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JAIDS Journal of Acquired Immune Deficiency Syndromes:
doi: 10.1097/QAI.0b013e318270d3cb
Epidemiology and Prevention

Family Network Proportion and HIV Risk Among Black Men Who Have Sex With Men

Schneider, John MD, MPH*,†; Michaels, Stuart PhD; Bouris, Alida PhD, MSW§

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Author Information

Departments of *Medicine and

Health Studies

National Opinion Research Center

§School of Social Service Administration, University of Chicago, Chicago, IL.

Correspondence to: John Schneider, MD, MPH, Departments of Medicine and Health Studies, University of Chicago Medicine, 5841 South Maryland Avenue, MC 5065, Chicago, IL 60637 (e-mail: jschnei1@medicine.bsd.uchicago.edu).

Supported by grants from the National Institutes of Health (U54 RR023560, 1R01DA033875-01, and R34MH097622).

Presented at IAS 2011 and 2012 in Rome, Italy, and Washington, DC.

The authors have no conflicts to disclose.

Received December 08, 2011

Accepted August 02, 2012

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Abstract

Objectives: Black men who have sex with men (BMSM) have the highest rates of HIV in the United States. Despite increased attention to social and sexual networks as a framework for biomedical intervention, the role of family in these networks and their relationship to HIV prevention have received limited attention.

Methods: A network sample (N = 380) of BMSM (n = 204) and their family members (n = 176) was generated through respondent-driven sampling of BMSM and elicitation of their personal networks. The proportion of personal network members who were family was calculated, and the weighted logistic regression was used to assess the relationship between this proportion and unprotected anal intercourse, sex-drug use (SDU), and group sex (GS), as well as intravention efforts to discourage these risk behaviors among their MSM social networks.

Results: 45.3% of respondents listed at least 1 family member in their close personal network. Greater family network proportion (having 2 or more family members in the close network) was associated with less SDU [adjusted odds ratio (AOR) 0.38, 95% CI: 0.17 to 0.87] and participation in GS (AOR 0.25, 95% CI: 0.10 to 0.67). For intravention, BMSM with greater family proportion were more likely to discourage GS (AOR 3.83, 95% CI: 1.56 to 9.43) and SDU (AOR 2.18, 95% CI: 1.35 to 3.54) among their MSM friend network. Moreover, increased male family network proportion was associated with lower HIV risk and greater intravention than increased female network proportion.

Conclusions: Nearly half of BMSM have a close family member with whom they share personal information. Combination prevention interventions might be made more potent if this often overlooked component of personal networks was incorporated.

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INTRODUCTION

From 2006 to 2009, HIV incidence among young black men who have sex with men (BMSM) aged 13–29 years increased by 48%, with HIV incidence unchanged among young white and Hispanic/Latino MSM.1 Nationwide, it is estimated that 1 in 16 BMSM will be diagnosed with HIV during their lifetime.2 Although the precise mechanisms underlying the disparities in HIV infection among BMSM are unknown, research has suggested that BMSM experience a constellation of risk factors that may increase vulnerability to infection, including higher rates of undiagnosed HIV,3 limited prevention interventions to reduce disparities,4 less knowledge of partner's HIV status,5 and higher levels of stigma, discrimination, and minority stress experiences.6

In addition to these factors, a growing body of research has focused on the role of social networks in facilitating HIV transmission among BMSM.7–11 To date, much of this research has examined the extent to which risk is distributed and transmitted through the sexual and social networks of BMSM, focusing on factors such as social norms that encourage HIV-related risk taking, the prevalence of drugs and injection drug use practices, sexual partner availability and selection, and the presence and transmission of sexually transmitted infections within densely populated networks.10–13 In addition, the degree of social support available within the personal networks of MSM has also emerged as a powerful correlate,11,12 with BMSM reporting higher levels of support reporting less sexual risk and higher rates of HIV testing.14,15

Understanding that the composition of social networks is important, as studies have found that the extent to which one's network is composed of friends, sexual partners, drug users/buddies, or family members has important implications for HIV-related risk behaviors.16,17 For example, among a sample of primarily African American drug-using men and women in Baltimore, the number of family members in one's social network was inversely associated with HIV-related drug and sexual risk behaviors,18 suggesting that the presence of family members in personal networks may operate as a promotive factor. In contrast, a previous study observed no association between the presence of family members in personal networks and drug injection practices.16

To date, relatively few studies have explored how the presence of family members in personal networks is potentially related to HIV prevention among MSM.19–22 Most research examining family influences has focused on negative family influences among young MSM (YMSM), such as family rejection and abuse, or has reflected an assumption that family members are not a positive source of support in the lives of YMSM.21,22 Although many YMSM experience family rejection, recent studies also suggest that large numbers have disclosed their sexual orientation to their families and experience nontrivial levels of family support. For example, in a study with black, Latino, and white YMSM aged 16–24 years in Chicago, high levels of disclosure of sexual orientation to families were observed, with 83% of youth with mothers/stepmothers in their life reporting maternal disclosure and 70% of youth with fathers/stepfathers in their life reporting paternal disclosure.22 Although Black YMSM reported less paternal disclosure and acceptance than white YMSM, there were no racial differences in maternal acceptance after controlling for important demographic confounders.

Although families have been a focal site for HIV/AIDS prevention with heterosexual populations, the potentially protective role of families among BMSM has received little empirical attention.19 However, recent studies indicate that many BMSM are out to their families, experience some level of family support, and that family support is positively associated with health and well-being. For example, although it is often suggested that BMSM do not disclose their sexual orientation to their families, Mays et al23 found high levels of family knowledge in sample of 1181 African American sexual minority adults. Specifically, 76% of mothers, 75% of sisters, 68% of brothers, 58.6% of fathers, and 48% of other close relatives were identified as knowing about one's sexual orientation. In a qualitative study with diverse HIV-positive men, family relationships were described as being important and as uniquely different from relationships with friends.19 Most men maintained close contact with their families, even when they did not live in close proximity to one another.19 In a separate study with majority white MSM living with HIV, support from family but not friends was significantly correlated with behavioral intentions to reduce HIV-related sexual risk behaviors.24

Finally, more recent studies on the social networks of HIV-positive persons indicate that families play a complex role in the lives of BMSM that warrants additional attention. For instance, although Wohl et al14 found that the social networks of black and Latino women and MSM tend to be predominantly populated by relatives, women reported a significantly greater number of relatives in their personal networks than do MSM. In addition, friend support appeared to be more available and significantly more important for BMSM relative to their peers.14 In a subsequent study,12 family support was associated with retention in care at the bivariate level but was not significant in multivariate analyses with BMSM. Rather, among BMSM, stressful relationships with network members were positively correlated with retention, leading to a hypothesis that “positive nagging” by network members may play an important role. Taken together, the extant research suggests that family members may play an important role but that additional research is needed to better understand the family networks of BMSM and how such networks may be related to HIV prevention.

As we enter the fourth decade of the HIV/AIDS epidemic, the lack of meaningful research on BMSM family networks represents a critical gap in the nation's ability to prevent HIV among BMSM, especially young BMSM who are being infected with HIV during adolescence and the transition to young adulthood.1 Although social networks and social support have both emerged as important correlates of HIV risk and prevention, additional research is needed to characterize the family networks of BMSM and how such networks may be capitalized on to support both existing and novel HIV prevention efforts. The present study sought to address these gaps in the literature. To the best of our knowledge, it is the first study to describe the family networks of BMSM and to examine the association between the proportion of close personal network members who were family and HIV risk and prevention practices.

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METHODS

Setting

Between January and June of 2010, BMSM were recruited in Chicago using respondent-driven sampling (RDS).25 All interviews took place at partnering community-based organizations by BMSM community members trained by the University of Chicago Survey Lab. HIV voluntary counseling and testing were conducted according to the standard protocols at each organization. All study procedures were approved by appropriate academic and community institutional review boards. Informed consent was obtained from all respondents and waived for network members listed by respondents.

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Study Participants
Eligibility Criteria

Study participants include both study respondents who were interviewed and the network members about whom they reported. Study respondents were eligible to participate if they (1) self-identified as African American or black, (2) identified as male, (3) were aged 18 years or older, (4) reported anal intercourse with a man within the past 12 months, and (5) were willing and able to provide informed consent at the time of the study visit. Network members were eligible if they were named by respondents during the interview.

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Recruitment

RDS has been widely applied to study hard-to-reach populations, such as injecting drug users, sex workers, and MSM.26–29 Recent theoretical and empirical work has assessed the strengths and weaknesses of RDS.26,30,31 This work has emphasized the importance of careful selection of “seeds” from diverse sources and sufficient iterative rounds of recruitment to penetrate further reaches of the larger social networked population being studied—“recruits.” To improve external validity, seeds were selected from 4 venues, either through referral from HIV program personnel (eg, case manager) or posting of fliers describing the study. In the case of referral, requests for popular or charismatic candidates were made to maximize first wave recruitment.25 Specifically, 21 seeds were recruited using these 2 approaches: (1) 4 seeds were recruited from a local Federally Qualified Health Center that provides HIV primary care; (2) 8 seeds were referred from existing group Effective Behavioral Intervention prevention programs32; (3) 4 seeds were recruited through fliers from a substance use treatment program; and (4) 5 seeds were recruited through fliers posted at a lesbian gay bisexual transgender care center. Each seed was given 4 vouchers and asked to refer up to 4 MSM from their social networks, with each subsequent recruit doing the same. To avoid duplicate enrollment, bilateral arm and wrist measurements were conducted on all respondents. All respondents were paid $50 for participation.

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Survey Instruments
Social Network Assessment

In designing our Men's Assessment of Social and Risk Networks questionnaire, we followed an established method of gathering network data used in several large national surveys, including the General Social Survey,33 the National Health and Social Life Survey,34 and the National Social Life, Health, and Aging Project.35 Some studies assess people's social and sexual networks by asking about connections with a predetermined list of different social contacts (eg, parents, partners, and individuals who provide material support). Because so little is known about BMSM's social lives, we did not make any a priori assumptions about the composition of their social networks, as this would have imposed a conceptual framework that dictated the types of contacts that were most important to these men. Instead, we used a more open-ended approach,36 which let BMSM reveal the characteristics of their personal social networks. This kept the focus on individuals with whom BMSM were most subjectively engaged,37 which was appropriate given our goal of identifying the people who are the most likely to be able to exercise some form of influence over BMSM.

We asked a “name generator”36 question during the course of face-to-face interviews to elicit a set of social network members who may influence respondent's risky behaviors. The name generator was selected to identify network “confidants”38 who have opportunities, through everyday interactions with the respondent, to exercise normative pressure or informal control, provide social support, and to exchange information or advice regarding risky behavior: “Let's make a list of your closest associates with whom you may share information about yourself, your physical and mental health, and your social and sexual lifestyles.” First names or other identifiers such as initials or nicknames were entered into a roster that was recorded for future reference. We then followed up with a series of “name interpreter” questions about each network member's relationship type and strength of tie. For relationship type, respondents were asked to examine a hand card with 19 relationship categories and to choose 1 that best described an individual. Family ties included parent, child/stepchild, sibling, in-law, and other relatives. Tie strength, frequency of communication, and communication content was measured as in previous national surveys33–35 with which our group has been involved. This process was looped over each of the 5 confidants listed from the initial name generator. Research has shown that 5 network members are optimal for time and effort to field personal network surveys.39

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Family Network Proportion

We focused on the confidant subnetwork that included family (of origin) to measure the proportion of personal network members who are family (in sociology, this is also referred to as embeddedness40). This resulted in a network of family members for each respondent ranging from 0 to 5 family members. The family network included the respondent and his nominated network members who were classified as mother, father, sister, brother, child/stepchild, and other female or male relatives. Family network proportion was calculated as the proportion of the confidant network members who were family. Family network proportion was further stratified into male and female family network proportion. Because respondents were asked to best characterize each network member with 1 best descriptor (eg, friend, parent), the individuals named could not be in multiple network categories.

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Sociodemographic, Attitude, and Behavior Measures

Age, education, employment, HIV status, unprotected anal intercourse (UAI), preferred sex position (“top, bottom, or versatile”), and whether the respondent has a physician to whom they go to were items adapted from the Centers for Disease Control and Prevention's National HIV Behavioral Surveillance Survey, MSM Cycle,41 and the visit 51 Core Behavioral Survey of the MACS (available at http://statepi.jhsph.edu/macs/forms.html). Sex-drug use (SDU) was measured as in previous work.42,43 Group sex (GS) was measured as “having sex with 2 or more individuals at the same time.” UAI, GS, and SDU were assessed in frequency terms over the past year and were coded for these analyses as present if they were reported as at least monthly. Intravention within a risk network was adapted from previous work44 and included a global assessment of whether respondents discouraged MSM network members from UAI, SDU, or GS. Respondents were asked to think of all the men who engage in high-risk behavior (could include straight, gay, and transgender men, etc.) and the interactions the respondent has had with these individuals in the past year. Respondents were asked how many of these men they discouraged from high-risk behaviors (all of them, some of them, none of them). HIV testing and counseling were offered onsite, and HIV-infected respondents were referred to appropriate services.

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Analysis
Respondent-Driven Sampling

To generate RDS weights, we asked respondents to estimate the number (degree) of MSM in their community who they know well, on a first name basis, and with whom they would likely have contact within the next 2 weeks. Estimation of this measure of degree was different from the degree calculated from the personal network generator of confidants described previously. Transformations to correct for the nonnormal distribution of degree were investigated using the ladder function in Stata (STATA 12, College Station, TX). We then generated RDS weights and compared these results with those obtained without the weights and assuming independent observations. These weights were used for all regression analyses.

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Risk Network Effect Analysis

The primary outcomes of this study were defined in terms of risk- and intravention-related behaviors: UAI, SDU, and GS. We examined these outcomes individually according to the following model45:

Equation (Uncited)
Equation (Uncited)
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where Y is the outcome measure, X represents 1 or more variables characterizing the respondent's network, and Z is the additional covariates selected because of their importance in previous research: individual sociodemographics (age, education, employment), HIV status, interview site, and MSM network size. Our parameter of interest is β, which describes the association between network characteristics and HIV risk and intravention practices. Two sets of outcome measures were defined: (1) the likelihood or reported frequency of engaging in UAI, SDU, and GS and (2) the likelihood of discouraging other MSM from engaging in UAI, SDU, and GS. The model first examined the relationship of family network proportion and one's risk behavior outcome controlling for all covariates. Second, it examined the relationship between family network proportion and whether a respondent would discourage one's risk behavior—a measure of intravention, again controlling for all covariates.

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RESULTS

Respondent-Driven Sampling

Twenty-one seeds generated the study respondent sample through 9 waves of RDS, with an average of 5.8 recruits per seed chain (range, 0–42) over all waves (n = 204 BMSM respondents). Six recruits (3%) were referred and deemed ineligible. With subsequent waves of recruitment, study respondents were younger, more likely to be HIV negative, and reported less SDU and GS compared to earlier waves (Table 1). Degree of MSM community members was on average 18.6 (SD 44.9), with a range of 2–500. The data were transformed with 1 divided by the square root of the respondent's network degree, which had the least-significant departure from normality.

Table 1
Table 1
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Family Network Proportion

Respondents (N = 204) reported 983 confidants, of which 176 were family members (1 respondent who identified 5 confidants did not identify the nature of the relationship and was excluded from the family analysis). Of 203 respondents, a total of 92 (45.3%) listed at least 1 family member as a confidant (out of a maximum of 5 possible), that is, someone with whom they might share information with about “physical and mental health, and social and sexual lifestyles.” Of the 203 black MSM respondents, 25.6% reported 2 or more family member confidants. Table 2 presents the demographic characteristics of respondents and identified confidants, and the nature of the relationship between respondents and the family members identified as confidants, which is further broken down for male and female kin. The proportion of respondents who reported SDU, UAI, and GS in the past 12 months was 77 (37.8%), 72 (35.8%), and 45 (22.3%), respectively. The type of drugs used by respondents in the past 12 months included: marijuana, 122 (60.4%); cocaine/crack, 39 (19.3%); psychedelics, 30 (14.9%); poppers, 20 (9.9%); heroin, 9 (4.5%); and methamphetamine, 4 (2.0%).

TABLE 2-a Characteri...
TABLE 2-a Characteri...
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The proportion of confidant network members who were family stratified by age categories and self-reported HIV status is depicted in Figure 1. The height of the bars represents the proportion of identified confidants who were family members. The shading within the bars depicts the type of family member and the percentages of each type of family member for a given age group or HIV status. For example, about 15% of the confidants mentioned by 18- and 19-year-old respondents (n = 19) were family members, and among these confidants, 13.3% were mothers, 23.3% were brothers, and 36.7% were other male kin. None of the respondents in the youngest age group included a father in their list of confidants. In contrast, among 20–24 years old, 10.1% of confidants named were fathers and other male kin, and brothers constituted a sizeable proportion of confidants (25.5%). Among 25–29 years old, only 5.5% of the confidants named were female (all sisters).

TABLE 2-b Characteri...
TABLE 2-b Characteri...
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Figure 1
Figure 1
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Overall family network proportion was not associated with HIV status or age in adjusted analyses. When family network proportion was stratified by gender into female and male family networks, respectively, several findings emerged. In bivariate analysis, HIV-positive status was associated with female family network proportion (coefficient, 0.64; P = 0.046). However, there was no association between age or HIV status and female network proportion in multivariate-adjusted ordered logistic regression models. With respect to male family network proportion, the age category 20–24 years was associated with male family network proportion (coefficient, 2.47; P = 0.039), but not HIV status in separate multivariate ordered logistic regression models.

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Family Network Proportion and Respondent Behavior

There were significant relationships between family network proportion and respondent HIV prevention behavior (Table 3). In particular, greater family proportion (having 2 or more family members in the close network) was associated with less SDU [adjusted odds ratio (AOR) 0.38, 95% CI: 0.17 to 0.87)] and less participation in GS (AOR 0.25, 95% CI: 0.10 to 0.67). With respect to intravention (discouraging a risk behavior), those with greater family network proportion were more likely to discourage GS (AOR 3.83, 95% CI: 1.56 to 9.43) and SDU (AOR 2.18, 95% CI: 1.35 to 3.54) among other MSM who engage in risky sex or use drugs. Although moderate levels of female family network proportion (female kin making up 20%–40% of confidant network) was associated with a lower odds of SDU (AOR 0.29, 95% CI: 0.12 to 0.71), it had no relationship with UAI, GS, or intravention. In contrast, increased male family network proportion was associated with more risk protection and discouraging others from engaging in SDU and GS. Additionally, respondents with greater family proportion were more likely to assume the “bottom” position (AOR 1.83, 95% CI: 1.07 to 3.14) in sex encounters with other men and were more likely to have a regular primary care physician (AOR 4.48, 95% CI: 1.09 to 18.49).

Table 3
Table 3
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DISCUSSION

To date, relatively little research has attempted to characterize the family networks of BMSM and to explore the potential relationships between the presence of family members in close personal networks and HIV-related risk and health-promoting behaviors. In the present study, we observed a number of interesting findings. First, we found that a substantial proportion of our sample (45.3%) reported having at least 1 family member as part of their close personal network. This suggests that families may represent an untapped site for additional prevention and intervention research with BMSM. Additionally, male family networks, and not female family networks, were present in all family networks and emerged as particularly salient for young BMSM. This finding was surprising, given previous research suggesting that female family members, in particular mothers and sisters, are more knowledgeable and accepting of BMSM's sexual orientation than are male family members, such as fathers.23 In general, fathers have tended to be understudied in the research literature on HIV prevention. Most family-based research has focused on female family members, especially mothers. To date, only 1 father-based intervention to prevent HIV among black adolescents has been developed and evaluated,46 and this focused on heterosexual youth. Although it is possible that the role of male family networks in our study is a unique artifact of our sample, additional research is needed to better understand the role of fathers, and brothers and other male relatives and how they could be further engaged in HIV prevention and treatment for BMSM.

Recent research has observed that social networks can protect against a range of health risk behaviors and health conditions,47,48 including HIV.11,12,14 In addition, research with sexual minority populations has found that high levels of family support and acceptance are negatively associated with reduced sexual risk taking.49,50 We observed a similar pattern of results in our sample, with the presence of family network proportion being negatively associated with the odds of engaging in HIV-related risk behaviors among BMSM. In addition, we found that a higher family network proportion in the close networks of BMSM was positively associated with the odds of discouraging HIV risk among fellow MSM. Although a number of HIV prevention interventions have used peer groups with BMSM,51,52 we know of no family network interventions for BMSM. In addition, we know of no interventions that have attempted to integrate existing family networks with other peer networks, a novel approach that has the potential to further strengthen the social networks of BMSM.

In addition, a better understanding of BMSM family networks is important for several reasons. First, relatively little is known about family dynamics among BMSM. Existing research examining the role of family acceptance on the health of sexual minority populations has focused primarily on youth and on white and Latino groups.50 Although many BMSM do encounter family rejection, many also experience family support, and additional research on the family networks of BMSM would make important contributions to the literature. Among a sample of urban HIV-positive BMSM, the majority of men reported that they had disclosed their HIV status to some or most/all of their family members.15 Even among men who had not disclosed their status, almost all participants indicated that family was important to them and offered support that was qualitatively different from the types of support offered from friends and sexual partners.18

The integration of social network theories with psychosocial theories underscoring the importance of family networks in HIV prevention offers great promise to efficacious prevention interventions that are being tested in social settings (the real world). In these scenarios, family networks of BMSM offer a naturally occurring mechanism through which to support the uptake of a range of HIV prevention interventions. Treatment as prevention,53 for example, might be strengthened if family networks are involved, in the intravention process. Many of the younger BMSM continue to live with their families of origin, an existing organic support that could further limit the cost of an HIV care system in the process of incorporating potent biomedical intervention.

As with any study, our findings must be interpreted within the context of study limitations. Our data are cross-sectional and thus do not permit causal attributions. In addition, the cross-sectional nature of our data does not allow us to assess how family networks of BMSM changes over time, and how such changes are potentially related to HIV risk and intravention. Prospective research in this area is needed and could help researchers to identify potentially important changes in network composition over time. Although our approach to characterizing the social networks of BMSM enabled us to avoid the imposition of a priori frameworks of family networks, we did not directly interview named confidants. Future research should seek to interview network confidants, as this will provide additional information on how to work with families to prevent HIV among BMSM. Despite these limitations, the present study has important applied implications for future research with BMSM. A network approach to family-based research with BMSM acknowledges that many BMSM have supportive family networks and can lay the foundation for research that addresses a serious gap in our current efforts to deliver culturally relevant interventions to many BMSM.

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REFERENCES

1. Prejean J, Ruiguang S, Hernandez A, et al.. Estimated HIV incidence in the United States, 2006-2009. PLoS One. 2011;6:e17502.

2. Hall HI, An Q, Hutchinson AB, et al.. Estimating the lifetime risk of a diagnosis of the HIV infection in 33 states, 2004-2005. J Acquir Immune Defic Syndr. 2008;49:294–297.

3. MacKellar DA, Valleroy LA, Secura GM, et al.. Unrecognized HIV infection, risk behaviors, and perceptions of risk among young men who have sex with men—opportunities for advancing HIV prevention in the third decade of HIV/AIDS. J Acquir Immune Defic Syndr. 2005;38:603–614.

4. Hemmige V, McFadden R, Cook S, et al.. HIV prevention interventions to reduce racial disparities in the United States: a systematic review. J Gen Intern Med. 2012;27:1047–1067.

5. Oster AM, Wiegand RE, Sionean C, et al.. Understanding disparities in HIV infection between black and white MSM in the United States. AIDS. 2011;25:1103–1112.

6. Meyer IH. Minority stress and mental health in gay men. J Health Soc Behav. 1995;36:38–56.

7. Harawa NT, Greenland S, Bingham TA, et al.. Associations of race/ethnicity with HIV prevalence and HIV-related behaviors among young men who have sex with men in 7 urban centers in the United States. J Acquir Immune Defic Syndr. 2004;35:526–536.

8. Millett GA, Flores SA, Peterson JL, et al.. Explaining disparities in HIV infection among black and white men who have sex with men: a meta-analysis of HIV risk behaviors. AIDS. 2007;21:2083–2091.

9. Adimora AA, Schoenbach VJ, Doherty IA. HIV and African Americans in the southern United States: sexual networks and social context. Sex Transm Dis. 2006;33(7 suppl):S39–S45.

10. Tobin KE, German D, Spikes P, et al.. A comparison of the social and sexual networks of crack-using and non-crack using African American men who have sex with men. J Urban Health. 2011;88:1052–1062.

11. Peterson JL, Rothenberg R, Kraft JM, et al.. Perceived condom norms and HIV risks among social and sexual networks of young African American men who have sex with men. Health Educ Res. 2009;24:119–127.

12. Wohl AR, Galvan FH, Myers HF, et al.. Do social support, stress, disclosure and stigma influence retention in HIV care for Latino and African American men who have sex with men and women? AIDS Behav. 2011;15:1098–1110.

13. Schneider JA, Cornwell B, Ostrow DG, et al.. Network mixing and network influences most linked to HIV infection and risk behavior in a Black men who have sex with men HIV epidemic. Am J Public Health. In Press.

14. Wohl AR, Galvan FH, Myers HF, et al.. Social support, stress and social network characteristics among HIV-positive Latino and African American women and men who have sex with men. AIDS Behav. 2010;14:1149–1158.

15. Lauby JL, Marks G, Bingham T, et al.. Having supportive social relationships is associated with reduced risk of unrecognized HIV infection among black and Latino men who have sex with men. AIDS Behav. 2012;16:508–515.

16. Latkin C, Mandell W, Oziemkowska M, et al.. Using social network analysis to study patterns of drug-use among urban drug-users at high-risk for HIV AIDS. Drug Alcohol Depend. 1995;38:1–9.

17. Friedman SR, Kottiri BJ, Neaigus A, et al.. Network-related mechanisms may help explain long-term HIV-1 seroprevalence levels that remain high but do not approach population-group saturation. Am J Epidemiol. 2000;152:913–922.

18. Latkin CA, Hua W, Forman VL. The relationship between social network characteristics and exchanging sex for drugs or money among drug users in Baltimore, MD, USA. Int J STD AIDS. 2003;14:770–775.

19. Serovich JM, Grafsky EL, Craft SM. Does family matter to HIV-positive men who have sex with men? J Marital Fam Ther. 2011;37:290–298.

20. Bouris A, Guilamo-Ramos V, Pickard A, et al.. A systematic review of parental influences on the health and well-being of lesbian, gay, and bisexual youth: time for a new public health research and practice agenda. J Prim Prev. 2010;31:273–309.

21. Garofalo R, Mustanski B, Donenberg G. Parents know and parents matter; is it time to develop family-based HIV prevention programs for young men who have sex with men? J Adolesc Health. 2008;43:201–204.

22. Mustanski B, Hunter J. Parents as agents of HIV prevention for gay, lesbian, and bisexual youth. In: Pequegnat W, Bell CC, eds. Family and HIV/AIDS: Cultural and Contextual Issues in Prevention and Treatment. 2012:249–260.

23. Mays VM, Chatters LM, Cochran SD, et al.. African American families in diversity: gay men and lesbians as participants in family networks. J Comp Fam Stud. 1998;29:73–87.

24. Kimberly JA, Serovich JM. The role of family and friend social support in reducing risk behaviors among HIV-positive gay men. AIDS Educ Prev. 1999;11:465–475.

25. Heckathorn D. Respondent-driven sampling: a new approach to the study of hidden populations. Soc Probl. 1997;44:174–199.

26. Iguchi MY, Ober AJ, Berry SH, et al.. Simultaneous recruitment of drug users and men who have sex with men in the United States and Russia using respondent-driven sampling: sampling methods and implications. J Urban Health. 2009;86:S5–S31.

27. Johnston LG, Khanam R, Reza M, et al.. The effectiveness of respondent driven sampling for recruiting males who have sex with males in Dhaka, Bangladesh. AIDS Behav. 2008;12:294–304.

28. Ramirez-Valles J, Heckathorn DD, Vázquez R, et al.. From networks to populations: the development and application of respondent-driven sampling among IDUs and Latino gay men. AIDS Behav. 2005;9:387–402.

29. Mimiaga MJ, Goldhammer H, Belanoff C, et al.. Men who have sex with men: perceptions about sexual risk, HIV and sexually transmitted disease testing, and provider communication. Sex Transm Dis. 2007;34:113–119.

30. Gile KJ, Handcock KS. Respondent-driven sampling: an assessment of current methodology. Sociol Methodol. 2010;40:285–327.

31. Goel S, Salganik MJ. Respondent-driven sampling as Markov chain Monte Carlo. Stat Med. 2009;28:2202–2229.

32. Centers for Disease Control and Prevention. 2009 Compendium of evidence-based HIV prevention interventions. 2010. Available at: http://www.cdc.gov/hiv/topics/research/prs/evidence-based-interventions.htm. Accessed October 17, 2012.

33. Gilman SE, Cochran SD, Mays VM, et al.. Risk of psychiatric disorders among individuals reporting same-sex partners in the National Comorbidity Survey. Am J Public Health. 2001;91:933–939.

34. Laumann EO, Gagnon JH, Michael RT, et al.. The Social Organization of Sexuality: Sexual Practices in the United States. Chicago, IL: University Of Chicago Press; 1994.

35. Cornwell B, Schumm LP, Laumann EO, et al.. Social networks in the NSHAP Study: rationale, measurement, and preliminary findings. J Gerontol B Psychol Sci Soc Sci. 2009;64:I47–I55.

36. Marsden PV. Core discussion networks of Americans. Am Sociol Rev. 1987;52:122–131.

37. Laumann EO, Marsden PV, Prensky D. The boundary specification problem in network analysis. In: Burt RS, Minor MJ, eds. Applied Network Analysis. New York, NY: Sage Publications; 1983:18–34.

38. McPherson M, Smith-Lovin L, Brashears ME. Social isolation in America: changes in core discussion networks over two decades. Am Sociol Rev. 2006;71:353–375.

39. Burt R. Network items and the general social survey. Soc Networks. 1984;6:293–339.

40. Granovetter M. Economic action and social structure: the problem of embeddedness. Am J Sociol. 1985;91:481–493.

41. Sanchez T, Finlayson T, Drak A, et al.. Human immunodeficiency virus (HIV) risk, prevention, and testing behaviors—United States, National HIV Behavioral Surveillance System: men who have sex with men, November 2003-April 2005. MMWR Surveill Summ. 2006;55:1–16.

42. Ostrow DG, Plankey MW, Cox C, et al.. Specific sex drug combinations contribute to the majority of recent HIV seroconversions among MSM in the MACS. J Acquir Immune Defic Syndr. 2009;51:349–355.

43. Ostrow DG, Stall RC. Alcohol, tobacco, and drug use among gay and bisexual men. In: Wolitski RJ, Stall R, Valdiserri RO, eds. Unequal Opportunity: Health Disparities Affecting Gay and Bisexual Men in the United States. Oxford, England: Oxford University Press; 2008:121–158.

44. Friedman SR, Maslow C, Bolyard M, et al.. Urging others to be healthy: ‘intravention' by injection drug users as a community prevention goal. AIDS Educ Prev. 2004;16:250–263.

45. McCullagh P, Nelder JA. Generalized Linear Models. Boca Raton, FL: CRC Press; 1999.

46. DiIorio C, McCarty F, Resnicow K, et al.. REAL men: a group-randomized trial of an HIV prevention intervention for adolescent boys. Am J Public Health. 2007;97:1084–1089.

47. Gallant MP. The influence of social support on chronic illness self-management: a review and directions for research. Health Educ Behav. 2003;30:170–195.

48. DiMatteo MR. Social support and patient adherence to medical treatment: a meta-analysis. Health Psychol. 2004;23:207–218.

49. Mustanski B, Newcomb M, Garofalo R. Mental health of lesbian, gay, and bisexual youth: a developmental resiliency perspective. J Gay Lesbian Soc Serv. 2011;23:204–225.

50. Ryan C, Russell ST, Huebner D, et al.. Family acceptance in adolescence and the health of LGBT young adults. J Child Adolesc Psychiatr Nurs. 2010;23:205–213.

51. Operario D, Smith CD, Arnold E, et al.. The Bruthas Project: evaluation of a community-based HIV prevention intervention for African American men who have sex with men and women. AIDS Educ Prev. 2010;22:37–48.

52. Wilton L, Herbst JH, Coury-Doniger P, et al.. Efficacy of an HIV/STI prevention intervention for black men who have sex with men: findings from the Many Men, Many Voices (3MV) project. AIDS Behav. 2009;13:532–544.

53. Cohen MS, Chen YQ, McCauley M, et al.. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365:493–505.

Cited By:

This article has been cited 1 time(s).

AIDS and Behavior
Social Support Network Characteristics and Sexual Risk Taking Among a Racially/Ethnically Diverse Sample of Young, Urban Men Who Have Sex with Men
Kapadia, F; Siconolfi, DE; Barton, S; Olivieri, B; Lombardo, L; Halkitis, PN
AIDS and Behavior, 17(5): 1819-1828.
10.1007/s10461-013-0468-2
CrossRef
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Keywords:

Black men who have sex with men; family network; HIV intravention; social networks

© 2012 Lippincott Williams & Wilkins, Inc.

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