Correlates of Prison Incarceration among Homeless Gay and Bisexual Stimulant-Using Young Adults

Abstract

Gay and bisexual (G/B) homeless adults face multiple challenges in life which may place them at high risk for incarceration. Yet, little is known about this understudied population in terms of risk for incarceration. Baseline data collected from a longitudinal study between October 2009 to March 2012 in Hollywood, California explored correlates of self-reported incarceration among G/B homeless stimulant-using adults (N=353). Findings revealed older age, less education, having children, as well as a history of injection drug use (IDU) and being born in the United States (U.S.) were positively associated with incarceration. Moreover, having poor social support and having received hepatitis information were also correlated with a history of incarceration. Our findings help us gain a greater awareness of homeless G/B adults who may be at greater risk for incarceration, which may be used by health care providers to design targeted interventions for this underserved population.

Gay and bisexual (G/B) stimulant-using homeless men are at high risk for one or more incarceration episodes. In one study, approximately 51% of G/B men had a previous prison term (Alarid, 2000). However, among this understudied population, correlates of incarceration are not well understood. While similar to heterosexual counterparts, pathways to homelessness among lesbian, gay, bisexual and transgender (LGBT) young adults result from leaving home early due to familial conflict over sexual orientation, need for freedom, and physical abuse (Cochran, Stewart, Ginzler, & Cauce, 2002). In a national sample, nearly half (46%) of LGBT young adults who were homeless had run away because of family rejection of sexual orientation or identity (Durso & Gates, 2012). As is prevalent in the literature, drug abuse often is connected with criminality (Fletcher & Chandler, 2012) and subsequent incarceration (Mumola & Karberg, 2006).

Among young men (17-28 years of age) who have had sex with men (MSM) and have been homeless, exposure to drugs such as powder cocaine (60%), 3,4 methylenedioxy methamphetamine MDMA (60%), hallucinogens (41%), crack cocaine (22%), and heroin (20%) (Clatts, Goldsamt, Yi, & Gwadz, 2005) are common and are risk factors for subsequent incarceration. Prior studies have explored the relationship between substance use and risk-taking behaviors (Hudson et al., 2009; Nyamathi et al., 2010) and incarceration (Mumola & Karberg, 2006). In one report of LGBT, 53% have reported a history of alcohol and substance abuse, and nearly one third (31%) had contact with the juvenile justice system (Durso & Gates, 2012).

A number of other factors that have been proposed in the literature are associated with incarceration. Type of social networks and support is an important contributing factor for continuation of drug use as peers may use drugs together. In a study among treatment-seeking drug users, increased time spent with those who are involved in drug use and criminal activities increased the propensity for crime (Best, Hernando, Gossop, Sidwell, & Strang, 2003).

Race/ethnicity, age, education and poor cognitive abilities may also be significant factors impacting history of incarceration. For example, black MSM were more likely to report recent arrest history as compared to white MSM (Lim, Sullivan, Salazar, Spaulding, & Dinenno, 2011). Drug use patterns may similarly differ by age and this can be seen with methamphetamine use. When considering age, among state prisoners, those between 25-34 had a higher percentage of methamphetamine use in the month before the offense compared to those 24 or younger, 35-44, 45-54 or 55 or older (12.6% versus 11% versus 11.5% versus 7.7% versus 3.3%) (Mumola & Karberg, 2006). For those who have abused drugs, cognitive capacity may also be affected. According to Moon et al. (2007), methamphetamine use damages the frontal lobe and leads to impaired executive function. While similar to amphetamine, methamphetamine, a potent stimulant affects the central nervous system and has been found to affect the function and structure of the brain affecting visual memory (Moon, Do, Park, & Kim, 2007).

Survival on the streets necessitates an understanding of street economy, a term coined to explain how a non-linear exchange may occur for drugs, sex and money (Lankenau, Clatts, Welle, Goldsamt, & Gwadz, 2005). While sex trading is driven by the need to obtain drugs or shelter (Newman, Rhodes, & Weiss, 2004); these particular types of activities often lead to interaction with law enforcement and criminality (Clatts et al., 2005). Among gay and transgender youth, nearly 44% reported being asked to exchange sex for money for food, drugs and shelter (Sifra-Quintana, Rosenthal, & Krehely, 2010). Among MSM, 71.4% of those who were bisexual had engaged in sex trade; 58% used methamphetamine in the past week, and 69.3% injected drugs in the past week (Newman et al., 2004). Interaction with law enforcement due to drug use may be prevalent as 32% of state and 26% of federal prisoners used drugs at the time of their offense (Mumola & Karberg, 2006). For G/B ex-offenders who are exiting institutions into community supervision, challenges with reintegrating into society may be a significant issue; however, the majority of the literature focuses on adolescents and youth and combines LGBT youth without primarily focusing on adult men between the ages of 18 to 46 years of age.

Thus, the aim of this study was to primarily focus on G/B homeless stimulant-using men as there is limited literature which focuses on this high risk for incarceration among this subpopulation. Raising awareness and an understanding of correlates in this subgroup is important as it may lead to the development of culturally-sensitive intervention approaches.

Comprehensive Health Seeking and Coping Paradigm (CHSCP)

The components of the Comprehensive Health Seeking and Coping Paradigm (CHSCP) which has guided this study include socio-demographic factors, situational, cognitive and social factors and coping responses. Sociodemographic factors that might be relevant to predictors of incarceration among G/B adults include age, education, and being born in the U.S. Situational factors such as being homeless (Cochran et al., 2002) and having a history of family rejection (Ryan, Huebner, Diaz, & Sanchez, 2009) may likewise influence a history of incarceration.

Social factors that might negatively predict incarceration may include poor social support, and support coming from drug users; while cognitive factors may include knowledge of hepatitis. Lack of consistent social relationships has been associated with more sexual partners and unprotected sexual activity (Seal et al., 2003). Finally, emotion-focused coping strategies not only includes use of drugs and alcohol, but as well poor decision-making leading to continuing use of these risky behaviors (Reyna & Rivers, 2008) and increased psychological distress (Ireland, Boustead, & Ireland, 2005). We believe that these variables influence the main outcome variable in this study which is self-reported incarceration.

Methods

Participants

Baseline data were analyzed among G/B homeless men who were enrolled in a randomized controlled trial focused on reducing stimulant use and other illicit drugs as well as promoting hepatitis B Virus (HBV), hepatitis C virus (HCV) and HIV disease prevention. In total, 353 stimulant (methamphetamine and/or powder cocaine and/or crack cocaine)-using men participated in the study. Eligibility criteria was a) age 18-46; b) self-reported being homeless; c) G/B identity; d) stimulant use within the previous three months; and e) no self-reported participation in drug treatment in the last 30 days. Stimulant use was confirmed by urine screening or by hair analysis, if the urine screening could not detect stimulant metabolite within the previous three months.

Procedure

Data were collected from October 2009 to March 2012 in a community research center in Hollywood, California. Two methods of recruitment were utilized: flyers were distributed by the staff in the Hollywood area and short in-service presentations were made at local community-based sites. If individuals were intoxicated or cognitively impaired (hallucinating or talking to themselves), they were excluded from the study. Potential participants received a comprehensive description of the study, an overview of the informed consent form in a private location, and a short (2 minute) screening assessment to confirm eligibility. The screening assessed demographic characteristics, homeless status, and substance use and abuse using the Texas Christian University Drug Screener (Simpson & Chatham, 1995).

Participants provided a blood sample which was tested for the HBV and HCV. After two days, research staff asked participants to return to receive results provided by the study nurse; at this time, a second informed consent was reviewed and signed to allow administration of the baseline questionnaire. Thereafter a rapid HIV test was administered by oral swab. A baseline assessment was administered by the research staff well trained in confidential data collection, which included respecting each individual as a person, not judging the participant on reported behaviors, and in administering questionnaires in a private location. Participants were paid $10 to complete the screening questionnaire and $20 to complete the baseline questionnaire. Both the UCLA and the Friends Research Institute, Inc. Institutional Review Boards approved the study.

Measures

Sociodemographic Information. The screening survey assessed for eligibility criteria of age, homeless status, G/B identity and stimulant use. Homelessness was assessed by asking where the potential participant spent the last evening. Options included homeless or transitional shelter, abandoned car, friend’s home or on the street. An individual was defined as homeless if they lacked a fixed, regular, and adequate nighttime residence, and they had a primary nighttime residence that was a supervised publicly or privately operated shelter designed to provide temporary living accommodations (Hoben, 1995). G/B status was self-reported by the individual of his perceived sexual identity: options included gay, bisexual or heterosexual. Stimulant use was determined by asking if a stimulant (such as amphetamine, methamphetamine, cocaine or crack) was used over the last three months. Stimulant use was also confirmed by urine screening or by hair analysis, if the urine screening could not detect substance abuse (SA) metabolite.

The baseline questionnaire assessed the following sociodemographic variables: age, education, race/ethnicity, marital status, relationship status in terms of being partnered or not, country of birth, having children, employment status and where participants have spent the last 30 nights. Participants were also asked if they saw a physician in the previous four months. Participants were also asked if they had been given any information about Hepatitis. Responses included yes/no.

Health Status. A self-reported one-item measure was used to assess general health status which asked about general health, ranging from excellent to poor and dichotomized as fair/poor vs. good/very good/excellent. Bodily pain was assessed by a single item asking about bodily pain in the past four months; answers on a six point scale ranged from none to very severe. For analytic purposes, responses were dichotomized as moderate/severe/very severe pain vs. less bodily pain (Stewart, Hays, & Ware, 1988).

Social Support was measured by a categorical item asking respondents who they turn to for friendship and support. Possible responses were primarily drug or alcohol users, primarily non-users of drugs or alcohol and equally divided by users and non-users and no one.

Injection drug use was assessed by asking participants if they had injected any recreational or illegal drugs. Responses included yes, within the last 30 days, yes, within the last 4 months, yes, more than four months ago and no, never. For analytic purposes, it was dichotomized as never used vs. ever used.

History of Incarceration was assessed by asking if the participant had ever spent time in prison or in both jail and prison.

Statistical Analyses

Descriptive statistics, including means, standard deviations, frequencies and percentages, were computed to present the sample sociodemographic and other background characteristics. Unadjusted relationships between these characteristics and having been incarcerated were examined using chi-square tests and t tests, depending on underlying distributions. Characteristics that were associated with incarceration history at the .10 level were then used as predictors in a logistic regression model for incarceration. Predictors in the resulting model with P values greater than 0.10 were removed one at a time in descending order to identify independent correlates of past incarceration that were significant at the .10 level in a multivariate context.

Using p-values higher than the standard .05 to identify predictors for a regression model reduces the chance of overlooking important relationships and failing to include important control variables in the model. Assuming over fitting (too many variables in the model) is not a problem, allowing predictors with p-values a little higher than .05 to remain in a multivariable model also serves to include adjusted relationships that might be more important in other samples. Of note, the SAS linear modeling procedure uses .50 and .10 as default significant levels for stepwise forward and backward techniques, respectively. However, when reporting results, care should be taken to focus on stronger associations.

The final model was assessed for multicollinearity, and was not found to be a problem. Model goodness of fit was verified with the Hosmer-Lemeshow test (Hosmer & Lemeshow, 2000). Statistical analyses were conducted using SAS Version 9.1.

Results

Sociodemographic Characteristics of Participants

The mean age of the sample (N = 353) was 34.6 ± 8.1 years (Table 1). The sample was nearly equally represented by Caucasian/whites (38%) and African American/black (36%); nearly three-quarters had never been married. Slightly over one-third of participants (38%) reported recent injection drug use (IDU). One-fourth reported fair/poor physical health. Moreover, 31%% were positive for hepatitis C virus (HCV) and 16.3%were positive for HIV. Nearly half (43.6%) of the sample reported a history of incarceration in prison specifically.

Table 1.

Sample Characteristics (N=353)

Measure	Mean	SD
Age	34.6	8.1
	N	%
Race/ethnicity
Caucasian/white	135	38.2
African American/black	126	35.7
Hispanic/Latino	48	13.6
Mixed	44	12.5
Marital status
Never Married	255	73.5
Living with male partner	26	7.5
Married to female	11	3.2
Divorced/Widowed	55	15.9
Partnered	81	23.0
U.S. Born	328	93.2
Children (yes)	109	30.9
Injection Drug Use (previous 30 days)	134	38.1
Given information about hepatitis	201	57.1
General Health
Health status (fair/poor)	88	25.0
Moderate/Severe bodily pain (yes)	142	40.2
Saw physician previous 4 months (yes)	49	13.9

Note. HCV=Hepatitis C virus; HIV is Human Immunodeficiency Virus

Unadjusted Associations between Sociodemographic Characteristics and Prison History

A number of categorical background variables were associated with prison history (Table 2). These included being US born and having children. In particular, men with a incarceration history were more likely to have been born in the US, and to report children than those without this history (97% vs. 90% and 43% vs. 22%, respectively). Race/ethnicity, having a sexual partner, history of employment, and poor/fair health were not related to history of incarceration. Additionally, when race/ethnicity was collapsed to Caucasian/white/non-white, men who were Caucasian/white were more likely to have reported being in prison than those who were not Caucasian/white (44% vs. 34%, p = .043, data not shown). Continuous correlates of incarceration included both age and education: older age and less education were found to be associated with prison or jail history.

Table 2.

Associations of Selected Variables with Incarceration History (n=351)

	Prison History
	Yes		No		p valuea
	Mean	SD	Mean	SD
Age	37.2	6.8	32.6	8.5	.001
Education	11.8	2.3	12.4	2.1	.016
	N	%	N	%
Race/Ethnicity:					.148
African American/Black	51	33.3	74	37.4
Caucasian/White	68	44.4	67	33.8
Hispanic/Latino	15	9.8	33	16.7
Mixed	19	12.4	24	12.1
U.S. Born	148	96.7	178	90.4	.019
Partnered	30	19.6	51	25.8	.175
Children	66	43.1	43	21.7	.001
Ever Employed	139	93.3	171	90.5	.352
Fair/Poor Health	40	26.3	47	23.7	.580
Received Hepatitis Information	96	62.8	103	52.3	.050
Saw physician previous 4 Months	30	19.7	19	9.6	.007
Lived Primarily on Street	85	55.6	108	54.6	.850
Ever Used Injection	115	75.2	102	51.8	.001
Social Support:
Drug/Alcohol	37	24.3	32	16.6	.043 (n=345)
Non Drug/Alcohol	39	25.7	49	25.4
Both	59	38.8	100	51.8
None	17	11.2	12	6.2

^aDetermined by two sample t-test for age and education and Chi-square test for the remaining variables.

Physical and mental health care were also related to having been in prison or jail. In particular, having seen a physician in the previous four months and requesting treatment for a mental health condition were highly associated with incarceration history. Less strongly associated was receiving hepatitis information. Finally, in terms of drug use, those who used injection drugs in their lifetime were more likely than those who did not to have a history of incarceration (75.2% vs. 51.8%). Moreover, either having no social support or receiving social support from substance users was also related to incarceration (35.5% vs. 22.8%, p < .01).

Adjusted Analysis

Logistic regression analysis indicated that age, having children and having been born in the US were directly related to incarceration history (Table 3). In contrast, education was inversely related to incarceration history. Lifetime injection drug use, having seen a doctor in the previous four months, poor social support and having received hepatitis information were also associated with incarceration history.

Table 3.

Logistic Regression Results for Incarceration History (n=339)

	Beta	S.E.	p value
Age	0.057	.02	.001
Education	−0.182	.06	.001
Children	1.196	.28	.001
US Born	1.227	.59	.001
IDU	1.005	.27	.001
Saw physician previous 4 Months	0.987	.37	.001
Got Hepatitis Information	0.651	.26	.001
Poor Support*	0.492	.28	.001

^*Either no social support or support only by other substance users

Discussion

Among G/B homeless adults, several factors influence a history of incarceration; these included being older, US-born, having children, having poorer education, injection drug use (IDU), seeing a physician in the previous 4 months, having been in receipt of hepatitis information, and receiving poor support. In our sample, G/B men with a history of incarceration were disproportionately affected by poor education. Our findings support those found by Alarid (2000), wherein in a sample of G/B men (N=56), the highest level of education was 11.6 years. In another sample of homeless men on parole (N=297), over two thirds of the total sample (69%) graduated from high school (Nyamathi, Marlow, Branson, Marfisee, & Nandy, 2012).

These findings point to several areas of consideration. First, it may be necessary to encourage successful completion of a GED. Second, moving beyond high school, it is necessary to link clients into vocational training which would enable them the ability to have a sustained income. Low educational attainment and skill levels should be considered major challenges that place G/B and other vulnerable populations at risk for incarceration.

Findings demonstrated that G/B men who had received hepatitis information were more likely to have been incarcerated. It is plausible that they may have received this information in the community prior to their incarceration or during their prior incarceration. In our study, we also found that among G/B homeless men, IDU was associated with incarceration. As over one-third of our sample had a history of IDU, receiving information about HCV would be likely because many may have learned they had HCV while incarcerated. Further, sexual health information could have been given while incarcerated. These findings highlight the need to promote ongoing health information and linkage into care.

Findings also indicated that receiving no social support or only receiving social support from another substance user was related to a history of incarceration. The type of social support one may receive may have a significant impact on behavior as it can provide either protection or lead to problematic consequences; in particular, one study found that social networks of women in recovery may include positive social support as well as those who enable drug use (Falkin & Strauss, 2003) as well-meaning family members may provide basic necessities such as money which may enable drug use (Strauss & Falkin, 2001). It is important to understand the nature of social support among high-risk populations as lack of support has the potential to increase or decrease positive behaviors.

We also found that being older and being born in the US was related to a history of incarceration. In one national sample, the average age of inmates was 39 years of age and 47.3% were sentenced to prison due to a drug offense (Federal Bureau of Prisons, 2013). Thus, it is plausible that older age is correlated with incarceration as many G/B men may have previous strikes against them which may increase their likelihood for incarceration. According to the Federal Bureau of Prisons, nearly three quarters (74.6%) of the incarcerated population has US citizenship (Federal Bureau of Prisons, 2013). It is important to note that in this sample, the majority 93.2% were born in the US; thus, are disproportionately represented in this sample.

Indeed our data also finds that those who were in prison were more likely to have seen a health care provider in the previous four months. It is probable that individuals who have interaction with the criminal justice system similarly interact with healthcare providers. This finding requires further exploration as there is clearly a window of opportunity for health care linkage and intervention for G/B homeless youth; however, it is probable than many are not adequately linked into care post release or jail. As G/B homeless stimulant users are not well understood, this group is combined with other sexual minorities which may have unique needs. As a result, minimal intervention work may be particularly tailored to age, drug types, frequency of use and past histories of incarceration-all of which may affect future illicit drug cessation and circumvention of recidivism.

Our findings point to several areas of intervention; namely, G/B homeless men are a population at risk for incarceration. Our findings indicate that being older and having less education were associated with self-reported incarceration. Poor education may also present challenges in terms of the ability to obtain employment due to poor job skills. Such lack of employment opportunities combined with a history of IDU may lead to the poor outcome of incarceration.

While our data our promising, in this study, the data are based on a self-report baseline questionnaire from a cross-sectional study. Thus, inferences regarding causality cannot be made between variables. Further, the study used a convenience sample limited to a very specific population of G/B men between 18–46 years of age, from one geographic area; all of which limits the ability to extrapolate to a larger population. Furthermore, as this study did not compare G/B men to a non G/B sample, it is not possible to confirm that any of these findings are specific to G/B males only as opposed to a homeless male stimulant-using population.

Nevertheless, as many G/B men had seen a practitioner and received hepatitis information, a window of opportunity to promote this information exists. As poor social support is likewise associated with incarceration, future research should be focused on designing comprehensive programs aimed at working with G/B homeless adults in an effort to promote culturally-sensitive linkage to positive social support and health care and drug treatment.