Egocentric network data can be analyzed at multiple levels: respondent, partnership, and partnership configuration.21 This article reports results of analyses that use the respondent as the unit of analysis. Respondents were grouped according to sex of their last 3 partners (i.e., MSOM, MSMW, WSOW, WSWM) and descriptive statistics were used to compare sexual network patterns and risk across these 4 groups. Statistical significance was assessed using χ2 tests (for categorical variables) or ANOVAs (for continuous variables). When these suggested significance, we followed-up with χ2 and post hoc Bonferroni t tests to pinpoint group differences.
Table 1 summarizes the socio-demographic characteristics and sexual risk behaviors of the 330 respondents who reported at least 1 partner in the network module, by grouping based on the sex of their last 3 sexual partners with no time limit. As seen in the table, there were some important differences beyond the traditional variations in gender, anatomy, sexual orientation, and income.
Over 20% of the sample self-reported being HIV-positive, with an additional 11% unsure of their status. Percentage was highest for MSOM (36%), followed by MSMW (19%), WSWM (15%), and WSW (2%). Over one-third of the sample (38%) reported trading sex, which was highest among MSOM (51%) and WSWM (38%). Just over half of each group (57%–58%) reported a current, steady partner except for MSOM (41%). About two-third of each group (66%–69%) reported 10 or more lifetime partners except for MSOM (82%). Per each age category 46.9% of the 18 to 25 years, 78.9% of the 26 to 34 year olds, 78.6% of the 35 to 44 years old, and 74.7% of the 45 years and over reported more than 10 partners.
Table 1 presents findings on type of partner, partnership duration, and condom use among respondents' last 3 partners (no time limit) by grouping based on the sex of their last 3 sexual partners with no time limit. A total of 728 partnerships were reported. About partner type, men were less likely than women to report at least 1 of their last 3 partners was a steady partner (55%–63% vs. 84%–85%), and more likely to report a nonsteady partner with whom they had had sex more than once (55%–56% vs. 45%–48%), a 1-time partner; (34%–37% vs. 12%–25%), and a transactional partner (i.e., one with whom they traded sex; 3%–5% vs. 1%–2%).
Median partnership duration was 26 months, and 33% of respondents reported at least 1 partnership lasting less than 1 month. MSOM (41%) and WSWM (34%) were most likely to report a partnership of less than 1 month.
Consistent condom use with all partners was very low: only 9% of the respondents reporting having always used condoms with all partners. Consistent condom use for anal sex ranged from 13% to 22%, which was generally higher than for vaginal sex (0%–14%).
Concurrency findings, based on the subsample of 144 respondents with “complete” partnership data, are reported in Table 2. Of those that reported complete partnership data 3 of the 144 respondents had 1 partner only: 1 was MSOM, 1 was WSOM, and 1 was MSMW. The point prevalence of concurrency was 24%, with 17% reporting 2 ongoing partners, and 7% reported 3 ongoing partners on the day of the interview. Concurrency varied by sex of partners, and was generally higher among MSOM and WSWM.
Cumulative prevalence of concurrency in the last 12 months was 40%, with 15% reporting 1 concurrency, 13% reporting 2, and 12% reporting 3. The upper limit, assuming concurrency if one partnership ended and another began in the same month, was 45%. Again, cumulative prevalence was highest for MSOM and WSWM. Removing the time restriction, cumulative prevalence of concurrency rose to 59% (upper limit was 70%); 27% reported 1 concurrency; 16% reported 2; and 16% reported 3. Prevalence was significantly higher for MSOM.
The overall median duration of overlap in concurrent partnerships was 4 months, with 28% of respondents reporting an overlap of 1 month or less. Among MSOM, 41% reported at least 1 overlap in partners with duration of less than 1 month, compared with 14% to 33% for the other groups. Median duration of overlap was 2.25 months for MSOM, compared with 1 to 15 months for the other groups.
Among respondents who reported at least 1 concurrency (no time limit), 72% reported unprotected sex with more than 1 of their partners. Most respondents (79%) believed their concurrent partners also were having sex with other partners.
Concurrency (no time limit) was related to gender, HIV, number of partners, and reported sex of the last 3 partners, but not self-reported sexual orientation, education, age, income, percent Native blood, and whether the respondent had ever traded sex or has a current partner (data not shown in table). Specifically, mean concurrency was significantly higher among respondents who were male (n = 60) than female or transgendered (n = 84; M[SD] = 1.33 [1.13] vs. = 0.88 [1.04], P < 0.01). In fact, 70% (42/60) of the males reported concurrency of at least one. Concurrency also was significantly higher among HIV-positive respondents (n = 21) compared with HIV-negative or HIV-unknown respondents (n = 123; M[SD] = 1.62[1.25] vs. 0.98[1.05], P < 0.01). Respondents with greater than 10 lifetime partners compared to those with less than 10 (M[SD] = 1.27[1.15] vs. 0.74[0.93], P < 0.01) reported more concurrent partners compared with those with less than 10 (M[SD] = 1.27[1.15] vs. 0.74[0.93], P < 0.01).
Partnership Mixing Across Race
Table 3 shows the breakdown of the racial composition of respondent's networks by sex of partner groupings. More than half (68%) of the sample reported all of their last 1 to 3 partners were of the same race/ethnicity: all Native (18%), all non-Hispanic black (3%), all non-Hispanic white (28%), or all of “other” race/ethnicity (19%). MSOM were least likely to report only Native partners (11% vs. 22%–24%) and most likely to report only white partners (40% vs. 18%–22%). About one-third of the sample reported that they had had partners of various races (by definition, these respondents reported more than 1 partner). Of the 239 respondents who reported the race of 2 or more partners, 57% reported partners of the same race, with 25 of 239 (10%) reporting all Native partners. Forty-three percent of the respondents with more than 1 partner reported partners of various races (data not shown in table).
Results from this study, the first national survey of GLBT AI/AN, revealed an alarmingly high prevalence of HIV (22%), indicating that this population merits attention in terms of STI prevention efforts. Rivaling HIV prevalence reported for black MSM and sub-Saharan Africans, MSOM in our study had the highest HIV prevalence (36%), followed by MSMW (19%) and WSWM (15%).
Further analyses suggested the high levels of HIV may be due to high numbers of lifetime partners, multiple short partnerships, and limited condom use. Men were more likely to have had a nonsteady sexual partner more than once, a one-time partner, and a transactional partner than women. Nevertheless, nearly half of the women reported having multiple partnerships. Additionally, consistent condom use with all partners was very low.
Concurrent sexual partnerships may be another critical factor in spreading HIV in GLBT AI/AN populations. Prevalence of concurrency in this population was quite high (24% point prevalence, 40% cumulative over last 12 months), with MSOM and WSWM reporting the highest levels (55% and 35%) of cumulative prevalence of concurrency in the past year. These levels are higher than the prevalence of concurrency in the past year among black populations (11%–21%)22 and are consistent with levels found in sub-Saharan Africa (e.g., Lesotho-55% and Cote d'Ivoire-36%)8 and among MSM in China (33%).23 Of the 85 respondents who reported at least 1 concurrency, 72% reported unprotected sex with more than 1 of their partners. Moreover, more than 75% of MSOM and 84% of the WSWM believed that at least 1 of their sexual partners also had concurrent partners. This combination of concurrency and inconsistent condom use may enhance the spread of HIV at the network level.
Additionally, an examination of partnership mixing by race indicated potential network patterns that could contain the epidemic within the small GLBT community (i.e., concurrency and assortative mixing) and bridge to other populations (disassortative mixing). Purely assortative mixing by race (i.e., Native partners only) occurred most frequently among women (WSOW and WSWM) and MSMW (22%–24%). Additionally, almost half of the respondents in these groups reported at least 1 Native partner. The uniformly high rate of AI/AN partner selection creates the potential for amplification of disease spread within this small community. Disassortive mixing by race occurred mostly among MSOM. Thus, MSOM who have high levels of unsafe sex, short partnership durations, and high prevalence of concurrency are also the ones partnering the most with non-AI/AN. Combined with high rates of selecting partners of other races, MSOM create the potential for effective bridging to other groups in the transmission network.
Bridging also can occur between the sexes. Although the MSMW subsample is fairly small and the findings should be interpreted with caution, there are a few trends in the data that are consistent with non-AI/AN MSMW populations.24–27 Specifically, our findings demonstrate that MSMW had a high number of sexual partners, engaged in high rates of unprotected anal sex with male and female partners, and engaged in unprotected vaginal sex with female partners. Thus, MSMW may be an effective bridge population across sex. The combination of high rates of concurrency and low condom use also makes WSWM an effective bridge population across race and sex. Specifically, WSWM in our study had very high rates of concurrency, second only to MSOM, and they reported 22% consistent condom use for anal sex and only 3% for vaginal sex.
There were several limitations to our study. As with other self-reports of sensitive information, our data are subject to the possible influences of social desirability and recall bias. Although we used computer-assisted self-interviewing to reduce inhibitions about disclosing, the accuracy of participants' responses cannot be determined. It is likely that any inaccuracies were related to underreporting of risk behaviors, however, meaning our findings are likely conservative estimates. Although the overall sample was rather large, some of the groups and specific pairings included small numbers of respondents. Additionally, a programming error, possibly exacerbated by the lengthy interview, led to some missing data on partnerships. This was less of an issue in the partnering analysis (n = 330, in which the analytic subsample was very similar to the overall sample) than the concurrency analysis (n = 144, in which the analytic subsample included fewer males, was more educated, was younger, and had higher incomes than those in the total sample). Also, the concurrency analyses were based only on respondents with “complete” data on in the network module, which could have biased it in either direction. Those with incomplete data who were excluded might include both individuals in long-term monogamous partnerships who could not recall details about early partners (which would inflate our estimate of concurrency) or highly sexually active individuals with multiple and concurrent partnerships who did not know the details about their partners (which would lower our estimate of concurrency). We did not include as concurrent partnerships that started and ended in the same month, which would also lower our estimate of concurrency. Finally, the network module only inquired about the last 3 partners. For many respondents, this was a small subset of their total sexual partners. For others currently in long-term partnerships, these may represent partners from many years ago for which their memory may be less reliable and their behaviors less representative of their current situation.
Despite these limitations, the findings provide some of the first insights into sexual networks and concurrency among GLBT AI/AN populations, a group that has been virtually ignored in HIV prevention efforts. The data demonstrate that GLBT AI/AN men and women deserve attention in HIV prevention efforts at individual, dyadic and population levels.
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