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. Author manuscript; available in PMC: 2018 Jul 1.
Published in final edited form as: Health Psychol. 2017 May 25;36(7):695–703. doi: 10.1037/hea0000509

Syndemic conditions and HIV transmission risk behavior among HIV-negative gay and bisexual men in a U.S. national sample

Jeffrey T Parsons 1,2,3, Brett M Millar 1,2, Raymond L Moody 1,2, Tyrel J Starks 1,2,3, H Jonathon Rendina 1,2,3, Christian Grov 1,4
PMCID: PMC5532533  NIHMSID: NIHMS878968  PMID: 28541070

Abstract

Objective

The syndemics framework has been utilized to explain the high rates of HIV infection among gay and bisexual men. However, most studies have relied primarily on urban or otherwise limited (e.g., single location) samples. We evaluated the prevalence of syndemics—here, depression, polydrug use, childhood sexual abuse, intimate partner violence, and sexual compulsivity—among gay and bisexual men from across the U.S., including non-urban areas.

Methods

Using data from a national sample of 1,033 HIV-negative gay and bisexual men, demographic differences in the prevalence of each syndemic condition and associations with HIV transmission risk behavior were examined.

Results

More than 62% of men reported at least one syndemic condition. Prevalence did not vary by U.S. region—however, a larger proportion of non-urban men and those with lower income and education levels were above the median number of syndemic conditions. In bivariate analyses, HIV transmission risk behavior was associated with each syndemic condition except for childhood sexual abuse, while in multivariate analyses, it was associated with polydrug use, sexual compulsivity, being Latino, and being single, and was highest among those reporting three or more syndemic conditions.

Conclusions

Rates of syndemic conditions among this national sample of gay and bisexual men were generally comparable to previous studies, however elevated rates in non-urban men suggest the need for targeted intervention and support. Links observed between syndemics and HIV transmission risk behavior highlight the ongoing need to address psychosocial concerns among gay and bisexual men in order to reduce their disproportionately high rates of HIV infection.

Introduction

Gay, bisexual, and other men who have sex with men continue to experience disproportionately high rates of HIV, accounting for 70% of all new HIV diagnoses in the U.S. in 2014 (Centers for Disease Control and Prevention, 2015a). Although the overall rate of new HIV infections has been on the decline for the past decade, rates continue to rise among this population (Centers for Disease Control and Prevention, 2015a, 2015b). Significant advances have recently been made in biomedical prevention strategies (e.g., pre-exposure prophylaxis; PrEP; Grant et al., 2010), which can be highly effective when combined with other strategies (e.g., frequent testing, condom use). However, evidence suggests that several ongoing epidemics experienced by gay and bisexual men are contributing to the disproportionate burden of HIV these men bear. Accordingly, addressing these syndemic conditions is vital to HIV prevention efforts.

The term ‘syndemic’ has emerged to describe multiple epidemics experienced by marginalized communities that are interconnected and mutually reinforcing, and which compound the risk for disease (Singer, 1994; Singer et al., 2006). Syndemic conditions are socially produced resulting from social and economic inequality—and factors such as poverty, limited access to education, limited access to healthcare, and environmental stigma contribute to the disproportionate burden of disease observed among urban racial and ethnic minorities (Singer, 2009). For gay and bisexual men, heterosexist social norms and the associated consequences of such norms (e.g., victimization, internalized stigma) are believed to drive the disproportionate burden of disease observed among these men (Meyer, 2003). The syndemics framework has been applied to risk for HIV transmission among gay and bisexual men (Dyer et al., 2012; Herrick et al., 2013; Mustanski, Garofalo, Herrick, & Donenberg, 2007; Parsons, Grov, & Golub, 2012). Stall and colleagues (2003) expanded on the SAVA syndemic (i.e., substance abuse, violence, and AIDS) observed among urban poor to include depression and childhood sexual abuse, and demonstrated associations between these conditions in a cross-sectional sample of gay and bisexual men (Singer, 1994, 2003). They observed an additive effect in which the number of these conditions was positively associated with HIV transmission risk behavior and HIV prevalence. More recently, Parsons and colleagues (2012) expanded the syndemics framework further to incorporate sexual compulsivity and additional studies have provided further evidence for the inclusion of sexual compulsivity in syndemic models (Dyer et al., 2012; Parsons et al., 2015). Collectively, the syndemics literature has provided evidence that experiences of violence (e.g., intimate partner violence, child sexual abuse), substance use (e.g., polysubstance use, binge drinking), psychological distress (e.g., depression) as well as other psychosocial conditions (e.g., sexual compulsivity) have a cumulative effect on HIV transmission risk (Mustanski et al., 2007; Parsons et al., 2012; Stall et al., 2003).

Since Stall et al. (2003), syndemic conditions have been examined in a variety of diverse samples of gay and bisexual men with relatively consistent findings (Ferlatte, Hottes, Trussler, & Marchand, 2014; Guadamuz et al., 2014; Herrick et al., 2013; Jie, Ciyong, Xueqing, Hui, & Lingyao, 2012; Mimiaga et al., 2015; Parsons et al., 2015; Wim, Christiana, & Marie, 2014; Williams et al., 2015), including one study of participants from 151 countries (Santos et al., 2014). However, relatively little research on syndemics has been done using large-scale national data from the U.S. That is, much of what is known about the impact of syndemics on HIV among gay and bisexual men has been taken from geographically restricted samples (Herrick, Stall, Egan, Schrager, & Kipke, 2014). This research has primarily focused on gay and bisexual men living in large metropolitan cities (Mimiaga et al., 2015; Herrick et al., 2013: Dyer et al., 2012), such as Chicago, IL (Mustanski et al., 2007), Los Angeles, CA (Herrick et al., 2014a), Miami, FL (Kurtz et al., 2012), and New York, NY (Parsons et al., 2012; 2015). The importance of syndemics research among gay and bisexual men living in large metropolitan areas is unquestionable given the high prevalence of HIV. However, the generalizability of this research is limited for those living in non-urban settings. As mentioned, adverse social conditions give rise to syndemics (Singer, 2009). Gay and bisexual men living in large metropolitan areas do experience stigma-based stress but also may benefit from greater community visibility and connectedness, social support, and health resources. Some evidence suggests gay and bisexual men in non-urban settings experience greater levels of sexual orientation based stigma but may also lack access to the potential benefits of a large visible and connected community (Meyer, 2003; Swank, Frost, & Fahs, 2012). Research with large samples of gay and bisexual men is needed to understand how the prevalence of syndemic conditions varies across demographic factors, including the prevalence of syndemic conditions across urban and non-urban settings.

Several studies have controlled for demographic factors in multivariate analyses examining the association between syndemic conditions and HIV risk (Herrick et al., 2013; Mustanski et al., 2007), yet few have reported on demographic differences in syndemic conditions. Among these studies, variables such as age, income, and race/ethnicity have been associated with various syndemic conditions (Dyer et al., 2012; Parsons et al., 2012; Stall et al., 2003). Two studies have examined demographic differences in the presence of a syndemic and both suggested that age was associated with experiencing two or more syndemic conditions (Dyer et al., 2012; Reed & Miller, 2016). Both studies focused exclusively on Black gay and bisexual men and thus race/ethnicity differences could not be examined. Previous research has not examined the association between demographic variables and the number of syndemic conditions present. Significant demographic differences have been reported in HIV incidence and prevalence among gay and bisexual men in the United States. National data suggest that rates of HIV infection are highest among young gay and bisexual men between the ages of 20 and 29 and among Black and Latino gay and bisexual men (CDC, 2015a). Examining demographic differences in syndemic burden is important in our understanding of the disproportionate rates of new HIV infections observed among specific groups.

In the present study, we sought to extend previous research by examining the co-occurrence of previously identified syndemic conditions—polydrug use, depression, childhood sexual abuse, intimate partner violence, and sexual compulsivity—and their association with HIV transmission risk behavior in a U.S. national sample of gay and bisexual men. We examined demographic differences in the prevalence of individual syndemic conditions, the median number of syndemic conditions, and sexual HIV transmission risk behavior. We also sought to compare men residing in urban areas to those in non-urban areas on exposure to syndemic conditions and using the urban/non-urban classification as a demographic covariate. Consistent with previous research, we hypothesized that syndemic burden would be positively associated with HIV transmission risk behavior. Additionally, we hypothesized that the prevalence of syndemic conditions and overall syndemic burden would be greater among gay and bisexual men living in non-urban areas compared to those living in gay and bisexual men living in urban areas.

Method

Participants

Data were taken from the first wave of survey responses collected in the One Thousand Strong project, a longitudinal study following a national cohort of 1,071 gay and bisexual men in the U.S. for a period of three years (Grov et al., 2016; Grov, Cain, Rendina, Ventuneac, & Parsons, 2016; Millar, Starks, Grov, & Parsons, 2016; Parsons, Rendina, Whitfield, & Grov, 2016). Potential participants were identified from a wider panel of approximately 22,000 gay and bisexual men provided by Community Marketing and Insights and were selected to reflect the diversity and distribution of gay and bisexual men across the U.S. as indicated by census statistics regarding the proportion of same-sex households and racial/ethnic diversity within each state. These panelists were drawn from over 200 sources (e.g., lesbian, gay, bisexual, and transgender (LGBT) events, social media and e-mail broadcasts distributed by LGBT organizations, as well as from mainstream social media), and an initial sample of 9,011 men were identified as potentially eligible if they were 18 or older, identified as a gay or bisexual male, and had regular internet access. Of the 9,011 men who were emailed an invitation to complete the screening survey, 6,371 did not open the email and another 90 emails were unable to be delivered. Of the 2,550 who opened the email, 2,393 (93.8%) completed the screening survey. Of these, 1,375 (57.5%) were deemed eligible, with the most common reasons for ineligibility being an HIV-positive status or not being sexually active with a man. Of the 1,375 eligible men, 1,071 (77.9%) completed all requirements of the assessment and were enrolled into the One Thousand Strong cohort. Full eligibility criteria also included being sexually active within the past year, having a stable postal address (i.e., not moving more than twice in 6 months), and being willing and able to complete at-home HIV/STI testing. There were some significant differences related to eligibility and response rates. Eligible participants were more likely to be White and younger, and those completing all requirements of the assessment were more educated and gay-identified. These significant findings, however, had small effect sizes. More detailed recruitment/enrollment procedures, milestones, and differences between responders and non-responders have been described elsewhere (Grov et al., 2016). Given our focus on behaviors that would put one at risk for HIV transmission, analyses for the present study are limited to the 1,033 men who reported not being on PrEP. Participants were compensated for survey completion with a $25 Amazon card. Informed consent was obtained online at each stage of screening and assessment, and all study protocols were approved by the City University of New York (CUNY) Institutional Review Board.

Measures

Participants completed an at-home hour-long online survey containing all measures for the present analyses. For syndemic conditions, we relied on measures which have been previously utilized in studies of syndemics among gay and bisexual men.

Demographics

Participants reported their date of birth, race and ethnicity, annual income, level of education, sexual identity, zip code, whether or not they had been on PrEP, and relationship status (whether partnered or single). Participants’ zip codes were classified into urban or non-urban using the Rural Urban Commuting Area coding system (RUCA 2.0), where any code above 1 was classified as non-urban.

Polydrug use

Participants reported on the use of any of the following substances in the past 90 days: cocaine, crack, crystal methamphetamine, marijuana, ecstasy, gamma-hydroxybutyrate (GHB), ketamine, heroin, and poppers. Participants reporting use of three or more of these were coded as having engaged in polydrug use (1 = yes, 0 = no). Although there have been some mixed findings about whether marijuana is associated with increased sex risk (Hendershot, Magnan, & Bryan, 2010) or not (Smith, Ferris, Simpson, Shelley, Pitts, & Richters, 2010), previous syndemics studies on gay and bisexual men have included it in polydrug use and have found that regular marijuana use was independently associated with sexual risk-taking (Mustanski et al., 2007).

Depression

The Center for Epidemiological Studies Depression Scale (Radloff, 1977) (CESD) consists of 20 items asking participants to rate how often they have experienced symptoms of depression with response options ranging from 0 (rarely or none of the time) to 3 (most or all of the time). Typically, the CESD asks individuals about the presence of symptoms within the past week. However, in order to match the timeframe of assessment of depressive symptoms with the period of HIV transmission risk behavior, the stem was adapted to ask participants about symptoms in “the last three months”—as has been done in previous studies of syndemics among gay and bisexual men (Parsons et al., 2012; Stall et al., 2003; Starks, Millar, Eggleston, & Parsons, 2014). In order to minimize the possibility that extending the assessment window to three months may artificially inflate scores by expanding the period over which symptoms are reported, we used the more conservative cut-off score of 23 as being indicative of depressive symptomology (α = .93), in accordance with previous studies of syndemics.

Childhood sexual abuse

Participants were asked if they had experienced sexual activity, into which they felt forced or scared by someone who was older than them, and whether they were aged 16 or younger at the time (1 = yes, 0 = no) (Stall et al., 2003).

Intimate partner violence

Participants indicated if they had experienced any of a range of forms of intimate partner violence within the last five years, using an adaptation of the Revised Conflict Tactics Scale (Straus, Hamby, Boney-McCoy, & Sugarman, 1996) by Greenwood and colleagues (Greenwood et al., 2002). Twelve items were answered yes or no, and participants who responded yes to any of these items were coded as a yes on a dichotomous variable indicating intimate partner violence.

Sexual compulsivity

The Sexual Compulsivity Scale (Kalichman & Rompa, 1995) is a 10-item scale measuring the impact of one’s sexual thoughts on daily functioning and the perceived inability to control sexual thoughts and/or behaviors rated on a Likert-type scale from 1 (not at all like me) to 4 (very much like me), with total scores ranging from 10–40, α = .89. Consistent with prior research, we used a cut-off score of 24 or more to indicate the presence of sexual compulsivity (Benotsch, Kalichman, & Kelly, 1999; Grov, Parsons, & Bimbi, 2010; Hook, Hook, Davis, Worthington Jr., & Penberthy, 2010; Ventuneac, Rendina, Grov, Mustanski, & Parsons, 2015).

HIV transmission risk behavior

Participants reported whether they had condomless anal sex in the past 90 days with a casual male partner (regardless of the partner’s HIV status), and/or with a main partner of HIV-positive or unknown status (1 = yes, 0 = no).

Analytic Plan

The presence of each syndemic condition reported by participants was summed to form an overall tally ranging from 0–5. The median number of syndemic conditions was compared across demographic characteristics (race and ethnicity, relationship status, sexual orientation, income, education, geographic region, and urban vs. non-urban) using a median test. The correlation between age and number of syndemic conditions utilized a Kendall’s Tau. Comparisons between urban and non-urban participants on each syndemic condition and HIV transmission risk were tested via chi-squared tests of independence. Bivariate associations between the presence of each syndemic condition and HIV transmission risk behavior (any condomless anal sex with a casual partner regardless of their HIV status, and/or with a main partner of HIV-positive or unknown status, in the past 90 days) were calculated as odds ratios. Logistic regressions, adjusting for age, education (ref = having more than a college degree), race and ethnicity (ref = White), relationship status (ref = partnered), income (ref = $50K or more), and urbanicity (ref = urban) were used to identify variables associated with each syndemic condition (Models 1–5) and with having had any sexual HIV transmission risk (Model 6). While detailing the tests of whether demographic variables moderated the associations between syndemics and HIV transmission risk behavior is beyond the scope of this paper, we did conduct the analyses and found no evidence of interactions between syndemic conditions and demographics (specifically, age, race/ethnicity. relationship status, income, or education).

Results

The majority of the sample was White (71.7%), gay-identified (95%), and had at least a Bachelor degree (55%). Nearly half (46.3%) earned $50,000 or more annually and the sample was almost evenly split by relationship status. Ages ranged from 18–79 years (M = 40.2, SD = 13.8). In total, 387 (37.5%) men reported no syndemic conditions, 325 (31.5%) reported one, 217 (21.0%) reported two, 76 (7.4%) reported three, and 28 (2.7%) reported four or five conditions. Table 1 displays demographic characteristics as well as comparisons of the percentage of participants within each demographic grouping reporting more than the median number of syndemic conditions (the grand median was 1) as utilized within the median tests. Syndemics were significantly more common among men at the lower levels of income and education as well as among those in non-urban areas. Also, age was inversely correlated with syndemic conditions, r = −0.12, p <.001.

Table 1.

Demographics and Percentage of Men Above the Grand Median of the Number of Syndemic Conditions, N = 1033

n % Comparison of Syndemic Conditions
Percentage above the median Interquartile Range Median Test χ2
Race and ethnicity
 Black/African American 78 7.6 30.8 0–2 6.00
 Latino 129 12.5 38.8 0–2
 White 741 71.7 29.1 0–2
 Multiracial/Other 85 8.2 36.5 0–2
Relationship status
 Single 526 50.9 31.2 0–2 .01
 Partnered 507 49.1 30.0 0–2
Sexual orientation
 Gay 979 94.8 30.6 0–2 1.62
 Bisexual 54 5.2 38.9 0–2
Income
 Below $20K 203 19.7 39.4a 1–2 28.36***
 Between $20–50K 356 34.5 37.4a 0–2
 Above $50K 474 45.9 22.8b 0–1
Education
 High School or less 77 7.5 39.0a 0–2 12.00**
 Some college 381 36.9 35.2a 0–2
 Bachelor degree 302 29.2 30.5a 0–2
 Graduate school or more 273 26.4 23.8b 0–1
Geographic region
 Northeast 197 19.1 32.5 0–2 .25
 South 366 35.4 30.3 0–2
 Midwest 188 18.2 30.9 0–2
 West 282 27.3 30.9 0–2
Urban vs. non-urban
 Urban 906 87.7 29.9a 0–2 4.65*
 Non-urban 127 12.3 39.4b 0–2
M SD
Age (years) 40.5 13.9
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Note.

*

p < 0.05;

**

p < 0.01;

***

p < 0.001;

Grand median = 1; Groups with different superscripts differ at p < .05.

Overall, 389 (37.7%) men reported recent HIV transmission risk behavior. The percentages of participants reporting recent sexual HIV transmission risk, grouped by number of syndemic conditions, are depicted in Figure 1. HIV transmission risk behavior was most commonly reported by those reporting three or more syndemic conditions. Table 2 shows comparisons between urban and non-urban participants for each syndemic condition, and having engaged in recent HIV transmission risk behavior. As mentioned, urban and non-urban participants differed significantly on the number of syndemic conditions they experienced, and these findings indicate this may be primarily driven by differences in sexual compulsivity.

Figure 1.

Figure 1

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Percentage of participants reporting recent (past 90 day) sexual HIV transmission risk behavior by number of syndemic conditions

Table 2.

Comparisons of Syndemic Prevalence Between Urban and Non-Urban Gay and Bisexual Men, N = 1,033

Urban (n = 906)
Non-urban (n = 127)
Test Statistic
n % n % χ2(1)
Syndemic health conditions
 Polydrug use 73 8.1 9 7.1 0.14
 Depression 234 25.8 42 33.1 2.98
 Childhood sexual abuse 180 19.9 34 26.8 3.23
 Intimate partner violence 338 37.3 48 37.8 0.01
 Sexual compulsivity 115 12.7 28 22.0 8.17**
HIV transmission risk behavior (past 3 months) 341 37.6 48 37.8 0.00
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Note.

*

p < 0.05;

**

p < 0.01;

***

p < 0.001;

Table 3 displays bivariate associations, expressed as odds ratios, showing that almost all of the syndemic conditions were associated with each other (except for polydrug use and childhood sexual abuse, and polydrug use and sexual compulsivity), and that each syndemic condition (except for childhood sexual abuse) was independently associated with having engaged in recent HIV transmission risk behavior.

Table 3.

Bivariate Associations Among Syndemic Conditions and Sexual HIV Transmission Risk Behavior

Depression Childhood Sexual Abuse Intimate Partner Violence Sexual Compulsivity HIV Transmission Risk Behavior
OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI)
Polydrug Use 1.65* (1.03, 2.65) 1.45 (0.87, 2.42) 2.42*** (1.54, 3.83) 1.07 (0.57, 2.03) 2.82*** (1.78, 4.48)
Depression --- 1.57** (1.14, 2.17) 2.42*** (1.83, 3.21) 2.97*** (2.07, 4.27) 1.40* (1.05, 1.85
Childhood Sexual Abuse --- 1.84*** (1.36, 2.50) 2.20*** (1.50, 3.24) 1.17 (0.86, 1.60)
Intimate Partner Violence --- 1.74** (1.22, 2.49) 1.41** (1.09, 1.83)
Sexual Compulsivity --- 2.55*** (1.78, 3.66)
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Note.

*

p < 0.05;

**

p < 0.01;

***

p < 0.001;

OR = odds ratio

Table 4 displays the results of six binary logistic regression models. The first five models show each of the individual syndemic conditions predicted by age, education, race and ethnicity, relationship status, income, and urbanicity, and each of the other syndemic conditions. The sixth model shows the odds of recent HIV transmission risk behavior predicted by the same covariates as above and each of the five syndemic conditions. Only intimate partner violence and younger age was associated the odds of polydrug use (Model 1), while depression was associated with intimate partner violence, sexual compulsivity, lower income, younger age, and being single (Model 2). The odds of reporting childhood sexual abuse was associated with intimate partner violence, sexual compulsivity, lower education and income, older age, and non-White race/ethnicity (Model 3). Intimate partner violence was associated with polydrug use, depression, childhood sexual abuse, lower income, younger age, and being partnered (Model 4), while sexual compulsivity was associated with depression, childhood sexual abuse, and non-urban status (Model 5). With the inclusion of all five syndemic conditions, having recent sexual HIV transmission risk was associated with polydrug use, sexual compulsivity, being Latino, and being single (Model 6).

Table 4.

Regressions Among Syndemic Conditions Among Gay and Bisexual Men, N = 1,033

Model 1: Polydrug Use Model 2: Depression Model 3: Childhood Sexual Abuse Model 4: Intimate Partner Violence Model 5: Sexual Compulsivity Model 6: HIV transmission risk behavior
AOR 95% CI AOR 95% CI AOR 95% CI AOR 95% CI AOR 95% CI AOR 95% CI
Age (years) .96*** .94, .98 .99* .98, 1.00 1.02** 1.01, 1.03 .98** .97, .99 1.01 1.00, 1.03 1.00 .99, 1.01
Education
 < College .38 .11, 1.30 1.66 .96, 2.89 1.88* 1.07, 3.32 .71 .41, 1.21 1.16 .58, 2.32 1.12 .66, 1.89
 Some college 1.02 .62, 1.70 1.33 .96, 1.84 1.52* 1.08, 2.14 .85 .63, 1.14 1.08 .72, 1.62 1.01 .76, 1.36
 > Degree (ref) 1.00 1.00 1.00 1.00 1.00 1.00
Race and ethnicity
 Black 1.51 .67, 3.41 .77 .43, 1.39 2.04* 1.18, 3.54 .75 .44, 1.27 .97 .46, 2.01 .75 .45, 1.27
 Latino 1.25 .66, 2.39 .95 .60, 1.50 1.77* 1.12, 2.81 1.19 .79, 1.79 .87 .48, 1.59 1.61* 1.08, 2.24
 Other 1.01 .45, 2.27 .99 .58, 1.69 1.80* 1.03, 3.14 .82 .50, 1.34 1.35 .71, 2.58 .85 .52, 1.40
 White (ref) 1.00 1.00 1.00 1.00 1.00 1.00
Relationship status
 Single 1.29 .80, 2.07 1.74*** 1.28, 2.37 .79 .57, 1.08 .70* .53, .92 .77 .53, 1.12 2.02*** 1.54, 2.66
 Partnered (ref) 1.00 1.00 1.00 1.00 1.00 1.00
Income
 Less than $50K .63 .37, 1.09 1.98*** 1.41, 2.80 1.52* 1.06, 2.18 1.42* 1.05, 1.92 .87 .57, 1.33 .97 .72, 1.31
 $50K or more (ref) 1.00 1.00 1.00 1.00 1.00 1.00
Urban
 Non-urban 1.02 .48, 2.16 1.16 .75, 1.80 1.23 .78, 1.94 .88 .58, 1.33 1.72* 1.05, 2.82 .95 .63, 1.43
 Urban (ref) 1.00 1.00 1.00 1.00 1.00 1.00
Syndemic condition
 Polydrug use ------ 1.32 .79, 2.21 1.38 .80, 2.39 2.06** 1.27, 3.34 .96 .49, 1.89 2.66*** 1.63, 4.32
 Depression 1.33 .80, 2.23 ------ 1.18 .83, 1.70 2.07*** 1.52, 2.81 2.95*** 1.98, 4.38 1.00 .73, 1.37
 CSA 1.42 .82, 2.45 1.20 .84, 1.72 ------ 1.71** 1.24, 2.38 1.87** 1.24, 2.82 1.01 .73, 1.42
 IPV 2.06** 1.27, 3.33 2.07*** 1.52, 2.81 1.71** 1.23, 2.38 ------ 1.43 .97, 2.10 1.26 .95, 1.67
 SC .97 .49, 1.89 2.95** 1.98, 4.38 1.86** 1.24, 2.81 1.45 .98, 2.12 ------ 2.72*** 1.86, 3.99
Model statistics
% correctly classified 92.1% 74.5% 79.8% 66.3% 86.4% 66.4%
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Note.

*

p < 0.05;

**

p < 0.01;

***

p < 0.001;

AOR = adjusted odds ratio; ref = referent group; CSA = childhood sexual abuse; IPV = intimate partner violence; SC = sexual compulsivity

Discussion

We examined the association between five syndemic conditions (polydrug use, depression, childhood sexual abuse, intimate partner violence, and sexual compulsivity) and recent HIV transmission risk behavior in a national sample of HIV-negative gay and bisexual men, finding further evidence that these factors intersect to exacerbate risk for HIV transmission. Among men reporting three or more syndemic conditions, more than 59% reported some recent HIV transmission risk behavior, while the lowest rates were observed among those reporting no syndemic conditions (less than 30%).

In addition, our findings provide further support for the inclusion of sexual compulsivity as among the nexus of syndemic conditions (Parsons et al., 2012). To our knowledge, the 2012 study of gay and bisexual men in New York City (data were collected in 2003–2004) was the first to demonstrate that sexual compulsivity could be a syndemic factor and other studies have produced similar findings in urban samples of gay and bisexual men (Dyer et al., 2012; Parsons et al., 2015). The present study is the first to have done so in a geographically diverse sample of HIV-negative gay and bisexual men in the United States.

These findings highlight the need to approach HIV transmission and high-risk sexual behavior within the context of overlapping health problems and to explore factors underlying these negative conditions. HIV transmission risk is not a function particularly of single syndemic factors but of the compounding of syndemic stressors. This fact points to the need for integrated interventions which are capable of addressing multiple syndemic factors within the same treatment. Alternatively, or in addition, this finding points to the need to identify common processes or deficits (such as difficulties with emotion regulation or minority stress) which may cut across syndemic condition and serve as mechanisms by which compounded syndemic problems confer risk. Such mechanisms would make prime targets for intervention. All told, the results of this study underscore the need to holistically approach HIV prevention as well as identify factors that foster resilience in the face of adversity (Herrick et al., 2011; Herrick, Stall, Goldhammer, Egan, & Mayer, 2014; Parsons et al., 2012). Although increases in syndemic conditions were positively associated with HIV transmission risk behavior, and 61.5% of men experiencing four or more syndemic factors reported HIV transmission risk behavior, it is equally important to investigate the resilient factors that prevented 38.5% of men with high levels of syndemic experiences from having also engaged in HIV transmission risk behavior.

To our knowledge, this was also the first study to compare syndemic conditions across urban and non-urban settings. We found that, although rates of polydrug use, depression, childhood sexual abuse, intimate partner violence, and HIV transmission risk behavior did not vary with respect to urbanicity, rates of sexual compulsivity and the experience of syndemic burden were found to be higher among men in non-urban settings. Our findings may be explained by the presence of sexual minority stress. Sexual minority stress is positively associated with sexual compulsivity (Pachankis et al., 2015, Rendina, Gamarel, Pachankis, Ventuneac, Grov, & Parsons, 2016), and the overall syndemic burden is higher among those who have a history of sexual orientation based adverse life events (Herrick et al., 2013). Previous research has demonstrated LGBT individuals living in non-urban communities experience greater rates of sexual orientation based discrimination, harassment, and victimization, as well as internalized stigma compared to LGBT individuals living in urban communities (Swank et al., 2012). This highlights the need for resources and care for gay and bisexual men in non-urban settings where lesbian, gay, bisexual, and transgender (LGBT) populations are likely to be smaller and where there may be fewer LGBT-affirming resources available to address syndemic conditions. Unfortunately, it is beyond the scope of the present study to have investigated the actual uptake of care among those in need and whether those participants felt such care was LGBT-affirming.

The rate of syndemics in the present study is similar to those published in a cross-sectional street-intercept study of gay and bisexual men in New York City (Parsons et al., 2012). In the present study, approximately 37.5% of men reported experiencing no syndemic conditions compared to 35% in the New York City study, and 10.1% reported experiencing 3 or more syndemic conditions compared to 9.4% in the New York City study. The rates observed in the present study are much lower than those in a recent study of highly sexually active gay and bisexual men in New York City, where only 7.9% of men reported experiencing no syndemic conditions and 43.4% reported experiencing 3 or more syndemic conditions (Parsons et al., 2015). One reason for the difference in rates may be the substantially higher rates of sexual compulsivity in the sample of highly sexually active gay and bisexual men. Conversely, the level at which men experienced two or more syndemic conditions (31.4%) appears to be higher in the present study compared to the early syndemic research on urban men who have sex with men (18%; Stall et al., 2003). In the study by Stall et al., sexual compulsivity was not assessed as a syndemic factor which may explain why 52% of the sample in this early research reported not experiencing any syndemic conditions. Rates from other studies are hard to compare as some have included multiple substance use categories (Mimiaga et al., 2015; Mustanski et al., 2007) and others have included multiple forms of stress as individual syndemic conditions (Ferlatte et al., 2014; Herrick et al., 2013). Taken together, the findings from the present study may be generalizable to the wider population of gay and bisexual men more broadly but that elevated rates would be expected in samples recruited based on perceived risk (e.g., high levels of sexual activity).

Results of regression analyses point to both the potential utility and limitations of syndemics theory to explain demographic disparities in HIV incidence. Younger age, lower income, and non-White racial or ethnic identity were all significant predictors of one or more syndemic factors and these demographic variables have well documented associations with HIV incidence (CDC, 2015b). At the same time, Latino ethnic identity and relationship status accounted for HIV incidence above and beyond syndemic factors, suggesting that syndemics alone do not account fully for all demographic disparities in incidence.

Limitations

Our findings should be understood in light of their limitations. Although geographically diverse, our sample was entirely HIV-negative, thus we cannot attest to the experience of HIV-positive individuals—however, the exploration of syndemics among HIV-positive individuals has been conducted in previous research (Mustanski et al., 2007; Parsons et al., 2012; Parsons et al., 2015; Santos et al., 2014). In fact, we intentionally enrolled an entirely HIV-negative sample because tracking seroconversions is an outcome of the larger study. The One Thousand Strong cohort was enrolled to match geographic diversity of gay and bisexual men in the U.S. and, to some extent, also mirrors the racial and ethnic composition of the U.S. population. It does not, however, reflect the ongoing racial and ethnic disparities in HIV burden among gay and bisexual men and, in fact, many men of color who would have otherwise been eligible were excluded during the enrolment process due to already being HIV-positive (Grov et al., 2016). Our response rate among those who opened the initial email about the study was comparable with other similar studies on national GBM samples—for example, 71.7% in Coleman, Horvath, Miner, Ross, Oakes, and Rosser (2010), 75.5% in Rosenberger et al. (2011), and 73.8% in Wagenaar, Sullivan, and Stephenson (2012)—as was our rate of unopened emails (e.g., Voytek et al., 2012). However, we also recognize that the sample is not representative of those who choose not to participate in research studies, including those who are not “out” about their sexual behavior with men. Additionally, our participants’ involvement in the study required stable residence and access to the internet, which may also limit the representativeness of the sample.

Data were taken from closed-ended computerized surveys. Other methods of data collection, including qualitative methods, or the use of different quantitative measures for capturing syndemic conditions (e.g., other indicators of depression) could have elucidated different nuances. Further, syndemics as an approach to holistically understanding HIV transmission is also not without its limitations. Specifically, some syndemics (i.e., childhood sexual abuse) lack a discrete intervention point. That is, given that the childhood sexual abuse would have occurred in years or even decades past, and at a time in which participants may not have come out as gay or bisexual, there is an inability to have intervened and prevented childhood sexual abuse from occurring. Thus, instead of focusing on the absence or presence of childhood sexual abuse, clinicians might be well served to focus on present-day trauma (presence/severity) resultant from this abuse (O’Cleirigh, Safren, & Mayer, 2012).

Next, our findings indicated that syndemic conditions intersect to compound risk for HIV transmission behavior, but our analysis was limited in that we examined additive effects (e.g., totalling the number of syndemic conditions). Although this resulted in significant findings, we also recognize that simply adding up conditions based on their absence/presence discounts the relatively magnitude that any one condition can exert or the synergy that could occur when specific conditions coincide—for example, depression and childhood sexual abuse are both treated as two conditions (a value of 2), much as polydrug use and intimate partner violence are, but the combined effect of these could act differently. Additionally, the various drugs that constitute the polydrug variable are not expected to be equally influential on outcomes, as some substances may be more associated with risk than others. The identification and addressing of processes that cut across multiple syndemic conditions may represent a valuable direction for future research.

Conclusions

The present study found that, among a U.S. national sample of gay and bisexual men, the presence of each syndemic condition (except for childhood sexual abuse) and a greater number of co-occurring conditions were associated with greater likelihood of reporting recent HIV transmission risk behavior, particularly among those with three or more syndemic conditions. Further, those men in non-urban areas and those with less income and education were more likely to experience a higher number of syndemic conditions, suggesting that a lack of access to resources may exacerbate the impact of these problems faced by gay and bisexual men. The need for integrated interventions to better address the mental health needs, substance use behaviors, and dynamics of interpersonal violence that are experienced by many gay and bisexual men, with an awareness of how these different experiences may co-occur or be linked, remains a vital focus in research, policy, and service provision, in the effort to reduce HIV infection rates among this disproportionately affected group. This need, however, may be greatest among men who live outside urban areas as they are likely to have substantially less in the way of LGBT-focused resources and culturally sensitive providers.

Acknowledgments

The One Thousand Strong study was funded by NIH/NIDA (R01 DA 036466: Jeffrey T. Parsons & Christian Grov, MPIs). We would like to acknowledge other members of the One Thousand Strong Study Team (Dr. Ana Ventuneac, Demetria Cain, Mark Pawson, Ruben Jimenez, Chloe Mirzayi, and Thomas Whitfield) and other staff from the Center for HIV/AIDS Educational Studies and Training (Andrew Cortopassi, Chris Hietikko, Doug Keeler, Chris Murphy, Carlos Ponton, and Brian Salfas). We would also like to thank the staff at Community Marketing and Insights, Inc. (David Paisley, Thomas Roth, and Heather Torch). Finally, special thanks to Dr. Jeffrey Schulden and Pamela Goodlow at NIDA. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Sources of Funding:One Thousand Strong was funded by the National Institutes of Health (R01 DA 036466: Parsons & Grov). Raymond L. Moody’s effort was funded by the National Institute of Drug Abuse (R01 DA 036466-S2; Parsons & Grov). H. Jonathon Rendina was supported by a National Institute on Drug Abuse Career Development Award (K01 DA039030).

Footnotes

Conflict of Interest: All authors declare that they have no conflict of interest.

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