HHS Public Access Author manuscript Author Manuscript AIDS Behav. Author manuscript; available in PMC 2021 August 01. Published in final edited form as: AIDS Behav. 2020 August ; 24(8): 2327–2335. doi:10.1007/s10461-020-02792-7. Sex partner behavior variation related to network position of and residential proximity to sex partners among young black men who have sex with men Yen-Tyng Chena,b, Rodal S. Issemaa,b, Anna Hottona,b, Aditya S. Khannaa,b, Babak M. Ardestania,b, John A. Schneidera,b,c, Abby Rudolphd Author Manuscript aChicago Center for HIV Elimination, Chicago bDepartment of Medicine, University of Chicago cDepartment of Public Health Sciences, University of Chicago dDepartment of Epidemiology and Biostatistics, College of Public Health, Temple University Abstract Author Manuscript This analysis examines how sex behaviors are influenced by a sex partner’s network bridging position and the residential proximity between the two. The study sample consisted of 437 young black men who have sex with men (YBMSM) in Chicago and their sex partners (2013-2014). Dyadic analyses that clustered on individuals using generalized estimating equations (n=1095 relationships) were conducted to assess the associations between different HIV-related sexual behaviors and the network position of and residential proximity to a partner. The odds of group sex was higher with partners who had high network bridging, regardless of how close they lived to one another. The odds of transactional sex was higher with partners who had high network bridging and lived in a different region of the city. Sex behaviors associated with an increased risk of HIV transmission were associated with the network structural position of and residential proximity to partners among YBMSM. Keywords men who have sex with men; sexual behaviors; social network analysis; African-American; geography Author Manuscript INTRODUCTION Young black men who have sex with men (YBMSM) bear a significant burden of the HIV epidemic in the United States. As estimated, 1 in 2 YBMSM are expected to be infected by HIV during their lifetime (1). Evidence has shown that the high HIV infection risk among YBMSM is not explained by individual-level risk behaviors (2). YBMSM often engage in less condomless sex, less drug use during or prior to sex, and have fewer sex partners Corresponding author: Yen-Tyng Chen, Department of Medicine, University of Chicago, 5841 S Maryland Ave, MC 5065, Chicago, IL 60637, Tel: 773-702-9977, Fax: 773-702-8998, ychen22@medicine.bsd.uchicago.edu; yenting1219@gmail.com. Chen et al. Page 2 Author Manuscript compared to their white counterparts (3, 4). Accordingly, the high HIV infection risk among YBMSM may be in part due to an interaction between the people with whom they interact and places where they spend time (2, 5–8). There is a growing emphasis on the need for research to understand factors that increase HIV risk among YBMSM from both network and spatial perspectives (5). Author Manuscript Network factors may explain the increased HIV burden among YBMSM in the context of safer sex behaviors (3, 9). Past research among YBMSM has found that HIV-related sex behaviors with a partner may be influenced by the demographic characteristics of their sex partner (e.g., age, race), partner type, and assortative mixing on risk behaviors (e.g., individuals who use drugs during or prior to sex also have a sex partner who also uses drugs during or prior to sex) (3, 7, 10, 11). The role of network structural position has recently been highlighted as relevant for HIV prevention and intervention among YBMSM (12–15). Individuals who hold bridging positions connect people who are not directly in contact with one another. Thus, those who act as network bridges can facilitate HIV transmission or the flow of intervention information between two distinct clusters of people who would otherwise not be connected (12, 16). In the context of HIV prevention, bridging positions have been used to select peer change agents to diffuse HIV pre-exposure prophylaxis (PrEP) prevention information because people who are a bridge are more likely to exhibit leadership traits within their networks and are able to intervene with MSM not typically identified within HIV prevention intervention (12, 15, 17). Author Manuscript From a spatial perspective, the HIV burden is often clustered in specific geographic areas and HIV clusters are often more common in neighborhoods that are predominately Black/ African American. Geographic proximity to an HIV “hot spot” plays an important role in HIV transmission. For example, in Chicago, the south side neighborhoods have the highest HIV prevalence and are also the areas where most YBMSM reside or spend time. If YBMSM select sex partners who also reside or spend time in the same high burdened neighborhoods or who are of the same race, the risk of HIV acquisition could be higher because the probability of partners being HIV-infected is higher in both of these scenarios. Author Manuscript Furthermore, an individual’s HIV transmission behaviors may differ based on whether or not a partner is a bridge and/or whether the two reside in the same neighborhood. Bridging relationships may include weaker ties than non-bridging relationships and bridging relationships may decay faster than non-bridging relationships (18). Therefore, bridging relationships tend to be less stable in terms of both duration and strength. In addition, geography can act as a boundary that fosters or constrains the formation of sex partnerships (19, 20), which in turn may also influence the strength of the relationship and the risk behaviors in which the two engage. Residing in close geographic proximity to a sex partner may result in relationships with more mutual control and commitment in part due to the shared physical/social environments (e.g., the partner knows a person’s family and friends in the area) (21). For example, having a sex partner living in close geographic proximity and who have common sex partners may increase mutual trust and familiarity and may, in turn, be associated with less likelihood of engaging in sexual behaviors that could increase the risk of HIV transmission/acquisition (21, 22). This scenario can occur in places like South AIDS Behav. Author manuscript; available in PMC 2021 August 01. Chen et al. Page 3 Author Manuscript Chicago (the largest contiguous urban black community in the US) (23) where BMSM in this area are predominately longtime residents (19). Although past research has suggested that sexual behaviors are influenced by both network features and space, limited research has examined how an individual’s sexual behaviors with a partner may be influenced by the partner’s network structural position and the residential proximity between the two. In this paper, we examine how a sex partner’s network bridging position and the residential proximity between an individual and their sex partner may be associated with an individual’s sexual behaviors with that partner. We hypothesize that condomless anal sex, using drugs during sex, group sex, transactional sex, and serodiscordant partnerships are more common with sex partners who are network bridges and who do not live in the same area than with sex partners who are not network bridges and who reside in the same area. Author Manuscript METHODS Sample and Data Collection Author Manuscript The data for this analysis were collected through a baseline assessment (n=618, 2013-2014) in the uConnect Study, a longitudinal cohort study which examined behavioral and social correlates of HIV among YBMSM in Chicago. The methods of uConnect have been described in detail elsewhere (9). In brief, respondent-driven sampling was used to recruit YBMSM who spent a majority of their time in South Chicago. Collectively, this region is one of the largest Black communities in the US and has a high HIV prevalence (23, 24). Study respondents were eligible to participate if they 1) self-identified as African American or Black, 2) were assigned male sex at birth, 3) were between 16 and 29 years of age, 4) reported oral or anal sex with a male within the past 24 months, 5) spent the majority of their time in South Chicago, and 6) were willing and able to provide informed consent at the time of the study visit. For this analysis, we excluded participants who identified as female and/or transgender (n=48). UConnect used a personal network inventory to collect the names (i.e., first name, last name, and nick name) of both confidants and sex partners over the past 6 months through an interviewer-administered survey. The current analysis focused only on the sex network. Specifically, participants were asked, “thinking back over the past six months, that is since Author Manuscript [month], how many people, including men, women, and transgender women have you had sexual activity with, even if only one time?” Once the names of the sex partners were generated, participants were asked to describe each partner with respect to demographic characteristics (e.g., age, race, and sexual orientation), relationship-level characteristics (e.g., type of sex partner), and sexual behaviors with that partner (e.g., group sex, transactional sex, drug use during or prior to sex). We additionally asked each individual to report on whether the sex partners listed were known to have sex with one another. We used a fuzzy matching algorithm as previously described (13) to determine when a sex partner named was also a study participant. Furthermore, we added the sexual relationships that existed between named sex partners based on the network inventory survey questions. The resulting sociometric network consisted of all connections that exist between study participants in AIDS Behav. Author manuscript; available in PMC 2021 August 01. Chen et al. Page 4 Author Manuscript addition to the ties that exist between named sex partners. Institutional Review Board approval was obtained for the study protocols. Measures Author Manuscript Network bridging position.—To measure bridging, we used Burt’s constraint score. Valente and Fujimoto suggest that Burt’s constraint score can be a measure for bridging when complete network information is not available (16). The constraint measure, proposed by Burt, is a technique to identify “structural holes” in a social network (25). Structural holes are individuals who connect non-redundant sources of information in a social network. A constraint index measures an individual’s access to structural holes. (26) A lower constraint score indicates an individual whose access to information is less constrained, and therefore represents higher network bridging. A higher constraint score indicates an individual whose access to information is more constrained, and therefore represents lower network bridging. The influenceR package in R was used to compute the constraint measure (27). Network bridging position was dichotomized based on the distribution of the constraint score with a cut-off score at 1. High network bridging was defined by constraint scores lower than 1 (around the lowest 20% of the constraint scores). Author Manuscript Author Manuscript Residential proximity.—We asked participants to report their and their sex partners’ home locations (e.g., cross-streets, neighborhoods). If participants were homeless, we asked the locations where they had slept most often in the past 7 days. Residential proximity was defined as whether a sex partner lived in the same “Chicago region” as the participant. Chicago is divided into 9 “regions” based on the 77 well-established Chicago community areas. The regions represent subdivisions of the city and generally reflect the socioeconomic environments of the community areas that make up the Chicago region. For example, the “south side region” is comprised of 12 Chicago community areas and is one of the most socially and economically disadvantaged areas in Chicago. Because most participants did not provide complete addresses for their and their sex partners’ home locations, we included participants and their sex partners where their residential “Chicago region” or their residential proximity can be identified so more participants and their sex partners could be included in the analysis. An important consideration for this analysis is that although the uConnect Study participants were only eligible to participate in the study if they lived in or spent a majority of their time in South Chicago (i.e., includes the south region, southeast region, and southwest region), partners could live anywhere in Chicago. Consequently, 72% of the sex dyads reside in distinct Chicago region. Two hundred twenty-seven sex partners (i.e., 17% of the 1322 sex partners listed in the personal network inventory) were dropped from the analyses due to missing information on their residential location, as this information was required to compute dyad residential proximity. Combined bridging position and residential proximity.—We created a categorical variable with four categories to represent the unique combinations of residential proximity and bridging position for each sex partner. Sex partners were categorized as: (1) low network bridging and live in the same region of Chicago, (2) low network bridging and do not live in the same region of Chicago, (3) high network bridging and live in the same region of Chicago, and (4) high network bridging and do not live in the same region of Chicago. AIDS Behav. Author manuscript; available in PMC 2021 August 01. Chen et al. Page 5 Author Manuscript Outcomes.—We measured five dichotomous outcomes which were defined as whether or not participants engaged in each of the following sexual behaviors with each listed sex partner in the past 6 months: any condomless anal sex (yes vs. no), using drugs during or prior to sex (defined as using non-injection drug or alcohol during or prior to sex; yes vs. no), any group sex (yes vs. no), any transactional sex (defined as paying or receiving money, drugs, shelter, or other good for sex; yes vs. no), and serodiscordant or serostatus unknown partnerships (yes vs. no). A serodiscordant or serostatus unknown partnership was defined as those with at least one person in the relationship living with HIV or having an unknown serostatus (individual or sex-partner) while the other was not living with HIV. Individual study participant’s HIV status was confirmed through testing during survey and sex partners’ HIV status was based on a report from the individual who listed them (i.e. the participant’s perception of their partner’s HIV status). All of these five outcomes were at the individual level and were reported for each specific sex partner. Author Manuscript Author Manuscript Covariates.—We included participants’ demographic characteristics, including age, educational attainment, sexual orientation, annual income, housing instability (measured by “what type of residence do you currently live in” and defined as rented room in hotel, stayed in shelter/halfway house, stayed in an apartment/ house for which they did not pay rent or they did not own or had no regular residence), having more than one main partner (yes vs. no), HIV status based on testing during survey visit, and sexual concurrency. Sexual concurrency was defined as the count of sexual partnerships within the past 6 months that overlapped based on the month and year of the first and last sexual intercourse with each sex partner. For sex partner characteristics, we included sex partners aged ≥10 years older than the participant, sex partner’s gender, and whether sex partner is the main partner. We also controlled for whether a sex partner was also a study participant or listed as a confidant (i.e. more than one relationship role). Analysis Author Manuscript Descriptive statistics of socio-demographic characteristics of the participants and their sex partners were summarized. Chi-square statistics (and Fisher’s Exact tests when cell counts were below 5) were used to assess statistically significant differences in partner characteristics across groups. Bivariate analyses were conducted to explore factors associated with each of the behavioral outcomes. Multivariable logistic regression analyses were performed to determine the joint effect of the partner’s bridging network position and residential proximity on the behavioral outcomes in each relationship using STATA 14.2 (StataCorp LP, Texas), was used To account for the fact that individuals reported multiple sex partners, we used a generalized estimating equation (GEE) logistic regression model with an exchangeable correlation structure and robust estimation of standard errors. The correlations from the exchangeable structure in the GEE model were 0.25 for condomless anal sex, 0.49 for sex drug use, 0.20 for group sex, 0.11 for transactional sex, and 0.32 for serodiscordant or serostatus unknown. AIDS Behav. Author manuscript; available in PMC 2021 August 01. Chen et al. Page 6 Author Manuscript RESULTS Author Manuscript Our sample included 437 individuals and 1095 sex partners (125 out of 1095 were also study participants) from the baseline study. Specific to this sample, the overall mean age of study participants was 23 (range 16-29), 67% identified as gay, 24% had unstable housing at the time of completing the survey, 41% were HIV-positive, and the mean count of sexual partnerships that overlapped with another sexual partnership was 1.6 (Table 1). Table 2 shows the characteristics of sex partners stratified by sex partners’ network bridging and residential proximity to the study participant who listed them. Among the four strata of network bridging and residential proximity, the largest group is comprised of sex partners who had low network bridging and who lived in a different region of Chicago from the individual who listed them (n=647; 60 % of all sex partners); the smallest group is comprised of sex partners who had a high network bridging position and who lived in the same region of Chicago as the individual who listed them (n=98; 9% of the total sex partners). The distribution of sex partner gender and presence of alcohol or drug use during or prior to sex between sex partner and the individual who listed them were similar across the four strata; the distribution of sex partner’s age, whether sex partner was the main partner, whether the sex partner was also a confidant, condomless anal sex, group sex, and serodiscordant or serostatus unknown partnership significantly varied across the specific combinations of network bridging and residential proximity. For example, group sex was more common with sex partners who had a higher network bridging scores (18%-21%) than it was with sex partners who had a low network bridging score (about 6%). The proportion of sex partners who were transactional partners was higher among sex partners who lived in a different region of Chicago (9-11%) than it was among sex partners who lived in the same region of Chicago (about 5%) as the participant. Author Manuscript Author Manuscript After adjusting for individual and sex partner characteristics, Table 3 displays the odds of engaging in different sexual behaviors with that partner based on the sex partner’s network position and whether the two lived in the same or different regions of Chicago. Individuals had a higher odds of engaging in group sex with sex partners who had a high network bridging position, regardless of whether or not they lived in the same region of Chicago. The adjusted odds ratio was 4.33 (95% CI: 1.52-12.35) times higher for sex partners who had a high network bridging position and lived in the same region of Chicago as the participant who listed them versus for sex partners who had a low network bridging position and lived in the same region of Chicago; the adjusted odds ratio was 3.73 (95% CI: 1.39-10.06) times higher for sex partners who had a high network bridging and lived in a different region of Chicago versus for sex partners who had a low network bridging position and lived in the same region of Chicago. Individuals had a higher odds of engaging in transactional sex with sex partners that had a high network bridging position and lived in a different region of Chicago (AOR=2.77, 95% CI: 1.07-7.18). The sex partner’s network position and/or residential proximity to the participant were not significantly associated with condomless anal sex, using alcohol or drugs during or prior to sex, or having serodiscordant or serostatus unknown sex partnerships. AIDS Behav. Author manuscript; available in PMC 2021 August 01. Chen et al. Page 7 Author Manuscript DISCUSSION Our findings demonstrate that YBMSM in Chicago have a higher odds of engaging in transactional sex with sex partners that are network bridges and live in a different area of Chicago. In addition, we found that group sex was more likely with partners who had high network bridging positions and that this association did not differ for partnerships where both lived in the same neighborhood vs. different neighborhoods. Author Manuscript Author Manuscript With respect to transactional sex, being a bridge and not living in close proximity may make the sexual relationship weaker and more unstable. A sex partner who is living in a distinct neighborhood and who occupies a bridging position may have fewer mutual friends with the participant and may have more sex partners who are part of a distinct network from the participant. Both the lack of mutual acquaintances and distinct networks of sex partners could be associated with higher risk transactional sex among the pair. By unpacking this transactional relationship further, we found that participants were more likely than their partners (who had high bridging positions) to be the ones receiving money or other goods; participants were also younger and more likely than their sex partners to live in more disadvantaged neighborhoods, to make less money, to have unstable housing. Thus, participants in more vulnerable positions (i.e., live in more disadvantaged neighborhoods, have fewer resources) were more likely to exchange sex for goods or money with partners who had more connections to non-mutual contacts. In this context, the participant may be less able to negotiate safer behaviors and could potentially be a greater risk for HIV acquisition with a person who is well-connected to distinct networks of people. This finding is broadly consistent with past research suggesting that both individual and structural social and economic disadvantage are associated with a greater likelihood of transactional sex as a means to gain access to basic needs or access to a particular social community (28–30). Our findings highlight the need for future research that further examines the relationship of both social and spatial bridges with transactional sex among YBMSM. Author Manuscript Our findings on the relationship between bridging position and group sex behavior provide new insights. Regardless of a sex partner’s residential proximity, we found that YBMSM had a higher odds of engaging in group sex with sex partners who occupied a bridging position. This indicates that group sex may not necessarily be more likely to happen with bridging sex partners. Rather, group sex is more likely to happen with a sex partner who has few interconnected sex partners and more otherwise unconnected sex partners. Individuals can quickly be introduced to other anonymous sex partners or sex partners who are less known to the individuals through the bridging sex partner in the group sex events or sex parties. However, the mechanism through which bridging position is associated with group sex is contrary to what we would expect (i.e., we expect that engage in group sex through a bridge whom an individual is less likely to know). We found that participants had a higher odds of engaging in group sex with sex partners who were also listed as their confidant and were 10 years older than them. It is possible that individuals may be more comfortable to seek previous unconnected sex partners during group sex events or parties through someone they already know. It is also possible that participants had to name sex partners and those named sex partners were more likely well known than those who were not named, who they had forgotten, or who were anonymous. However, further examination is needed to further AIDS Behav. Author manuscript; available in PMC 2021 August 01. Chen et al. Page 8 Author Manuscript understand the contexts of group sex based on the interplay between network position and space. Author Manuscript Author Manuscript We did not find differences in condomless anal sex, using drugs during sex, and serodiscordant sexual partnerships based on the network position of the partner or the residential proximity between the pair. Condomless anal sex and using drugs before or during sex may be more strongly influenced by the perceived risk of HIV transmission/ acquisition with a particular partner based on individual (i.e., their own HIV status and viral load, whether or not they are on PrEP) and partner attributes (i.e., perceived HIV status, viral load of HIV positive partner, etc.). For example, past research has indicated that YMSM use rational decision-making strategies to decide whether to engage in condomless anal sex by calculating the risk of HIV transmission based on partners’ PrEP use or viral load (31). As seen in Table 3, individuals had a higher odds of engaging in condomless anal sex with main partners and confidants, suggesting that relationship-level attributes such as trust, intimacy, etc. may also play a role in an individual’s decision regarding condom use. Similarly, using drugs during sex has also been shown to be related to an individual-level decision-making processes in which MSM consider both psychological and physical concerns (e.g., increased sexual pleasure during both receptive and insertive anal sex) (32). Study participants mostly spent their time in the south side region of Chicago, which is the region with the highest prevalence of HIV infection (24). In terms of serodiscordant partnerships, it is possible that individuals’ or sex partners’ PrEP use or use of antiretroviral (ART) medicines may influence the decision regarding engaging sex with a serodiscordant or serostatus unknown partner. In the current sample, less than 5% of HIV negative participants had ever used PrEP; among HIV positive participants, 50% had ever used ART and about 23% reported that they were virally suppressed. As we did not have information on the PrEP use and the ART use for sex partners who were not also study participants, we were not able to further explore how engagement in care may play a role in risk behaviors within serodiscordant partnerships. Author Manuscript A few limitations should be acknowledged. In order to examine sexual behaviors by a sex partner’s network bridging score and a sex partner’s residential proximity to the individual, we created binary variables to categorize each sex partner based on their network bridging value (high constraint vs. low constraint) and their residential proximity (same Chicago region vs different Chicago region). For the residential proximity variable, we were not able to use the actual geographic distance in miles or travel time in minutes between members of a dyad because most participants did not provide full address information for themselves and their sex partners. Participants mostly provided cross-street, neighborhoods, or Chicago community areas information for their and their sex partners’ home location. Therefore, we used the Chicago region which represents a cluster of neighborhoods with similar social and cultural characteristics. We compared those who were missing residential information and excluded in the analysis with those who were included in the analysis. There were some differences in those who were missing residential information (e.g., less likely to be main partners). However, these factors were controlled in the analysis. Our data only permitted examination of the residential proximity between the two individuals’ residential areas. It is possible that sexual behaviors take place somewhere other than the participant’s or sex partner’s home, particularly with group sex. However, we did not have information on the AIDS Behav. Author manuscript; available in PMC 2021 August 01. Chen et al. Page 9 Author Manuscript locations where partners met one another or where group or transactional sex took place. In terms of the network construction, not all the sex partners were participants in the study and the sexual partnerships between each listed sex partner were based on the report from study participants. Thus, those who were study participants were more likely to have more central network positions due to the matching protocol. However, this is accounted for with a covariate in the final model. Additionally, anonymous partners may be named by individual study participants, but these anonymous partners are less likely to match and therefore less likely to hold network bridging positions. It has been previously noted that unobserved relationships between the named sex partners across study participants can bias the construction of network position. Although a method for imputing missing data has been suggested to alleviate such a bias (15), we were not able to impute the missing relational data because the relational information between each of the sex partners across network clusters was unavailable. Author Manuscript Despite these limitations, our findings demonstrate how residential proximity between sex partners and the sex partner’s network position may influence the sexual behaviors between the pair. HIV prevention interventions may target YBMSM who have a greater opportunity to bridge connections between people and promote the use of condoms and PrEP. Furthermore, PrEP linkage services should also incorporate supportive resources for housing and employment to empower those who have fewer resources, especially in neighborhoods that have been historically marginalized due to racism, such as the south side region of Chicago. 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[PubMed: 26525571] Author Manuscript Author Manuscript AIDS Behav. Author manuscript; available in PMC 2021 August 01. Chen et al. Page 12 Table 1. Author Manuscript Participant characteristics, uConnect study 2013-2014 (n = 437 individuals) Participant characteristics Total Age 22.9 ± 3.2 Sexual orientation Gay 294 (67.4%) Bisexual 130 (29.8%) Straight/Other 12 (2.8%) Less than high school education Annual income less than $USD20,000 27 (6.2%) 342 (79.5%) a 104 (23.9%) Sexual concurrency for sex partners in the past 6 months 1.6 ± 1.0 Current housing instability Author Manuscript Number of sex partner b 2.5 ± 1.4 More than one main partner 64 (14.6%) HIV-positive 181 (41.4%) a Housing instability was defined as (1) rented room in hotel, (2) stayed in shelter or halfway house, (3) stayed in an apartment or house for which they did not pay rent or they did not own, or (4) had no regular residence by the time to completion of the survey. b Each participant named up to 6 sex partners Author Manuscript Author Manuscript AIDS Behav. Author manuscript; available in PMC 2021 August 01. Author Manuscript Author Manuscript Author Manuscript Author Manuscript Table 2. Chen et al. Sex partner characteristics stratified by their network bridging and their residential proximity to the individual who listed them, uConnect Study, 2013-2014 (n= 1095 sex partners) a Low bridging & Same Chicago region (n = 210) Low bridging & Different Chicago region (n = 647) High bridging & Same Chicago region (n = 98) High bridging & Different Chicago region (n = 140) n (%) n (%) n (%) n (%) 97 (8.9) 20 (9.6) 67 (10.4) 1 (1.0) 9 (6.4) 0.01 Male 945 (86.3) 187 (89.1) 542 (83.8) 91 (92.9) 125 (89.3) 0.06 Female 113 (10.3) 19 (9.1) 75 (11.6) 7 (7.1) 12 (8.6) Sex partner characteristics AIDS Behav. Author manuscript; available in PMC 2021 August 01. Partner is ≥10 years older Total P-value b Partner gender Transgender Main partner 37 (3.4) 4 (1.9) 30 (4.6) 0 (0.0) 3 (2.1) 417 (38.7) 79 (38.2) 217 (34.2) 60 (61.2) 61 (43.6) <0.001 Partner is also a study participant 125 (11.4) 0 (0.0) 0 (0.0) 66 (67.4) 59 (42.1) <0.001 Partner is also a confidant 149 (13.6) 31 (14.8) 43 (6.7) 42 (42.9) 33 (23.6) <0.001 First met through mobile applications 159 (14.6) 40 (19.1) 91 (14.1) 9 (9.2) 19 (13.6) 0.12 Condomless anal sex with individual 361 (33.1) 61 (29.3) 187 (29.0) 51 (52.0) 62 (44.3) <0.001 Sex-drug use with individual 393 (36.0) 77 (36.8) 220 (34.2) 38 (38.9) 58 (41.4) 0.37 Group sex with individual 97 (9.3) 13 (6.5) 41 (6.6) 19 (20.9) 24 (17.8) <0.001 Transactional sex with individual 92 (8.4) 12 (5.7) 59 (9.1) 5 (5.1) 16 (11.4) Serodiscordant partnership or at least one person has an unknown serostatus 468 (42.7) 97 (46.2) 288 (44.5) 35 (35.7) 48 (34.3) 0.14 0.048 a Network bridging was measured by Burt’s constraint score. High network bridging was defined with constraint score that was lower than 1 (around the lowest 20% of the total constraint scores); low network bridging was defined with constraint score that was greater than 1. b Chi-square test or Fisher’s Exact test for cell size under 5. Page 13 Chen et al. Page 14 Table 3. Author Manuscript Adjusted Odds of an individual engaging in specific sexual behaviors with a sex partner, uConnect Study, 2013-2014 (n = 1095 sex partners) Condomless anal sex Sex drug use Group sex Transactional sex aOR (95% CI) aOR (95% CI) aOR (95% CI) aOR (95% CI) Sex partner characteristics Network position & residential proximity Low bridging & same Chicago region 1.00 1.00 1.00 1.00 Low bridging & different Chicago region 1.31 (0.90, 1.92) 0.85 (0.64, 1.14) 1.08 (0.51, 2.30) 1.41 (0.68, 2.93) High bridging & same Chicago region 1.37 (0.64, 2.92) 1.29 (0.76, 2.18) 4.33 (1.52, 12.35)** 2.06 (0.56, 7.52) High bridging & different Chicago region 1.24 (0.62, 2.49) 1.29 (0.84, 2.00) 3.73 (1.39, 10.06)* 2.77 (1.07, 7.18)* 0.63 (0.37, 1.06) 0.72 (0.45, 1.16) 3.44 (1.90, 6.23)*** 3.34 (1.68, 6.64)*** Partner is ≥10 years older Author Manuscript Gender Male 1.00 1.00 1.00 1.00 Female 0.19 (0.09, 0.40)*** 1.29 (0.78, 2.12) 0.79 (0.38, 1.64) 0.96 (0.39, 2.36) Transgender 0.28 (0.11, 0.70)** 2.34 (1.25, 4.38)** 0.33 (0.05, 2.34) 0.98 (0.23, 4.12) Main partner 3.53 (2.49, 5.01)*** 0.94 (0.73, 1.21) 0.72 (0.36, 1.45) 0.25 (0.12, 0.53)*** Partner was also a participant 1.48 (0.74, 2.98) 0.89 (0.55, 1.45) 0.30 (0.09, 1.00)* 0.50 (0.16, 1.62) Partner was also an confidant 1.75 (1.12, 2.73)* 1.16 (0.81, 1.64) 5.45 (2.32, 12.81)*** 0.82 (0.31, 2.15) First met through mobile applications 0.92 (0.61, 1.38) 0.71 (0.49, 1.05) 0.24 (0.06, 0.99)* 0.74 (0.37, 1.49) Age 0.98 (0.93, 1.04) 1.07 (1.01, 1.13)* 1.02 (0.94, 1.11) 1.08 (0.97, 1.20) Less than high school 0.83 (0.37, 1.84) 1.20 (0.55, 2.63) 0.93 (0.26, 3.35) 1.22 (0.36, 4.10) Participant characteristics Author Manuscript Sexual orientation * Gay 1.00 1.00 1.00 1.00 Bisexual 1.02 (0.68, 1.53) 0.92 (0.60, 1.41) 3.99 (2.03, 7.84)*** 1.65 (0.85, 3.20) Straight/other 1.41 (0.51, 3.88) 0.89 (0.27, 2.93) 1.78 (0.27, 11.82) 0.41 (0.07, 2.31) Income (<$20,000) 0.71 (0.45, 1.11) 1.19 (0.73, 1.93) 0.73 (0.36, 1.48) 2.57 (1.03, 6.40)* Housing instability 1.22 (0.80, 1.85) 1.02 (0.67, 1.56) 0.45 (0.22, 0.93)* 2.43 (1.26, 4.70)** Concurrency 1.27 (1.04, 1.54)* 1.28 (1.07, 1.52)** 1.23 (0.94, 1.61) 1.20 (0.92, 1.57) More than one main partner 0.76 (0.50, 1.16) 0.85 (0.51, 1.40) 1.16 (0.52, 2.58) 1.12 (0.55, 2.27) HIV-positive 1.17 (0.80, 1.71) 0.97 (0.66, 1.41) 2.11 (1.13, 3.93)* 1.04 (0.53, 2.01) P < 0.05, Author Manuscript ** P < 0.01, *** P < 0.001 AIDS Behav. Author manuscript; available in PMC 2021 August 01.