-up. A total of 398 incarceration events were reported over a total of 1151.2 person years of follow-up with an estimated annualized incarceration incidence rate of 35% [95% confidence interval (CI): 31% to 38%]. The incidence of incarceration was directly related to the frequency of incarceration at enrollment (Table 1). Almost half (49%) of younger participants (aged younger than 30 years) reported some form of incarceration before enrollment or during study follow-up. Among older participants (30 years or more), 73% reported some form of incarceration before and/or during study follow-up (Table 2). New incarcerations during study follow-up ranged from 12.1% in Washington, DC, to 31.0% in Atlanta, GA (Table 3).
Multivariable logistic regression analyses showed that incarceration during study follow-up was significantly associated with household income of less than $30,000 per year [adjusted odds ratio (aOR), 1.74; 95% CI: 1.10 to 2.76]; lower education (high school education or less) (aOR, 1.83; 95% CI: 1.27 to 2.62), previous incarceration frequency at enrollment (once vs. never, aOR, 2.49; 95% CI: 1.40 to 4.42; twice vs. never, aOR, 2.63, 95% CI: 1.43 to 4.86; 3 times or more vs. never, aOR, 3.13; 95% CI: 2.00 to 4.91). Several of the behavioral (ie, drug use in the past 6 months) and psychosocial variables (ie, history of childhood violence, early sexual experience, depressive symptomatology, and low levels of social support) were significant in the univariate analysis but did not remain significant in the multivariable analysis. One psychosocial characteristic—perceived racism—did, however, remain significant in the multivariable logistic analyses. Incarceration during study follow-up was significantly associated with high levels of perceived racism (aOR, 1.82; 95% CI: 1.02 to 3.27) (Table 3).
One thousand twelve BMSM (79% participants) who tested HIV negative at enrollment were included in the analysis that assessed whether incarceration during the past 6 months of study follow-up was a predictor of incident HIV acquisition. The analysis did not find a statistically significant association between incarceration and HIV acquisition (adjusted hazard ratio, 1.69; 95% CI: 0.64 to 4.44) after controlling for demographics (ie, age, sexual identify, education, income, housing, employment, student status, and insurance status) and unprotected receptive anal intercourse (data not shown).
Almost one quarter of BMSM enrolled in the study reported a recent incarceration during study follow-up with an estimated incarceration incidence rate of 35%. This study is the first to document an incarceration incidence estimate, specifically among BMSM in the United States. Differences in city-specific new incarcerations during study follow-up were also observed. The city-specific differences should be interpreted with caution given differences in site recruitment strategies and locations. The association between incarceration during study follow-up and lower education and income is not a surprising finding given that lower education increases the probability of incarceration,7 and the relationship between education and income is well known. However, this study is the first to show that BMSM are at particularly high risk for incarceration.
The observed relationship between new incarcerations during study follow-up and history of incarceration is also not surprising. A report by Department of Justice revealed that almost 73% of all black offenders released from jail in 1994 were rearrested.19 Several childhood factors related to adult incarceration have also been described in the literature.20 Data from the ongoing, 20-year Chicago Longitudinal Study comprising low-income minority children (93% black) identified several predictors of adult offending or future incarceration. Common predictors of any future adult conviction, felony conviction, or any incarceration (jail) term included family public aid receipt by child’s age 3, negative home environment from birth to 5 years of age (frequent family conflict, family financial problems, and parental substance abuse), maltreatment experiences between 4 and 13 years of age (substantiated abuse or neglect as documented by court and Department of Child and Family Services records), troublemaking behavior at school and home from 9 to 12 years of age (ie, does not follow rules and gets into fights), and number of school moves between 10 and 14 years of age.20
However, the observed relationship between incarceration during study follow-up and high levels of perceived racism is an interesting finding. It has been noted that discrimination may occur in any number of steps leading up to sentencing.21 Data from the Department of Justice revealed that there were no racial differences in being stopped by law enforcement, but black men were more likely to be subjected to a search of their cars and greater force used or threatened against them compared with their white counterparts.22 There is also evidence indicating that blacks receive harsher sentences than whites who commit the same crime.7 Furthermore, this study found no association between new incarcerations during study follow-up and HIV acquisition. This is similar to the findings of Wohl et al23 who found no association between incarceration and HIV infection among a case–control study of 610 HIV-infected black men (40% MSM) in North Carolina.
Although this analysis contributes to our understanding of the predictors of new incarceration and the relationship between incident incarcerations and HIV among BMSM, there are several study limitations to consider. The observed study findings cannot be generalized to BMSM as a whole because participants were recruited from a community sample of BMSM in the 6 US cities. Self-reported incarceration during study follow-up may have been underestimated as a result of social desirability bias given the stigma and discrimination associated with being incarcerated. Finally, there were a small number of incarceration-related questions resulting in a limited analysis about the circumstances surrounding incarceration during study follow-up. Specifically, we did not assess incarcerations for new crimes versus parole violations. In addition, data indicated that some participants misinterpreted the ACASI question “How many times have you spent 1 or more nights in jail or prison?” as “How many nights did you spend in jail or prison?” Therefore, if the reported number was greater than 1, it was set to 1 in the incidence calculation, which resulted in a more conservative incident estimate. Despite these limitations, this analysis is the first to our knowledge to describe the predictors of new incarceration among BMSM.
CONCLUSIONS AND RECOMMENDATIONS
This study demonstrates that US BMSM enrolled and followed up in the HPTN 061 study were affected by incarceration. Future studies among BMSM should incorporate incarceration-specific questions to enhance scientific understanding of the impact of incarceration among BMSM. Given that almost one quarter of participants reported a recent incarceration during study follow-up, BMSM enrolled in this study may have also been at risk for lower employment prospects, limited housing opportunities, and reduced access to care that exist for black male ex-offenders in general. This study also adds to the body of literature describing the devastating impact of incarceration among black men in the United States and highlights the urgent need for structural- and policy-level approaches to prevent new and reoccurring incarcerations and their resulting negative consequences for black men and their families, networks, and whole communities. These structural- and policy-level solutions may include a greater investment in education,24 conflict resolution, and job training resources24 for black youth and adults pre- and postincarceration and reforming federal restrictions for ex-offenders related to voting, receiving food stamps, public housing, and student financial aid.
Alan Greenberg, MD, MPH, with the George WA University (GWU) Clinical Research Site and HPTN Scholar mentor; HPTN 061 Study Participants; HPTN 061 Protocol Co-Chairs: Beryl Koblin, PhD, Kenneth Mayer, MD, Darrell Wheeler, PhD, MPH; HPTN 061 Protocol Team Members; HPTN Network Laboratory, Johns Hopkins University School of Medicine; Statistical and Data Management Center, SCHARP; HPTN CORE Operating Center, FHI 360; Black Gay Research Group; Clinical Research Sites, Staff and CABs at Emory University, Fenway Institute, GWU School of Public Health and Health Services, Harlem Prevention Center, NY Blood Center, San Francisco Department of Public Health, the University of California, Los Angeles (UCLA) Center for Behavioral & Addiction Medicine, and Joe Kimbrell, MA, MSW, with the Louisiana Public Health Institute.
2. Harawa N, Adimora A. Incarceration
, African Americans and HIV
: advancing a research agenda. J Natl Med Assoc. 2008;100:57–62.
4. Glaze LE. Bureau of Justice Statistics Bulletin. Correctional Populations in the United States, 2009. Washington, DC: US Bureau of Justice Statistics; 2010. NCJ Publications no. 231681. Available at: http://bjs.ojp.usdoj.gov/content/pub/pdf/cpus09.pdf
. Accessed December 29, 2011.
6. Fullilove RE. Mass incarceration
in the United States and HIV
/AIDS: cause and effect? Ohio St. J. Crim. L. 2011;9:353–358.
7. Hattery A, Smith E. African American Males and the Incarceration
Problem. Not Just Confined to Prison. Thousand Oaks, CA: Sage Publications, Inc; 2007:233–284.
8. Roberts DE. The social and moral cost of mass incarceration
in African American communities. Stanford Law Rev. 2004;56:1271–1305.
9. Freudenberg N. Jails, prisons, and the health of urban populations: a review of the impact of the correctional system on community health. J Urban Health. 2001;78:214–235.
11. Kulkarni S, Baldwin S, Lightstone A, et al.. Is incarceration
a contributor to health disparities? Access to care of formerly incarcerated adults. J Community Health. 2010;35:268–274.
13. Adimora A, Shoenbach V, Francis E, et al.. Concurrent partnerships among rural African Americans with recently reported heterosexually transmitted HIV
infection. J Acquir Immune Defic Syndr. 2003;34:423–429.
14. Millett GA, Peterson JL, Wolitski RJ, et al.. Greater risk for HIV
infection of black men who have sex with men: a critical literature review. Am J Public Health. 2006;96:1007–1019.
16. Berkman LF, Syme SL. Social networks, host resistance, and mortality: a nine-year follow-up study of Alameda County residents. Am J Epidemiol. 1979;109:186–204.
17. US Department of Health and Human Services. CES-D Scale. Bethesda, MD: US Department of Health and Human Services, National Institutes of Health; 2004.
18. SAS Institute. SAS Version 9.2. Cary, NC: SAS Institute, Inc; 2008.
20. Ou S, Reynolds A. Childhood predictors of young adult male crime. Child Youth Serv Rev. 2010;32:1097–1107.
21. Meeker J, Jesilow P, Aranda J. Bias in sentencing: a preliminary analysis of community service sentences. Behav Sci L. 1992;10:197–206.
23. Wohl A, Johnson D, Jordan W, et al.. High-risk behaviors during incarceration
in African-American men treated for HIV
at three Los Angeles public medical centers. J Acquir Immune Defic Syndr. 2000;24:386–392.
24. Lichtenstein B. Drugs, incarceration
, and HIV
/AIDS among African American men: a critical literature review and call to action. Am J Mens Health. 2009;3:252–264.
Keywords:© 2014 by Lippincott Williams & Wilkins
black MSM; incarceration; HIV; HPTN 061